ISG Software Research Analyst Perspectives

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We offer a portfolio of advisory, research, thought leadership and digital education services to help optimize market strategy, planning and execution. <a href="https://www.ventanaresearch.com/services/vendors/analyst_relations" rel="noopener">Analyst Relations</a> <a href="https://www.ventanaresearch.com/services/vendors/demand_generation" rel="noopener">Demand Generation</a> <a href="https://www.ventanaresearch.com/services/vendors/product-marketing" rel="noopener">Product Marketing</a> <a href="https://www.ventanaresearch.com/vendor-coverage" target="_self" role="menuitem">Market Coverage</a> <a href="https://www.ventanaresearch.com/briefing" target="_self" role="menuitem">Request a Briefing</a> </div> <ul></ul> <div class="bottom_rich_text"> </div> </div> </div> </div> </div> </div> <script src="https://blog.isg-research.net/hs-fs/hub/2035844/hub_generated/template_assets/90531223305/1725882478811/Ventana_Research_2023/js/mmenu.min.js"></script> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div id="hs_cos_wrapper_Structured_data" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"></div> <div class="body-container-wrapper"> <div class="blog-header background-image post_page_2" data-bg-color="secondary" style="background-size:cover;background-position:50%;background-repeat:no-repeat;background-image:url(https://blog.isg-research.net/hubfs/_images/_backgrounds/314838419_1200px.jpg)">  <div class="row-fluid"> <div class="blog-header__inner dnd-row"> <div class="blog--post__image dnd-section">  <h1 class="analyst-header-title">Analyst Perspectives</h1>  </div> </div> </div> </div> <div class="content-wrapper-listing blog-single"> <div class="blog-content-wrapper"> <div>  <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://blog.isg-research.net/ibm-builds-on-analytics-and-bi-foundation">IBM Builds on Analytics and BI Foundation</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/david-menninger"> David Menninger </a> on 29 November 2022 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png?width=200&name=AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png?width=100&name=AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png 100w, https://blog.isg-research.net/hs-fs/hubfs/AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png?width=200&name=AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png 200w, https://blog.isg-research.net/hs-fs/hubfs/AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png?width=300&name=AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png 300w, https://blog.isg-research.net/hs-fs/hubfs/AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png?width=400&name=AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png 400w, https://blog.isg-research.net/hs-fs/hubfs/AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png?width=500&name=AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png 500w, https://blog.isg-research.net/hs-fs/hubfs/AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png?width=600&name=AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> In today’s data-driven world, organizations need real-time access to up-to-date, high-quality data and analysis to keep pace with changing market dynamics and make better strategic decisions. By mining meaningful insights from enterprise data quickly, they gain a competitive advantage in the market. Yet, organizations face a multitude of challenges when transitioning into an analytics-driven enterprise. Our Analytics and Data Benchmark Research shows that more than one-quarter of organizations... </div> <a href="https://blog.isg-research.net/ibm-builds-on-analytics-and-bi-foundation"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/embedded-analytics">embedded analytics</a>, <a href="https://blog.isg-research.net/topic/analytics">Analytics</a>, <a href="https://blog.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://blog.isg-research.net/topic/ibm">IBM</a>, <a href="https://blog.isg-research.net/topic/ibm-watson">IBM Watson</a>, <a href="">AI and Machine Learning</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://blog.isg-research.net/2014/07/30/ibm-brings-sophistication-to-customer-analytics-and-prediction">IBM Brings Sophistication to Customer Analytics and Prediction</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/isg-software-research"> ISG Software Research </a> on 30 July 2014 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-19.png?width=200&name=vr_ngce_research_08_all_channels_for_customer_engagement-19.png" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-19.png?width=100&name=vr_ngce_research_08_all_channels_for_customer_engagement-19.png 100w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-19.png?width=200&name=vr_ngce_research_08_all_channels_for_customer_engagement-19.png 200w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-19.png?width=300&name=vr_ngce_research_08_all_channels_for_customer_engagement-19.png 300w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-19.png?width=400&name=vr_ngce_research_08_all_channels_for_customer_engagement-19.png 400w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-19.png?width=500&name=vr_ngce_research_08_all_channels_for_customer_engagement-19.png 500w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-19.png?width=600&name=vr_ngce_research_08_all_channels_for_customer_engagement-19.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> During recent IBM analyst big data event, I learned about a new product, <a href="http://www-03.ibm.com/software/products/fi/predictive-customer-intelligence" target="_blank">IBM Predictive Customer Intelligence</a>. It extracts and processes customer-related data from multiple sources to analyze customer-related activities and has capabilities to predict customer behavior and actions. Predictive Customer Intelligence is built on IBM’s big data platform and supports extraction and integration of data from multiple sources, internal and external, and from structured and unstructured data. It can... </div> <a href="https://blog.isg-research.net/2014/07/30/ibm-brings-sophistication-to-customer-analytics-and-prediction"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/social-media">Social Media</a>, <a href="https://blog.isg-research.net/topic/customer-analytics">Customer Analytics</a>, <a href="https://blog.isg-research.net/topic/customer-experience">Customer Experience</a>, <a href="https://blog.isg-research.net/topic/voice-of-the-customer">Voice of the Customer</a>, <a href="https://blog.isg-research.net/topic/ibm-predictive-customer-intelligence">IBM Predictive Customer Intelligence</a>, <a href="https://blog.isg-research.net/topic/analytics">Analytics</a>, <a href="https://blog.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://blog.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/collaboration">Collaboration</a>, <a href="https://blog.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://blog.isg-research.net/topic/customer-service">Customer Service</a>, <a href="https://blog.isg-research.net/topic/ibm">IBM</a>, <a href="https://blog.isg-research.net/topic/information-applications">Information Applications</a>, <a href="https://blog.isg-research.net/topic/call-center">Call Center</a>, <a href="https://blog.isg-research.net/topic/contact-center">Contact Center</a>, <a href="https://blog.isg-research.net/topic/contact-center-analytics">Contact Center Analytics</a>, <a href="https://blog.isg-research.net/topic/ibm-watson">IBM Watson</a>, <a href="https://blog.isg-research.net/topic/text-analytics">Text Analytics</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://blog.isg-research.net/2014/06/14/genesys-and-ibm-to-improve-customer-engagement-with-ibm-watson">Genesys and IBM to Improve Customer Engagement with IBM Watson</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/isg-software-research"> ISG Software Research </a> on 14 June 2014 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-20.png?width=200&name=vr_ngce_research_08_all_channels_for_customer_engagement-20.png" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-20.png?width=100&name=vr_ngce_research_08_all_channels_for_customer_engagement-20.png 100w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-20.png?width=200&name=vr_ngce_research_08_all_channels_for_customer_engagement-20.png 200w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-20.png?width=300&name=vr_ngce_research_08_all_channels_for_customer_engagement-20.png 300w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-20.png?width=400&name=vr_ngce_research_08_all_channels_for_customer_engagement-20.png 400w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-20.png?width=500&name=vr_ngce_research_08_all_channels_for_customer_engagement-20.png 500w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-20.png?width=600&name=vr_ngce_research_08_all_channels_for_customer_engagement-20.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> The contact center market continues to shift focus from handling customer calls as efficiently as possible to providing superior customer engagement across multiple touch points. The latest advancement is an joint <a href="http://www-03.ibm.com/press/us/en/pressrelease/44128.wss" target="_blank">announcement from IBM</a> <a href="http://www.genesys.com/about-genesys/newsroom/news/ibm-watson-and-genesys-partner-to-power-smarter-customer-experiences" target="_blank">and Genesys</a> who have signed a partnership agreement to provide “smarter customer engagement”. The agreement includes a technology partnership and a joint marketing plan, and brings together IBM’s <a href="http://www-03.ibm.com/innovation/us/watson/pdf/ibm_watson_engagement_brochure.pdf" target="_blank">Watson Engagement Advisor</a> and Genesys’ <a href="http://www.genesys.com/platform-services" target="_blank">Customer Experience Platform</a>. </div> <a href="https://blog.isg-research.net/2014/06/14/genesys-and-ibm-to-improve-customer-engagement-with-ibm-watson"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/social-media">Social Media</a>, <a href="https://blog.isg-research.net/topic/customer-experience">Customer Experience</a>, <a href="https://blog.isg-research.net/topic/genesys">Genesys</a>, <a href="https://blog.isg-research.net/topic/mobile-apps">Mobile Apps</a>, <a href="https://blog.isg-research.net/topic/self-service">Self-service</a>, <a href="https://blog.isg-research.net/topic/operational-performance">Operational Performance</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://blog.isg-research.net/topic/customer-service">Customer Service</a>, <a href="https://blog.isg-research.net/topic/call-center">Call Center</a>, <a href="https://blog.isg-research.net/topic/cognitive-computing">Cognitive Computing</a>, <a href="https://blog.isg-research.net/topic/contact-center">Contact Center</a>, <a href="https://blog.isg-research.net/topic/crm">CRM</a>, <a href="https://blog.isg-research.net/topic/ibm-watson">IBM Watson</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://blog.isg-research.net/2014/03/13/ibm-delivers-new-talent-management-suite">IBM Delivers New Talent Management Suite</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/isg-software-research"> ISG Software Research </a> on 13 March 2014 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_hca_06_technology_for_human_capital_analytics_improvement-7.png?width=200&name=vr_hca_06_technology_for_human_capital_analytics_improvement-7.png" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_hca_06_technology_for_human_capital_analytics_improvement-7.png?width=100&name=vr_hca_06_technology_for_human_capital_analytics_improvement-7.png 100w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_hca_06_technology_for_human_capital_analytics_improvement-7.png?width=200&name=vr_hca_06_technology_for_human_capital_analytics_improvement-7.png 200w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_hca_06_technology_for_human_capital_analytics_improvement-7.png?width=300&name=vr_hca_06_technology_for_human_capital_analytics_improvement-7.png 300w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_hca_06_technology_for_human_capital_analytics_improvement-7.png?width=400&name=vr_hca_06_technology_for_human_capital_analytics_improvement-7.png 400w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_hca_06_technology_for_human_capital_analytics_improvement-7.png?width=500&name=vr_hca_06_technology_for_human_capital_analytics_improvement-7.png 500w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_hca_06_technology_for_human_capital_analytics_improvement-7.png?width=600&name=vr_hca_06_technology_for_human_capital_analytics_improvement-7.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> At its recent Connect 2014 event IBM announced IBM Kenexa Talent Suite, an<a href="http://www-03.ibm.com/press/us/en/pressrelease/43032.wss" target="_blank"> integrated talent management suite</a>. The release strengthens its <a href="http://www.ibm.com/social-business/us/en/build-a-smarter-workforce.html" target="_blank">Smarter Workforce</a> initiative by combining IBM and Kenexa products and services in one human capital management (HCM) offering. IBM Kenexa Talent Suite also addresses increasing efforts by human resources organizations to optimize their activities through more effective use of technology, a topic covered in <a href="http://stephanmillard.ventanaresearch.com/2014/02/05/the-human-capital-management-technology-revolution-in-2014/" target="_blank">our 2014 HCM research agenda</a>. Specifically, the... </div> <a href="https://blog.isg-research.net/2014/03/13/ibm-delivers-new-talent-management-suite"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/big-data">Big Data</a>, <a href="https://blog.isg-research.net/topic/mobile">Mobile</a>, <a href="https://blog.isg-research.net/topic/sap">SAP</a>, <a href="https://blog.isg-research.net/topic/social-media">Social Media</a>, <a href="https://blog.isg-research.net/topic/hcm">HCM</a>, <a href="https://blog.isg-research.net/topic/kenexa">Kenexa</a>, <a href="https://blog.isg-research.net/topic/recruiting">Recruiting</a>, <a href="https://blog.isg-research.net/topic/analytics">Analytics</a>, <a href="https://blog.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://blog.isg-research.net/topic/business-collaboration">Business Collaboration</a>, <a href="https://blog.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/collaboration">Collaboration</a>, <a href="https://blog.isg-research.net/topic/ibm">IBM</a>, <a href="https://blog.isg-research.net/topic/oracle">Oracle</a>, <a href="https://blog.isg-research.net/topic/workforce-performance">Workforce Performance</a>, <a href="https://blog.isg-research.net/topic/cognitive-computing">Cognitive Computing</a>, <a href="https://blog.isg-research.net/topic/hr">HR</a>, <a href="https://blog.isg-research.net/topic/ibm-watson">IBM Watson</a>, <a href="https://blog.isg-research.net/topic/social">Social</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://blog.isg-research.net/2014/01/13/ibm-bets-a-billion-to-mobilize-watson-business-unit-to-monetize-cognitive-computing">IBM Bets a Billion to Mobilize Watson Business Unit and Monetize Cognitive Computing</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/mark-smith"> Mark Smith </a> on 13 January 2014 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner-2.jpg?width=200&name=vr_techaward_winner-2.jpg" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner-2.jpg?width=100&name=vr_techaward_winner-2.jpg 100w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner-2.jpg?width=200&name=vr_techaward_winner-2.jpg 200w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner-2.jpg?width=300&name=vr_techaward_winner-2.jpg 300w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner-2.jpg?width=400&name=vr_techaward_winner-2.jpg 400w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner-2.jpg?width=500&name=vr_techaward_winner-2.jpg 500w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner-2.jpg?width=600&name=vr_techaward_winner-2.jpg 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> With much fanfare and a rarely seen introduction by CEO Ginni Rometty, IBM launched IBM Watson as a new business unit focused on cognitive computing technology and solutions, now being led by<a href="http://www-03.ibm.com/press/us/en/pressrelease/42869.wss" target="_blank"> Senior Vice President Mike Rhodin. The announcement is summarized here</a>:. Until now IBM Watson was important but had neither this stature in IBM’s organizational structure nor enough investment to support what the company proclaims is the third phase of computing. As IBM tells it, computing paradigms began... </div> <a href="https://blog.isg-research.net/2014/01/13/ibm-bets-a-billion-to-mobilize-watson-business-unit-to-monetize-cognitive-computing"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/big-data">Big Data</a>, <a href="https://blog.isg-research.net/topic/sales-performance">Sales Performance</a>, <a href="https://blog.isg-research.net/topic/social-media">Social Media</a>, <a href="https://blog.isg-research.net/topic/supply-chain-performance">Supply Chain Performance</a>, <a href="https://blog.isg-research.net/topic/it-performance">IT Performance</a>, <a href="https://blog.isg-research.net/topic/operational-performance">Operational Performance</a>, <a href="https://blog.isg-research.net/topic/analytics">Analytics</a>, <a href="https://blog.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://blog.isg-research.net/topic/business-collaboration">Business Collaboration</a>, <a href="https://blog.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://blog.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://blog.isg-research.net/topic/cio">CIO</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://blog.isg-research.net/topic/financial-performance">Financial Performance</a>, <a href="https://blog.isg-research.net/topic/governance-risk-compliance-grc">Governance, Risk & Compliance (GRC)</a>, <a href="https://blog.isg-research.net/topic/information-applications">Information Applications</a>, <a href="https://blog.isg-research.net/topic/information-management">Information Management</a>, <a href="https://blog.isg-research.net/topic/location-intelligence">Location Intelligence</a>, <a href="https://blog.isg-research.net/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://blog.isg-research.net/topic/workforce-performance">Workforce Performance</a>, <a href="https://blog.isg-research.net/topic/cognitive-computing">Cognitive Computing</a>, <a href="https://blog.isg-research.net/topic/discovery">Discovery</a>, <a href="https://blog.isg-research.net/topic/exploration">Exploration</a>, <a href="https://blog.isg-research.net/topic/ibm-watson">IBM Watson</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://blog.isg-research.net/2013/07/04/ibm-improving-the-science-to-apply-business-analytics-for-better-customer-engagement">IBM Improving the Science to Apply Business Analytics for Better Customer Engagement</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/isg-software-research"> ISG Software Research </a> on 04 July 2013 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_leadershipwinner-14.png?width=200&name=vr_leadershipwinner-14.png" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_leadershipwinner-14.png?width=100&name=vr_leadershipwinner-14.png 100w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_leadershipwinner-14.png?width=200&name=vr_leadershipwinner-14.png 200w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_leadershipwinner-14.png?width=300&name=vr_leadershipwinner-14.png 300w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_leadershipwinner-14.png?width=400&name=vr_leadershipwinner-14.png 400w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_leadershipwinner-14.png?width=500&name=vr_leadershipwinner-14.png 500w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_leadershipwinner-14.png?width=600&name=vr_leadershipwinner-14.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> I recently wrote how <a href="http://richardsnow.ventanaresearch.com/2013/05/10/ibm-making-customer-analytics-smarter/" target="_blank">IBM is making customer analytics smarter</a>. Since then IBM has run events in North America and Europe to demonstrate how it is continuing these efforts and expanding into other areas. Outside of the customer space you can read how my colleagues assess its efforts: <a href="//marksmith.ventanaresearch.com/2013/02/01/ibm-provokes-social-collaboration-and-smarter-workforce-revolution/" target="_blank">Mark Smith discusses HR</a>, <a href="//robertkugel.ventanaresearch.com/2013/06/14/ibm-showcases-big-data-and-analytics-for-business/" target="_blank">Robert Kugel sees its impact on business overall</a>, and <a href="http://tonycosentino.ventanaresearch.com/2013/04/10/ibms-five-lenses-for-big-data-analytics/" target="_blank">Tony Cosentino addresses it in IT</a>. Our research My focus remains the customer and I have learned more about what IBM is doing in social... </div> <a href="https://blog.isg-research.net/2013/07/04/ibm-improving-the-science-to-apply-business-analytics-for-better-customer-engagement"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/social-media">Social Media</a>, <a href="https://blog.isg-research.net/topic/customer-analytics">Customer Analytics</a>, <a href="https://blog.isg-research.net/topic/customer-experience">Customer Experience</a>, <a href="https://blog.isg-research.net/topic/speech-analytics">Speech Analytics</a>, <a href="https://blog.isg-research.net/topic/voice-of-the-customer">Voice of the Customer</a>, <a href="https://blog.isg-research.net/topic/mobile-apps">Mobile Apps</a>, <a href="https://blog.isg-research.net/topic/self-service">Self-service</a>, <a href="https://blog.isg-research.net/topic/analytics">Analytics</a>, <a href="https://blog.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://blog.isg-research.net/topic/business-collaboration">Business Collaboration</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/collaboration">Collaboration</a>, <a href="https://blog.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://blog.isg-research.net/topic/customer-service">Customer Service</a>, <a href="https://blog.isg-research.net/topic/ibm">IBM</a>, <a href="https://blog.isg-research.net/topic/call-center">Call Center</a>, <a href="https://blog.isg-research.net/topic/contact-center">Contact Center</a>, <a href="https://blog.isg-research.net/topic/contact-center-analytics">Contact Center Analytics</a>, <a href="https://blog.isg-research.net/topic/crm">CRM</a>, <a href="https://blog.isg-research.net/topic/desktop-analytics">Desktop Analytics</a>, <a href="https://blog.isg-research.net/topic/ibm-watson">IBM Watson</a>, <a href="https://blog.isg-research.net/topic/text-analytics">Text Analytics</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://blog.isg-research.net/2013/05/26/ibm-watson-engagement-advisor-for-smarter-customer-service-2">IBM Watson Engagement Advisor for Smarter Customer Service</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/isg-software-research"> ISG Software Research </a> on 25 May 2013 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo3-1.jpg?width=200&name=vr_2012_techaward_winner_logo3-1.jpg" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo3-1.jpg?width=100&name=vr_2012_techaward_winner_logo3-1.jpg 100w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo3-1.jpg?width=200&name=vr_2012_techaward_winner_logo3-1.jpg 200w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo3-1.jpg?width=300&name=vr_2012_techaward_winner_logo3-1.jpg 300w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo3-1.jpg?width=400&name=vr_2012_techaward_winner_logo3-1.jpg 400w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo3-1.jpg?width=500&name=vr_2012_techaward_winner_logo3-1.jpg 500w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_2012_techaward_winner_logo3-1.jpg?width=600&name=vr_2012_techaward_winner_logo3-1.jpg 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> Recently <a href="//marksmith.ventanaresearch.com/2012/12/11/ibm-watson-advances-a-new-category-of-cognitive-computing/" target="_blank">my colleague Mark Smith wrote about the IBM Watson platform</a>. Mark is our expert on technically complex subjects like <a href="http://www.ibm.com/watson" target="_blank">IBM Watson</a> and‎ cognitive computing and the value it can provide to organizations and wrote <a href="//www.ventanaresearch.com/whitepapers/register.aspx?id=3364" target="_blank">an educational white paper on the topic</a>. In fact IBM Watson was awarded the 2012 Ventana Research Technology Innovation Award. I focus on the customer and the customer experience, but I became engaged with the launch of the <a href="http://www-03.ibm.com/press/us/en/photo/41135.wss" target="_blank">IBM Watson Engagement Advisor</a>, which uncannily brings the... </div> <a href="https://blog.isg-research.net/2013/05/26/ibm-watson-engagement-advisor-for-smarter-customer-service-2"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/social-media">Social Media</a>, <a href="https://blog.isg-research.net/topic/customer-analytics">Customer Analytics</a>, <a href="https://blog.isg-research.net/topic/customer-experience">Customer Experience</a>, <a href="https://blog.isg-research.net/topic/social-crm">Social CRM</a>, <a href="https://blog.isg-research.net/topic/mobile-apps">Mobile Apps</a>, <a href="https://blog.isg-research.net/topic/self-service">Self-service</a>, <a href="https://blog.isg-research.net/topic/operational-performance">Operational Performance</a>, <a href="https://blog.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://blog.isg-research.net/topic/cloud-computing">Cloud Computing</a>, <a href="https://blog.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://blog.isg-research.net/topic/customer-service">Customer Service</a>, <a href="https://blog.isg-research.net/topic/ibm">IBM</a>, <a href="https://blog.isg-research.net/topic/call-center">Call Center</a>, <a href="https://blog.isg-research.net/topic/cognitive-computing">Cognitive Computing</a>, <a href="https://blog.isg-research.net/topic/contact-center">Contact Center</a>, <a href="https://blog.isg-research.net/topic/contact-center-analytics">Contact Center Analytics</a>, <a href="https://blog.isg-research.net/topic/crm">CRM</a>, <a href="https://blog.isg-research.net/topic/ibm-watson">IBM Watson</a>, <a href="https://blog.isg-research.net/topic/text-analytics">Text Analytics</a> <hr> </div> <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://blog.isg-research.net/2012/12/11/ibm-watson-advances-a-new-category-of-cognitive-computing">IBM Watson Advances a New Category of Cognitive Computing</a></h2> <div class="author-meta"> Posted by <a href="https://blog.isg-research.net/author/mark-smith"> Mark Smith </a> on 11 December 2012 </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner_logo-3.jpg?width=200&name=vr_techaward_winner_logo-3.jpg" width="200" !important: srcset="https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner_logo-3.jpg?width=100&name=vr_techaward_winner_logo-3.jpg 100w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner_logo-3.jpg?width=200&name=vr_techaward_winner_logo-3.jpg 200w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner_logo-3.jpg?width=300&name=vr_techaward_winner_logo-3.jpg 300w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner_logo-3.jpg?width=400&name=vr_techaward_winner_logo-3.jpg 400w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner_logo-3.jpg?width=500&name=vr_techaward_winner_logo-3.jpg 500w, https://blog.isg-research.net/hs-fs/hubfs/Imported_Blog_Media/vr_techaward_winner_logo-3.jpg?width=600&name=vr_techaward_winner_logo-3.jpg 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <a href="http://www.ibm.com/watson" target="_blank">IBM Watson</a> blends existing and innovative technology into a new approach called cognitive computing. At the simplest operational level it is technology for asking natural language-based questions, getting answers and support appropriate action to be taken or provide information to make more informed decisions. The technology relies on massive processing power to yield probabilistic responses to user questions using sophisticated analytical algorithms. A cognitive system like Watson accesses... </div> <a href="https://blog.isg-research.net/2012/12/11/ibm-watson-advances-a-new-category-of-cognitive-computing"> Read More </a> Topics: <a href="https://blog.isg-research.net/topic/sales-performance">Sales Performance</a>, <a href="https://blog.isg-research.net/topic/supply-chain-performance">Supply Chain Performance</a>, <a href="https://blog.isg-research.net/topic/machine-learning">Machine Learning</a>, <a href="https://blog.isg-research.net/topic/it-performance">IT Performance</a>, <a href="https://blog.isg-research.net/topic/operational-performance">Operational Performance</a>, <a href="https://blog.isg-research.net/topic/business-analytics">Business Analytics</a>, <a href="https://blog.isg-research.net/topic/business-intelligence">Business Intelligence</a>, <a href="https://blog.isg-research.net/topic/business-performance">Business Performance</a>, <a href="https://blog.isg-research.net/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://blog.isg-research.net/topic/financial-performance">Financial Performance</a>, <a href="https://blog.isg-research.net/topic/ibm">IBM</a>, <a href="https://blog.isg-research.net/topic/information-management">Information Management</a>, <a href="https://blog.isg-research.net/topic/workforce-performance">Workforce Performance</a>, <a href="https://blog.isg-research.net/topic/cognitive-computing">Cognitive Computing</a>, <a href="https://blog.isg-research.net/topic/expert-systems">Expert Systems</a>, <a href="https://blog.isg-research.net/topic/ibm-watson">IBM Watson</a> <hr> </div> <script> // Check active classes var checkClass = function() { if ( $('.fil_item').hasClass('hide') ) { $('.fil_item').removeClass('hide'); } }; // Category filters $('.all').click( function() { checkClass(); }); // Active tag $('.bttn').click(function(){ $('.bttn').removeClass('active'); $(this).addClass('active'); }) </script> </div> <div class="blog-numeric-pagination span12 ">   </div> </div> <div class="blog-sidebar">   <style> .blog-sidebar h3 { font-size: 18px; margin-bottom: 30px; position: relative; color: var(--light_blue); padding-top:40px; } .btn-secondary, .filter-expand-link { text-transform: uppercase; background-color: #113049!important; border-color: #113049!important; color: #ffffff!important; transition: all .15s ease-in-out; animation-timing-function: ease-in-out; font-family: 'Open Sans', sans-serif; font-style: normal; font-weight: 500; text-decoration: none; font-size: 0.875rem; line-height: 1.4000000000000001rem; border-radius: 6px; height: 3.5rem; text-align: center; padding: 0 2.8125rem; border: 1px solid; display: -webkit-inline-box; display: -ms-inline-flexbox; display: inline-flex; -webkit-box-align: center; -ms-flex-align: center; align-items: center; } .filter-expand-link { text-transform: uppercase; background-color: #113049!important; border-color: #113049!important; color: #ffffff!important; transition: all .15s ease-in-out; animation-timing-function: ease-in-out; font-family: 'Open Sans', sans-serif; font-style: normal; font-weight: 500; text-decoration: none; font-size: 0.875rem; line-height: 1.4000000000000001rem; border-radius: 6px; height: 3.5rem; text-align: center; padding: 0 2.8125rem; border: 1px solid; display: -webkit-inline-box; display: -ms-inline-flexbox; display: inline-flex; -webkit-box-align: center; -ms-flex-align: center; align-items: center; } </style> <a href="https://cta-redirect.hubspot.com/cta/redirect/2035844/960cd0b7-7494-40d3-ac1c-5825d5a075be"><img class="hs-cta-img" id="hs-cta-img-960cd0b7-7494-40d3-ac1c-5825d5a075be" style="border-width:0px;" src="https://no-cache.hubspot.com/cta/default/2035844/960cd0b7-7494-40d3-ac1c-5825d5a075be.png" alt="JOIN OUR COMMUNITY"></a><script charset="utf-8" src="https://js.hscta.net/cta/current.js"></script><script type="text/javascript"> hbspt.cta.load(2035844, '960cd0b7-7494-40d3-ac1c-5825d5a075be', {"useNewLoader":"true","region":"na1"}); </script> <h3>Our Analyst Perspective Policy</h3> <ul> <li style="display: none; list-style: none;"> Ventana Research’s Analyst Perspectives are fact-based analysis and guidance on business, <g class="gr_ gr_12 gr-alert gr_gramm gr_inline_cards gr_run_anim Punctuation only-ins replaceWithoutSep" id="12" data-gr-id="12">industry</g> and technology vendor trends. 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If you have any issue with an Analyst Perspective, please email them to <a href="mailto:ChiefResearchOfficer@ventanaresearch.com" style="color: #284a7b;">ChiefResearchOfficer@ventanaresearch.com</a> </li> </ul> <a class="btn-secondary" href="https://www.ventanaresearch.com/analyst-perspective-policy">View Policy</a>  <div id="hs_cos_wrapper_module_168621267066296" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><style> </style> <h3 style="color: #255a89;">Our Analysts</h3>  <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://davidmenninger.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=100&name=Menninger.David%20Pic.Circle.png" alt="David Menninger" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=50&name=Menninger.David%20Pic.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=100&name=Menninger.David%20Pic.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=150&name=Menninger.David%20Pic.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=200&name=Menninger.David%20Pic.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=250&name=Menninger.David%20Pic.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=300&name=Menninger.David%20Pic.Circle.png 300w"> <h5 class="analyst_name">David Menninger</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://jefforr.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=100&name=Orr.Jeff.Circle.png" alt="Jeff Orr" width="100" data-constrained="true" caption="false" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=50&name=Orr.Jeff.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=100&name=Orr.Jeff.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=150&name=Orr.Jeff.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=200&name=Orr.Jeff.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=250&name=Orr.Jeff.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=300&name=Orr.Jeff.Circle.png 300w" sizes="(max-width: 100px) 100vw, 100px"> <h5 class="analyst_name">Jeff Orr</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://keithdawson.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=100&name=Dawson.Keith%20Pic.Circle.png" alt="Keith Dawson" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=50&name=Dawson.Keith%20Pic.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=100&name=Dawson.Keith%20Pic.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=150&name=Dawson.Keith%20Pic.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=200&name=Dawson.Keith%20Pic.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=250&name=Dawson.Keith%20Pic.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=300&name=Dawson.Keith%20Pic.Circle.png 300w"> <h5 class="analyst_name">Keith Dawson</h5> </a> </div> <div class="span6" style="text-align:center;"> <a href="https://marksmith.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=100&name=Smith.Mark%20Pic.Circle.png" alt="Mark Smith" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=50&name=Smith.Mark%20Pic.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=100&name=Smith.Mark%20Pic.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=150&name=Smith.Mark%20Pic.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=200&name=Smith.Mark%20Pic.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=250&name=Smith.Mark%20Pic.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=300&name=Smith.Mark%20Pic.Circle.png 300w"> <h5 class="analyst_name">Mark Smith</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://mattaslett.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=100&name=Aslett.Matt%20Pic.Circle.png" alt="Matt Aslett" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=50&name=Aslett.Matt%20Pic.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=100&name=Aslett.Matt%20Pic.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=150&name=Aslett.Matt%20Pic.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=200&name=Aslett.Matt%20Pic.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=250&name=Aslett.Matt%20Pic.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=300&name=Aslett.Matt%20Pic.Circle.png 300w"> <h5 class="analyst_name">Matt Aslett</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://matthewbrown.isg-research.net/"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=100&name=profile_vr_matthew_brown_circle_900x900.png" alt="Matthew Brown" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=50&name=profile_vr_matthew_brown_circle_900x900.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=100&name=profile_vr_matthew_brown_circle_900x900.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=150&name=profile_vr_matthew_brown_circle_900x900.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=200&name=profile_vr_matthew_brown_circle_900x900.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=250&name=profile_vr_matthew_brown_circle_900x900.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=300&name=profile_vr_matthew_brown_circle_900x900.png 300w"> <h5 class="analyst_name">Matthew Brown</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://robertkugel.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=100&name=Kugel.Robert%20Pic.Circle.png" alt="Robert Kugel" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=50&name=Kugel.Robert%20Pic.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=100&name=Kugel.Robert%20Pic.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=150&name=Kugel.Robert%20Pic.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=200&name=Kugel.Robert%20Pic.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=250&name=Kugel.Robert%20Pic.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=300&name=Kugel.Robert%20Pic.Circle.png 300w"> <h5 class="analyst_name">Robert Kugel</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://stephenhurrell.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=100&name=Hurrell.Stephen%20Pic.Circle.png" alt="Stephen Hurrell" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=50&name=Hurrell.Stephen%20Pic.Circle.png 50w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=100&name=Hurrell.Stephen%20Pic.Circle.png 100w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=150&name=Hurrell.Stephen%20Pic.Circle.png 150w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=200&name=Hurrell.Stephen%20Pic.Circle.png 200w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=250&name=Hurrell.Stephen%20Pic.Circle.png 250w, https://blog.isg-research.net/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=300&name=Hurrell.Stephen%20Pic.Circle.png 300w"> <h5 class="analyst_name">Stephen Hurrell</h5> </a> </div> </div>   <div class="row-fluid">  <div style="text-align: center;"> <a href="https://blog.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://blog.isg-research.net/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=100&name=ISG_Bug_Reverse_Transparent.png" alt="ISG Software Research" width="100" data-constrained="true" caption="false" 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href="https://blog.isg-research.net/topic/cio">CIO (112)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cio-callenges">cio callenges (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cirro">Cirro (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cisco">Cisco (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ciso">CISO (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/clarabridge">Clarabridge (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/clarity-systems">Clarity Systems (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/clickfox">Clickfox (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/close">close (43)</a> </li> <li style="display:none;"> <a 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href="https://blog.isg-research.net/topic/customer-journey-maps">Customer Journey Maps (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/customer-life-cycle">customer life cycle (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/customer-performance">Customer Performance (109)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/customer-relationship-management">Customer Relationship Management (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/customer-service">Customer Service (289)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/customer-service-and-support">customer service and support (20)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cxm">CXM (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/cybersecurity">Cybersecurity (5)</a> </li> <li 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Discovery (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-fabric">data fabric (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-governance">Data Governance (155)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-integration">Data Integration (82)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-integrity">data integrity (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-intelligence">Data Intelligence (15)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-lake">Data Lake (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-lakes">data lakes (43)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-management">Data Management (88)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-mart">data mart (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-mining">Data Mining (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-observability">Data Observability (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-operations">data operations (101)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-ops">Data Ops (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-orchestration">Data Orchestration (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-pipelines">Data Pipelines (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-platforms">data platforms (45)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-preparation">Data 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href="https://blog.isg-research.net/topic/data-visualization">Data Visualization (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-viz">data viz (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/data-warehousing">Data Warehousing (19)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/database">Database (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/database-as-a-service">Database as a Service (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/database-com">database.com (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/datameer">Datameer (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dataops">dataops (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dataprep">DataPrep (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/datawatch">Datawatch (14)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dayforce">dayforce (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ddi">DDI (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/debt">debt (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/decision">decision (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/decision-hub">Decision Hub (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/decision-intelligence">Decision Intelligence (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/decision-management">Decision Management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/decusoft">Decusoft (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/deep-learning">Deep Learning (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dell">Dell (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dell-boomi">Dell Boomi (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/demand-chain">Demand Chain (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/demand-generation">Demand Generation (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/demand-management">demand management (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/demand-planning">Demand Planning (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/design">design (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/designed-data">designed data 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href="https://blog.isg-research.net/topic/digital-marketing">Digital Marketing (28)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-operations">Digital Operations (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-publishing">Digital Publishing (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-security">Digital Security (23)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-technology">Digital Technology (292)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/digital-transformation">Digital transformation (20)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/direct-data-mapping">Direct Data Mapping (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/disaster-recovery">Disaster Recovery (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/discovery">Discovery (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/discovery-analytics">discovery analytics (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/discovery-tools">discovery tools (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/distribution">distribution (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dns">DNS (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/document-management">Document Management (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/dodd-frank">Dodd-Frank (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/domestic-payroll">Domestic Payroll (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/domo">Domo 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href="https://blog.isg-research.net/topic/dynamics-nav-dynamics-sl">Dynamics NAV Dynamics SL (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/e-discovery">e-discovery (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/echopass">Echopass (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/eclipse">Eclipse (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/edi">EDI (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ediscovery">eDiscovery (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/editorial">Editorial (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/effectiveness">effectiveness (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/eg-solutions">eg Solutions (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/elasticube">elasticube (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/eloqua">Eloqua (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/embedded-analytics">embedded analytics (95)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/emc">EMC (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/employee-engagement">Employee Engagement (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/employee-experience">employee experience (47)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/employee-onboarding">Employee Onboarding (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/employee-productivity">Employee Productivity (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/empower">Empower (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/end-to-end">end-to-end (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/endeca">endeca (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enghouse-interactive">Enghouse interactive (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enkata">Enkata (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-applications">Enterprise Applications (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-data-strategy">Enterprise Data Strategy (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-messaging-internet-of-things-iot-middle">Enterprise messaging, Internet of Things, IoT, mid (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-profitability-management">enterprise profitability management (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-resource-planning">Enterprise Resource Planning (72)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-risk-management">enterprise risk management (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-software">Enterprise Software (27)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-spreadsheet">enterprise spreadsheet (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterprise-tax">Enterprise Tax (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/enterworks">Enterworks (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/environment-management">Environment Management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/environmental">Environmental (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/envision">Envision (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/epicor">Epicor (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/epiphany">Epiphany (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/equifax">Equifax (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/equity-research">equity research (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/erm">ERM (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/erp">ERP (83)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/erp-and-continuous-accounting">ERP and Continuous Accounting (150)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/error">error (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/esg">ESG (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/esri">ESRI (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/essbase">Essbase (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ethority">eThority (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/event-data">Event Data (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/event-discovery">Event discovery (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/event-stream">Event Stream (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/event-stream-processing">Event Stream Processing (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/event-streams">Event Streams (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/exacttarget">ExactTarget (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/exadata">exadata (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/exalytics">Exalytics (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/excel">Excel (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/excentive">Excentive (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/executive">executive (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/expense">expense (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/expense-management">expense management (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/experience-management">Experience Management (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/expert-systems">Expert Systems (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/exploration">Exploration (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/exploratory-analytics">exploratory analytics (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/explorium">Explorium (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/extended-close">extended close (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/extended-reality">extended reality (16)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/external-data-platform">External Data Platform (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/exterro">Exterro (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/f-type">F-Type (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fasb">FASB (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fast-close">Fast close (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/feedback">Feedback (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fei">FEI (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ferf-ceo">FERF CEO (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/field-service">Field Service (29)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/finance">finance (53)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/finance-analytics">Finance Analytics (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/finance-cloud">finance cloud (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/finance-financial-applications-financial-close">Finance Financial Applications Financial Close (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/finance-performance-management">Finance Performance Management (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/finance-transformation">finance transformation (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial">financial (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-analytics">financial analytics (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-applications">Financial Applications (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-close">Financial Close (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-governance">Financial Governance (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-management">Financial Management (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-model">financial model (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-performance">Financial Performance (561)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-performance-2">financial performance (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-performance-management">Financial Performance Management (237)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-performance-management-fpm">Financial Performance Management (FPM) (14)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-planning">financial planning (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-regulation">financial regulation (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-reporting">financial reporting (15)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-risk-management">financial risk management (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-services">Financial Services (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-software">financial software (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-standards">financial standards (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-statement">financial statement (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financial-systems">financial systems (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financialforce">FinancialForce (15)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financialforce-com">FinancialForce.com (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/financials">financials (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/five9">Five9 (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/flow">flow (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fms">FMS (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/for-example-genesys">for example Genesys (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/forecast">Forecast (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/forecasting">forecasting (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fpa">FP&A (22)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fpm">FPM (83)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fraud">Fraud (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fuel50">Fuel50 (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/fusion-applications">Fusion 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(1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/gooddata">Gooddata (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/google">Google (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/governance">Governance (49)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/governance-risk">Governance & Risk (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/governance-risk-and-compliance">Governance Risk and Compliance (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/governance-risk-compliance-grc">Governance, Risk & Compliance (GRC) (143)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/grc">GRC (55)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/grc-governance-risk-compliance-risk-management-wat">GRC, governance, risk, 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href="https://blog.isg-research.net/topic/iac">IaC (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/iasb">IASB (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ibm">IBM (73)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ibm-business-analytics">IBM Business Analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ibm-db2">IBM DB2 (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ibm-predictive-customer-intelligence">IBM Predictive Customer Intelligence (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ibm-spss">IBM SPSS (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ibm-watson">IBM Watson (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ibp">IBP (4)</a> </li> <li style="display:none;"> <a 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href="https://blog.isg-research.net/topic/influencers">Influencers (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/infodiscovery">InfoDiscovery (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/infomgt-location">InfoMgt; Location (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/infopia">InfoPia (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/infor">Infor (31)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/infor-birst">Infor Birst (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/informatica">Informatica (22)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/informatica-cloud">Informatica Cloud (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/informatica-hparser">Informatica HParser (1)</a> </li> <li 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href="https://blog.isg-research.net/topic/information-builders-summit-2019">Information Builders Summit 2019 (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/information-discovery">Information Discovery (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/information-life-cycle-management">Information Life Cycle Management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/information-management">Information Management (381)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/information-management-im">Information Management (IM) (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/information-optimization">Information Optimization (52)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/information-platform">Information Platform (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/information-technology">Information Technology (47)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/infosphere">InfoSphere (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/initiatives-management">Initiatives Management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/initiatives-planning">Initiatives Planning (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/inkling">inkling (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/innovation-awards">Innovation Awards (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/insights">Insights (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/intacct">Intacct (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/integrated-business-planning">Integrated Business Planning (38)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/intelligent-automation">Intelligent Automation (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/intelligent-cx">Intelligent CX (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/intelligent-marketing">intelligent marketing (16)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/intelligent-memory">Intelligent Memory (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/intelligent-sales">intelligent sales (22)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/intelligent-self-service">Intelligent Self-Service (22)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/interactions">Interactions (1)</a> </li> 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href="https://blog.isg-research.net/topic/office-of-finance">Office of Finance (504)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/office-of-revenue">Office of Revenue (39)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/office-of-sales">Office of Sales (15)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/olap">OLAP (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/omnichannel">Omnichannel (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/omnichannel-commerce-digital-kdigital">Omnichannel, Commerce, Digital kDigital (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/on24">On24 (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/onboarding">Onboarding (1)</a> </li> <li style="display:none;"> <a 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href="https://blog.isg-research.net/topic/openworld">OpenWorld (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/opera-solutions">Opera Solutions (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/operational-data-platforms">operational data platforms (39)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/operational-intelligence">Operational Intelligence (180)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/operational-management">Operational Management (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/operational-performance">Operational Performance (696)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/operational-performance-management-opm">Operational Performance Management (OPM) (13)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/operational-planning">Operational Planning (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/operations">Operations (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/operations-supply-chain">Operations & Supply Chain (90)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/oracle">Oracle (78)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/oracle-cloud">Oracle Cloud (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/oracle-fusion-hcm">Oracle Fusion HCM (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/orcaeyes">OrcaEyes (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/orchestration">Orchestration (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/order-management">Order Management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/order-to-cash">Order-to-Cash (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/overall-operational-leadership">Overall Operational Leadership (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/oversight-systems">Oversight Systems (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/overtone">Overtone (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/paas">PaaS (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/panopticon">Panopticon (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/paraccel">Paraccel (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pardot">Pardot (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/partner-experience">Partner Experience (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/partner-management">partner management (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/patersons">Patersons (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/paxata">Paxata (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pay-equity">Pay Equity (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pay-for-performance">Pay for Performance (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/payroll-management">Payroll Management (17)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/payroll-optimization">Payroll Optimization (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pdi">PDI (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pentaho">Pentaho (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/people-analytics">People Analytics (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/people-cloud">People Cloud (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/peoplefluent">Peoplefluent (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/peoplesoft">PeopleSoft (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/performance">Performance (30)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/performance-analytics">Performance Analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/performance-management">Performance Management (89)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/perillon">Perillon (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/personalization">Personalization (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pervasive">Pervasive (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pim">PIM (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pim-product-information-management-sales-marketing">PIM, Product Information Management, Sales, Market (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pipkins">Pipkins (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pitney-bowes">Pitney Bowes (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pivotal-hd">Pivotal HD (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pivotlink">PivotLink (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/planmill">PlanMill (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/planning">Planning (88)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/planview">Planview (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/plateau">Plateau (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/platfora">Platfora (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/platform-as-a-service">Platform as a service (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/playbook">Playbook (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/plex">Plex (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/plunk">Plunk (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/portfolio-management">Portfolio Management (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/portrait-software">Portrait Software (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/potus-department-of-labor-flsa-part-541-overtime-r">POTUS, Department of Labor, FLSA, Part 541, Overti (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/powercenter">PowerCenter (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/predictive">Predictive (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/predictive-analytics">Predictive Analytics (203)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/predictive-hcm">Predictive HCM (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/predictive-planning">Predictive Planning (49)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/predixion">Predixion (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/price-and-revenue-management">Price and Revenue Management (70)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/price-optimization">Price Optimization (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pricing-and-promotion-management">Pricing and Promotion Management (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pricing-management">pricing management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pro">PRO (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/process-management">process management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/process-mining">Process Mining (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/procure-to-pay">Procure-to-Pay (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/procurement">procurement (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/product-experience-management">product experience management (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/product-information-management">Product Information Management (90)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/professional-services">Professional Services (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/professional-services-automation">Professional Services Automation (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/profit-velocity">Profit Velocity (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/profitability">Profitability (14)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/profitability-management">profitability management (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/project-management">Project Management (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/project-planning">Project Planning (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/project-portfolio-management">Project Portfolio Management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/projecthelp">ProjectHelp (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/projectops">ProjectOps (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/projector">Projector (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/promptbook">Promptbook (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/property-technology">Property Technology (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pros">PROS (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pros-pricing">PROS Pricing (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/psa">PSA (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/publishing">Publishing (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/purchasing">purchasing (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/purchasing-sourcing-payments">Purchasing/Sourcing/Payments (16)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pv-accelerator">PV Accelerator (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/pxm">PXM (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qad">QAD (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qlik">Qlik (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qlik-qlik-sense">Qlik Qlik Sense (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qlik-qonnections">Qlik Qonnections (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qlik-analytics-qlik-sense-qlik-business-intelligen">Qlik, Analytics, Qlik Sense, Qlik, Business intell (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qliktech">Qliktech (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qlikview">QlikView (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qualtrics">Qualtrics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/quantrix">Quantrix (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/quinterian">Quinterian (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/quotas">Quotas (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/qvidian">Qvidian (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/r">R (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/ransomware">Ransomware (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rapide">Rapide (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rapidminer">Rapidminer (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rdbms">RDBMS (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/real-estate">real estate (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/real-time">Real-time (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/reconciliation">Reconciliation (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/recovery">Recovery (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/recruiting">Recruiting (41)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/recurring-revenue">Recurring Revenue (19)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/report">report (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/reporting">Reporting (78)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/reporting-xbrl-ixbrl-document-management">Reporting, XBRL, iXBRL, document management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/research">Research (16)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/resilience">Resilience (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/responsetek">ResponseTek (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/retail-analytics">Retail Analytics (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue">Revenue (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue-and-lease-accounting">revenue and lease accounting (15)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue-management">Revenue Management (33)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue-performance">Revenue Performance (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue-performance-management">Revenue Performance Management (13)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue-recognition">revenue recognition (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revenue-lease-and-tax-accounting">Revenue, Lease and Tax Accounting (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revolution">Revolution (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/revolution-analtyics">Revolution Analtyics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rightnow">RightNow (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rim">RIM (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/risk">Risk (37)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/risk-compliance-grc">Risk & Compliance (GRC) (17)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/risk-analytics">Risk Analytics (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/riversand">Riversand (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/roambi">Roambi (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/robotic-automation">robotic automation (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/robotic-finance">robotic finance (38)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/robotic-process-automation">Robotic Process Automation (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/roi">ROI (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rpa">RPA (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/rypple">Rypple (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sop">S&OP (13)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/saas">SaaS (27)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sab-miller">SAB Miller (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/saba">Saba (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sage">Sage (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sage-software">Sage Software (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales">Sales (169)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-and-operations-planning">Sales and Operations Planning (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-cloud">Sales Cloud (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-coaching">Sales Coaching (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-commission">Sales Commission (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-compensation">Sales Compensation (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-effectiveness">Sales Effectiveness (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-enablement">sales enablement (16)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-enablement-and-execution">Sales Enablement and Execution (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-engagement">Sales Engagement (25)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-force-automation">Sales Force Automation (13)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-forecasting">Sales Forecasting (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-operations">Sales Operations (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-performance">Sales Performance (446)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-performance-management">Sales Performance Management (77)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-performance-management-spm">Sales Performance Management (SPM) (13)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-planning">Sales Planning (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-planning-and-analytics">Sales Planning and Analytics (18)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-tax">Sales Tax (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-marketing-sales-performance-management-marke">Sales, Marketing, Sales Performance Management, Ma (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sales-sfa-spm-sales-performance-management-sales-c">Sales, SFA, SPM, Sales Performance Management, Sal (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/salescloud">SalesCloud (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/salesforce-com">Salesforce.com (58)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap">SAP (76)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-epm">SAP EPM (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-hana">SAP HANA (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-insider">SAP insider (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-lumira">SAP Lumira (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-netweaver">SAP NetWeaver (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-predictive-analytics">SAP predictive analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sap-teched">SAP TechEd (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sapphire">SAPPHIRE (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sarbanes-oxley">Sarbanes Oxley (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sas">SAS (26)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sas-institute">SAS institute (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sasb">SASB (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sase">SASE (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/savi">Savi (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/scm">SCM (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/scm-demand-planning">SCM Demand Planning (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/scout-rfp">Scout RFP (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/scribe-software">Scribe Software (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/search">Search (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sec">SEC (19)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sec-software">SEC Software (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/secfinops">SecFinOps (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/secops">SecOps (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/security">Security (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/security-posture">Security Posture (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sedar">SEDAR (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/self-service">Self-service (41)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/semantic-model">semantic model (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/service-supply-chain">Service & Supply Chain (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/service-cloud">Service Cloud (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/servigistics">Servigistics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sfa">SFA (24)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sfdc">SFDC (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sharepoint">SharePoint (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/shoretel">ShoreTel (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/siemens-enterprise-communications">Siemens Enterprise Communications (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/signal-demand">Signal Demand (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/silverpop">SilverPop (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/simba">Simba (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smart-financial-close">Smart Financial Close (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smart-manufacturing">Smart Manufacturing (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smart-phones">Smart Phones (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smart-watches">Smart Watches (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smarter-analytics">Smarter Analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smarter-workforce">Smarter Workforce (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/smb">SMB (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/snaplogic">SnapLogic (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/snowfly">Snowfly (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/soa">SOA (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/soc">SOC (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social">Social (13)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-business">Social Business (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-collaboration">Social Collaboration (17)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-crm">Social CRM (128)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-dynamx">Social Dynamx (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-media">Social Media (365)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-media-analytics">Social Media Analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-media-intelligence">Social Media Intelligence (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/social-recognition">Social Recognition (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/socialtext">SocialText (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sococare">SoCoCare (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/softscape">Softscape (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/software">Software (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/software-as-a-service">Software as a Service (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sourcing">sourcing (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sovereign-cloud">Sovereign Cloud (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sox">SOX (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/spago-solutions">Spago Solutions (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/spatial-data-quality">Spatial Data Quality (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/speech-analytics">Speech Analytics (177)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/splunk">Splunk (8)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/spm">SPM (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/spotfire">Spotfire (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/spreadsheets">Spreadsheets (10)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/spss">SPSS (9)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sql-h">SQL-H (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sqlstream">SQLstream (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/star-analytics">Star Analytics (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/statistics">Statistics (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/stibo-systems">Stibo Systems (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/stratahadoop">Strata+Hadoop (56)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/streaming-analytics">Streaming Analytics (28)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/streaming-data">Streaming Data (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/streaming-data-events">Streaming Data & Events (32)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/subscriber-experience">Subscriber Experience (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/subscription-billing">Subscription Billing (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/subscription-management">Subscription Management (68)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/subscription-recurring-revenue-zuora">Subscription, Recurring Revenue, Zuora (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/successfactors">SuccessFactors (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sumo-logic">Sumo Logic (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sumtotal">SumTotal (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sumtotal-systems">SumTotal Systems (11)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sungard">Sungard (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sunsystems">Sunsystems (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/supplier-relationship-management">supplier relationship management (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/supply-chain">Supply Chain (12)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/supply-chain-management">supply chain management (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/supply-chain-performance">Supply Chain Performance (253)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/supply-chain-planning">Supply Chain Planning (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/surface">Surface (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/surveys">Surveys (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sustainability">Sustainability (38)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sustainability-and-esg">Sustainability and ESG (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sustainability-management">Sustainability Management (7)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/swordciboodle">SwordCiboodle (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sybase">Sybase (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sybase-iq">Sybase IQ (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/sybase-mobile-industry">Sybase. 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style="display:none;"> <a href="https://blog.isg-research.net/topic/tax-planning">tax planning (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tax-software">Tax Software (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tax-datawarehouse">Tax-Datawarehouse (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tax-tax-provision-transfer-pricing">tax; tax provision; transfer pricing (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tcm">TCM (6)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/technology">Technology (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/technology-innovation">Technology Innovation (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/technology-innovation-award">Technology Innovation Award (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/technology-spending">Technology Spending (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/technology-vendors">Technology Vendors (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/telephony">Telephony (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/teradata">Teradata (16)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/teradata-aster">Teradata Aster (4)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/text-analytics">Text Analytics (182)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tez">Tez (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/thomson-reuters-multinational">Thomson-Reuters multinational (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/threat-landscape">Threat Landscape (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/threat-management">Threat Management (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tibco">Tibco (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tidemark">Tidemark (5)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/time-attendance">Time & Attendance (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tm">TM (2)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/tm1">TM1 (3)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/topic">Topic (1)</a> </li> <li style="display:none;"> <a href="https://blog.isg-research.net/topic/total-compensation-management">Total Compensation Management (46)</a> </li> <li style="display:none;"> 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and BI Foundation", "mainEntityOfPage": "https://blog.isg-research.net/ibm-builds-on-analytics-and-bi-foundation", "datePublished": "29/11/2022", "dateModified": "29/11/2022", "articleBody": "In today’s data-driven world, organizations need real-time access to up-to-date, high-quality data and analysis to keep pace with changing market dynamics and make better strategic decisions. By mining meaningful insights from enterprise data quickly, they gain a competitive advantage in the market. Yet, organizations face a multitude of challenges when transitioning into an analytics-driven enterprise. Our Analytics and Data Benchmark Research shows that more than one-quarter of organizations find it challenging to access data sources and integrate data and analytics in business processes. Vendors such as IBM offer a broad set of analytics tools with self-service capabilities that allows organizations to reduce IT dependencies and enables decision-makers to recognize performance gaps, market trends and new revenue opportunities. Its technology can simplify data access for self-service applications, enabling users to make business decisions informed by insights and take the guesswork out of decision-making. IBM is a leading software provider and has offerings in almost all business sectors. IBM Business Analytics offers data analytics and artificial intelligence (AI) with an integrated workflow to enable organizations to implement data-driven decisions and reduce data and process silos. IBM Cognos Analytics with Watson is its business intelligence (BI) solution that can integrate reporting, analysis, dashboards, stories, explorations, modeling, and other functionality. Users can access data modules, packages, datasets, and uploaded files as sources of data. Reports and dashboards continue to be the most important type of analytics for organizations. Our research shows that more than three-quarters of users still use traditional reports and dashboards to drive insights. Some of IBM’s other offerings include its Planning Analytics for budgeting and forecasting, Watson Studio to automate MLOps, SPSS for advanced statistical analytics, and CPLEX to build optimization models. Ventana Research has examined various IBM offerings as part of our focus on data and how organizations are adopting strategies to derive greater value from analytics. My colleague Matt Aslett recently covered IBM Cloud Pak for Data in his perspective. Cloud Pak combines the functionality for data compute, management and governance with automation and AI to support self-service analytics and data science. Our colleague, Rob Kugel, has covered IBM Planning Analytics in the past. IBM has invested heavily in augmented intelligence research that builds on its existing technology ecosystem. I’ve written previously on how organizations can use augmented intelligence to reduce dependency on artificial intelligence and machine learning (AI/ML) skills. It can enable organizations to automate AI/ML analyses and accelerate business processes. As large enterprises continue to evolve in response to constant competitive pressures and unforeseen events, they need a broad range of analytical capabilities. IBM can help organizations keep up with the increasing volume of data and analytics workloads, improve processes and potentially reduce IT costs. IBM recently announced new software designed to help enterprises break down data and analytics silos to facilitate data-driven decisions and navigate unpredictable disruptions: IBM Business Analytics Enterprise, which is a suite including Cognos Analytics with Watson and Planning Analytics with Watson; and also IBM Analytics Content Hub, which enables users to access analyses from multiple vendors in a unified dashboard. Our research shows that organizations have an increasing need for analytics and planning tools, and they are looking for technologies that can help them accelerate their processes. IBM had also previously announced an expansion to its embeddable-AI software portfolio with the release of three new libraries designed to help IBM Ecosystem partners, clients and developers build their own AI-powered products and bring them to market. This expansion allows users a scalable way to build natural language processing (NLP), speech-to-text and text-to-speech capabilities into applications across any hybrid, multi-cloud environment. IBM has made strides in bringing its products together but must continue to do to align them even more closely together, so users can seamlessly move between products. Organizations need a broad set of analytics capabilities, and the IBM portfolio provides those capabilities along with an ecosystem where users can perform all types of analysis. I recommend that organizations that are in the process of becoming data-driven evaluate IBM’s data and analytics capabilities. Their portfolio enables organizations to integrate enterprise data and allows them to build digital, operational, analytical, data science and AI models, and automate processes using intelligent workflows. Further, IBM enables users to deploy data science, predictive analytics, and data visualization within its unified ecosystem to gain insights and accelerate decision-making. And IBM’s Watson is helping to expand its augmented intelligence capabilities to make analytics easier to use and more powerful. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/AP_DM_IBM_Builds_on_Analytics_and%20BI_Foundation.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://blog.isg-research.net/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "IBM Brings Sophistication to Customer Analytics and Prediction", "mainEntityOfPage": "https://blog.isg-research.net/2014/07/30/ibm-brings-sophistication-to-customer-analytics-and-prediction", "datePublished": "30/07/2014", "dateModified": "30/07/2014", "articleBody": "During recent IBM analyst big data event, I learned about a new product, IBM Predictive Customer Intelligence. It extracts and processes customer-related data from multiple sources to analyze customer-related activities and has capabilities to predict customer behavior and actions. Predictive Customer Intelligence is built on IBM’s big data platform and supports extraction and integration of data from multiple sources, internal and external, and from structured and unstructured data. It can process data created by third-party products, such as text-based files of data created by converting speech to text. The product can capture and analyze customer interactions from multiple communication channels such as voice, email, text messages, chat and Web usage scripts and social media posts. Predictive Customer Intelligence has four primary modules, for predictive modeling, reporting, real-time scoring and a real-time analytics data repository, which are connected by the IBM Integration Bus. These modules support a predefined process in which users build models from customer data stored in analytics real-time customer database and use them or predefined models to run real-time analysis against the customer data and produce scores, recommendations, reports and dashboards related to customer activities. The outputs can be delivered through a variety of channels such as outbound email, direct mail or text message. This can help contact center agents provide personalized and contextualized responses to customers’ questions. Other outputs can be used to produce targeted marketing campaigns or to respond to customer interactions through other communications channels. My benchmark research into next-generation customer analytics shows a need for such a product because companies have up to 21 potential sources of customer data. These include transactional business applications such as CRM and ERP, customer data warehouses, spreadsheets, call recordings and text-based files containing content from email, forms, letters, text messages, chat scripts, Web scripts and social media posts. All of these not only contain valuable customer information but also interaction data from which companies need to derive insights into customers’ feelings about products and services and other aspects of the business. The research shows companies have difficulty in extracting value from this data, partially because on average they use only six sources of customer data in their customer analytics. Interaction data is especially problematic because most of it is unstructured and requires tools that can automatically access and extract insights from them; few companies have such tools. This situation also is becoming more complex, as my benchmark research into next-generation customer engagement shows: Companies are supporting more channels of interaction and expect volumes of interactions to grow in every channel as our research shows up to 17 channels in play. IBM Predictive Customer Intelligence has capabilities that can help companies meet these challenges. However, a close look reveals that it is not one but 10 individual products (not including three connectors) packaged together. Organizations therefore need to understand the cost and operational impact of managing and use these products. At the big data analytics event, Frank Theisen (IBM VP of front-office transformation for Europe) summed up the information challenges companies face; they need to know: What happened? Why did it happen? What can be learned? What action should be taken? What could happen in the future? Ventana Research believes that big data analytics can answer these questions. For example, my benchmark into next-generation customer analytics shows that one-quarter (26%) of companies have deployed a dedicated customer analytics product and have found it has helped them improve the customer experience and their analysis of business performance. More generally my colleague Tony Cosentino wrote about three Ws that are key: What data you have, what information you want to derive from data, and what action should be taken as a result of insights gained from it. Once you can answer these questions you can decide which analytics product best fits your requirements. IBM focuses intensively on its technology sometimes to the extent of obscuring the business applications of those systems. One prime example is that more and more IBM big data products are moving to the direction of IBM Watson and methods of cognitive computing. Basically Watson is a platform that can search very large volumes of information to deliver insights from the data by use of natural language, and it is smart in that it learns as it searches, so that future answers are more refined and targeted to the questions asked. Such capabilities are particularly useful for analyzing the very large volumes of customer interaction data companies accumulate; they help identify trends, hot issues and focused information to help personalize responses and put them in the context of an overall customer relationship. Our next-generation customer analytics benchmark research shows usability is the top priority for selecting analytics software: 64 percent of companies said it is very important. To provide it vendors should support point-and-click access to information on mobile devices and visual ways of showing the results of analytics. One case study IBM used during the day illustrated this; the user collects a vast array of data, integrates it and delivers analysis in visual formats on Apple iPads. This is well-suited for assisting customer-related activities that happen in real time (such as phone calls) where users need instant access to up-to-date information in forms they can understand immediately. Companies already have huge amounts of customer-related data, and if you factor in the increasing volume of electronic communications, social media and the coming Internet of Things, this need will grow more acute. IBM has a variety of analytic products and is developing more. The challenge is to figure out which IBM products can best process what data and produce the required information and insights to drive decisions and action. Predictive Customer Intelligence and IBM’s other big data analytics are worth considering in organizations’ efforts to improve understanding of customers and their experiences. Regards, Richard J. Snow VP & Research Director", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-19.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "ISG Software Research", "url": "https://blog.isg-research.net/author/isg-software-research", "sameAs": "https://www.linkedin.com/company/ventana-research" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Genesys and IBM to Improve Customer Engagement with IBM Watson", "mainEntityOfPage": "https://blog.isg-research.net/2014/06/14/genesys-and-ibm-to-improve-customer-engagement-with-ibm-watson", "datePublished": "14/06/2014", "dateModified": "14/06/2014", "articleBody": "The contact center market continues to shift focus from handling customer calls as efficiently as possible to providing superior customer engagement across multiple touch points. The latest advancement is an joint announcement from IBM and Genesys who have signed a partnership agreement to provide “smarter customer engagement”. The agreement includes a technology partnership and a joint marketing plan, and brings together IBM’s Watson Engagement Advisor and Genesys’ Customer Experience Platform. IBM Watson first became known by beating expert human contestants on the TV show Jeopardy! Since then it has impacted the medical industry by advising doctors on medical care, and more recently IBM created a smart mobile app that is able to advise and resolve customer issues. IBM Watson is an cognitive computing platform that uses machine learning to provide responses to questions through its natural language question based search interface that can process large volumes of information including a knowledge base of history and trained responses to find the most relevant and probabilistic response. Its machine learning can refine its responses from previous interactions, thus making the outcomes increasingly relevant. In the mobile app it can capture text entered into the app, search data from in-house and publicly available information sources and return information most closely related to the request. For example Watson can capture a customer’s request for an insurance quote, search all available insurance information based on the person’s extended customer profile and return information on the most appropriate policy for that customer and circumstances and refine it based on the individual unique requirements. The IBM Watson technology received the Ventana Research Technology Innovation Award for its ability to change how companies operate in taking actions and making decisions. Genesys was an early developer of customer/telephony integration (CTI) and call routing. Over time management has combined acquisitions and internal development efforts to create a contact center in the cloud product set that is available in the cloud. Its original product set has thus been extended to include management of multiple channels of communication, single-queue routing regardless of type of interaction, workforce optimization, an agent desktop and analytics. Nearly half of companies in my benchmark research into the contact center in the cloud are considering such systems to improve customer engagement. Several research studies including next generation customer engagement show that companies are deploying more channels of interaction to meet customer expectations; on average companies now support more than seven channels with seventeen possible. These are a combination of what are commonly called assisted channels, in which a person responds to the customer, and self-service where the customer interacts solely with technology, such as an interactive voice response (IVR) system. The research shows that both approaches create issues. Assisted service depends on the skills of the people who handle interactions and their abilities to access the right systems and information. The agent’s desktop is a major determinant of whether this is hard or easy. Self-service depends on how well companies have set up the technology and how closely it fits customer expectations. In this respect my research shows that companies have not done a very good job; for example, nearly two-thirds of IVR interactions and Web-based self-service attempts end up with the customer taking the option to speak with an agent. In simple terms these systems are not smart enough. The IBM/Genesys partnership is intended to address this. Genesys has built interfaces from its agent desktop and self-service channels to pass data to IBM Watson, which applies its cognitive computing capabilities and returns with specific information to the questions asked. The results can be passed to the agent through the desktop to suggest the best action or delivered to the customer through the self-service channel. In either cases the customer gets relevant information, which contributes to a better experience, and the company may get a better business outcome. If you want to understand more about cognitive computing, our educational overview will help and my colleagues recent analysis of IBM billion dollar investment into IBM Watson. My research has led me to insist that the customer experience is now the primary business differentiator and is the top driver for improving customer engagement in three quarters (74%) of organizations according to our customer engagement research. It has almost become impossible to compete solely on product, service or price; how customers feel during and after interactions is what counts and what determines the actions they take. This new partnership has the potential to deliver better responses to customer inquiries and requests and should thus improve the experience. It also provides a competitive advantage for Genesys to differentiate its offering to others in providing truly a smarter agent desktop and customer self-service. The alliance of these two major vendors will be worth watching for companies striving to improve internal business processes and better meet customer expectation for relevant and timely responses to their questions. Regards, Richard J. Snow VP & Research Director – Customer Engagement", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Imported_Blog_Media/vr_ngce_research_08_all_channels_for_customer_engagement-20.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "ISG Software Research", "url": "https://blog.isg-research.net/author/isg-software-research", "sameAs": "https://www.linkedin.com/company/ventana-research" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "IBM Delivers New Talent Management Suite", "mainEntityOfPage": "https://blog.isg-research.net/2014/03/13/ibm-delivers-new-talent-management-suite", "datePublished": "13/03/2014", "dateModified": "13/03/2014", "articleBody": "At its recent Connect 2014 event IBM announced IBM Kenexa Talent Suite, an integrated talent management suite. The release strengthens its Smarter Workforce initiative by combining IBM and Kenexa products and services in one human capital management (HCM) offering. IBM Kenexa Talent Suite also addresses increasing efforts by human resources organizations to optimize their activities through more effective use of technology, a topic covered in our 2014 HCM research agenda. Specifically, the release integrates talent management process automation capabilities with collaboration and also can be complemented with its workforce analytics to help organizations be more efficient and productive; our benchmark research shows these are the leading benefits of using human capital analytics systems. The new suite provides a direction for IBM’s HCM products and strengthens its market position, as it combines IBM’s strongest talent management applications with platform-level collaboration services, analytics and big data functionality – all of which IBM does well – in a centralized, role-based portal environment. Our research shows that collaboration and big data technologies are the top choices for improving analytics and that such capabilities are increasingly being used by executives and managers to make decisions, and IBM seems on track with these needs in this new release. In addition, the suite that operates in cloud computing environment combines a set of applications spanning acquisition and optimization of talent through recruiting, skills assessment, performance management, succession planning and compensation along with social collaboration. Additionally, the suite can be complemented with IBM Watson Foundations, which provides for big data and information management capabilities. This in effect offers information optimization capabilities across human capital information. For more about IBM’s investments in the Watson business unit, see my colleague Mark Smith’s recent analysis. Using it organizations will be able to predict broader workforce trends, including insights based on social information gathered within the system. I would expect IBM to do even more with leveraging big data, analytics and planning into its applications especially with predictive analytics since it has a very in-depth set of software from the IBM portfolio. Talent Suite also incorporates capabilities from IBM SmartCloud Connections to provide collaboration services. The company says that adding social collaboration to learning will be added to the suite later in 2014 where it already provides learning on mobile technology. This release should raise the bar on competition among the large vendors. With IBM, Oracle and SAP all offering parts of the core human capital management suite and strong next-generation capabilities, customers have more options to choose from. What’s most interesting about this latest round of suites is the power of the next-generation capabilities being announced from other large HCM vendors including collaboration and mobile with Oracle, and collaboration and analytics with SAP. These next-generation capabilities from the larger size HCM vendors, along with more from smaller vendors, offer customers more than just simple process automation benefits. Many organizations today already have automated some of these talent management processes. So evaluating IBM’s release and the products of other large vendors is not primarily a question of getting new HR processes automated, though that may be the case. Rather, it is about looking at the advantages of having a full suite with next-generation capabilities. Integration centralizes the information, administrative tasks and the user experience, bringing less administration for HR and IT and more consistency for users. In addition, better analytical and collaboration capabilities can increase productivity (61%) or enable organizations to better engage and retain more of their workforce (52%), among several other benefits we saw in our research on human capital analytics. On the downside, organizations can lose some best-of-breed functionality in certain modules, and there are costs of implementation and training – critical considerations for most organization. Overall, however, if you have not looked at IBM recently, this new suite is worth considering, especially if your organization already uses any of its other talent management products. Regards, Ventana Research", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Imported_Blog_Media/vr_hca_06_technology_for_human_capital_analytics_improvement-7.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "ISG Software Research", "url": "https://blog.isg-research.net/author/isg-software-research", "sameAs": "https://www.linkedin.com/company/ventana-research" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "IBM Bets a Billion to Mobilize Watson Business Unit and Monetize Cognitive Computing", "mainEntityOfPage": "https://blog.isg-research.net/2014/01/13/ibm-bets-a-billion-to-mobilize-watson-business-unit-to-monetize-cognitive-computing", "datePublished": "13/01/2014", "dateModified": "13/01/2014", "articleBody": "With much fanfare and a rarely seen introduction by CEO Ginni Rometty, IBM launched IBM Watson as a new business unit focused on cognitive computing technology and solutions, now being led by Senior Vice President Mike Rhodin. The announcement is summarized here:. Until now IBM Watson was important but had neither this stature in IBM’s organizational structure nor enough investment to support what the company proclaims is the third phase of computing. As IBM tells it, computing paradigms began with the century-old tabular computing, followed by the age of programmatic computing, in which IBM developed many products and advancements. The third phase is cognitive computing, an area in which the company has invested significantly to advance its technology. IBM has been on this journey for some time, long before the IBM Watson system beat humans on Jeopardy!. Its machine-learning efforts started with the IBM 704 and computer checkers in the 1950s, followed by decades of utilizing the computing power of the IBM 360 mainframe, the IBM AS/400, the IBM RS/6000 and even IBM XT computers in the 1980s. Now IBM Watson is focused on reaching the full potential of cognitive computing. If IBM is right that cognitive computing will be the next wave of innovation in the industry and a new phase of computing, it has placed itself at the center of a substantial new market opportunity. Even at the most basic level to simplify the process of making information more available is what IBM Watson provides and our information optimization research finds is very important to 65 percent of organization. The company says it has invested $1 billion and placed up to two thousand skilled people in the new business unit. It also is spending $100 million on the incubation of companies that are building on the Watson platform, and has a new and dedicated building in Lower Manhattan, known as Silicon Alley, its focal point for cognitive computing ideas that IBM has unveiled to the public. There is no question that IBM Watson is innovate as we recognized in 2012 as being the recipient of our overall operation innovation technology innovation award. These recent actions build on IBM’s announcement last fall that it is commercializing IBM Watson to enable developers and partners to innovate on the platform. Its launch of the IBM Watson Developers Cloud marketplace introduces new offerings and content essential to building its ecosystem of resources to meet existing and future demand for applications of cognitive computing. The step is essential in that it will maximize the number of products using IBM Watson and provide IBM with a springboard to exponentially grow its efforts. At the same time, IBM is working with academic institutions IBM’s announcements included new products to complement the IBM Watson portfolio and give it a broader footprint and value to customers. The first new product announced is IBM Watson Discovery Advisor, a tool that helps pharmaceutical companies plow through massive volumes of big data. This is a good place to start, as harvesting the right information for specific roles and purposes is the foundation of cognitive computing, enabling organizations not just to access information but to synthesize it. The next announcement was IBM Watson Analytics, a product previously known as Project Neo and introduced to the market last fall, which my colleague Tony Cosentino covered. Incubated in IBM’s business analytics group and using a spectrum of analytic and discovery technology, the product and people who worked on it and other efforts are being transferred to the IBM Watson business unit. Though it was not initially built for IBM Watson today, the discovery and exploratory technology integrates the pillars of analytics, helping facilitate a knowledge discovery process whereby you can explore data through natural language and discover new insights. The move to shift IBM Watson Analytics was unexpected and introduces new pressure to market and sell the product. It has growing potential for line-of-business analysts, who will want to examine this and other tools from IBM’s business analytics group. Only time will tell if IBM will be able to fully monetize the product’s potential through its IBM Watson effort, but the move could be its short-term method to gain customers and revenue. It definitely will be a complement when it interfaces to IBM Watson and utilizes the knowledge that Watson creates. The next major product announcement was IBM Watson Explorer, a big data analytics tool that enables collaborative discovery, navigation and search across information in applications. Both analytics tools advance the science of big data technologies but focus on more than just the mechanics of what big data does, as described by the “four V’s”: volume, variety, velocity and veracity. Rather, they address the value of what is possible through the so-called W’s, focusing on the who, what, where, when and why. This is what we call information optimization, facilitating the business potential of not just big data but of cognitive computing. For its part, IBM is applying its big data and information management efforts to IBM Watson, categorizing them as IBM Watson foundations. This is critical as our information optimization research finds that organizations do not have enough capabilities to integrate and normalize information from disparate sources as the largest shortcoming of technology in 45 percent of organizations. By integrating and utilizing these big data and business analytics tools as part of IBM Watson, cognitive computing will from a competency perspective be more advanced even if these products are not directly needed for enabling IBM Watson. With this much at stake IBM was not going to leave customer endorsements to chance, and while it has taken some criticism that customer commitment might not be as high as it has claimed, that question was answered at the IBM Watson event. For one, the medical and healthcare industry was front and center to validate its commitment to IBM, represented by organizations such as the Cleveland Clinic and Memorial Sloan-Kettering Cancer Center. Most interesting was an early peek at the potential of mass consumerization of IBM Watson. The first example was presented by e-commerce facilitator Fluid: Its Fluid XPS is focused on changing the digital experience of consumers by gaining access to information about their needs for products and services in a holistic manner. The example it promoted cold weather gear for camping by asking a question as a front end to the North Face website. A second example was the potential to have IBM Watson be the natural language interface for finding a vacation destination, specifying certain criteria like class, price, type and climate of location; today this requires repetitive tasks such as filling out forms and making your own comparisons to determine where you want to go and for what price. The concept was presented by Terry Jones, the former CEO of Sabre and Travelocity and chairman of Kayak. He has more than 40 years of experience in the travel industry and now consults about business innovation through his company, called Essential Ideas. IBM also demonstrated how cognitive computing can provide the next generation of marketing can synthesize the interactions and psychology of individuals to more effectively market to them. These examples point to the potential of enabling natural-language recognition technology to discover relevant responses that guide users’ actions and decisions. As part of my analysis over the past couple of years, I’ve been following this step forward and wrote about the new category of cognitive computing. In 2013, IBM brought forward IBM Watson Engagement Advisor and focused on smarter customer service through a simpler engagement approach to improving the customer experience, a topic my colleague Richard Snow has assessed. This effort by IBM is as our customer engagement research has found is centered on improving the customer experience as found in 74 percent of organizations. I have also seen IBM demonstrate similar solutions for employees and managers as part of human capital management. More important, these solutions embrace mobile computing whereby devices can be used as input and response tools anywhere, at any time which our research finds smartphones accessible to be used in 73 percent of organizations according to our information optimization research. Intellectually, IBM continues to advance its research and scientific developments to ensure that it can transition its work into products that customers can use. At the launch of the IBM Watson business unit, IBM Research’s Dr. Guruduth Banavar brought forward some of the latest thinking on cognitive science and the ability to teach machines to reason and what is called neurosynaptics, a discussion that is available on IBM Research’s cognitive computing page. The material is fascinating; it provides insight on the future of computing and how it will impact roles and businesses in the next decade. As it begins to scale its offering, part of IBM’s challenge is to manage the continuous information feeds that effectively make IBM Watson smarter. While IBM does not talk much about the content aspects of what is required, it is clearly more than just loading files, and these efforts are just as important as librarians are to libraries, whereby they are not just stewards to a collection of books but ensure the value and improvement of the library. There is still a level of mystery on the technical mechanics and readiness of the platform that the company needs to address before the natural-language interface is ready to work its magic. In addition, IBM is still using a natural-language form of text and working through how it can make voice mainstream with IBM Watson, as Apple and Google and others have done. IBM has been working on speech in research for some time and more recently with Nuance, who IBM announced a partnership with back in 2011, but it has yet to demonstrate this capability to the mainstream public, which indicates hesitation on how fast it plans to use voice and speech as the interface. While IBM was not able to fully monetize its early efforts in speech technology, it is now becoming mainstream in the consumer market but has yet to evolve significantly in the business markets as part of enterprise software. I am looking forward to seeing more of what it can do in terms of voice and speech input and Watson talking iteratively to help expedite what is truly natural language for humans. IBM does not often create new business units and elevate them to this level of commitment and investment for the future. While the business goals for IBM Watson are lofty from both revenue and computing perspectives, no other company – not even Microsoft, Oracle or SAP – has both the established technology foundation and the people and financial resources that IBM has to make this a reality. IBM should be congratulated for making the investment in cognitive computing and helping create new jobs and opportunity that will incubate not just in Silicon Alley but across the globe as others realize the full potential. Our technology innovation research finds that increasing the value of an organization is very important to over half (56%) of organizations which is exactly what IBM is hoping will increase its business opportunity. If you want to catch up on the dialogue and resources related to this topic, you can search #IBMWatson on Twitter and follow @IBMWatson. If you want to learn more about IBM Watson and cognitive computing, go to www.ibm.com/watson and you will find more information about the technology, our research on the topic and the value of this new computing paradigm. Regards, Mark Smith CEO & Chief Research Officer", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Imported_Blog_Media/vr_techaward_winner-2.jpg", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Mark Smith", "url": "https://blog.isg-research.net/author/mark-smith", "sameAs": "http://www.linkedin.com/in/markallensmith" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "IBM Improving the Science to Apply Business Analytics for Better Customer Engagement", "mainEntityOfPage": "https://blog.isg-research.net/2013/07/04/ibm-improving-the-science-to-apply-business-analytics-for-better-customer-engagement", "datePublished": "04/07/2013", "dateModified": "04/07/2013", "articleBody": "I recently wrote how IBM is making customer analytics smarter. Since then IBM has run events in North America and Europe to demonstrate how it is continuing these efforts and expanding into other areas. Outside of the customer space you can read how my colleagues assess its efforts: Mark Smith discusses HR, Robert Kugel sees its impact on business overall, and Tony Cosentino addresses it in IT. Our research My focus remains the customer and I have learned more about what IBM is doing in social media, identity reconciliation, visualization, mobile apps and big data. As part of its customer analytics portfolio, IBM has social media analytics. Going beyond basic social media analytics, the product brings together IBM research assets for demographic, geographic and behavioral analytics, uses its SPSS advanced analysis to support sentiment analysis and segmentation, is capable of identifying influencers and analyzing their social activities, has big data built in, and includes a series of prebuilt dashboards that can be configured to individual user requirements. It works with several forms of social input, including blogs, microblogs, review sites, news sites and video. The analysis can identify hot topics, trends and brand risks, as well as measuring customer sentiment, a company’s reach, geographic variations and a company’s share of comments posted on social media sites. Perhaps most importantly it can understand root causes of posts and thus identify new business opportunities, spot weaknesses in products, services and marketing and sales messages and suggest improvements. The combination of capabilities allows users to build closed-loop processes that, for example, analyze social content and its associated demographic profile, build targeted surveys to learn about different customer segments in more detail, apply predictive analytics, and build outreach programs to specific groups within a segment. We recently awarded TELERYX our 2013 Business Technology Leadership Award for Social Media that use IBM to do many of the items that I have listed. My research into the contact center in the cloud shows that today companies need to support multiple channels for customer engagement or risk losing certain customer segments including the traditional ones like inbound calls (96%) and outbound calls (76%). The research shows that on average companies support approximately five different channels. Among other challenges, this demand has added to the issue of identity resolution – finding out who the customer is. Each channel typically has its own identifier, for example, a fixed line phone number, a mobile phone number, an email address, a Twitter handle, a LinkedIn reference number and of course a home address. When customers have multiple account numbers and variations of their names, companies have a big job to tie these all together to identify which interactions are with the same person. IBM designed Infosphere Identity Insight to help prevent fraud, but it also can support analysis of customer data to identify who a customer really is. The technical details are rather complicated, but as the customer experience grows in importance and therefore knowing the customer becomes even more important, companies should pay more attention to this issue and evaluate how products such as Identity Insight can help. I continued my update about IBM products at a recent analyst event in London on big data. Many of the topics mirrored what my colleagues have written about in the blogs I identified earlier, but a couple of things struck home to me. When IBM talks big data, it means really big. One case study presentation talked about downloading hundreds of thousands of terabytes of data after a flight so engineers can analyze the plane’s performance. To support this level of processing, IBM has developed new hardware and software tools that make previous data analysis performance look slow in comparison. This scale makes processing of customer data seem simple, and I realized that big data only comes into customer engagement in processing social media posts and call recordings, both of which companies typically have in the hundreds of thousands. In this context it is surprising that although IBM has built advanced text analytics into its products, it has yet to include voice analytics. The other aspect of big data analytics that struck me as increasingly important in my field is predictive analytics. In this era when the customer is king, predicting customer behavior is the most important business analytics capability according to our technology innovation benchmark to help companies be more forward looking. IBM puts this all into the context that analytics is evolving. First there was descriptive analytics, which told users what had happened, then came predictive analytics, which told companies what might happen, then came descriptive analytics, which tells users how they can achieve the best outcome from their activities, and now we are moving into an era of cognitive analytics, which uses past and current events from as many sources of data as possible to tell users what their next action should be. As IBM adds these abilities to its products, users can process more forms of customer data and build more advanced predictive models; this is something else companies should evaluate. One of the sessions at the London event focused on making analytics easier to use. IBM demonstrated 20 different ways of visualizing information, not all of which are yet generally available. Beyond that IBM also gave a glimpse of nearly 200 other ways of visualizing data – yes, 200 – that can be configured to match any requirements. As these capabilities become available, users will have access to them on mobile devices, which will support setting up a range new uses on the device. All this might seem excessive, but during discussions on customer metrics I have learned that the form presentation, especially visualization, of metrics is almost as important as the actual numbers; something as simple has having a chart scaled the wrong way around can create a wrong impression. But making visualization actionable will require more improvement by IBM to make the discovery process on it more interactive as my colleague has pointed out. Another session focused on Watson Engagement Advisor, which I wrote about earlier this year. This recently launched IBM platform allows companies to build smart mobile apps. It is based on the Watson platform, which can intelligently search for information buried in any form of structured or text-based data. It thus enhances mobile apps by connecting customer requests to the information they are looking for and can, for example, lead customers through complex purchases by using rules-based searches driven by context. Engagement Advisor can search publicly available sources of data, so it could be a concern that companies undermine customer trust by demonstrating how much personal data they can access. However, designed correctly these apps have the potential to dramatically improve what customers can achieve through self-service; they have the capability to intelligently connect to a person if a transaction does not complete within the app. It is early days in their adoption, but I recommend that companies track how this kind of analytics could help them innovate in customer engagement. Over all these sessions I learned a lot about how IBM is applying its considerable resources to systems that support customer engagement. With building on the demand of business analytics that our research finds as the most important technology innovation priority as first ranked by 39 percent of organizations. Building on IBM business analytics technology portfolio is the investment in advancing research and development of future use for the area of customer analytics. Underpinning many of these developments are research teams that not many other companies could afford and a product portfolio that through a combination of in-house developments and numerous acquisitions spans information management, big data, marketing, customer feedback, analytics, mobile apps in the cloud. I imagine that pulling all these sources into the solutions I have described is not easy, even for a company of IBM’s size. However from what I heard and saw, IBM is becoming a major force in what is now a vital area for customer analytics and how to improve customer engagement and customer experience management. Regards, Richard J. Snow VP & Research Director", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Imported_Blog_Media/vr_leadershipwinner-14.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "ISG Software Research", "url": "https://blog.isg-research.net/author/isg-software-research", "sameAs": "https://www.linkedin.com/company/ventana-research" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "IBM Watson Engagement Advisor for Smarter Customer Service", "mainEntityOfPage": "https://blog.isg-research.net/2013/05/26/ibm-watson-engagement-advisor-for-smarter-customer-service-2", "datePublished": "25/05/2013", "dateModified": "25/05/2013", "articleBody": "Recently my colleague Mark Smith wrote about the IBM Watson platform. Mark is our expert on technically complex subjects like IBM Watson and‎ cognitive computing and the value it can provide to organizations and wrote an educational white paper on the topic. In fact IBM Watson was awarded the 2012 Ventana Research Technology Innovation Award. I focus on the customer and the customer experience, but I became engaged with the launch of the IBM Watson Engagement Advisor, which uncannily brings the two together. I conclude from my research into customer experience management and discussions around the customer experience that consumers want three related things from companies: to recognize them as individuals, to handle any interaction within the context of their overall relationship and previous interactions, and to provide answers that are personalized to their individual needs. Furthermore, as I described in my recent blog about the 2.0 customer, they are increasingly likely to interact with companies through smart mobile devices. Added up these requirements present a major challenge for companies, and the solution lies in data. Organizations have ever increasing volumes of customer data, found in records in CRM, ERP and other business applications, letters, forms, email, call recordings, scripts collected during Web and chat sessions, text messages, video recordings and now social media posts. These all add up to what we call big data, and it comes in structured, semistructured and unstructured forms. To provide a personalized, in-context response to any interaction, companies have to make sense of all this data and build applications that follow typical customer interactions (for example, a request for information, a billing inquiry, a sales inquiry or a complaint) and use it as the interaction is taking place. This is the context in which IBM Watson Engagement Advisor debuts. It uses the Watson platform to analyze all available data, make sense of it and provide information back to the application the consumer is using to interact with the organization. Its built-in natural-language processing engine allows it to extract relevant words and phrases and combinations of both from text-based input and to search for relevant data in customer records, documents and other relevant sources. To use IBM’s favorite word, Watson is smart, so once it has followed a process, it learns from that and can improve how it carries out the process in the future. The consumer can thus interact using natural language and receive answers that are personalized and in context, and which should improve in both senses over time and experience. I recognize that companies may have difficulty understanding this new approach to customer experience management. To engage them IBM has announced an early customer adoption program in which it will provide support and guidance on what interactions are appropriate to automate in this way and how to configure the technology and gain access to the data sources; the target of the program is to have an initial system running in six weeks. My recommendation here is the same as I made last year when several vendors announced tools that help companies build mobile customer service apps: Think of the customer first and build apps to match what they want, not what you think will improve the efficiency of your interaction-handling. It is often said that customer service is the only true differentiator in competitive markets. The challenge I see is that the boundaries between marketing, sales and customer service are blurring, and what consumers want is answers, and they want them immediately during every interaction. As data volumes and types grow, finding answers is like looking for the proverbial needle in a haystack. Watson may be a platform capable of matching up to this challenge. I recommend that companies looking to improve the customer experience take a close look at the IBM Watson Engagement Advisor. Regards, Richard J. Snow VP & Research Director", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Imported_Blog_Media/vr_2012_techaward_winner_logo3-1.jpg", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "ISG Software Research", "url": "https://blog.isg-research.net/author/isg-software-research", "sameAs": "https://www.linkedin.com/company/ventana-research" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "blog.isg-research.net", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "IBM Watson Advances a New Category of Cognitive Computing", "mainEntityOfPage": "https://blog.isg-research.net/2012/12/11/ibm-watson-advances-a-new-category-of-cognitive-computing", "datePublished": "11/12/2012", "dateModified": "11/12/2012", "articleBody": "IBM Watson blends existing and innovative technology into a new approach called cognitive computing. At the simplest operational level it is technology for asking natural language-based questions, getting answers and support appropriate action to be taken or provide information to make more informed decisions. The technology relies on massive processing power to yield probabilistic responses to user questions using sophisticated analytical algorithms. A cognitive system like Watson accesses structured and unstructured information within an associated knowledge base to return responses that are not simply data but contextualized information that can inform users’ actions and guide their decisions. This is a gigantic leap beyond human decision-making using experience based on random sources from the industry and internal sets of reports and data. This innovative new approach to computing is designed to aid humans by working with natural language – English in the case of today’s Watson. This approach earned Watson the 2012 Technology Innovation Award in the category of Overall Operational Innovation. For those of you who are not used to the word cognitive, the foundation of cognition is the sum of all the thinking processes that contribute to gaining knowledge for problem-solving. In computational systems these processes are modeled using hardware and software; machine-based cognition thus is a step toward imbuing an artificial system with attributes we typically consider human: the abilities to think and learn. Watson builds on a foundation of evidence from preexisting decisions and knowledge sources that it can load for reference in future inquiries. The evidence-based reasoning that Watson employs to answer question is part of the big deal in its approach. Watson supports three types of engagement – ask, discover and decide – that take natural language questions, find facts to support a decision process, then gets probabilistic guidance on decisions. This goes beyond search and retrieval technology; machine learning and processing of questions using very large volumes of data, commonly referred to as big data, is the foundation on which Watson as a cognitive system operates. Most important is the continuous learning method and what I would call adaptive intelligence. While machine learning and pattern-based analytics are part of the cognitive system, the ability to process big data efficiently to provide a probabilistic set of recommendations is just the kind of innovation many industries need. IBM has focused much of its work on Watson on healthcare, with potential life-saving implications in an environment where doctors must make crucial decisions in the midst of pressure from the complexity, costs, overload of information and policies. Watson can ingest large volumes of information from reports and documents that can accelerate its learning processes to support a range of healthcare needs. Watson can be used in three areas in healthcare: teaching, practice and payment. IBM works with Wellpoint to support doctors in making decisions, and also eliminating waste or misapplied treatments that insurance providers have to cover. Watson is being used today to determine where improvements can be made in cancer treatment. IBM has targeted specific Watson solutions to help in the research, diagnosis and treatment, care and utilization aspects of battling cancer. IBM has a huge opportunity to bring innovation to business through the use of Watson, and has been experimenting with a number of deployments to test its potential. Innovative technology is a priority today for business improvement initiatives (60%) and to improve the quality of business processes (57%) – the top two factors driving technology selection according to our business technology innovation benchmark research. IBM has been working with organizations in healthcare and financial services, but believes Watson could be useful in just about every industry that must have what I call better situation intelligence that must accommodate current conditions and preexisting information to determine the best answer. While IBM will not be the only supplier of cognitive systems, it is pretty much the sole supplier of one that can be purchased and adapted to a business today. IBM is still working to improve the methods by which its cognitive system operates, as well as the interface with which it delivers answers. As IBM moves forward, it will be challenged to create attractive packages and prices for Watson and its computing technology (i.e. hardware, memory, storage and processing potential), as this new approach is not something that organizations have experienced before. Despite this challenge, IBM Watson represents a step forward that the IT and technology industry does not see very often. After my assessment of IBM Watson at the IBM Analyst Insights (Twitter: @AnalystInsights) where I got to have an in depth discussion with the leaders of IBM Watson provided more insight to what is possible with the technology and path for its investments into its cognitive system. I would recommend that organizations take a look at the future of business technology computing that will be able to make a significant impact on the operations of any organization. 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ISG Software Research Analyst Perspectives | IBM Watson