David Menninger's 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.</p> <p><strong><a href="https://www.ventanaresearch.com/services/vendors/analyst_relations" rel="noopener">Analyst Relations</a></strong></p> <p><strong><a href="https://www.ventanaresearch.com/services/vendors/demand_generation" rel="noopener">Demand Generation</a></strong></p> <p><strong><a href="https://www.ventanaresearch.com/services/vendors/product-marketing" rel="noopener">Product Marketing</a></strong></p> <p><strong><a href="https://www.ventanaresearch.com/vendor-coverage" target="_self" role="menuitem">Market Coverage</a></strong></p> <p><strong><a href="https://www.ventanaresearch.com/briefing" target="_self" role="menuitem">Request a Briefing</a></strong><br><br><br></p></div> <span id="hs_cos_wrapper_dnd_area-module-2_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_simple_menu" style="" data-hs-cos-general-type="widget" data-hs-cos-type="simple_menu"><ul></ul></span> <div class="bottom_rich_text"> </div> </div> </div> </div> </div> </div> <script src="https://davidmenninger.isg-one.com/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 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://davidmenninger.isg-one.com/hubfs/_images/_backgrounds_expertise/2024_VR_AI_Expertise_Image_AdobeStock_637057734_1200px.jpg); ">  <div class="row-fluid"> <div class="blog-header__inner dnd-row"> <div class="blog--post__image dnd-section"> <img class="analyst-header-photo" src="https://davidmenninger.isg-one.com/hubfs/_images/_team/Menninger.David%20Pic.Circle.png" style="padding: 10px; "> <br> <h1 class="analyst-header-title">David Menninger's 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://davidmenninger.isg-one.com/2011/04/29/analytics-for-it-cobblers-children-need-shoes">Analytics for IT: Cobbler’s Children Need Shoes</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-one.com/author/david-menninger"> David Menninger </a> on <span class="post-date">29 April 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>As part of our largest-ever <span style="text-decoration: underline;"><a href="//www.ventanaresearch.com/bam" target="_blank">research study on business analytics</a></span>, which surveyed more than 2,600 organizations covering the maturity and competency of business, IT and vertical industries<span style="text-decoration: underline;">,</span> we looked at how IT is applying analytics to support their own business activities. One of the things we found is that, charged with enabling business units to use information systems as effectively as possible, the IT department, like the shoemaker’s barefoot children in the old tale, typically stands last...</p> </div> <a href="https://davidmenninger.isg-one.com/2011/04/29/analytics-for-it-cobblers-children-need-shoes"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-one.com/topic/predictive-analytics">Predictive Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/business-performance">Business Performance</a>, <a href="https://davidmenninger.isg-one.com/topic/information-applications">Information Applications</a>, <a href="https://davidmenninger.isg-one.com/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-one.com/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/it-analytics">IT Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/it-service-management">IT Service Management</a>, <a href="https://davidmenninger.isg-one.com/topic/itil">ITIL</a>, <a href="https://davidmenninger.isg-one.com/topic/itsm">ITSM</a>, <a href="https://davidmenninger.isg-one.com/topic/it-performance-management-itpm">IT Performance Management (ITPM)</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://davidmenninger.isg-one.com/2011/04/20/predictive-analytics-are-on-the-rise">Predictive Analytics Are on the Rise</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-one.com/author/david-menninger"> David Menninger </a> on <span class="post-date">20 April 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>In various forms, business intelligence (BI) – as queries, reporting, dashboards and online analytical processing (OLAP) – is being used increasingly widely. And as basic BI capabilities spread to more organizations, innovative ones increasingly are exploring how to take advantage of the next step in the strategic use of BI: predictive analytics. The trend in Web searches for the phrase “predictive analytics” gives one indication of the <span style="text-decoration: underline;"><a href="http://www.google.com/insights/search/#q=predictive%20analytics&cmpt=q">rise in interest in this area</a></span>. From 2004 through 2008, the...</p> </div> <a href="https://davidmenninger.isg-one.com/2011/04/20/predictive-analytics-are-on-the-rise"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-one.com/topic/predictive-analytics">Predictive Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/predixion">Predixion</a>, <a href="https://davidmenninger.isg-one.com/topic/r">R</a>, <a href="https://davidmenninger.isg-one.com/topic/revolution-analtyics">Revolution Analtyics</a>, <a href="https://davidmenninger.isg-one.com/topic/sales">Sales</a>, <a href="https://davidmenninger.isg-one.com/topic/sales-performance">Sales Performance</a>, <a href="https://davidmenninger.isg-one.com/topic/sas">SAS</a>, <a href="https://davidmenninger.isg-one.com/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-one.com/topic/supply-chain-performance">Supply Chain Performance</a>, <a href="https://davidmenninger.isg-one.com/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-collaboration">Business Collaboration</a>, <a href="https://davidmenninger.isg-one.com/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/business-mobility">Business Mobility</a>, <a href="https://davidmenninger.isg-one.com/topic/business-performance">Business Performance</a>, <a href="https://davidmenninger.isg-one.com/topic/business-technology">Business Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/cio">CIO</a>, <a href="https://davidmenninger.isg-one.com/topic/cloud-computing">Cloud Computing</a>, <a href="https://davidmenninger.isg-one.com/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://davidmenninger.isg-one.com/topic/financial-performance">Financial Performance</a>, <a href="https://davidmenninger.isg-one.com/topic/ibm-spss">IBM SPSS</a>, <a href="https://davidmenninger.isg-one.com/topic/information-builders">Information Builders</a>, <a href="https://davidmenninger.isg-one.com/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/kxen">KXEN</a>, <a href="https://davidmenninger.isg-one.com/topic/netezza">Netezza</a>, <a href="https://davidmenninger.isg-one.com/topic/oracle">Oracle</a>, <a href="https://davidmenninger.isg-one.com/topic/workforce-performance">Workforce Performance</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://davidmenninger.isg-one.com/2011/04/01/the-information-management-technology-revolution-in-2011">The Information Management Technology Revolution in 2011</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-one.com/author/david-menninger"> David Menninger </a> on <span class="post-date">01 April 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>The information management (IM) technology market is undergoing a revolution similar to the one in the <a href="//davidmenninger.ventanaresearch.com/2011/03/21/the-business-intelligence-technology-revolution-in-2011/">business intelligence (BI) market</a>. We define information management as the acquisition, organization, control and use of information to create and enhance business value. It is a necessary ingredient of successful BI implementations, and while some vendors such as <a href="//davidmenninger.ventanaresearch.com/2010/11/27/ibm-makes-infosphere-information-server-a-force-in-it/">IBM</a>, Information Builders, Pentaho and <a href="//davidmenninger.ventanaresearch.com/2011/03/14/sap-enterprise-information-management-4-0-a-technology-secret/">SAP</a> are in addition integrating their BI and IM offerings, each discipline involves...</p> </div> <a href="https://davidmenninger.isg-one.com/2011/04/01/the-information-management-technology-revolution-in-2011"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-one.com/topic/data-quality">Data Quality</a>, <a href="https://davidmenninger.isg-one.com/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-one.com/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-collaboration">Business Collaboration</a>, <a href="https://davidmenninger.isg-one.com/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/business-technology">Business Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/cio">CIO</a>, <a href="https://davidmenninger.isg-one.com/topic/complex-event-processing">Complex Event Processing</a>, <a href="https://davidmenninger.isg-one.com/topic/data-governance">Data Governance</a>, <a href="https://davidmenninger.isg-one.com/topic/data-integration">Data Integration</a>, <a href="https://davidmenninger.isg-one.com/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-one.com/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/it-performance-management-itpm">IT Performance Management (ITPM)</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://davidmenninger.isg-one.com/david-menninger/2011/03/21/the-business-intelligence-technology-revolution-in-2011">The Business Intelligence Technology Revolution in 2011</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-one.com/author/david-menninger"> David Menninger </a> on <span class="post-date">20 March 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>The business intelligence (BI) technology market is undergoing a revolution. I’ve been working in this segment for 20 years, and it is and has been an exciting market in which to work, but its dynamic nature can be daunting to organizations trying to evaluate, purchase and deploy BI to improve their business processes. And despite the advances our <a href="//www.ventanaresearch.com/bipm">benchmark research</a> shows high levels of dissatisfaction with and immaturity in BI capabilities within organizations.</p> </div> <a href="https://davidmenninger.isg-one.com/david-menninger/2011/03/21/the-business-intelligence-technology-revolution-in-2011"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-one.com/topic/sales-performance">Sales Performance</a>, <a href="https://davidmenninger.isg-one.com/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-one.com/topic/supply-chain-performance">Supply Chain Performance</a>, <a href="https://davidmenninger.isg-one.com/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-collaboration">Business Collaboration</a>, <a href="https://davidmenninger.isg-one.com/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/business-mobility">Business Mobility</a>, <a href="https://davidmenninger.isg-one.com/topic/business-performance">Business Performance</a>, <a href="https://davidmenninger.isg-one.com/topic/business-technology">Business Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/cio">CIO</a>, <a href="https://davidmenninger.isg-one.com/topic/cloud-computing">Cloud Computing</a>, <a href="https://davidmenninger.isg-one.com/topic/collaboration">Collaboration</a>, <a href="https://davidmenninger.isg-one.com/topic/customer-contact-center">Customer & Contact Center</a>, <a href="https://davidmenninger.isg-one.com/topic/enterprise-software">Enterprise Software</a>, <a href="https://davidmenninger.isg-one.com/topic/financial-performance">Financial Performance</a>, <a href="https://davidmenninger.isg-one.com/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/mobility">Mobility</a>, <a href="https://davidmenninger.isg-one.com/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/it-performance-management-itpm">IT Performance Management (ITPM)</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://davidmenninger.isg-one.com/david-menninger/2011/03/18/sas-and-its-business-intelligence-information-management-direction">SAS and its Business Intelligence & Information Management Direction</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-one.com/author/isg-software-research"> ISG Software Research </a> on <span class="post-date">17 March 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>I recently attended SAS Institute’s annual analyst conference. My colleague covered the multibillion-dollar company’s <a href="//marksmith.ventanaresearch.com/2011/03/15/sas-institute-the-multi-billion-dollar-business-analytics-supplier-2/">strategy and the event</a>. Now I want to look into some of the details of SAS’s products for business analytics and how they are supported with business intelligence (BI), and information management. Although SAS is not a publicly traded company and therefore is not required to make the financial disclosures that others are, the company revealed numerous financial statistics....</p> </div> <a href="https://davidmenninger.isg-one.com/david-menninger/2011/03/18/sas-and-its-business-intelligence-information-management-direction"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-one.com/topic/sas">SAS</a>, <a href="https://davidmenninger.isg-one.com/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-one.com/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/business-performance">Business Performance</a>, <a href="https://davidmenninger.isg-one.com/topic/business-technology">Business Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/cio">CIO</a>, <a href="https://davidmenninger.isg-one.com/topic/collaboration">Collaboration</a>, <a href="https://davidmenninger.isg-one.com/topic/enterprise-software">Enterprise Software</a>, <a href="https://davidmenninger.isg-one.com/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-one.com/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/mobility">Mobility</a>, <a href="https://davidmenninger.isg-one.com/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/it-performance-management-itpm">IT Performance Management (ITPM)</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://davidmenninger.isg-one.com/david-menninger/2011/03/14/sap-enterprise-information-management-4-0-a-technology-secret">SAP Enterprise Information Management 4.0: A Technology Secret</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-one.com/author/david-menninger"> David Menninger </a> on <span class="post-date">13 March 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>SAP has launched its Enterprise Information Management (EIM) 4.0 release as part of its “<span style="text-decoration: underline;"><a href="https://www.sapevents.com/SAP/RunBetterTour/index.cfm?fuseaction=reg.Landing">Run Better Tour</a></span>.”  It includes a <span style="text-decoration: underline;"><a href="http://www.sap.com/solutions/sapbusinessobjects/large/eim/index.epx">broad range of information management components</a></span> spanning data integration, data quality, data profiling, metadata management and more. The launch was done in conjunction with <span style="text-decoration: underline;"><a href="//davidmenninger.ventanaresearch.com/2011/03/02/sap-business-intelligence-4-0/">SAP Business Intelligence (BI) 4.0</a></span>, which got much bigger billing at the event –to the point where one might call this a stealth marketing campaign. However, the event did identify three themes intended...</p> </div> <a href="https://davidmenninger.isg-one.com/david-menninger/2011/03/14/sap-enterprise-information-management-4-0-a-technology-secret"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-one.com/topic/data-quality">Data Quality</a>, <a href="https://davidmenninger.isg-one.com/topic/sap">SAP</a>, <a href="https://davidmenninger.isg-one.com/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-one.com/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/business-technology">Business Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/cio">CIO</a>, <a href="https://davidmenninger.isg-one.com/topic/complex-event-processing">Complex Event Processing</a>, <a href="https://davidmenninger.isg-one.com/topic/data-governance">Data Governance</a>, <a href="https://davidmenninger.isg-one.com/topic/data-integration">Data Integration</a>, <a href="https://davidmenninger.isg-one.com/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-one.com/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/it-performance-management-itpm">IT Performance Management (ITPM)</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://davidmenninger.isg-one.com/david-menninger/2011/03/02/sap-business-intelligence-4-0">SAP Business Intelligence 4.0</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-one.com/author/david-menninger"> David Menninger </a> on <span class="post-date">01 March 2011 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Last week SAP launched the 4.0 Release of its Business Intelligence and Enterprise Information Management products in conjunction with the New York City stop on its “<span style="text-decoration: underline;"><a href="https://www.sapevents.com/SAP/RunBetterTour/index.cfm?fuseaction=reg.Landing">SAP Run Better Tour</a></span>”. My colleague Mark Smith has already covered the announcement in the context of some of today’s<a href="//marksmith.ventanaresearch.com/2011/02/25/sap-retrofits-business-intelligence-and-information-management-to-meet-it-and-business-needs/"> <span style="text-decoration: underline;">major technology trends</span></a>. In this post, I’ll focus on the specifics of the product announcements.</p> </div> <a href="https://davidmenninger.isg-one.com/david-menninger/2011/03/02/sap-business-intelligence-4-0"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-one.com/topic/sap">SAP</a>, <a href="https://davidmenninger.isg-one.com/topic/social-media">Social Media</a>, <a href="https://davidmenninger.isg-one.com/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/business-technology">Business Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/cio">CIO</a>, <a href="https://davidmenninger.isg-one.com/topic/collaboration">Collaboration</a>, <a href="https://davidmenninger.isg-one.com/topic/enterprise-software">Enterprise Software</a>, <a href="https://davidmenninger.isg-one.com/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-one.com/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/mobility">Mobility</a>, <a href="https://davidmenninger.isg-one.com/topic/operational-intelligence">Operational Intelligence</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://davidmenninger.isg-one.com/2010/11/27/advantages-and-challenges-of-in-memory-databases-and-processing">Advantages and Challenges of In-Memory Databases and Processing</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-one.com/author/david-menninger"> David Menninger </a> on <span class="post-date">26 November 2010 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Interest in and development of in-memory technologies have increased over the last few years, driven in part by widespread availability of affordable 64-bit hardware and operating systems and the performance advantages in-memory operations provide over disk-based operations. Some software vendors, such as SAP with its High-Performance Analytic Appliance (HANA) project <a href="http://www.sap.com/about/newsroom/press.epx?PressID=14179" target="_blank">has been advancing with momentum</a>, have even suggested that we can put our entire analytic systems in memory.</p> </div> <a href="https://davidmenninger.isg-one.com/2010/11/27/advantages-and-challenges-of-in-memory-databases-and-processing"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-one.com/topic/database">Database</a>, <a href="https://davidmenninger.isg-one.com/topic/enterprise-data-strategy">Enterprise Data Strategy</a>, <a href="https://davidmenninger.isg-one.com/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/cio">CIO</a>, <a href="https://davidmenninger.isg-one.com/topic/complex-event-processing">Complex Event Processing</a>, <a href="https://davidmenninger.isg-one.com/topic/in-memory-computing">In-Memory Computing</a>, <a href="https://davidmenninger.isg-one.com/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-one.com/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/it-performance-management-itpm">IT Performance Management (ITPM)</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://davidmenninger.isg-one.com/2010/11/27/ibm-makes-infosphere-information-server-a-force-in-it">IBM Makes InfoSphere Information Server a Force in IT</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-one.com/author/david-menninger"> David Menninger </a> on <span class="post-date">26 November 2010 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>In the weeks leading up to and as part of its Information On Demand Conference that <a href="//www.ventanaresearch.com/blog/commentblog.aspx?id=4022" target="_blank">my colleague assessed</a>, IBM introduced version 8.5 of InfoSphere Information Server and several related product updates. <a href="//www.ventanaresearch.com/research/article.aspx?id=3750" target="_blank">As my colleague suggested earlier</a>, IBM has an ambitious agenda to provide comprehensive information management capabilities through a combination of product development and acquisitions. The breadth of this portfolio is impressive, and <a href="http://www-01.ibm.com/software/data/integration/" target="_blank">InfoSphere Information Server 8.5</a> makes significant strides...</p> </div> <a href="https://davidmenninger.isg-one.com/2010/11/27/ibm-makes-infosphere-information-server-a-force-in-it"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-one.com/topic/enterprise-data-strategy">Enterprise Data Strategy</a>, <a href="https://davidmenninger.isg-one.com/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-analytics">Business Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/cio">CIO</a>, <a href="https://davidmenninger.isg-one.com/topic/data-integration">Data Integration</a>, <a href="https://davidmenninger.isg-one.com/topic/ibm">IBM</a>, <a href="https://davidmenninger.isg-one.com/topic/information-management">Information Management</a>, <a href="https://davidmenninger.isg-one.com/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/it-performance-management-itpm">IT Performance Management (ITPM)</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://davidmenninger.isg-one.com/2010/11/27/its-alive-a-look-at-why-the-software-ecosystem-matters-to-you">It’s Alive!: A Look at Why the Software Ecosystem Matters to You.</a></h2> <div class="author-meta"> Posted by <a href="https://davidmenninger.isg-one.com/author/david-menninger"> David Menninger </a> on <span class="post-date">26 November 2010 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png" width="200" !important: srcset="https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=100&name=Slider_3.png 100w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=200&name=Slider_3.png 200w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=300&name=Slider_3.png 300w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=400&name=Slider_3.png 400w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=500&name=Slider_3.png 500w, https://davidmenninger.isg-one.com/hs-fs/hubfs/Homepage_Slider/Slider_3.png?width=600&name=Slider_3.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>With the ongoing spate of mergers and acquisitions in the software industry, I’d like to offer some perspective on what these acquisitions mean to software-purchasing organizations. Think of the software industry as a thriving ecosystem, with large software companies at the top of the food chain. Small companies are formed and, if they have an interesting idea and some good marketing, they grow. The really good ones may continue to grow and be independent, but most of the good ideas eventually...</p> </div> <a href="https://davidmenninger.isg-one.com/2010/11/27/its-alive-a-look-at-why-the-software-ecosystem-matters-to-you"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://davidmenninger.isg-one.com/topic/analytics">Analytics</a>, <a href="https://davidmenninger.isg-one.com/topic/business-intelligence">Business Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/enterprise-software">Enterprise Software</a>, <a href="https://davidmenninger.isg-one.com/topic/information-technology">Information Technology</a>, <a href="https://davidmenninger.isg-one.com/topic/operational-intelligence">Operational Intelligence</a>, <a href="https://davidmenninger.isg-one.com/topic/it-performance-management-itpm">IT Performance Management (ITPM)</a> <hr> </div> <script> // Check active classes var checkClass = function() { if ( $('.fil_item').hasClass('hide') ) { $('.fil_item').removeClass('hide'); 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If you have any issue with an Analyst Perspective, please email them to <a href="mailto:ChiefResearchOfficer@isg-research.net">ChiefResearchOfficer@isg-research.net</a></p> </li> </ul> <a class="btn-secondary" href="https://www.isg-research.net/analyst-perspective-policy">View Policy</a></span>  <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://davidmenninger.isg-one.com/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://davidmenninger.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=50&name=Menninger.David%20Pic.Circle.png 50w, https://davidmenninger.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=100&name=Menninger.David%20Pic.Circle.png 100w, https://davidmenninger.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=150&name=Menninger.David%20Pic.Circle.png 150w, https://davidmenninger.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=200&name=Menninger.David%20Pic.Circle.png 200w, https://davidmenninger.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=250&name=Menninger.David%20Pic.Circle.png 250w, https://davidmenninger.isg-one.com/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://davidmenninger.isg-one.com/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://davidmenninger.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=50&name=Orr.Jeff.Circle.png 50w, https://davidmenninger.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=100&name=Orr.Jeff.Circle.png 100w, https://davidmenninger.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=150&name=Orr.Jeff.Circle.png 150w, https://davidmenninger.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=200&name=Orr.Jeff.Circle.png 200w, https://davidmenninger.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=250&name=Orr.Jeff.Circle.png 250w, 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8.625 6.835 15.645 15.453 15.999 191.179 7.839 344.627 161.316 352.465 352.465.353 8.618 7.373 15.453 15.999 15.453h48.068c9.034-.001 16.329-7.474 16.005-16.504z" /></g></svg></span> </span> </a> </li> </ul> </div> </div> <div class="bottom_area copy_and_description"> <div class="copyright"> <p>© ISG. 2025 All rights reserved.</p> </div> <div class="description"> <p style="text-align: center;"><span>When you visit or interact with our sites, services or tools, we or our authorised service providers may use cookies for storing information to help provide you with a better, faster and safer experience and for marketing purposes.</span></p> </div> </div> </div> </footer></div>  <script defer src="/hs/hsstatic/content-cwv-embed/static-1.1293/embed.js"></script> <script src="https://davidmenninger.isg-one.com/hs-fs/hub/2035844/hub_generated/template_assets/94278782902/1725882474552/Ventana_Research_2023/Ventana_Research_2023_child.min.js"></script> <script> var hsVars = hsVars || {}; hsVars['language'] = 'en'; </script> <script src="/hs/hsstatic/cos-i18n/static-1.53/bundles/project.js"></script> <script src="https://davidmenninger.isg-one.com/hs-fs/hub/2035844/hub_generated/module_assets/90531062927/1702386872146/module_90531062927_Header-Global.min.js"></script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Analytics for IT: Cobbler’s Children Need Shoes", "mainEntityOfPage": "https://davidmenninger.isg-one.com/2011/04/29/analytics-for-it-cobblers-children-need-shoes", "datePublished": "29/04/2011", "dateModified": "29/04/2011", "articleBody": "As part of our largest-ever research study on business analytics, which surveyed more than 2,600 organizations covering the maturity and competency of business, IT and vertical industries, we looked at how IT is applying analytics to support their own business activities. One of the things we found is that, charged with enabling business units to use information systems as effectively as possible, the IT department, like the shoemaker’s barefoot children in the old tale, typically stands last in line for resources to manage its own performance. In trying to understand and tune the collection of networking and operating systems, middleware and applications an enterprise needs to operate, IT professionals usually have to make do with small sets of historical data stored in spreadsheets and data warehouses and marts that are not as well managed as the systems they maintain to support the business. In most cases IT cannot apply the same level of analytics to its own operations that it provides to business units. This also has effects beyond IT itself: To the extent that the result is subpar performance of its core information systems, the business will suffer. To break out of this frustrating cycle, IT needs to make the rest of the organization aware of the role it actually performs, of course, and it needs metrics and measurements, which require analytics to standardize and routinely generate them. IT needs to be able to analyze both historical and real-time events involving data and processes so managers can determine the right level of automation and efficiency to demand from the technology. And IT needs the capability delivered by predictive analytics to anticipate situations and outcomes so it can prepare properly for them. In short, the CIO and IT staff need to manage their portfolio as a business asset, not merely a collection of technologies. Metrics about its own operations and systems also enable IT to determine priorities for improvement. To fully understand the state of their existing investments and processes, IT organizations should not just measure them but analyze them to develop insights on future outcomes of their systems. This more sophisticated approach to analytics can help IT determine where to focus resources and what to do with legacy systems. Knowing this, it is possible to prioritize precious budget dollars and justify IT investments more convincingly. Our research found that IT’s concerns currently center on cost and operational efficiency. The most important financial metrics are return on investment, cost per project, budget utilization and adherence to budget. The most important process metrics address timeliness in IT’s core function of service to the business: delivery of projects on time, speed of technology implementation and help desk response time. In our research, which we presented in this webinar on IT analytics, of the participants’ perceptions of which metrics are most important for executives and managers, two loomed large: business user satisfaction and compliance with service level agreements (SLAs). The executives themselves rated the two metrics nearly equal in importance, but their management reports (vice presidents) by a slight margin most often named adherence to governance and risk management requirements rather than either of those. These responses suggest that people may work somewhat at cross-purposes in pursuing IT analytics. The research also finds strong suggestions that organizations ought to involve more people in the process of establishing requirements for defining analytics. Research participants asserted overwhelmingly that they and the head of their business unit are involved in establishing requirements important to their jobs, but percentages drop for heads of other business units and business analysts in other business units. This disparity takes on more weight when we recall that business user satisfaction and SLA compliance are important metrics for leaders. For analytics to deliver value, they must be available to those who need them; the research shows that this is an issue for many organizations. No more than half have analytics generally available to address any of seven major IT management tasks, and only for budget analysis are analytics completely available in even one-fourth of organizations. In a related finding, more than half said it is very important to make it simpler to provide analytics and metrics; less than 10 percent said that is only somewhat important or not important. As well, over a third said they can significantly improve their use of analytics and performance indicators, and over a third are not satisfied with the process currently used to create analytics. The process of applying analytics also impacts IT’s effectiveness. The IT Analytics benchmark research found that users in nearly two-thirds of all organizations spend most of their time in unproductive chores that precede analyzing their data: preparing it for analysis, reviewing it for quality and consistency and waiting for it. And before that, issues in collecting the data raise another roadblock. In more than half of organizations, doing that is very difficult or a challenge that impedes creating metrics and performance indicators. These functional barriers also can get in the way of analysts performing important tasks. Among capabilities they need in order to work effectively with analytics and metrics, 42 percent said access to source data is the most important, and at least one-third identified as most important the abilities to search for existing data and analytics, to take action based on analytics and to design and maintain both business models and metrics for analytics. Applying predictive analytics to project future outcomes, a hallmark of advanced maturity in the use of IT analytics, was cited by 31 percent. IT professionals need appropriate tools to facilitate these and other analytics-related activities. In more than half of these organizations, business intelligence technologies for query, reporting, analysis are the most important of these tools. Yet even in this technologically astute environment, desktop spreadsheets are often used to generate analytics and are an important information source for building IT. But spreadsheets require manual effort to populate the data and are prone to error, and thus are not appropriate for collaborative and enterprise-wide activities. We think their widespread use is a factor in half of organizations being only somewhat satisfied or not satisfied with their organization’s current technology for creating and applying analytics. As part of our benchmark research methodology, Ventana Research has developed a model for assessing maturity that classifies organizations at four maturity levels (from bottom to top, Tactical, Advanced, Strategic and Innovative) in each of four categories: People, Process, Information and Technology. With respect to their use of and plans for IT analytics, our Maturity Index analysis found only 15 percent whose responses place them at the highest Innovative level of maturity. One important finding reflecting on organizations’ maturity is that two-thirds said the data used in preparing metrics and performance indicators is only somewhat accurate or somewhat inaccurate. As well, it takes 35 percent of organizations more than one week to provide updated metrics and performance indicators to people and nearly as many up to a week to provide them. It is a positive sign that improvements, if made, will be done most often to improve business processes or decision-making rather than for operational efficiency and cost savings. The first two motivations are more likely to produce better business results. Similarly, maximizing IT effectiveness and improving the value of IT to business managers are more important than issues involving resources, costs and budget. However, these opinions come from organizations that plan to change the way they generate and apply analytics in the next 12 to 18 months, and they comprise only 28 percent of the total; another 36 percent said changes are needed but are not currently a priority. The primary barriers to such an initiative are both fiscal (lack of resources and budget) and perceptual (lack of awareness and a sense that the business case is not strong enough). Recognizing a problem but not being willing or able to remedy it is another sign of immaturity. To maximize its value, IT should use analytics and metrics to help set its own goals and objectives and to ensure they serve the business strategies of the organization. This innovative path is embracing IT performance management. Few organizations have taken the necessary steps to actually manage performance and align, optimize and understand the range of their IT processes and resources. We believe, and this benchmark research confirms, that it is time for them to take those steps, supported by executive management in providing resources. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-one.com/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-one.com", "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": "Predictive Analytics Are on the Rise", "mainEntityOfPage": "https://davidmenninger.isg-one.com/2011/04/20/predictive-analytics-are-on-the-rise", "datePublished": "20/04/2011", "dateModified": "20/04/2011", "articleBody": "In various forms, business intelligence (BI) – as queries, reporting, dashboards and online analytical processing (OLAP) – is being used increasingly widely. And as basic BI capabilities spread to more organizations, innovative ones increasingly are exploring how to take advantage of the next step in the strategic use of BI: predictive analytics. The trend in Web searches for the phrase “predictive analytics” gives one indication of the rise in interest in this area. From 2004 through 2008, the number of Web search was relatively steady. Beginning in 2009, the number of searches rose significantly and has continued to rise. While a market for products that deliver predictive analytics has existed for many years and enterprises in a few vertical industries and specific lines of business have been willing to pay large sums to acquire those capabilities, this constitutes but a fraction of the potential user base. Predictive analytics are nowhere near the top of the list of requirements for business intelligence implementations. In our recent benchmark research on business analytics, participants from more than 2,600 organizations ranked predictive analytics 10th among technologies they use today to generate analytics; only one in eight companies use them. Planning and forecasting fared only slightly better, ranking sixth with use by 26 percent. Yet in other research, 80 percent of organizations indicated that applying predictive analytics is important or very important. For the untapped majority, technology has now advanced to a stage at which it is feasible to harness the potential of predictive analytics, and the value of these advanced analytics is increasingly clear. Like BI, predictive analytics also can appear in several identities, including predictive statistics, forecasting, simulation, optimization and data mining. Among lines of business, contact centers and supply chains are most interested in predictive analytics. By industry, telecommunications, medicine and financial services are among the heavier users of these analytics, but even there no more than 20 percent now employ them. Ironically, our recent research on analytics shows that finance departments are the line of business least likely to use predictive analytics, even though they could find wide applicability for them. Predictive analytics defined broadly have a checkered history. Some software vendors have long offered tools for statistics, forecasting and data mining including Angoss, SAS and SPSS, which is now part of IBM. I was part of the team at Oracle that acquired data mining technology for the Oracle database a dozen years ago. Companies like KXEN sprang up around that time, perhaps hoping to capitalize on what appeared to be a growing market. The open source statistics project known simply as R has been around for more than a decade and some BI vendors like Information Builders have embedded into their product called WebFOCUS RStat. But then things quieted down for almost a decade as the large vendors focused on consolidating BI capabilities into a single platform. Around 2007, interest began to rise again, as BI vendors looked for other ways to differentiate their product offerings. Information Builders began touting its successes in predictive analytics with a customer case study of how the Richmond, Va., police department was using the technology to fight crime. In 2008 Tibco acquired Insightful and Netezza acquired NuTech, both to gain more advanced analytics. And in 2009 IBM acquired SPSS. As well these combinations, there are signs that more vendors see a market in supplying advanced analytics. Several startups have focused their attention on predictive analytics, including some such as Predixion with offerings that run in the cloud. Database companies have been pushing to add more advanced analytics to their products, some by forming partnerships with or acquiring advanced analytics vendors and others by building their own analytics frameworks. The trend has even been noted by mainstream media: For example, in 2009 an article in The New York Times suggested that “data mining has entered a golden age, whether being used to set ad prices, find new drugs more quickly or fine-tune financial models.” Thus the predictive analytics market seems to be coming to life just as need intensifies. The huge volumes of data processed by major websites and online retailers, to name just two types, cannot be moved easily or quickly to a separate system for more advanced analyses. The Apache Hadoop project has been extended with a project called Mahout, a machine learning library that supports large data sets. Simultaneously, data warehouse vendors have been adding more analytics to their databases. Other vendors are touting in-memory systems as the way to deliver advanced analytics on large-scale data. It is possible that this marriage of analytics with large-scale data will cause a surge in the use of predictive analytics – unless other challenges prevent more widespread use of these capabilities. One is the inherent complexity of the analytics themselves. They employ arcane algorithms and often require knowledge of sampling techniques to avoid bias in the analyses. Developing such analytics tools involves creating models, deploying them and managing them to understand when a model has become “stale” or outdated and ought to be revised or replaced. It should be obvious that only the most technically advanced user will have (or desire) any familiarity with this complexity; to achieve broad adoption, either there must be more highly trained users (which is unlikely) or vendors must mask the complexity and make their tools easier to use. It also is possible that a lack of understanding of the business value these analyses provide is holding back adoption. Predictive analytics have been employed to advantage in certain segments of the market; other segments can learn from those deployments, but it is up to vendors to make the benefits and examples more widely known. In an upcoming benchmark research I’ll be investigating what is necessary to deploy these techniques more broadly and looking for the best practices from successful implementations. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-one.com/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-one.com", "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": "The Information Management Technology Revolution in 2011", "mainEntityOfPage": "https://davidmenninger.isg-one.com/2011/04/01/the-information-management-technology-revolution-in-2011", "datePublished": "01/04/2011", "dateModified": "01/04/2011", "articleBody": "The information management (IM) technology market is undergoing a revolution similar to the one in the business intelligence (BI) market. We define information management as the acquisition, organization, control and use of information to create and enhance business value. It is a necessary ingredient of successful BI implementations, and while some vendors such as IBM, Information Builders, Pentaho and SAP are in addition integrating their BI and IM offerings, each discipline involves different aspects of the use of information and will require it sometimes integrated and sometimes separate. Some might consider information management as the “plumbing” behind BI. They take it for granted and only notice when it is missing. We have a more holistic view. Our recent benchmark research on business analytics shows that, for example, organizations struggle to collect all the data they need, with two-thirds of them stating they spend more time in data related activities than analytic ones. Three key issues are driving our information research agenda in 2011: 1) Combining all the sources and types of data into an integrated information architecture. 2) Enabling organizations to manage and analyze larger volumes of information. 3) Providing accessibility to information throughout the organization. We’ll be updating our information management benchmark research this year to see how these central issues are impacting IM overall. In addition we will focus on five technology innovations my colleague has identified as the business technology revolution in 2011: cloud computing, mobile technologies, social media, analytics of more types over more data and collaboration. Let me flesh out each of these a bit as they impact the evolution of IM. As I pointed out in “Clouds Are Raining Corporate Data,” cloud computing is having an increasingly large influence over the IT landscape. It’s likely that, whether you realize it or not, corporate data exists and/or is migrating outside the walls of your organization. Cloud-based applications and services raise information management challenges that don’t necessarily exist in on-premises deployments. We’re investigating these issues now in our Business Data in the Cloud benchmark research program and where many new providers dealing with cloud data like Dell Boomi, Jitterbit and Snapdata play into the existing landscape of IBM, Informatica, iWay Software, Oracle, Pervasive and Syncsort to name just a few. Mobile technologies are enabling organizations to deliver information to users when and where they need it. They are one of the forces driving cloud adoption as organizations look to make it easier to deliver applications to users regardless of their location. Mobile applications also are consuming and producing more location-related information and creating a need to manage this kind of data. In the world of information management, social media has created entirely new challenges. Most social media data is unstructured text and is forcing organizations to embrace text analytics to deal with it, in many cases for the first time. The volumes of social media data and the speed with which it should be collected and analyzed also present new challenges. From an IM perspective, organizations must learn how to solve these challenges while enforcing appropriate data quality, data governance and life-cycle management policies. Analytics present an additional set of IM challenges. The necessity of managing more data and different types of data has led to the adoption of large-scale technologies such as Hadoop. In research that is under way now we are researching the various ways of dealing with these huge data volumes and the role of Hadoop in that process. Predictive analytics also create IM challenges. Sampling, which is a key to producing unbiased predictive models, may or may not become less critical as database analytics grow in popularity. The models and the scores that such analytics produce are another form of data that must be managed and retained, often for compliance and auditing purposes. We’ll be studying these issues as part of predictive analytics benchmark research that will commence in the first part of 2011. Collaboration provides a means to communicate and extend the processes of IM. It creates a new channel not only for delivery of information but also for input into the delivery process. Using collaboration tools such as Twitter, Chatter or Tibbr can help organizations use data and related information by involving more people. This wider audience collectively contains more knowledge about the underlying data and can also comment on its quality, which ultimately will lead to better data and more trust in it. Collaboration tools also provide a mechanism to link the workflows of information management with the constituents involved in the process. Information management continues to evolve and grow, somewhat to my surprise as indicated in my recent assessment of Informatica. These changes present challenges for IT groups and lines of business alike. With our IM research agenda, we hope to provide useful information to both functions and help you navigate together through this changing landscape and achieve the goal of creating and enhancing business value. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-one.com/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-one.com", "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": "The Business Intelligence Technology Revolution in 2011", "mainEntityOfPage": "https://davidmenninger.isg-one.com/david-menninger/2011/03/21/the-business-intelligence-technology-revolution-in-2011", "datePublished": "20/03/2011", "dateModified": "20/03/2011", "articleBody": "The business intelligence (BI) technology market is undergoing a revolution. I’ve been working in this segment for 20 years, and it is and has been an exciting market in which to work, but its dynamic nature can be daunting to organizations trying to evaluate, purchase and deploy BI to improve their business processes. And despite the advances our benchmark research shows high levels of dissatisfaction with and immaturity in BI capabilities within organizations. Challenges remain to spread adoption of BI among a wider audience and improve its use in organizations. We have recently seen progress in integrating information management and analytics into a single framework, but more work remains. The use of collaboration will help improve dialogue and delivery of information to business users. Organizations can also adopt and support mobile BI technologies to enhance productivity and broaden the reach of BI. Technology exists today to apply analytics to all information regardless of volume, data type and origin. However, organizations still struggle to evaluate alternatives for supporting large data sets including location data, event data and machine-generated data, all of which can contribute to more accurate analyses of their business processes. Also as the proportion and volume of unstructured data grow, users will need to incorporate text analytics to complement structured data analysis. On top of these challenges businesses now operate at Internet speeds and must analyze data and events as they are created or miss fleeting market opportunities. Organizations must develop their analytical capabilities further not just to provide data but to optimize business decisions. To enhance decision-making and improve business outcomes, they must move beyond historical analysis to look forward through planning, forecasting and predictive analysis. And the dramatic rise in popularity of social media creates another source of information to incorporate in the decision-making process and another channel for involving larger groups in feedback processes. We see five underlying technology innovations impacting BI and creating the aforementioned revolution: cloud computing, mobile technologies, social media, analytics of more types over more data, and collaboration. My colleague has identified these five areas as the business technology revolution in 2011, and all are directly relevant to BI. As I’ve previously pointed out in “Clouds are Raining Corporate Data”, cloud-based BI systems are rising in popularity. So are other types of cloud applications, which means that more and more of the data organizations need to analyze will reside in the cloud. I’ll be examining the issues of business data in the cloud in a benchmark research program that is just about to get under way. Mobile technologies are invading the enterprise through employees. As mobile devices have developed more capabilities and larger form factors appear in tablets, business users on the go are demanding access to BI wherever they may be. Some software vendors and innovative enterprises have recognized these devices as vehicles to enable front-line BI and decision-making capabilities. More organizations are supporting their business users and realizing benefits of both broader BI adoption and enhanced productivity of their workforce. Social media has created several new challenges for businesses and their use of BI. First, this rich source of information can help companies understand customers and prospects, their characteristics, their opinions and their experiences in interacting with the organization. But analyzing unstructured social media content is new to most organizations. Second, social media can also play a role in collaborating on BI-aided decision-making processes (discussed below). Third, social media is a source of information and opinions about the BI products and services organizations may be evaluating. Finally, the combination of social media and mobile technologies is increasing demand for real-time data and instant analysis of it. Collaboration technologies, as applied to BI, are not the same as social media. Social media such as Twitter, Chatter or Tibbr may be used as part of a social process, but collaboration is more than just a conversation. It includes workflow and approval processes as well as tracking communication associated with BI decision-making. Social media can be the delivery vehicle for some of the information and conversation tracking, but it is not sufficient on its own. Innovative organizations recognize the processes involved in BI are as important as the technology and take steps to provide collaborative support to their BI activities. The rise of social media has helped raise awareness of collaboration in general, but many organizations are still confused about how to apply collaboration to the BI process. At the core of BI, analytics have evolved beyond simple historical analysis. More advanced analytic techniques have been available for decades but are still not widely embraced. For example, our recent analytics research shows that only 25% of organizations are using planning and forecasting in their BI applications. However, in business areas such as finance, planning with what-if and scenario modeling has been common for years, in part because the volumes of data were smaller and more easily managed. In other specific business functions such as fraud detection, predictive analytics have played a significant role for years despite their cost and complexity because of the magnitude of the savings that could be achieved. With these business areas paving the way and with the advent of information management technologies that can marry larger volumes of data with more powerful analytics, organizations can now deploy these capabilities across a much wider range of business problems. I’ll be examining the role of advanced analytics and the obstacles still facing organizations as they try to deploy these capabilities. In short, while the challenges are great, so are the opportunities. It’s an exciting time in the BI market. As you assess how the business technology revolution affects your BI efforts, please check back here for updated research that can help your organization mature in its use of BI. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-one.com/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-one.com", "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": "SAS and its Business Intelligence & Information Management Direction", "mainEntityOfPage": "https://davidmenninger.isg-one.com/david-menninger/2011/03/18/sas-and-its-business-intelligence-information-management-direction", "datePublished": "17/03/2011", "dateModified": "17/03/2011", "articleBody": "I recently attended SAS Institute’s annual analyst conference. My colleague covered the multibillion-dollar company’s strategy and the event. Now I want to look into some of the details of SAS’s products for business analytics and how they are supported with business intelligence (BI), and information management. Although SAS is not a publicly traded company and therefore is not required to make the financial disclosures that others are, the company revealed numerous financial statistics. Business intelligence represents over $200 million in license revenue to SAS. That’s a significant figure, larger than publicly traded BI vendors QlikTech (NASDAQ: QLIK) and Actuate (NASDAQ: BIRT) have and smaller than but still in the same order of magnitude as MicroStrategy (NASDAQ: MSTR) and Information Builders. These figures are consistent with results in our benchmark research on business intelligence and performance management: 18% of our research respondents reported using SAS products, which places it in the middle of the pack. SAS has a broad portfolio of BI products including query, reporting, OLAP, visualization and dashboarding. The existing product line lags behind competitive offerings’ collaboration and mobile capabilities, but SAS has plans to address these areas. An upcoming release, planned for later in 2011, will focus on visualization, some in-memory capabilities, expanded collaboration and mobile deployments. SAS has a history in the visualization space with its JMP product. The new release will bring more visualization along with in-memory technology to the core BI product. The visualization capabilities will be delivered in both iPad and Flash versions. My colleague highlighted collaboration as one of five technologies creating a revolution in business in 2011. On the collaboration front, SAS provided integration with Microsoft Outlook last summer and will be expanding those capabilities. I am a fan of Outlook integration. The product may not be as sexy as Salesforce Chatter or other social media channels, but a collaboration channel must have critical mass to be successful. That is, if the people you need to interact with aren’t present on that channel, your communications won’t reach the intended recipients. Integration with Outlook solves that problem because everyone in the enterprise uses e-mail and it is the dominant client software. Sure, I’d like to see a roadmap that includes other collaboration channels, but Outlook is the logical starting point and can be a bridge until those other channels are more widely adopted. Users should be aware that many SAS applications were built before its BI stack was available and are still based on separate components. Newer applications such as Customer Intelligence are based on the BI stack, but older applications are migrating to the BI stack only over time. This obviously impacts integration among parts of the product line. But since many applications are not based on the BI stack, there is less pull-through from sales of those applications, and this suggests that the BI products are succeeding on their own. When it comes to information management, SAS let’s its wholly owned software business handle the development of its products and to the marketing and sales activities. DataFlux, acquired by SAS more than 10 years ago, maintains a separate identity and a separate product line from SAS Data Integration, although the underlying components and metadata, rules and transformations can be shared and process flows can be orchestrated between the two lines. DataFlux, with over 2,300 customers, provides data integration, data quality and master data management capabilities. In 2011 it will be moving into complex event processing for operational intelligence. See our benchmark research on the subject here. While the SAS and DataFlux information management products can deal with cloud-based data, they do not yet offer a software-as-a-service versions of their products, which some other vendors do. SAS also needs to provide more integration between its BI products and the information management products. For instance, data lineage and glossary information cannot be surfaced through the BI products today, although SAS can provide impact analysis of where information is used in the BI products. Business analytics at SAS is a separate category from BI. In it SAS includes statistics, forecasting, predictive analytics and text analytics. Our recent BI and performance management benchmark research shows that less than one-quarter of respondents use predictive analytics. However, in our newly completed benchmark research on business analytics 80% of organizations said that it is important or very important to apply predictive analytics to predict future outcomes, so we expect usage to grow. SAS has a long history in the analytics space and a well-developed product line, but it is still extending its algorithms. In 2011 SAS will be focusing on new algorithms for high-frequency data and more powerful optimization techniques. Part of the development centers around high-performance computing techniques that distribute processing across multiple servers to handle large volumes of data quickly. These high-performance techniques will be delivered as an analytic appliance. SAS also plans to provide operational analytics through workflow and business rules. In all the talk of high-performance computing, SAS said little about Hadoop. I expect to hear more from SAS on this topic, but the plans are still in the formative stages. (For discussion of what other organizations are doing with Hadoop, see my previous post “Living in the Era of Hadoop and Large-Scale Data”. SAS is also working on enterprise search capabilities, which we believe are important as discussed here So while most of SAS’s business derives from applications, there is a robust tools business for BI, analytics and information management. Whether you are an SAS customer or not, I hope this recap of what’s going on at SAS helps you understand some of the ways in which analytics and BI are becoming more intertwined. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "ISG Software Research", "url": "https://davidmenninger.isg-one.com/author/isg-software-research", "sameAs": "https://www.linkedin.com/company/ventana-research" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-one.com", "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": "SAP Enterprise Information Management 4.0: A Technology Secret", "mainEntityOfPage": "https://davidmenninger.isg-one.com/david-menninger/2011/03/14/sap-enterprise-information-management-4-0-a-technology-secret", "datePublished": "13/03/2011", "dateModified": "13/03/2011", "articleBody": "SAP has launched its Enterprise Information Management (EIM) 4.0 release as part of its “Run Better Tour.” It includes a broad range of information management components spanning data integration, data quality, data profiling, metadata management and more. The launch was done in conjunction with SAP Business Intelligence (BI) 4.0, which got much bigger billing at the event –to the point where one might call this a stealth marketing campaign. However, the event did identify three themes intended to highlight EIM capabilities: event insight, trusted data and text processing. The goal here was to communicate the integration SAP has achieved within and between its BI and EIM products. IBM announced a similar advance with its InfoSphere products and Informatica has also invested heavily in integrating its information management products. Our Information Management benchmark research validates this approach, finding that incompatible tools create a significant obstacle to organizations’ quest for consistent sets of data. With this release SAP also announced three new products: SAP BusinessObjects Data Services, SAP BusinessObjects Information Steward and SAP Business Objects Event Insight. Data Services brings together ETL (extract, transform and load) capabilities, data quality and text processing into a single set of services. With this release, SAP supports address cleansing for more than 230 countries. In addition, the data quality components are available as an embeddable set of self-contained libraries requiring no application server. This architecture makes it easier to embed within third party applications. Data services is also the engine for moving, transforming and loading data and metadata into SAP’s in-memory, high performance analytic application, HANA. This suggests high throughput rates for Data Services, since HANA is about performance and real-time access to data. Text data processing, formerly based on Insight, which was a separate acquired technology, has been consolidated with data services in 4.0. A demo is available of the text data processing capabilities being used to perform sentiment analysis of a tweet stream in what is becoming a required showpiece for all BI software vendors. While sentiment analysis of social media data makes for an interesting demo, it remains a very difficult problem to solve. If in the demo you view the tweets with a strong positive sentiment, you’ll see that first page includes 10 tweets. While those tweets contain positive sentiment with words like “excellent,” “thanks” or “positive,” it turns out that seven of the ten are actually expressions of positive sentiment about reviews of the event, not the event itself. I’ve seen the same flaw in other vendors’ tweet stream analyses as well. While most of these products, including SAP’s, allow you to extend the libraries used for determining sentiment and context to produce more accurate results, I would use caution before relying too heavily on these automated analyses. The second of the three new products, Information Steward, provides data governance capabilities designed to help increase, in SAP’s words, business users’ trust in the data. Trust is an important issue. Our Data Governance research found that only 9 percent of organizations completely trust their data for decision-making. Information Steward provides, among other things, profiling and data quality dashboards, including the ability, accessible from the front-end BI tools, to drill down into the details behind quality scores and key performance indicators. Users can even see which records have failed in recent integration processes. Another capability, Cleansing Package Builder, can profile a set of data to derive rules about that data. These automatically derived rules can then be reviewed and modified or augmented as necessary. The third new piece to the SAP EIM portfolio, Event Insight, manages event-based data to enable operational intelligence using real-time data. The new product is based on the Aleri technology acquired as part of the Sybase portfolio of products. Event Insight has three basic capabilities: the ability to process streams of data such as network traffic, combine that with historical data, and deliver the information in real time to users. In order to help increase scale and reduce network congestion, SAP has architected technology to “push down” some of the event filtering to decentralized servers. The historical data is still centralized, so the rule execution must still happen at the central server. This technology is part of what is known as complex event processing; our research into operational intelligence found a need for improved efficiency of business processes utilizing events. SAP placed significantly less emphasis on security than have other information management vendors I’ve spoken with. For instance, there was no mention of data masking, which competitive products provide. Another area that was noticeably lacking was integration with Hadoop. Many information management vendors are incorporating Hadoop into the product strategies and I expect we’ll hear more from SAP on this in the future. Overall, the integration delivered in this release should benefit users; SAP now has the unusual opportunity to provide that integration all the way from ERP applications through information management processes to business intelligence. My colleague has pointed out the importance of business and IT engagement and where SAP is integrating the technologies further to meet that need. In addition, SAP’s HANA provides evidence that SAP wants to exploit the larger information and analytics opportunity further by accelerating the processing of data to information for a range of business needs. Now SAP needs to decide if it should market this set of technology further to capitalize on the demand or just keep it part of the business intelligence efforts. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-one.com/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-one.com", "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": "SAP Business Intelligence 4.0", "mainEntityOfPage": "https://davidmenninger.isg-one.com/david-menninger/2011/03/02/sap-business-intelligence-4-0", "datePublished": "01/03/2011", "dateModified": "01/03/2011", "articleBody": "Last week SAP launched the 4.0 Release of its Business Intelligence and Enterprise Information Management products in conjunction with the New York City stop on its “SAP Run Better Tour”. My colleague Mark Smith has already covered the announcement in the context of some of today’s major technology trends. In this post, I’ll focus on the specifics of the product announcements. SAP BusinessObjects Business Intelligence Release 4, more than three years in the making, supersedes SAP BusinessObjects Enterprise XI Release 3.1. The new release includes several other product name changes as well – for example, the Xcelsius visualization tool was renamed Dashboards – so if you, like I, were confused you can download a list of all the name changes through the following link: http://download.sap.com/download.epd?context=1DA760BA0F1EC83BE393EBA644F81666F51DD9A22B64430471986DC9069E0006EA2364413D2990C3DC0B25B525C25CBC22407270EEBDE423. The name changes were confusing, but it quickly became clear that three common themes run through all 4.0 products: better integration; the incorporation of real-time capabilities; and improvements in the user interface, including support for a variety of mobile platforms. One of the key reasons to consider SAP products rather than “best of breed” products from independent vendors is integration. Integration can mean different things to different people. From a technical point of view, integration means being able to access to data and information across applications, processes and business silos. From a user desktop point of view, it means being able to work in a common user interface on top and a common semantic layer underneath. (These, by the way, make systems easier to learn as well as to use.) Release 4.0’s improved integration capabilities address both points of view, but pay particular attention to the latter, and with good reason. Our latest benchmark research in business intelligence (BI) found usability to be the number-one consideration in evaluating a vendor and its products, especially on the business side, so these improvements should be welcomed by those evaluating new BI purchases. Other large vendors such as IBM are also focusing on this same theme in their stack of BI products. SAP executives also stressed that the new release’s real-time capabilities run throughout the product portfolio and its underlying architecture, allowing 4.0 products to collect large and store large volumes of data in real time and to display the results in real time as well. For instance, its Event Insights product collects and delivers real-time information as it occurs, while on the front end, SAP Business Objects Dashboards processes updates in real time and displays revised information as the underlying data changes. None of these capabilities matter, however, without the ability to collect and to prepare data in a timely fashion. Our benchmark research has shown that 96 percent of organizations take two or more days to deliver important metrics and key performance indicators (KPIs) to users. We at Ventana Research believe that’s too long. For this reason, release 4.0 supports the SAP High-Performance Analytic Appliance (SAP HANA), an in-memory database technology that speeds the processing of large amounts of data. While it is not a required part of the BI toolset, it is available if necessary to accomplish real-time database processing and analysis. To present that data, SAP has greatly expanded the capabilities of Dashboards. For example, SAP demonstrated the ability to link dashboard components so that changes in the data selected in one component would be reflected in similar changes to the other components displayed on the screen. It reminded me of work my colleagues and I did on ExpressObjects in the mid-1990s; in fact, in the middle of the demonstration I got a message via Twitter from a colleague who had worked with me on the product and who had the same impression as he was watching the webcast of the event. It was a good idea then and it’s a good idea now. What SAP brings to the table is a broader, more tightly integrated stack of products than we were able to offer at the time and a more modern platform that supports a variety of thin-client and mobile devices. Overall the Dashboards provide a nice user experience and incorporate some reasonable interactive visualization capabilities, including the ability to lasso a data bar to narrow the display or to drill down directly from the graphs. However, they don’t offer all the visualization techniques and interactivity of some specialist products such as Tibco Spotfire or Tableau Software’s Tableau Desktop. Another area SAP stressed was self-service BI. The SAP Explorer 4.0 provides an easy-to-use, search-based mechanism to access data from a variety of different entry points, including mobile devices. I first saw the 4.0 version of this tool at SAP Tech Ed demonstrated on an Apple iPad and I was impressed. It includes an associative search approach much like QlikView that allows you to search on characteristics you know rather than a rigid set of predefined keys such as product name. The user interface in the latest version is clean and modern, making it both pleasing to the eye and easy to understand. Explorer comes up a little short with respect to a broader definition of self-service, however. SAP has focused almost entirely on enabling ad hoc queries or searches without an existing or predefined query. In most cases, Explorer requires the data and metadata to exist already in an SAP Business Objects Universe. The exception is Excel; users can load and navigate Excel spreadsheet data using Explorer without outside assistance. I hope SAP will develop this aspect of self-service more fully so that users will be able to navigate data from other sources on their own without the intervention of someone with knowledge of Universes. Two areas that didn’t receive much emphasis at the launch are advanced analytics and predictive analytics. In SAP parlance, “advanced analysis” equals online analytics processing (OLAP) – or at least it did prior to the name changes I discussed above. The OLAP analysis capabilities are primarily oriented around the drill-and-pivot navigation of historical data analysis, in part because SAP’s enterprise performance management technology is still separate from its core BI products. I expect SAP will turn to HANA as a way to provide additional planning and what-if analysis. Today HANA’s Multidimensional Expressions (MDX) capabilities are limited to Excel, but SAP is working on expanding those capabilities. SAP is delivering predictive analytics, another key element, using its Predictive Workbench, but this product is based on IBM’s SPSS technology, which may explain why it had a lesser role in the 4.0 launch. In total, the Release 4.0 SAP provides a robust and relatively complete set of BI capabilities. Although individual point products may perform a specific set of functions better, if you are looking for a comprehensive, well-integrated BI platform with good mobile support, you should put SAP on your list of products to consider. Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-one.com/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-one.com", "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": "Advantages and Challenges of In-Memory Databases and Processing", "mainEntityOfPage": "https://davidmenninger.isg-one.com/2010/11/27/advantages-and-challenges-of-in-memory-databases-and-processing", "datePublished": "26/11/2010", "dateModified": "26/11/2010", "articleBody": "Interest in and development of in-memory technologies have increased over the last few years, driven in part by widespread availability of affordable 64-bit hardware and operating systems and the performance advantages in-memory operations provide over disk-based operations. Some software vendors, such as SAP with its High-Performance Analytic Appliance (HANA) project has been advancing with momentum, have even suggested that we can put our entire analytic systems in memory. I hope it will be helpful to take a look at what an “in-memory” system is, what it is good for and what some of the concerns about it are. First of all, nearly all systems involve some combination of memory and disk operations, but the roles each of these plays may differ. The fundamental value proposition relates to the greater speed of memory-based operations vs. disk-based input/output (I/O) operations. It is easy to understand that computer operations in memory can be significantly faster than any operation involving I/O. Many types of system performance have been enhanced by leveraging memory in the form of caches. If information can be retrieved from a cache rather than the disk, the operation will complete more quickly. What types of applications can benefit from in-memory technology? Very fast, high-volume transaction processing can be accomplished using one type of in-memory technology. Examples include IBM solidDB, Oracle TimesTen, Membase and VoltDB. Complex event processing (CEP) is another type of in-memory system. Examples of CEP include IBM, Progress Software’s Apama, Streambase, Sybase Aleri recently bought by SAP and also Vitria. Other types of analytics can be performed in-memory, including more conventional query and analysis of historical data. Beyond SAP is QlikView who I recently assessed, Tibco Spotfire and now Tableau. All of these systems deal with historical data. Another category of in-memory systems involves forward-looking calculations, models and simulations. Examples include IBM Cognos TM1 and Quantrix who my colleague recently covered (See: “Quantrix Gets Pushy with Plans”). Over the years database performance has been greatly improved by advances in caching schemes. A logical extension of caching might be to put the entire database in memory and eliminate any disk-based operations. Well, it’s not quite that simple. There are some complexities, such as recoverability, that must be dealt with when the system is entirely in memory. I suspect you’ve heard the term “ACID compliant”; the “D” stands for durability. It represents the notion that a transaction once committed will be durable or permanently recorded. Without creating a copy of the transaction somewhere other than in the memory of the affected system, you can’t recover the transaction and therefore cannot provide durability. Even in analytical systems the notion of durability is important because you need to be able to ensure that the data was loaded properly into the system. I’ve seen three schemes for dealing with the durability issue. Each has advantages and challenges: 1) Write data to disk as well as putting it in memory. The challenge here is whether you can write to the disk fast enough to keep up with the data that is being loaded into memory. 2) Put the data in memory on two different machines. The risk here is if both machines go down, you lose the data. 3) Use a combination of #1 and #2 above. Putting data in-memory on two machines provides some level of protection that allows time for a background process or asynchronous process to write data out to disk. In this case you need to understand what scheme a vendor is using and whether it meets your service level agreements. In some streaming applications the history and recoverability are left to other systems (such as the system of record) and the operations on the streaming data are allowed to operate “without a net,” so to speak. This method assumes that if the system goes down, you can live without the data that was in transit – either because it will be recovered elsewhere or because it wasn’t important enough to keep. An example might be stock-trading data being analyzed with an in-memory complex event processing system. If the CEP system crashes, the quotes being analyzed could be recovered from the exchange that generated them. Another issue is that memory is much more expensive than spinning disk. In considering the enormous and ever-increasing volumes of data produced and consumed in the world of analytics, cost could be a significant obstacle. In the future, cost structures may change, but for the near term, memory still exacts a premium relative to the same quantity of disk storage. As a result memory-based systems need to be as efficient as possible and fit as much data as possible into memory. Toward this end, many in-memory analytic systems use columnar representation because it offers a compact representation of the data. Thus the key issue here as you compare vendors is to understand how much memory each requires to represent your data. Remember to take into consideration temp space or working space for each user. I think the technology market understands accelerating DBMS and CEP operations as we found in our benchmark research on Operational Intelligence and Complex Event Processing, but I doubt that it fully understands how in-memory technology can transform calculations, modeling and simulations over large amounts of data. Today’s CPUs are very good (and fast) at performing calculations, as millions of users know from their work with spreadsheets. An overwhelming majority (84%) of organizations in our benchmark research on BI and performance management said it is important or very important to add planning and forecasting to their efforts, and these activities are calculation-intensive. Applying spreadsheet-style calculations to large amounts of data is a challenge. Often you run out of memory or performance is so poor that it is unusable. Relational databases are another obstacle. Performing spreadsheet-type calculations on data in relational databases is difficult because each row in an RDBMS is independent from every other row. In performing simple interrow calculations – for example, computing next year’s projected sales as a function of this year’s sales – you could be accessing two entirely different portions of the database and therefore different portions of the disk. Multiply that simple example by hundreds or thousands of formulas needed to model your business operations and you can see how you might have to have the whole database in-memory to get reasonable performance. Assuming you can fit the data in-memory, these types of seemingly random calculation dependences can be handled easily and efficiently. Remember, RAM stands for random-access memory. The next consideration is that most in-memory databases used for analytics do not scale across machines. SAP’s HANA may change some of that. Tibco’s ActiveSpaces has promise as well. I’ll be interested to see who tackles this challenge first, but I don’t believe the internode communications infrastructure exists yet to make random access of data across nodes feasible. So for the time being, calculation models will most likely need to be confined to data located on a single machine to deliver reasonable performance. It’s clear that in-memory databases can provide needed benefits, but they will have to handle these challenges before wide adoption becomes likely. Let me know your thoughts or come and collaborate with me on Facebook, LinkedIn and Twitter . Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-one.com/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-one.com", "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 Makes InfoSphere Information Server a Force in IT", "mainEntityOfPage": "https://davidmenninger.isg-one.com/2010/11/27/ibm-makes-infosphere-information-server-a-force-in-it", "datePublished": "26/11/2010", "dateModified": "26/11/2010", "articleBody": "In the weeks leading up to and as part of its Information On Demand Conference that my colleague assessed, IBM introduced version 8.5 of InfoSphere Information Server and several related product updates. As my colleague suggested earlier, IBM has an ambitious agenda to provide comprehensive information management capabilities through a combination of product development and acquisitions. The breadth of this portfolio is impressive, and InfoSphere Information Server 8.5 makes significant strides in tying the various pieces together. In the same way that IBM has sought to unify capabilities further up the BI stack with IBM Cognos 10, as I assessed, one of the key pieces of InfoSphere 8.5 is a new interface. InfoSphere Blueprint Director provides a broader view of the process associated with data integration projects. It also improves reusability, access to metadata, life-cycle management and collaboration. At first blush Blueprint Director might look like a data integration workflow, but it is really much broader, extending to the reports and analytics for which the data is being prepared. Throughout the process you can access the specs and metadata using some of the same tools that end users access, such as the Business Glossary. It will be interesting to learn how far these blueprints extend the reusability paradigm. The key will be how fine-grained it is and how well the developers have encapsulated and exposed the end points, which could occur at any step in the process if it is granular enough. This release includes many under-the-cover enhancements, too. Version 8.5 includes autodiscovery of warehouse schema and some of the business glossary information from existing systems. High availability via clustering and fail-over mechanisms is available in both production and development environments. The release also provides scalability and load balancing at the domain and database tiers for development teams. Parallel processing of XML data provides another area of performance improvements. I was impressed to learn that IBM has created a shared transaction context from change-data capture all the way through the date integration and data quality stages so you can insure integrity and recoverability of the movement of data through the system. And support for third-party source-code control systems is available via the SCCS standard. If your organization uses data in multiple languages, you can now apply data-quality rules to more locales, including Argentina, Brazil, Chile, Peru, Mexico, the Netherlands, India, Traditional Chinese and Japanese Kana. In its data warehouse portfolio, IBM announced InfoSphere Warehouse enhancements, a new Warehouse Pack and extensions to its Smart Analytics Systems. Optim Performance Manager and IBM Mashup Center are now bundled with InfoSphere Warehouse. In addition, SAS functions can execute inside the DB2 database engine. SAS has been making efforts to partner with other data warehouse vendors to provide similar capabilities. It makes for interesting bedfellows in that IBM owns SPSS, which competes with SAS, but the collaboration is good for joint SAS/IBM customers because it minimizes the need to move data around in order to perform advanced analytics. IBM also added a third Warehouse Pack to its offerings. Supply Chain Insight comes with a predefined data model and 20 Cognos reports designed to perform analyses across vendor performance, inventory and distribution aspects of the supply chain process. Supply chain analytics are generally well understood, as my colleague noted, so a packaged offering can automate and speed the process of implementation, but you should expect additional work to be required. IBM describes these analyses as “examples” of the types of analyses you would perform and provides customization guidelines. Announced in April, IBM’s data warehouse appliance offering, Smart Analytics, has been extended with three new systems. Two systems based on x86 architectures have been added to the lower end of the product family, and a system using IBM’s Power technology has been added, including a version with solid-state storage. The result is a product line that is nearly as broad as Teradata’s but much less unified. It will be interesting to see how the Netezza acquisition will affect these appliance offerings, assuming the deal is completed. I would expect the Netezza products to play a prominent role in future Smart Analytics offerings, so we suggest caution with respect to purchasing the existing products. In addition to the enhancements above, IBM updated a variety of other pieces of the stack. This is where I think IBM still faces some challenges. The product set is complicated and could use some rationalization. Several updates were announced. Initiate Master Data Service 9.5 has capabilities helpful for creating and managing trusted data with external data sources and partners. It also provides a mashup composer for operating on trusted data. Traceability Server 3.0 adds more connections to master-data sources, serial number management and performance enhancements. Data Architect 7.5.3 adds support for Cognos and InfoSphere Warehouse with autodiscovery capabilities. And Guardiam Data Redaction 1.1.2 supports French, German and Spanish and can provide redaction for unstructured documents in FileNet. Somewhat buried in these announcement was a technology preview of Hadoop-based “big data” analytics software called IBM InfoSphere BigInsights running both on premises and in the IBM Test Development cloud. It is only available for development purposes currently, but it is worth noting because it indicates the importance of Hadoop to IBM, which has even created its own distribution of Hadoop. I expect to see other vendors embracing Hadoop as well, as indicated in my earlier blog post regarding Hadoop World. IBM is a force to be reckoned with in information management. It competes head-to-head with Oracle and SAP and also with Informatica, which has been steadily building its portfolio through acquisitions. IBM’s recent announcements help unify its stack. In contrast with the Cognos 10 portion of the stack I assessed recently, the company seems to have done a better job of integrating with third-party technologies but still has further to go in unifying the many components it offers. That said, the integration with its offerings for master data management and data warehousing make IBM InfoSphere Information Server 8.5 worthy of consideration. Let me know your thoughts or come and collaborate with me on Facebook, LinkedIn and Twitter . Regards, David Menninger – VP & Research Director", "image": { "@type": "ImageObject", "url": "http://cdn2.hubspot.net/hubfs/2035844/Homepage_Slider/Slider_3.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://davidmenninger.isg-one.com/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "davidmenninger.isg-one.com", "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": "It’s Alive!: A Look at Why the Software Ecosystem Matters to You.", "mainEntityOfPage": "https://davidmenninger.isg-one.com/2010/11/27/its-alive-a-look-at-why-the-software-ecosystem-matters-to-you", "datePublished": "26/11/2010", "dateModified": "26/11/2010", "articleBody": "With the ongoing spate of mergers and acquisitions in the software industry, I’d like to offer some perspective on what these acquisitions mean to software-purchasing organizations. Think of the software industry as a thriving ecosystem, with large software companies at the top of the food chain. Small companies are formed and, if they have an interesting idea and some good marketing, they grow. The really good ones may continue to grow and be independent, but most of the good ideas eventually get bought by larger, more established companies. It happens this way for several reasons. Most larger companies can’t innovate at the rate smaller companies can. They are too constrained by large installed bases and lengthy release cycles. I’ve witnessed three-year release cycles, and former colleagues have told me of similar or longer release cycles. If you couple that with the typical adoption curves of the Global 2000, it easily can mean five years or more from the conception of a new innovation or product feature until it is actually helping the customers it is intended to benefit. By contrast, in the span of five years a successful venture-funded enterprise software company could have created a new product from scratch and sold it to hundreds or thousands of customers. Large companies “outsource” or plant seeds of innovation by shedding some of their best and brightest employees who tire of the big-company environment. Sometimes it happens with the blessing of and perhaps even investment backing from the former employer. In most of the cases I’ve observed, however, it is born more out of frustration than cooperation. Individuals just get fed up with trying to get their ideas to market. Software developers take pride in seeing their products being used by customers. The deferred gratification offered to developers by the largest software companies doesn’t work for some individuals. These individuals go out on their own or with a few colleagues to build their better mouse traps. Many, but not all, of these individuals were part of a smaller entrepreneurial environment in the past and prefer to operate in that world. For them the long hours and lousy pay are more than offset by a refrigerator full of free soda and many nights of free pizza or Asian take-out. Some of these ideas have merit and begin to take hold in the market among early adopters looking for a competitive edge. Witness the analytical database market from which I’ve recently come. Despite established offerings from the largest vendors, companies like Aster Data, Greenplum, Infobright, Kognitio, ParAccel and Vertica have all enjoyed some measure of success in the market. Eventually, big companies are compelled to compete with these new technologies. For example, Oracle recently began offering hybrid columnar compression to compete with the columnar methods that most of the emerging vendors use. In other cases the big companies buy rather than build these new technologies – often after a period of attempting to compete with the new technology. IBM’s recently announced agreement to acquire Netezza, which my colleague analyzed, is a prime example. In either case the upstart has advanced the industry – either by creating something new that gets a larger distribution channel following its acquisition or by prodding the bigger vendors to do something new. What does all this mean for the IT organization that has to consider whether to use new technology now (from a smaller vendor) or wait until the bigger vendor offers it? I’ve been both bigger vendor and smaller vendor with respect to this issue, and I saw three general categories of software purchasers: 1) Big organizations 2) Fast-moving small or midsize business or divisions of larger organizations that need a technological advantage or have a specific technological challenge 3) Conservative organizations whose competitive advantage is based on something other than technology. Let’s dispose of the last and easiest one first. Conservative organizations that have found a competitive advantage based on something other than technology, such as offering superior customer service (such as Nordstrom’s) don’t need to rush to adopt the latest technology until it has been proven by others. There are always risks involved when working with smaller vendors and newer technologies. So they choose to let someone else bear those risks. The second category above is nearly as easy. These sizes of organizations are ideally suited for new technology. Think, for example, of the social gaming companies such as Zynga that have to tackle technical challenges that most other organizations have never even encountered. They had no choice but to consider newer technologies such as cloud-based ones and analytical databases to meet their business requirements. The least obvious category is large organizations. Clearly, they can’t “bet the farm” on some new technology. They have a fiduciary responsibility to act in a prudent manner. However, to completely ignore newer technologies is not prudent either. They could be passed by a competitor (small or large) that adopts a new technology faster. Think of Blockbuster getting “NetFlixed.” In this case, a portfolio-based strategy makes sense; that is, a portion of the IT budget should be earmarked for newer technologies. In the same way that new technology vendors prompt established vendors to offer better, more competitive products, bringing a new technology into an established IT organization can prompt a little healthy competition. You will probably also find that the new technology meets business requirements better than the existing technology in some (but not all) respects. Regardless of where you fit in the new-technology adoption cycle, push your vendor to pursue new technologies that look promising. Believe it or not, software companies (the good ones at least) will listen to their customers. If you see something in the market that can benefit your organization, ask your vendor reps what they plan to do to address this new category or capability. You may be pleasantly surprised, and in any case you’ll learn something about the vendor. Let me know your thoughts or come and collaborate with me on Facebook, LinkedIn and Twitter . 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David Menninger's Analyst Perspectives | Information Technology