ISG Software Research Analyst Perspectives

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GenAI-based assistants and co-pilots are now widely adopted, with individuals and enterprises adopting <span><a href="https://davidmenninger.isg-research.net/generative-ai-ushers-in-a-new-age-of-content-and-model-creation">GenAI</a></span> models to automate the generation of text, digital images, audio, video and code, amongst other things.</p> </div> <a href="https://research.isg-one.com/analyst-perspectives/agentic-ai-reliability-requirements-for-data"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://research.isg-one.com/analyst-perspectives/topic/analytics">Analytics</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/ai">AI</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/ai-machine-learning">AI & Machine Learning</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/generative-ai">Generative AI</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/analytics-and-data">Analytics and Data</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://research.isg-one.com/analyst-perspectives/trintech-provides-reliable-record-to-report-productivity">Trintech Provides Reliable Record-to-Report Productivity</a></h2> <div class="author-meta"> Posted by <a href="https://research.isg-one.com/analyst-perspectives/author/robert-kugel"> Robert Kugel </a> on <span class="post-date">25 February 2025 </span> </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://research.isg-one.com/hs-fs/hubfs/Trintech_Provides_Reliable_Record-to-Report_Productivity.png?width=200&name=Trintech_Provides_Reliable_Record-to-Report_Productivity.png" width="200" !important: srcset="https://research.isg-one.com/hs-fs/hubfs/Trintech_Provides_Reliable_Record-to-Report_Productivity.png?width=100&name=Trintech_Provides_Reliable_Record-to-Report_Productivity.png 100w, https://research.isg-one.com/hs-fs/hubfs/Trintech_Provides_Reliable_Record-to-Report_Productivity.png?width=200&name=Trintech_Provides_Reliable_Record-to-Report_Productivity.png 200w, https://research.isg-one.com/hs-fs/hubfs/Trintech_Provides_Reliable_Record-to-Report_Productivity.png?width=300&name=Trintech_Provides_Reliable_Record-to-Report_Productivity.png 300w, https://research.isg-one.com/hs-fs/hubfs/Trintech_Provides_Reliable_Record-to-Report_Productivity.png?width=400&name=Trintech_Provides_Reliable_Record-to-Report_Productivity.png 400w, https://research.isg-one.com/hs-fs/hubfs/Trintech_Provides_Reliable_Record-to-Report_Productivity.png?width=500&name=Trintech_Provides_Reliable_Record-to-Report_Productivity.png 500w, https://research.isg-one.com/hs-fs/hubfs/Trintech_Provides_Reliable_Record-to-Report_Productivity.png?width=600&name=Trintech_Provides_Reliable_Record-to-Report_Productivity.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span>Trintech provides finance departments in larger and midsize enterprises with software to accelerate their accounting close processes while achieving hard and fast accuracy and compliance requirements with less effort. The financial records of an enterprise must be periodically reviewed and summarized to create financial statements that inform executives and interested third parties of the organization’s financial condition and performance. A consolidation of the financial records and other...</span></p> </div> <a href="https://research.isg-one.com/analyst-perspectives/trintech-provides-reliable-record-to-report-productivity"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://research.isg-one.com/analyst-perspectives/topic/office-of-finance">Office of Finance</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/erp-and-continuous-accounting">ERP and Continuous Accounting</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/digital-finance">digital finance</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/consolidate-and-close-management">Consolidate and Close Management</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://research.isg-one.com/analyst-perspectives/the-power-of-payroll-its-more-than-just-a-paycheck">The Power of Payroll: It’s More than Just a Paycheck</a></h2> <div class="author-meta"> Posted by <a href="https://research.isg-one.com/analyst-perspectives/author/matthew-brown"> Matthew Brown </a> on <span class="post-date">20 February 2025 </span> </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://research.isg-one.com/hs-fs/hubfs/The_Power_of_Payroll.png?width=200&name=The_Power_of_Payroll.png" width="200" !important: srcset="https://research.isg-one.com/hs-fs/hubfs/The_Power_of_Payroll.png?width=100&name=The_Power_of_Payroll.png 100w, https://research.isg-one.com/hs-fs/hubfs/The_Power_of_Payroll.png?width=200&name=The_Power_of_Payroll.png 200w, https://research.isg-one.com/hs-fs/hubfs/The_Power_of_Payroll.png?width=300&name=The_Power_of_Payroll.png 300w, https://research.isg-one.com/hs-fs/hubfs/The_Power_of_Payroll.png?width=400&name=The_Power_of_Payroll.png 400w, https://research.isg-one.com/hs-fs/hubfs/The_Power_of_Payroll.png?width=500&name=The_Power_of_Payroll.png 500w, https://research.isg-one.com/hs-fs/hubfs/The_Power_of_Payroll.png?width=600&name=The_Power_of_Payroll.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Payroll is one of the most universal touchpoints within any organization, impacting every employee on a regular basis. It’s the one thing every employee notices if it does not work perfectly. Yet, despite its far-reaching presence, payroll often operates quietly in the background, treated as an administrative function focused solely on ensuring people are paid accurately and on time. This perception, while understandable, drastically undervalues what payroll can offer.</p> </div> <a href="https://research.isg-one.com/analyst-perspectives/the-power-of-payroll-its-more-than-just-a-paycheck"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://research.isg-one.com/analyst-perspectives/topic/human-capital-management">Human Capital Management</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/payroll-management">Payroll Management</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/employee-experience">employee experience</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://research.isg-one.com/analyst-perspectives/zoho-evolves-portfolio-for-enterprises-using-ai">Zoho Evolves Portfolio for Enterprises Using AI</a></h2> <div class="author-meta"> Posted by <a href="https://research.isg-one.com/analyst-perspectives/author/keith-dawson"> Keith Dawson </a> on <span class="post-date">20 February 2025 </span> </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://research.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=200&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png" width="200" !important: srcset="https://research.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=100&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png 100w, https://research.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=200&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png 200w, https://research.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=300&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png 300w, https://research.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=400&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png 400w, https://research.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=500&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png 500w, https://research.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=600&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Zoho’s recent analyst conference was an opportunity to explore how the India-founded software company is faring in its efforts to extend its enterprise business, and to place AI at the center of its product portfolio. It appears the company is having some success on both fronts.</p> </div> <a href="https://research.isg-one.com/analyst-perspectives/zoho-evolves-portfolio-for-enterprises-using-ai"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://research.isg-one.com/analyst-perspectives/topic/contact-center">Contact Center</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/customer-experience-management">Customer Experience Management</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/customers-and-cx-business-technologies">Customers and CX - Business & Technologies</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://research.isg-one.com/analyst-perspectives/prophixs-fpa-plus-brings-higher-performance-to-midsize-enterprises">Prophix’s FP&A Plus Brings Higher Performance to Midsize Enterprises</a></h2> <div class="author-meta"> Posted by <a href="https://research.isg-one.com/analyst-perspectives/author/robert-kugel"> Robert Kugel </a> on <span class="post-date">19 February 2025 </span> </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://research.isg-one.com/hs-fs/hubfs/Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png?width=200&name=Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png" width="200" !important: srcset="https://research.isg-one.com/hs-fs/hubfs/Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png?width=100&name=Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png 100w, https://research.isg-one.com/hs-fs/hubfs/Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png?width=200&name=Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png 200w, https://research.isg-one.com/hs-fs/hubfs/Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png?width=300&name=Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png 300w, https://research.isg-one.com/hs-fs/hubfs/Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png?width=400&name=Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png 400w, https://research.isg-one.com/hs-fs/hubfs/Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png?width=500&name=Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png 500w, https://research.isg-one.com/hs-fs/hubfs/Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png?width=600&name=Prophix%E2%80%99s_FP%26A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span data-contrast="auto">While headlines tend to focus on flashier topics, arguably the biggest business impact from technology advances over the past two decades has been on helping midsize enterprises improve their performance. These organizations have the same requirements as larger ones but have fewer resources to address those needs. Prophix has been at the forefront of using technology innovation to close that gap throughout this period. Its latest advances include Prophix One, introduced last year, and FP&A...</span></p> </div> <a href="https://research.isg-one.com/analyst-perspectives/prophixs-fpa-plus-brings-higher-performance-to-midsize-enterprises"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://research.isg-one.com/analyst-perspectives/topic/office-of-finance">Office of Finance</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/business-planning">Business Planning</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/digital-finance">digital finance</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://research.isg-one.com/analyst-perspectives/sugarcrm-as-a-revenue-platform-with-ai-for-sellers">SugarCRM as a Revenue Platform with AI for Sellers</a></h2> <div class="author-meta"> Posted by <a href="https://research.isg-one.com/analyst-perspectives/author/stephen-hurrell"> Stephen Hurrell </a> on <span class="post-date">19 February 2025 </span> </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://research.isg-one.com/hs-fs/hubfs/SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png?width=200&name=SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png" width="200" !important: srcset="https://research.isg-one.com/hs-fs/hubfs/SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png?width=100&name=SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png 100w, https://research.isg-one.com/hs-fs/hubfs/SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png?width=200&name=SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png 200w, https://research.isg-one.com/hs-fs/hubfs/SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png?width=300&name=SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png 300w, https://research.isg-one.com/hs-fs/hubfs/SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png?width=400&name=SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png 400w, https://research.isg-one.com/hs-fs/hubfs/SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png?width=500&name=SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png 500w, https://research.isg-one.com/hs-fs/hubfs/SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png?width=600&name=SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p style="margin-top: 0cm; margin-right: 0cm; margin-bottom: 0cm; vertical-align: baseline; padding-left: 0cm;"><span>I was recently a guest of SugarCRM at their 2025 Analyst summit with an opportunity to meet with the executive team and new CEO, David Roberts.</span></p> </div> <a href="https://research.isg-one.com/analyst-perspectives/sugarcrm-as-a-revenue-platform-with-ai-for-sellers"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://research.isg-one.com/analyst-perspectives/topic/sales-engagement">Sales Engagement</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/office-of-revenue">Office of Revenue</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/revenue-performance-management">Revenue Performance Management</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://research.isg-one.com/analyst-perspectives/how-software-can-help-usage-pricing-adoption">How Software Can Help Usage Pricing Adoption</a></h2> <div class="author-meta"> Posted by <a href="https://research.isg-one.com/analyst-perspectives/author/stephen-hurrell"> Stephen Hurrell </a> on <span class="post-date">13 February 2025 </span> </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://research.isg-one.com/hs-fs/hubfs/How_Software_Can_Help_Usage_Pricing_Adoption.png?width=200&name=How_Software_Can_Help_Usage_Pricing_Adoption.png" width="200" !important: srcset="https://research.isg-one.com/hs-fs/hubfs/How_Software_Can_Help_Usage_Pricing_Adoption.png?width=100&name=How_Software_Can_Help_Usage_Pricing_Adoption.png 100w, https://research.isg-one.com/hs-fs/hubfs/How_Software_Can_Help_Usage_Pricing_Adoption.png?width=200&name=How_Software_Can_Help_Usage_Pricing_Adoption.png 200w, https://research.isg-one.com/hs-fs/hubfs/How_Software_Can_Help_Usage_Pricing_Adoption.png?width=300&name=How_Software_Can_Help_Usage_Pricing_Adoption.png 300w, https://research.isg-one.com/hs-fs/hubfs/How_Software_Can_Help_Usage_Pricing_Adoption.png?width=400&name=How_Software_Can_Help_Usage_Pricing_Adoption.png 400w, https://research.isg-one.com/hs-fs/hubfs/How_Software_Can_Help_Usage_Pricing_Adoption.png?width=500&name=How_Software_Can_Help_Usage_Pricing_Adoption.png 500w, https://research.isg-one.com/hs-fs/hubfs/How_Software_Can_Help_Usage_Pricing_Adoption.png?width=600&name=How_Software_Can_Help_Usage_Pricing_Adoption.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Based on the number of invitations I have received to speak on the topic, usage pricing (also referred to as consumption pricing) is hot. But as I have remarked elsewhere, it is not new. I recall a conversation with a customer over 30 years ago when I was involved with <span style="color: black;">analytic software who asked, “Why can’t we just pay for the software we use?” And this of course makes sense: only pay for what you use. In fact, I assert that <span style="background-color: white;">by 2027, over one-half of all enterprises will deploy a mixed revenue...</span></span></p> </div> <a href="https://research.isg-one.com/analyst-perspectives/how-software-can-help-usage-pricing-adoption"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://research.isg-one.com/analyst-perspectives/topic/subscription-management">Subscription Management</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/revenue-management">Revenue Management</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/office-of-revenue">Office of Revenue</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://research.isg-one.com/analyst-perspectives/adapting-to-higher-inflation-longer-with-profitability-management">Adapting to Higher Inflation Longer with Profitability Management</a></h2> <div class="author-meta"> Posted by <a href="https://research.isg-one.com/analyst-perspectives/author/robert-kugel"> Robert Kugel </a> on <span class="post-date">05 February 2025 </span> </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://research.isg-one.com/hs-fs/hubfs/Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png?width=200&name=Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png" width="200" !important: srcset="https://research.isg-one.com/hs-fs/hubfs/Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png?width=100&name=Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png 100w, https://research.isg-one.com/hs-fs/hubfs/Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png?width=200&name=Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png 200w, https://research.isg-one.com/hs-fs/hubfs/Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png?width=300&name=Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png 300w, https://research.isg-one.com/hs-fs/hubfs/Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png?width=400&name=Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png 400w, https://research.isg-one.com/hs-fs/hubfs/Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png?width=500&name=Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png 500w, https://research.isg-one.com/hs-fs/hubfs/Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png?width=600&name=Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span>In anticipation of conditions that suggested accelerating price increases, I wrote in 2021 about <a href="https://robertkugel.isg-research.net/managing-price-inflation-effectively-with-technology">how technology could be useful in an inflationary period</a>, anticipating the world we live in now. Responding effectively to changes in costs is always challenging, but even more so because of the choppy and chaotic nature of the current environment. Inflation may have abated from its highs throughout the rich world but is still an important factor in business decisions. Many enterprises have limited...</span></p> </div> <a href="https://research.isg-one.com/analyst-perspectives/adapting-to-higher-inflation-longer-with-profitability-management"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://research.isg-one.com/analyst-perspectives/topic/office-of-finance">Office of Finance</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/business-planning">Business Planning</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/erp-and-continuous-accounting">ERP and Continuous Accounting</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/subscription-management">Subscription Management</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/digital-finance">digital finance</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/revenue-management">Revenue Management</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://research.isg-one.com/analyst-perspectives/redpanda-lowers-the-complexity-and-cost-of-streaming-and-event-data">Redpanda Lowers the Complexity and Cost of Streaming and Event Data</a></h2> <div class="author-meta"> Posted by <a href="https://research.isg-one.com/analyst-perspectives/author/matt-aslett"> Matt Aslett </a> on <span class="post-date">04 February 2025 </span> </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://research.isg-one.com/hs-fs/hubfs/Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png?width=200&name=Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png" width="200" !important: srcset="https://research.isg-one.com/hs-fs/hubfs/Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png?width=100&name=Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png 100w, https://research.isg-one.com/hs-fs/hubfs/Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png?width=200&name=Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png 200w, https://research.isg-one.com/hs-fs/hubfs/Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png?width=300&name=Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png 300w, https://research.isg-one.com/hs-fs/hubfs/Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png?width=400&name=Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png 400w, https://research.isg-one.com/hs-fs/hubfs/Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png?width=500&name=Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png 500w, https://research.isg-one.com/hs-fs/hubfs/Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png?width=600&name=Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span style="color: black;">I recently wrote about the need for enterprises to </span><span><a href="https://mattaslett.isg-research.net/harness-events-to-process-data-at-the-speed-of-business">harness events</a></span> <span style="color: black;">to </span><span style="color: black; background-color: white;">process and act upon data at the speed of business. The </span><span><a href="https://blog.isg-research.net/eda-with-events-brokers-enable-stream-processing"><span style="background-color: white;">core technologies</span></a></span><span style="color: black; background-color: white;">that enable enterprises to process and analyze data in real time have been in existence for many years and are widely adopted. However, streaming and events technologies are also commonly seen as a niche requirement, separate from an enterprise’s primary focus on batch processing of data at rest. One of the reasons for this is an entrenched reliance on...</span></p> </div> <a href="https://research.isg-one.com/analyst-perspectives/redpanda-lowers-the-complexity-and-cost-of-streaming-and-event-data"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://research.isg-one.com/analyst-perspectives/topic/analytics-data">Analytics & Data</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/streaming-data-events">Streaming Data & Events</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://research.isg-one.com/analyst-perspectives/databricks-scores-massive-funding-round-continues-to-expand-its-offerings">Databricks Scores Massive Funding Round, Continues to Expand Its Offerings</a></h2> <div class="author-meta"> Posted by <a href="https://research.isg-one.com/analyst-perspectives/author/david-menninger"> David Menninger </a> on <span class="post-date">29 January 2025 </span> </div> <hr>  </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://research.isg-one.com/hs-fs/hubfs/Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png?width=200&name=Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png" width="200" !important: srcset="https://research.isg-one.com/hs-fs/hubfs/Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png?width=100&name=Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png 100w, https://research.isg-one.com/hs-fs/hubfs/Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png?width=200&name=Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png 200w, https://research.isg-one.com/hs-fs/hubfs/Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png?width=300&name=Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png 300w, https://research.isg-one.com/hs-fs/hubfs/Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png?width=400&name=Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png 400w, https://research.isg-one.com/hs-fs/hubfs/Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png?width=500&name=Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png 500w, https://research.isg-one.com/hs-fs/hubfs/Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png?width=600&name=Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Databricks <span><a href="https://www.databricks.com/company/newsroom/press-releases/databricks-raising-10b-series-j-investment-62b-valuation">recently announced</a></span> its Series J funding round, successfully raising $10 billion at a valuation of $62 billion. Led by Thrive Capital alongside high-profile investors such as Andreessen Horowitz and Insight Partners, the company intends to invest this capital towards new artificial intelligence (AI) products, acquisitions and significant expansion of its international operations. In the announcement, Databricks reported that it expects to achieve an annual revenue run rate of $3...</p> </div> <a href="https://research.isg-one.com/analyst-perspectives/databricks-scores-massive-funding-round-continues-to-expand-its-offerings"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://research.isg-one.com/analyst-perspectives/topic/analytics">Analytics</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/ai">AI</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/ai-machine-learning">AI & Machine Learning</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/data-platforms">data platforms</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/model-building-and-large-language-models">Model Building and Large Language Models</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/data-intelligence">Data Intelligence</a>, <a href="https://research.isg-one.com/analyst-perspectives/topic/analytics-and-data">Analytics and Data</a> <hr> </div> <script> // Check active classes var checkClass = function() { if ( $('.fil_item').hasClass('hide') ) { $('.fil_item').removeClass('hide'); 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100px) 100vw, 100px" srcset="https://research.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=50&name=Menninger.David%20Pic.Circle.png 50w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=100&name=Menninger.David%20Pic.Circle.png 100w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=150&name=Menninger.David%20Pic.Circle.png 150w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=200&name=Menninger.David%20Pic.Circle.png 200w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=250&name=Menninger.David%20Pic.Circle.png 250w, https://research.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://research.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://research.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=50&name=Orr.Jeff.Circle.png 50w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=100&name=Orr.Jeff.Circle.png 100w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=150&name=Orr.Jeff.Circle.png 150w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=200&name=Orr.Jeff.Circle.png 200w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=250&name=Orr.Jeff.Circle.png 250w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=300&name=Orr.Jeff.Circle.png 300w" sizes="(max-width: 100px) 100vw, 100px"> <h5 class="analyst_name">Jeff Orr</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://keithdawson.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://research.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=100&name=Dawson.Keith%20Pic.Circle.png" alt="Keith Dawson" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://research.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=50&name=Dawson.Keith%20Pic.Circle.png 50w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=100&name=Dawson.Keith%20Pic.Circle.png 100w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=150&name=Dawson.Keith%20Pic.Circle.png 150w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=200&name=Dawson.Keith%20Pic.Circle.png 200w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=250&name=Dawson.Keith%20Pic.Circle.png 250w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=300&name=Dawson.Keith%20Pic.Circle.png 300w"> <h5 class="analyst_name">Keith Dawson</h5> </a> </div> <div class="span6" style="text-align:center;"> <a href="https://marksmith.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://research.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=100&name=Smith.Mark%20Pic.Circle.png" alt="Mark Smith" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://research.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=50&name=Smith.Mark%20Pic.Circle.png 50w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=100&name=Smith.Mark%20Pic.Circle.png 100w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=150&name=Smith.Mark%20Pic.Circle.png 150w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=200&name=Smith.Mark%20Pic.Circle.png 200w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=250&name=Smith.Mark%20Pic.Circle.png 250w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=300&name=Smith.Mark%20Pic.Circle.png 300w"> <h5 class="analyst_name">Mark Smith</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://mattaslett.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://research.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=100&name=Aslett.Matt%20Pic.Circle.png" alt="Matt Aslett" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://research.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=50&name=Aslett.Matt%20Pic.Circle.png 50w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=100&name=Aslett.Matt%20Pic.Circle.png 100w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=150&name=Aslett.Matt%20Pic.Circle.png 150w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=200&name=Aslett.Matt%20Pic.Circle.png 200w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=250&name=Aslett.Matt%20Pic.Circle.png 250w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=300&name=Aslett.Matt%20Pic.Circle.png 300w"> <h5 class="analyst_name">Matt Aslett</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://matthewbrown.isg-research.net/"> <img class="analyst_img" style="width: 100px;" src="https://research.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=100&name=profile_vr_matthew_brown_circle_900x900.png" alt="Matthew Brown" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://research.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=50&name=profile_vr_matthew_brown_circle_900x900.png 50w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=100&name=profile_vr_matthew_brown_circle_900x900.png 100w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=150&name=profile_vr_matthew_brown_circle_900x900.png 150w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=200&name=profile_vr_matthew_brown_circle_900x900.png 200w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=250&name=profile_vr_matthew_brown_circle_900x900.png 250w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=300&name=profile_vr_matthew_brown_circle_900x900.png 300w"> <h5 class="analyst_name">Matthew Brown</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://robertkugel.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://research.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=100&name=Kugel.Robert%20Pic.Circle.png" alt="Robert Kugel" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://research.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=50&name=Kugel.Robert%20Pic.Circle.png 50w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=100&name=Kugel.Robert%20Pic.Circle.png 100w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=150&name=Kugel.Robert%20Pic.Circle.png 150w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=200&name=Kugel.Robert%20Pic.Circle.png 200w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=250&name=Kugel.Robert%20Pic.Circle.png 250w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=300&name=Kugel.Robert%20Pic.Circle.png 300w"> <h5 class="analyst_name">Robert Kugel</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://stephenhurrell.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://research.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=100&name=Hurrell.Stephen%20Pic.Circle.png" alt="Stephen Hurrell" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://research.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=50&name=Hurrell.Stephen%20Pic.Circle.png 50w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=100&name=Hurrell.Stephen%20Pic.Circle.png 100w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=150&name=Hurrell.Stephen%20Pic.Circle.png 150w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=200&name=Hurrell.Stephen%20Pic.Circle.png 200w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=250&name=Hurrell.Stephen%20Pic.Circle.png 250w, https://research.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=300&name=Hurrell.Stephen%20Pic.Circle.png 300w"> <h5 class="analyst_name">Stephen Hurrell</h5> </a> </div> </div>   <div class="row-fluid">  <div style="text-align: center;"> <a href="https://blog.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://research.isg-one.com/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=100&name=ISG_Bug_Reverse_Transparent.png" alt="ISG Software Research" width="100" data-constrained="true" caption="false" 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href="https://research.isg-one.com/analyst-perspectives/archive/2014/11">November 2014 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2014/10">October 2014 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2014/09">September 2014 <span class="filter-link-count" dir="ltr">(10)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2014/08">August 2014 <span class="filter-link-count" dir="ltr">(7)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2014/07">July 2014 <span class="filter-link-count" dir="ltr">(7)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2014/06">June 2014 <span class="filter-link-count" dir="ltr">(16)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2014/05">May 2014 <span class="filter-link-count" dir="ltr">(9)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2014/04">April 2014 <span class="filter-link-count" dir="ltr">(15)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2014/03">March 2014 <span class="filter-link-count" dir="ltr">(14)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2014/02">February 2014 <span class="filter-link-count" dir="ltr">(13)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2014/01">January 2014 <span class="filter-link-count" dir="ltr">(16)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2013/12">December 2013 <span class="filter-link-count" dir="ltr">(6)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2013/11">November 2013 <span class="filter-link-count" dir="ltr">(15)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2013/10">October 2013 <span class="filter-link-count" dir="ltr">(10)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2013/09">September 2013 <span class="filter-link-count" dir="ltr">(11)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2013/08">August 2013 <span class="filter-link-count" dir="ltr">(17)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2013/07">July 2013 <span class="filter-link-count" dir="ltr">(12)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2013/06">June 2013 <span class="filter-link-count" dir="ltr">(13)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2013/05">May 2013 <span class="filter-link-count" dir="ltr">(21)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2013/04">April 2013 <span class="filter-link-count" dir="ltr">(19)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2013/03">March 2013 <span class="filter-link-count" dir="ltr">(35)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2013/02">February 2013 <span class="filter-link-count" dir="ltr">(27)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2013/01">January 2013 <span class="filter-link-count" dir="ltr">(31)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2012/12">December 2012 <span class="filter-link-count" dir="ltr">(20)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2012/11">November 2012 <span class="filter-link-count" dir="ltr">(21)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2012/10">October 2012 <span class="filter-link-count" dir="ltr">(25)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2012/09">September 2012 <span class="filter-link-count" dir="ltr">(21)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2012/08">August 2012 <span class="filter-link-count" dir="ltr">(26)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2012/07">July 2012 <span class="filter-link-count" dir="ltr">(24)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2012/06">June 2012 <span class="filter-link-count" dir="ltr">(27)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2012/05">May 2012 <span class="filter-link-count" dir="ltr">(32)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2012/04">April 2012 <span class="filter-link-count" dir="ltr">(23)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2012/03">March 2012 <span class="filter-link-count" dir="ltr">(21)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2012/02">February 2012 <span class="filter-link-count" dir="ltr">(13)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2012/01">January 2012 <span class="filter-link-count" dir="ltr">(14)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2011/12">December 2011 <span class="filter-link-count" dir="ltr">(14)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2011/11">November 2011 <span class="filter-link-count" dir="ltr">(19)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2011/10">October 2011 <span class="filter-link-count" dir="ltr">(28)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2011/09">September 2011 <span class="filter-link-count" dir="ltr">(26)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2011/08">August 2011 <span class="filter-link-count" dir="ltr">(20)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2011/07">July 2011 <span class="filter-link-count" dir="ltr">(12)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2011/06">June 2011 <span class="filter-link-count" dir="ltr">(22)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2011/05">May 2011 <span class="filter-link-count" dir="ltr">(28)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/archive/2011/04">April 2011 <span class="filter-link-count" dir="ltr">(19)</span></a> </li> <li style="display:none;"> <a 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href="https://research.isg-one.com/analyst-perspectives/topic/tagetik">Tagetik <span class="filter-link-count" dir="ltr">(5)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/topic/talemetry">Talemetry <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/topic/talend">Talend <span class="filter-link-count" dir="ltr">(4)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/topic/talent-acquisition">Talent Acquisition <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/topic/talent-generation">Talent Generation <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/topic/talent-management">Talent 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href="https://research.isg-one.com/analyst-perspectives/topic/tax-compliance">tax compliance <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/topic/tax-department">tax department <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/topic/tax-planning">tax planning <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/topic/tax-software">Tax Software <span class="filter-link-count" dir="ltr">(1)</span></a> </li> <li style="display:none;"> <a href="https://research.isg-one.com/analyst-perspectives/topic/tax-datawarehouse">Tax-Datawarehouse <span class="filter-link-count" dir="ltr">(2)</span></a> </li> <li style="display:none;"> <a 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"headline": "Agentic AI Reliability Requirements for Data", "mainEntityOfPage": "https://research.isg-one.com/analyst-perspectives/agentic-ai-reliability-requirements-for-data", "datePublished": "25/02/2025", "dateModified": "25/02/2025", "articleBody": "It is now more than two years since the launch of ChatGPT introduced the world to generative AI (GenAI) and large language models (LLMs). GenAI-based assistants and co-pilots are now widely adopted, with individuals and enterprises adopting GenAI models to automate the generation of text, digital images, audio, video and code, amongst other things. More than four-fifths (81%) of participants in ISG’s Market Lens study on GenAI are using chat-based services, such as ChatGPT, with 72% using GenAI for text generation and translation, 43% for code generation, and 42% for image generation. ISG’s recent Market Lens study on GenAI also indicated that the primary motivations for enterprise adoption of these GenAI models include improved efficiency, business growth and cost savings. The rapid rate of adoption of GenAI models and assistants has been matched by the rapid pace of expansion of GenAI-related capabilities. While LLMs triggered the initial adoption of GenAI, attention quickly expanded to associated capabilities such as retrieval-augmented generation. This is being adopted by enterprises to make GenAI more suitable for addressing enterprise use-cases by grounding the output of GenAI models in enterprise data to improve trust. The latest focus of attention in the AI space is agentic AI, with multiple software providers introducing agents that combine multiple models and assistants to take GenAI beyond the automation of discreet functions to address complete business tasks. The rise of agentic AI is a natural outcome of enterprise requirements related to GenAI. While individual users can play around with various GenAI models and services to fulfill discreet requirements, enterprises have more complex processes and requirements that need to be served by a combination of models and applications. The variety of GenAI models available presents enterprises with the upfront challenge of understanding the suitability of models to specific business tasks and processes and approving specific models for enterprise use. While many models can be used without modification for non-critical use-cases, in many cases enterprises will need to train, tune, prompt or ground the model with enterprise information to ensure that they can trust its output. Grounding a model with enterprise data can only be successful if the enterprise has trust in the data being used to ground the model. As such, it is imperative for enterprises to ensure the validity, quality and reliability of enterprise data. As was explained in ISG’s State of Generative AI Market Report, AI-ready data is data that is clean, well-organized and compliant with regulatory standards. The need for good data management is by no means new. Enterprises have been concerned about data quality and reliability as it relates to business intelligence for many years. Despite that, many enterprises find themselves struggling with data that is fragmented, inconsistent and not easily accessible. The importance of good data management is an even greater priority in relation to AI for three key reasons. Firstly, while BI uses data to support decisions that are taken by employees, enterprises adopting AI are relying on data to make and automate decisions in real-time. Secondly, those decisions are increasingly critical—for example spotting fraudulent activity and delivering customer service—so the risks associated with failure are heightened. Thirdly, the use of AI is increasingly a board-level concern. If the CEO is driving increased adoption of AI, and has expectations about improving efficiency, innovation and growth, then AI initiatives had better deliver. Increased enterprise focus on AI is therefore a forcing function for enterprises to take long-overdue steps to improve data management and data governance. As my colleague David Menninger recently explained, enterprises also need to govern the security, privacy and explainability of the application, while also being conscious of the criticality of detecting and preventing bias as well as identifying and eliminating toxicity. I assert that through 2026, one-third of enterprises will realize that a lack of AI and ML governance has resulted in biased and ethically questionable decisions. Finally, once models have been selected, trained, grounded and governed, enterprises also need to be able to ensure that recommendations and automated decisions are conducted in the context of reasoning and driver-based planning models and applications, and that they can also identify and measure the value delivered by an AI project to explain and justify the investment. Individual models deployed in isolation can be used to serve discreet, well-defined functions (like code conversion or drafting an email). Given the variety of requirements, however, it is clear that individual models will not be enough to serve more complex business use cases, such as responding to a customer service inquiry. In addition to training, tuning, prompting or grounding via RAG, the output of GenAI models also needs to be combined with other AI models to address predictive machine learning, reasoning, planning, budgeting and risk assessment. Similar to the way in which different combinations of atoms come together to form different molecules, we see software providers and enterprises alike bringing together different combinations of AI models to form agents to fulfil specific business tasks. I recommend that all enterprises explore the potential benefits of agentic AI. While they do so, however, they should also be cognizant of the advice of my colleague Robert Kugel and his assertion that enterprises need to invest in generative automation to address the even greater levels of complexity involved in collaborative business processes. Regards, Matt Aslett", "image": { "@type": "ImageObject", "url": "https://research.isg-one.com/hubfs/Agentic_AI_Reliability_Requirements_for_Data.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Matt Aslett", "url": "https://research.isg-one.com/analyst-perspectives/author/matt-aslett", "sameAs": "https://www.linkedin.com/in/matt-aslett/" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "research.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": "Trintech Provides Reliable Record-to-Report Productivity", "mainEntityOfPage": "https://research.isg-one.com/analyst-perspectives/trintech-provides-reliable-record-to-report-productivity", "datePublished": "25/02/2025", "dateModified": "25/02/2025", "articleBody": "Trintech provides finance departments in larger and midsize enterprises with software to accelerate their accounting close processes while achieving hard and fast accuracy and compliance requirements with less effort. The financial records of an enterprise must be periodically reviewed and summarized to create financial statements that inform executives and interested third parties of the organization’s financial condition and performance. A consolidation of the financial records and other departmental close processes involves an intricate set of repeated processes that must be performed in a prescribed order and fashion. Enterprise software enables finance and accounting departments to be more productive throughout the close by automating calculations, coordinating the execution of processes and facilitating communication among participants. For larger and even midsize enterprises, software is needed to handle the record-to-report (R2R) cycle because it can be complex, requiring the coordination of numerous people in and outside the department, as well as multiple systems and sources of data. Beyond financial consolidation, the R2R cycle includes performing reconciliations and adjusting of entries during the close as well as authoring, editing and updating narratives in the creation of disclosure documents. All of these must adhere to internal controls that require defined processes including reviews and approvals by multiple individuals. During the financial close, all financial transactions are reconciled, reviewed and adjusted as needed to prepare the financial statements. These include the balance sheet, income statement, cash flow statement and the statement of shareholders’ equity. There are iterative portions of the process that involve cycles of reviews and levels of approvals. For publicly held corporations, financial statement quality and fidelity are of utmost importance. The desire to make the department more productive and resilient has led to increased investment in technology to assist in performing the full consolidate and close cycle. One key objective within the R2R process is to minimize the time it takes to complete the accounting close, with the generally accepted norm being one business week. Shortening the close means that all downstream tasks can be finished sooner, providing executives, managers, directors and shareholders with information about the enterprise’s financial performance and health sooner. ISG Research asserts that by 2028, two-thirds of finance and accounting departments will improve their use of readily available technology to close their quarterly books within six business days, up from one-half that can do it today. Trintech provides Cadency, a platform that streamlines balance sheet reconciliations; handles high-volume transactions matching and intercompany accounting chores to reduce workloads; automates journal entry creation and posting to ensure consistency, accuracy and auditability; and that documents financial governance models and handles their compliance and related reporting. It also has software for managing the close process, and the platform also applies analytics to identify areas of financial risk and offer strategies for addressing them. These capabilities have become even more essential as remote and hybrid working have become the norm, since they can overcome the challenges of managing time-sensitive, business-critical processes in a more complex working environment that makes collaboration and coordination difficult. To support these functions, it’s necessary for enterprises to facilitate data integration, which Trintech does though targeted APIs, integration with common ERP systems and its data-as-a-service offering. Cadency Direct, built on the ServiceNow platform, automates a department’s close-to-report processes while providing native workflows and triggers to enterprises using the Now Platform. Our financial close research has found that tighter control of the intricate operations involved in the financial close, as well as an ongoing continuous improvement approach to refining the processes are regarded as the most effective ways of streamlining and shortening the close process. Not only does software like Cadency Direct help ensure that tasks are started on time, that hand-offs are smooth and timely, and that there is complete visibility into the status of the process at any time, it ensures that the close is managed consistently and, as enterprises refine that process, those changes remain baked in. For midsize enterprises, Trintech offers Adra, software for transactions matching, account reconciliations and task management, along with related analytics to provide visibility and insight to evaluate the department’s efficiency and quality in managing the close process. Adra is designed specifically for the budgets and operating needs of midsize enterprises by streamlining the implementation process, reducing the amount of training required. Transactions matching substantially reduces the time spent ensuring the accuracy and fidelity of financial statements by automating the tedious tasks of matching transactions with bank and credit card statements, point-of-sale systems, and other internal or external sources of data. Midsize enterprises typically do not have the transactions volume and complex legal entity and systems complexity typical of larger ones, and Adra offers an advantage in its cost to deploy and maintain, without sacrificing performance. Additionally, Trintech and Planful have a strategic partnership in place to provide finance organizations with an integrated close management system that includes Planful’s consolidation system. The combination enables enterprises to accelerate their R2R process while increasing control and auditability. Trintech’s T-Recs simplifies and automates the reconciliation process by integrating with various transactional systems. The software matches transactions between different systems, ensuring that discrepancies are identified and resolved promptly. T-Recs is designed to address the needs of organizations with large volumes of transactions, providing immediate insights into discrepancies to keep the accounting staff ahead of the curve. ReconNET is designed to automate high-volume transaction and matching to accelerate reconciliations while providing detective and preventative controls for risk management. Trintech is a member of Built on Workday, a program that makes it possible for partners to apply their intellectual property to create and maintain applications that operate natively on the Workday platform. The software is available on the Workday Marketplace to facilitate its acquisition. For more than two decades, our research has focused on practical and affordable processes and technology to streamline the operations of finance and accounting departments. Steady advances have increased the importance of using automation to enable enterprises to use software to speed the close while promoting accuracy and control, allowing finance and accounting staff to spend more time on work that takes advantage of their experience and expertise. These advances will continue over the next five years, especially the use of artificial intelligence using machine learning (AI/ML) to identify potential errors and fraud and further reduce the time spent by the staff on repetitive processes. Cloud-based systems enable vendors to immediately incorporate advances in their software so that they are available to customers without their having to upgrade. I recommend that enterprises review the systems and processes they use to manage their R2R cycle. Those that take longer than one business week to complete their accounting close should investigate how technology can accelerate and improve their performance. As part of that process, I recommend that they investigate how Trintech’s offerings can help streamline and shorten their accounting close. Regards, Robert Kugel", "image": { "@type": "ImageObject", "url": "https://research.isg-one.com/hubfs/Trintech_Provides_Reliable_Record-to-Report_Productivity.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Robert Kugel", "url": "https://research.isg-one.com/analyst-perspectives/author/robert-kugel", "sameAs": "https://www.linkedin.com/in/robertkugel" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "research.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 Power of Payroll: It’s More than Just a Paycheck", "mainEntityOfPage": "https://research.isg-one.com/analyst-perspectives/the-power-of-payroll-its-more-than-just-a-paycheck", "datePublished": "20/02/2025", "dateModified": "20/02/2025", "articleBody": "Payroll is one of the most universal touchpoints within any organization, impacting every employee on a regular basis. It’s the one thing every employee notices if it does not work perfectly. Yet, despite its far-reaching presence, payroll often operates quietly in the background, treated as an administrative function focused solely on ensuring people are paid accurately and on time. This perception, while understandable, drastically undervalues what payroll can offer. Imagine a payroll system that does more than simply process paychecks. What if payroll could do more than just pay people? What if it became a strategic powerhouse—boosting employee engagement, shaping smarter workforce planning and even improving financial wellness? Today’s advancements in payroll technology have unlocked new opportunities for organizations willing to rethink its role. For many employees, their most consistent interaction with their employer comes through payroll systems. Payroll systems are an often-overlooked communication channel. Employees already interact with payroll regularly—making it the perfect platform to share personalized messages about benefits enrollment, training opportunities or work anniversaries. These systems handle routine tasks like viewing paychecks, checking deductions or accessing earnings history. These regular interactions represent untapped potential. Imagine if routine payroll interactions became opportunities to celebrate milestones, promote wellness programs or share career opportunities. These small but meaningful touchpoints could transform ordinary transactions into moments that build trust and connection. Beyond engagement, payroll systems hold great potential as tools for strategic decision-making. They generate data that offers deep insights into labor costs, overtime trends and workforce distribution. For too long, this rich data has been sitting in the shadows, underutilized. By unlocking its potential, businesses can move from reactive management to proactive, data-driven strategy. By analyzing these patterns, businesses can make more informed decisions about staffing, retention strategies and shift scheduling. Integrating payroll with other HR systems unlocks powerful possibilities. For example, linking payroll data with performance metrics could reveal correlations between compensation and productivity, or help identify retention risks. Similarly, integrating payroll with workforce planning tools provides a comprehensive view of labor dynamics, enabling smarter hiring and team realignments. These integrations create a more cohesive picture of the workforce, aligning payroll insights with broader business goals. Financial stress is a growing concern for employees, impacting productivity and well-being. Payroll systems can ease this burden through features like earned wage access, which gives employees flexibility to draw part of their pay before payday. These tools foster financial stability and contribute to a more satisfied, productive workforce. Because of this, I assert that by 2026, one-third of enterprises will offer earned wage access (EWA) to their workforce as on-demand payroll offerings become available for workers who desire and demand pay flexibility. Modern payroll platforms can also incorporate tools and resources for financial education, such as budgeting advice or retirement planning. These initiatives don’t just benefit employees—they support a more stable, engaged workforce that’s better equipped to focus on organizational goals. Of course, seizing these opportunities isn’t always easy. Significant barriers still prevent many organizations from fully realizing payroll’s potential. Legacy systems, designed primarily for wage processing often suffer from a lack of flexibility, scalability and integration capabilities, preventing organizations from leveraging payroll as a strategic tool. Additionally, siloed payroll systems that don’t integrate with broader HR or financial tools limit the flow of data, stifling innovation. Upgrading to modern payroll technology can overcome these limitations, opening the door to real-time data, automation and advanced analytics. Another challenge is cultural resistance. Many organizations continue to see payroll as a transactional, back-office function. Changing this perception requires a shift in how payroll’s role is viewed—not as a necessary task, but as a platform that can contribute to broader business goals. Fortunately, advancements in payroll technology are addressing these challenges. Real-time payroll capabilities, for instance, allow employees to view and access their earnings as they are earned, reducing financial stress and providing greater flexibility. For employers, these systems offer immediate insights into labor costs, improving budget management and enabling better forecasting. Artificial intelligence (AI) and analytics are transforming payroll into a dynamic, data-driven function. For instance, AI can automate compliance checks, flagging errors in tax calculations or benefits deductions before they escalate. It can also uncover patterns in payroll data, such as overtime trends linked to employee turnover, enabling HR to proactively adjust workloads or retention strategies. Similarly, analytics tools provide real-time insights into labor costs, helping organizations optimize shift schedules and improve budget management. Together, these technologies free HR teams to focus on strategic initiatives, turning payroll into a proactive driver of business success. Because of this, I assert that by 2028, one-fifth of enterprises will benefit from payroll platforms that use AI to detect errors and omissions that would prohibit the payroll run, like missed punches, and nudge managers to take action and resolve. Payroll touches every employee and every paycheck—it’s the most consistent connection between people and their organization. By reimagining payroll as a strategic asset, businesses can unlock its potential to drive engagement, inform planning and support employee well-being. Are your current systems fully integrated with other HR tools? Do they offer advanced features like real-time payroll or earned wage access? By rethinking payroll’s role, and leveraging technology with intention and purpose, you can transform it from a routine process into a strategic asset that drives engagement, informs planning, and improves employee well-being. For a deeper dive into the trends and solutions shaping modern payroll systems, explore ISG’s latest Payroll Management Research. It’s time to stop seeing payroll as just another task—and start imagining what it could do for your people, your workforce, and your business. Regards, Matthew Brown", "image": { "@type": "ImageObject", "url": "https://research.isg-one.com/hubfs/The_Power_of_Payroll.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Matthew Brown", "url": "https://research.isg-one.com/analyst-perspectives/author/matthew-brown", "sameAs": "https://www.linkedin.com/in/matthewwbrown/" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "research.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": "Zoho Evolves Portfolio for Enterprises Using AI", "mainEntityOfPage": "https://research.isg-one.com/analyst-perspectives/zoho-evolves-portfolio-for-enterprises-using-ai", "datePublished": "20/02/2025", "dateModified": "20/02/2025", "articleBody": "Zoho’s recent analyst conference was an opportunity to explore how the India-founded software company is faring in its efforts to extend its enterprise business, and to place AI at the center of its product portfolio. It appears the company is having some success on both fronts. Zoho’s software suite includes nearly 60 applications that extend into almost every facet of business activity, from front to back office. Of those, a significant number are relevant to customer experience professionals in sales, service and marketing. This group of professionals is engaged in work that is critical to company health, but at the same time underappreciated and often under-resourced. They are also operating at a moment when many of the basic processes and underlying assumptions of CX are being reconfigured and reevaluated. It is a strange time to be a CX professional, especially when it comes to contact centers and service delivery. Much of the uncertainty in today’s environment has to do with the development of tools that use AI for process automation. There have been significant productivity gains already in the contact center, with more expected as those centers become more closely connected with other siloed CX teams and processes across the enterprise. Zoho has been developing AI applications and incorporating them into the suite wherever practical, and our research finds these advancements are helping Zoho improve their overall performance, with the company achieving an Exemplary rating in our recent ISG Buyers Guide on advanced contact centers. It’s worth noting that their AI development pre-dates the current industry conversations around generative and agentic AI tools, and this gives them valuable perspective on these current conversations. In the analyst presentations, Zoho executives went out of their way to address the limitations of some approaches to AI in software apps. For example, they noted that introducing AI into certain tools raises issues of compliance—can an LLM be made to “forget” certain pieces of information once they have been learned? It has an impact on information retention policies. They also mentioned the idea of productivity, suggesting that there are subtle limits to the kinds of productivity increases AI can usher in. While 10x or 100x improvements in programming productivity are possible, they argue you can’t necessarily expect that kind of explosion from certain processes that require human intervention to verify the accuracy of unstructured AI output, like creating legal briefs or corporate annual reports. It’s fair to say that the kinds of processes being automated in CX and contact centers have more in common with those human-verifiable activities than with programming, suggesting something of a cap on the improvements to be seen from AI in CX. Assuming that those limitations can be overcome (which is likely), the boom in productivity has other downstream effects that need to be worked through. Zoho used the analogy of previous technology revolutions causing disruptions in ways that the business world at large has trouble digesting. When farm productivity increased massively due to automation and scale, more farmers had to leave the profession, and farm incomes did not keep up; farmers did not reap the benefits of their own productivity. Similarly, the textile industry is now so extremely productive that traditional weavers are effectively gone. Zoho uses these comparisons to suggest that because business models can undergo such radical change in a short period of time, businesses must look for new sources of value in their enterprise software. Zoho locates that value in providing privacy, trust and the assurance of compliance. In their telling, practical usage of Zoho’s AI applications will proceed in three stages. First, the tools are enhancing the user experience by surfacing and executing on contextual business data. That is where things stand so far. (I take “contextual” to mean ensuring that the technology understands the context of the interaction with the user, which requires a finer sense of the business relationship, data and actions while respecting the permissions necessary to have access to information and answers.) The second phase is in creating tools that enact “AI-enabled verifiable actions,” which is a way of describing AI agents and their ability to perform actions that don’t necessarily require human verification. This is where current work is being done. And the third stage, still to come, will ultimately be the aforementioned explosion of productivity, and its unforeseeable consequences. Zoho’s AI platform, Zia, is being described as a bridge that connects LLMs to applications, allowing customers to pick one and let it be the underlying LLM for a specific app. Zia Agent Studio then facilitates creation and deployment of comprehensive agents that live in a unified data platform leveraging a broad set of existing tools and a common trust layer. This suggests that over time, Zoho’s offering should be perceived less as a collection of point solutions, or apps for narrowly defined business functions, and more as a platform company with centralized data, tools for customers to innovate, and a common AI element cutting across the application set. This tracks with our ISG Research assertion that by 2028, enterprises will replace many CX point solutions with broad, interdepartmental, multifunction suites. Zoho’s stated goal is to move from the SMB and mid-markets towards becoming an enterprise software supplier. This has been a strategy since at least 2022. Clearly the company sees the opportunity to use AI as a catalyst to evolve the app collection into a cohesive platform, and to use the platform as a selling point in seizing enterprise-level opportunities. From the point of view of enterprise CX, Zoho can successfully make that argument. Their apps run the gamut from trouble ticketing and help desk to basic contact center voice services, messaging, many CRM functions, automated marketing, and the reporting and analytics needed to support enterprise CX. In short, it’s possible to assemble a bundle from Zoho that contains enough cross-functional, cross-departmental tools to support an enterprise-level effort to manage the customer lifecycle. That puts the Zoho suite on par with other competitive customer experience management toolkits such that in 2024, they were rated Exemplary in the ISG Buyers Guide on customer experience management. Zoho also presented details of the CX roadmap that indicate the company is putting significant investment into enhancing user productivity, communications capabilities, engagement tools and the analytics to support those functions. And the areas of investment appear to be balanced between developing AI capabilities and other aspects of the toolset outside of AI. This builds on top of its work in analytics which propelled the company to an Exemplary rating in the ISG Buyers Guide on Analytics and Data. In light of this, I think enterprise buyers should consider Zoho’s offering for many CX needs. The perception of Zoho as a collection of SMB-focused niche applications is somewhat unfair. Based on the continued evolution of the underlying platform, and the emphasis on tying the disparate components together through AI and data management, I believe the Zoho CX portfolio is well-suited to the needs of many mid-market-to-large enterprises, especially those that are just now taking steps to rationalize and harmonize tools and processes that span CX departments. Regards, Keith Dawson", "image": { "@type": "ImageObject", "url": "https://research.isg-one.com/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Keith Dawson", "url": "https://research.isg-one.com/analyst-perspectives/author/keith-dawson", "sameAs": "www.linkedin.com/in/keith-dawson-b17b71" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "research.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": "Prophix’s FP&A Plus Brings Higher Performance to Midsize Enterprises", "mainEntityOfPage": "https://research.isg-one.com/analyst-perspectives/prophixs-fpa-plus-brings-higher-performance-to-midsize-enterprises", "datePublished": "19/02/2025", "dateModified": "19/02/2025", "articleBody": "While headlines tend to focus on flashier topics, arguably the biggest business impact from technology advances over the past two decades has been on helping midsize enterprises improve their performance. These organizations have the same requirements as larger ones but have fewer resources to address those needs. Prophix has been at the forefront of using technology innovation to close that gap throughout this period. Its latest advances include Prophix One, introduced last year, and FP&A Plus, the latest evolution of their financial planning and analysis (FP&A) platform. We gave Prophix One our Digital Innovation Award for the Office of Finance in 2024. Prophix One is a finance and accounting platform that provides enterprises a single point of entry and common authentication for financial applications. It uses in-memory cube technology to enable enterprises to handle complex planning tasks built on very large datasets to eliminate barriers to support integrated business planning. The platform and its dedicated data store support the use of artificial intelligence (AI) using machine learning to compress planning cycles with better forward intelligence and high participation planning. A major benefit of using planning software that runs on Amazon Web Services (AWS), as Prophix does, is that it allows enterprises to operate at scale elastically with the needs of the business, providing midsize enterprises with a superior performance-cost experience. The platform also makes it possible for customers to start with any application and expand as their needs evolve while maintaining a common user experience and full data integration. FP&A Plus is the company’s latest version of its business planning software. Prophix was early in addressing the need for enterprises to bring together their operational and financial planning across their entire organization. This integration creates a comprehensive business management tool that supports better decision-making, improves organizational and individual business unit performance while respecting financial constraints and objectives. This approach to business planning provides executives and managers with a robust tool that enables them to manage more effectively to improve performance and agility. This method of business planning is infeasible using stand-alone spreadsheets because of their inherent technical limitations. ISG Research rated Prophix as Assurance in the Business Planning Buyers Guide where these improvements help address areas of its products for improvement. Despite the business benefits that enterprises can achieve from business-focused planning, our research finds that more than half of enterprises rely on spreadsheets to manage their planning and budgeting processes. I believe one reason is that despite the limitations of stand-alone spreadsheets, many potential buyers have not found the benefits of a dedicated application to be overwhelmingly better. That’s about to change and FP&A Plus shows why. FP&A Plus is engineered to take full advantage of a web-based planning platform. For Prophix customers, its Infinix engine running on AWS scales and performs to the needs of the customer, regardless of the scope or complexity of the enterprise or the business planning models. For example, rapid iterations of detailed stock-keeping unit (SKU) level forecasts and their impact on operations and finance are feasible. Staffing-heavy businesses can quickly gauge the effects of a range of wage and benefit scenarios by worker types and locations. The potential impact of tariffs or other forces affecting input costs can be modeled, along with the results of management responses to those changes. The software takes advantage of techniques developed over the past decade to optimize performance and cost, including containerized elastic resource scaling, column stores for rapid data retrieval and bitmap indexing to streamline search and filtering. An important feature of the Prophix platform that makes high-performance business relevance possible is its unified data store. Unlike a general-purpose construct such as a data warehouse, everything that users of FP&A Plus need is readily available and easily accessible, with labels that are immediately recognized and understood. Connectors automatically pull information from all necessary source systems (such as ERP and CRM) into the platform, transforming it to create a usable unitary source. This addresses a major barrier faced by FP&A professionals. They often have less time to do forward-looking analysis because the mechanical process of pulling together and collating data takes up so much time that little remains for using data to spot trends, find opportunities and isolate issues to create better-informed forecasts, plans and decisions. Our Analytics and Data Benchmark Research found that two-thirds of analysts spend considerable time on data preparation and reviewing data for quality and consistency issues, leaving less time for analysis. By substantially eliminating the time required for data preparation and data quality control, financial and business analysts have more time to concentrate on analytical work. Having consistent, reliable data resident on the platform makes automating updates and self-service reporting possible. FP&A Plus has a feature that automates commentary generation for tables. Professionals can have the system write the basic text and then edit it with additional insights or recommendations. By automating the collection of data, reports and dashboards can be timelier. By broadening the set and scope of data readily available with more information on which to base analyses, including external data, the FP&A group can provide more incisive perspectives and insights, enabling executives and managers to make better-informed decisions sooner. Having a planning platform that facilitates scenario planning is likely to provide a competitive advantage. ISG Software Research asserts that by 2028, only 20% of enterprises will have all the data they need to understand trade-offs in their scenario planning to improve agility, up from 12% today. The Infinix platform uses in-memory processing to speed calculations and data compression to allow faster processing and reduced storage requirements, which cuts costs without affecting data integrity. It applies directed acyclic graphics routines to streamline calculations and data flows, which cut models’ processing time and scalability. To handle the most common aspects of an integrated business plan, the software facilitates collecting and incorporating sales forecasts and workforce plans so that updates to price lists, benefit costs, projected headcount levels and the like are instantly reflected in projected income statements, proforma balance sheets and statements of cash flows, whether these are monthly, quarterly or annual. Multiple scenarios driven by key performance metrics or other macro assumptions can be created on the fly and compared side by side. Moreover, having the operational and financial data at hand makes it possible to do product- or channel-level profitability analysis to make informed decisions around pricing strategies. This enables enterprises to adopt a profitability management discipline, a more effective approach to widening margins compared to having profitability objectives. One issue that FP&A professionals confront in bringing together financial and operational plans is orchestrating the process to support rapid reforecasting cycles. Prophix has an easy-to-configure workflow manager to enable time-challenged administrators to manage by exception, letting the system handle routine matters. I’ve written extensively about the potential for AI and generative AI (GenAI) to have a significant positive impact on finance department productivity. There’s almost no end to the ways technology can enhance departmental productivity. This goes beyond simple efficiency gains to include important contributors to extending the capabilities of the staff to improve the performance of the entire enterprise. The feasible and cost-efficient use cases that AI and GenAI can bring to finance organizations over the next five years by software providers will depend heavily on their foundational technology. Prophix One and FP&A Plus are designed to support these advances. I strongly recommend that enterprises that manage their forecasting, planning, budgeting and reporting using stand-alone spreadsheets shift to a cloud-based planning platform. Those that are currently using an on-premises dedicated application also should consider moving to the cloud. In either case, I recommend that they evaluate Prophix for this purpose as well as its other financial management capabilities. Regards, Robert Kugel", "image": { "@type": "ImageObject", "url": "https://research.isg-one.com/hubfs/Prophix%E2%80%99s_FP&A_Plus_Brings_Higher_Performance_to_Midsize_Enterprises.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Robert Kugel", "url": "https://research.isg-one.com/analyst-perspectives/author/robert-kugel", "sameAs": "https://www.linkedin.com/in/robertkugel" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "research.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": "SugarCRM as a Revenue Platform with AI for Sellers", "mainEntityOfPage": "https://research.isg-one.com/analyst-perspectives/sugarcrm-as-a-revenue-platform-with-ai-for-sellers", "datePublished": "19/02/2025", "dateModified": "19/02/2025", "articleBody": "I was recently a guest of SugarCRM at their 2025 Analyst summit with an opportunity to meet with the executive team and new CEO, David Roberts. SugarCRM is a venerable CRM offering that started as an open-source project and over the years has matured into a very flexible CRM system with offerings for sales, marketing and service. The new CEO, David Roberts joined the company toward the end of 2024 and has spent his time talking to customers, analysts and partners to draw up a new strategy for SugarCRM in terms of reviewing the ideal customer profile (ICP) and setting out a new go-to-market plan and product roadmap. Leadership has doubled down on the previously announced focus on Manufacturing and Wholesale Distribution, which is to say they will not only be supporting this vertical, but also will intentionally market to these potential customers. In terms of the size of customers, the target is those with up to 2000 employees. Smaller companies will be served by partner resellers either via co-selling or selling directly by partners. The company will deliberately be seeking out partners with domain expertise in manufacturing and wholesale distribution. As to the product itself, the new strategy will prioritize functionality that is targeted at helping management and also individual sellers. Given the focus on manufacturing and wholesale, the sales-I product, acquired in 2024, will be especially important as it allows for deep analysis of non-CRM data such as ERP data to identify existing accounts that have the potential for upsell and cross-sell based on similarities to other customers past purchases. While new customer acquisition is important, for many manufacturing and distribution enterprises, much of their revenue derives from existing customers. SugarCRM has been very deliberate in the usage of generative artificial intelligence and predictive AI on its underlying platform. CRM data is typically a combination of structured data such as account records and unstructured data such as emails, calls and texts. Traditionally, unstructured data was reliant on sellers manually entering the data, including meeting notes and summaries. This data entry activity is seen as a chore for many, and accuracy and timing are often an issue. Starting with emails and voice to text capabilities, SugarCRM will be releasing additional automated data collection during 2025. Many current buyers are looking for a trusted partner to work with, rather than being sold to, so it is important that sellers are well prepared before engaging with a company. SugarCRM showcased their ability to summarize meeting notes and emails between buyers and sellers to better prepare sellers, and to be used as a valuable source to help managers monitor and coach. We believe that through 2026, one-third of enterprises will deploy AI-assisted sales productivity tools to reduce admin tasks and free more time for buyer engagement. In addition, using sales-i enables recommendations of products and services to offer a customer. The company has also been focused on usability with two aims; uniformity of experience and enhanced navigation. Interestingly they have focused on having colors be uniform across data presentations such as graphic displays so that a data point referencing sales stage, for instance, will always use the same color pallet across graph and tabular displays. SugarCRM has always had a very flexible data model, which can be a blessing and a curse. In general, the larger the customer, the more they will dictate the implementation design. However smaller organizations are looking to follow best practices from the provider or the implementation partner. Up until now, it has been the SugarCRM professional team that has maintained templates to be used as part of implementation, leaving the product itself as a tabula rasa shell. It was announced that as part of the new go-forward roadmap, these templates will be productized with the aim of building more best practices into the base product. In theory this should help sales with intentional demos that fit the target ICP, speed up implementation and hence time to value, and make it easier for the product to also come with prebuilt analytics and workflows that can be modified as needed. SugarCRM is a solid product, and the executive team is taking deliberate steps to make their go-to-market model more predictable and repeatable. Focusing on manufacturing is a good move, but manufacturing is not Silicon Valley or SaaS tech, and typical messaging will need to carefully be phrased to appeal and connect with potential customers. Likewise, touting AI without connection to positive outcomes may not resonate. The announced product roadmap is deliberate and speaks to a focus on delivering realizable value as opposed to the latest technology or the newest “shiny object”. For many in their target market, the focused capabilities of SugarCRM will be more appropriate than “shiny object” offerings and using AI. And while SugarCRM has had some previous resets, under the new CEO and with commitment from investors, SugarCRM is developing an identity that will be of serious interest to manufacturing and distribution companies. I strongly recommend that for those who are looking to modernize the front office, SugarCRM may be a more appropriate CRM system that you should evaluate. Regards, Stephen Hurrell", "image": { "@type": "ImageObject", "url": "https://research.isg-one.com/hubfs/SugarCRM_as_a_Revenue_Platform_with_AI_for_Sellers.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Stephen Hurrell", "url": "https://research.isg-one.com/analyst-perspectives/author/stephen-hurrell", "sameAs": "https://www.linkedin.com/in/stephenhurrell" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "research.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": "How Software Can Help Usage Pricing Adoption", "mainEntityOfPage": "https://research.isg-one.com/analyst-perspectives/how-software-can-help-usage-pricing-adoption", "datePublished": "13/02/2025", "dateModified": "13/02/2025", "articleBody": "Based on the number of invitations I have received to speak on the topic, usage pricing (also referred to as consumption pricing) is hot. But as I have remarked elsewhere, it is not new. I recall a conversation with a customer over 30 years ago when I was involved with analytic software who asked, “Why can’t we just pay for the software we use?” And this of course makes sense: only pay for what you use. In fact, I assert that by 2027, over one-half of all enterprises will deploy a mixed revenue model that includes subscriptions and usage pricing in addition to one-time sales as enterprises make adjustments to remain competitive. Going back to the days of the on-premise, perpetual license business software application market, when it came to the split of risk between buyer and seller, it was really caveat emptor—the buyer carried most of the risk. Wind the clock to the turn of the century, and the advent of per-seat, by-subscription and termed contracts shifted the risk to be more equitably shared as the buyer could decline renewal if that particular purchase did not deliver the expected benefits. Wind on still further and there has been more discussion about usage pricing in the last 18 months than in the previous 18 years. I wrote a paper on subscription and usage pricing in September 2020, so what has changed since then? Generative Artificial Intelligence (GenAI) is what has changed. The initial wave of public AI providers chose to offer free, then paid-for subscription pricing as their monetization model. More recent business offerings have proposed usage models based on individual queries. Salesforce has announced per-transaction charges for their most common agent offerings. Though some providers plan on offering AI-driven features as part of their standard applications and without charging specifically for them, I believe a key driver for the majority of pronouncements on proposed usage-based pricing for GenAI offerings is cost. Training and running models is expensive. And directly linked to this expense, at least on the execution side, is how many AI-based queries or transactions are run. So, in essence, cost-plus for usage charges is a significant share of these pricing models. And while there are some good reasons for why usage pricing is an attractive option, it does present problems as to how it fits into the way businesses and consumers operate. A major attraction of subscription pricing was that it established a predictable revenue stream that continued until the customer cancelled or in the event of termed contracts, until the contract was not renewed. This predictability is attractive to both buyer and seller. For the buyer, the resulting recurring payments can be projected against fixed, budgeted amounts of expenditure. Likewise for sellers, although the initial amount received is smaller than the amount for a one-time sale, the recurring revenue over time can be projected with relative ease. Contrast this with the unpredictability of a usage-based pricing model, where neither the revenue for a seller or expense for a buyer are known in advance. This is not typically how businesses operate where expenditure is agreed against budgeted amounts of spend. This would be operationally problematic as well; would the AI based activity stop if that month’s budgeted amount of expense had been reached? In addition, processing usage data is potentially a problem to solve as well. As the price to be charged by a supplier is based on how much has been used, there is a need to acquire and ingest transactional data. So how can software help in resolving some of these issues? When it comes to addressing the impact of usage on the predictability of expense and revenue for both the buyer and the seller, there are several methods that are deployed. The simplest method is the concept of a digital wallet, that a buying enterprise would draw down against as used and then top up with funds as needed. It effectively operates as a Purchase Order (P.O.) defining how much money has been budgeted or allocated for a set of defined products or services. But this still does not help with predictability as it would be hard to know when top-ups will be needed. Forecasting of usage would certainly help both buyers and sellers and would address revenue recognition concerns for suppliers as they need a concept of an “average” usage pattern to establish a baseline. This would also be helpful information for use cases beyond expense and revenue considerations. Usage data is a record of how your product and service is being used in terms of what, when and by whom. Many subscription and management providers are now offering integrated data ingestion and transformation functionality, sometimes referred to as data mediation, a legacy of their origin in the telco industry. There are also specialist providers in this area, while other enterprises are looking to use general data mart or warehouse models. Managing usage data requires the collection, filtering, aggregating and normalizing potentially large volumes of data. Pricing these transactions often requires accumulating the data over a period for tiered pricing based on hitting volume targets. For performance reasons, incrementally processing the data may be preferrable. And as mentioned this data has value as source of usage data that can be used for monitoring adoption, identifying profiles for up- and cross-sell and in general information as to what is used, when and by whom. When considering usage pricing, whether as a buyer or as seller, know that it is not just about how the price is calculated. It also relates to how an enterprise puts in place technology and processes to make sure the promise of usage is fully realized within the confines of budget and expenditure controls and while providing visibility into other ways that the data can be used in terms of understand patterns and projected future consumption. Make sure you ask your provider, whether a point solution, a subscription management and billing system, or platform—or as part of an integrated front and back office—about how their offerings can help not with just pricing, but also as to whether they have both the technology and the processes to also help with enabling the model to work with existing business norms. Regards, Stephen Hurrell", "image": { "@type": "ImageObject", "url": "https://www.isg-research.net/hubfs/How_Software_Can_Help_Usage_Pricing_Adoption.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Stephen Hurrell", "url": "https://research.isg-one.com/analyst-perspectives/author/stephen-hurrell", "sameAs": "https://www.linkedin.com/in/stephenhurrell" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "research.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": "Adapting to Higher Inflation Longer with Profitability Management", "mainEntityOfPage": "https://research.isg-one.com/analyst-perspectives/adapting-to-higher-inflation-longer-with-profitability-management", "datePublished": "05/02/2025", "dateModified": "05/02/2025", "articleBody": "In anticipation of conditions that suggested accelerating price increases, I wrote in 2021 about how technology could be useful in an inflationary period, anticipating the world we live in now. Responding effectively to changes in costs is always challenging, but even more so because of the choppy and chaotic nature of the current environment. Inflation may have abated from its highs throughout the rich world but is still an important factor in business decisions. Many enterprises have limited or no ability to raise prices and are forced to find ways to minimize the impact of rising costs. And while it’s true that some organizations have a degree of pricing power, behind this generalization is a more complex reality because this ability to raise prices varies depending on specific products, customers and channels. Companies can best address the challenges of inflation by adopting a technique that ISG Software Research calls “profitability management.” Profitability management goes beyond setting targets. Most companies manage to profitability objectives: CEOs are accountable for meeting company-wide financial objectives, including return on equity or return on assets, because investors use these in assessing the financial health and attractiveness of a business. In turn, they assign responsibility for achieving profitability to business unit owners across and down an organization. Sales quotas are put in place to achieve revenue goals are, and budget owners have cost and margin objectives. However, this is not the same as profitability management. Profitability management is a software-enabled discipline that’s especially useful in today’s rapidly changing market conditions. In an inflationary environment, sellers must be able to quickly adapt by having a full understanding of the true economic costs of products, the cost to serve customers and to operate channels. An enterprise must be able to make pricing decisions that enable it to successfully execute a go-to-market strategy. Because revenue recognition and stock-based compensation can distort measures of economic profitability, chief financial officers must have an appropriate set of lenses through which to view targets and results simultaneously from multiple perspectives. Profitability management is not simple, which is the reason it can be a source of sustainable competitive advantage. From an organizational perspective, profitability management poses challenges because it is a cross-functional effort that integrates finance and sales to achieve an optimal balance of revenue and margin objectives. This is a more effective performance management tool because it is a data- and analytics-based approach designed to consistently achieve higher sales and fatter margins. ISG Software Research asserts that by 2026, just 35% of enterprise financial planning and analysis teams will deliver actionable customer and product profitability analysis. Finance departments that do will be a strategic asset. A profitability management initiative involves parallel efforts by the Office of Finance and the sales organization. The first, handled by financial planning and analysis, requires setting up and running a profit analytics program. These analytics provide the rest of the organization with consistent and reliable detailed information about product, customer and channel profitability to support better decisions about pricing, product bundling, sales quotas, incentive compensation and production. The second supports a price and revenue management structure in the sales organization that achieves an optimal trade-off between revenue and margin. Organizations that use software to gain better insight into a buyer’s willingness to pay can set the highest possible price in a transaction with the greatest likelihood of getting the business. They also use software to identify potential cost reductions or find ways of disaggregating offerings (for instance, separating handling and shipping charges). Profitability management uses an analytics-driven business discipline designed to enable enterprises to achieve superior market share and profitability objectives. At the heart of the challenge is the ability to quantify the profitability of specific products, customers and channels and every permutation of these. That does not happen in most companies today. Our Office of Finance benchmark research found that only 34% manage customer profitability, and just 30% of companies manage product profitability. Profitability is determined by revenues minus costs, so it is axiomatic that organizations must fully understand the true economic costs of products, customers and channels. The enterprise must then use these insights to make decisions about pricing, marketing, quotas, territories and incentive compensation. Both efforts rely on software to deal with large data sets and often complex analytics to achieve the best results in dynamic market conditions. Economic costing is a better approach than financial accounting measures for understanding profitability. Statutory accounting is designed for financial—not operational—management. Accounting costs can be abstract and divorced from economic costs and cash flow. This includes generally accepted accounting principles for revenue recognition and equity compensation. Financial accounting suffers from basic analytical issues such as the sunk-cost fallacy. Economic costing is often a better way to determine the profitability of serving a specific customer or class of customers, as well as the cost to serve a specific channel or geography. Enterprises with a deeper, more economically accurate understanding of all costs are better able to control them. In being able to control them, costs can be managed in a way that is consistent with organizational strategy, resources and market position. Revenues are a function of units sold times the price per unit. Setting that price can be challenging. The most straightforward and longstanding approaches to price setting are a cost-plus calculation or just charging what competitors are charging. More recently, though, demand-based pricing has achieved a following because technology makes this approach practical. Demand-based pricing uses an estimate of the perceived value to the buyer of a good or service as the central element in setting prices. Demand-based pricing enables an enterprise to reliably achieve higher revenues and higher margins than other approaches because it is based on the buyer’s willingness to pay. Charging more when the buyer is willing to pay produces higher profits without sacrificing revenue and market share. At the heart of demand-based pricing is a price and revenue-optimization technique that uses market segmentation to achieve strategic objectives such as increased profitability or higher market share. Price and revenue optimization has demonstrated repeatable results. It first came into wide use in the travel and hospitality industry in the 1980s. It enabled hotels and airlines to maximize returns from less flexible travelers, such as people on business trips, while minimizing the unsold inventory by selling incremental seats on flights or hotel rooms at discounted prices to vacationers. Ideally, cross-functional initiatives such as profitability management are led by the CEO, whose involvement and commitment are necessary to mediate with authority the inevitable differences between conflicting objectives and constraints. If the initiative does not spontaneously come from the CEO, I suggest the CFO should be a champion. This individual should make profit analytics a top three priority and advocate the use of demand-based, intelligent pricing in the leadership team. I recommend that every finance organization—and specifically the FP&A group—routinely measure customer, product and channel profitability using an economic costing method to do the analysis. This is most effective when done as part of a coordinated cross-functional effort. The sales organization, the sales operations team and/or a pricing group manage and review the pricing of products, services and contracts. Marketing creates campaigns and offers, which need to be tied to revenue and profitability objectives. And operations—whether manufacturing, services or fulfillment—must be involved to understand the nature of costs, constraints and other details. It’s common to hear it said that business has never been more challenging. It’s a marketing line designed to grab your attention. In reality, business challenges never fundamentally change. Enterprises must offer customers appealing products or services, attract and retain the best talent, market and sell effectively, maintain financial control and so on. What does change are the tools—especially technology—that businesses can use to enhance competitiveness and improve performance. Technology—and the ability of some clever enough to use it to gain an advantage—is the real challenge. In inflationary times, profitability management is just such a tool that enables enterprises to outperform rivals. Regards. Robert Kugel", "image": { "@type": "ImageObject", "url": "https://www.isg-research.net/hubfs/Adapting_to_Higher_Inflation_Longer_with_Profitability_Management.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Robert Kugel", "url": "https://research.isg-one.com/analyst-perspectives/author/robert-kugel", "sameAs": "https://www.linkedin.com/in/robertkugel" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "research.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": "Redpanda Lowers the Complexity and Cost of Streaming and Event Data", "mainEntityOfPage": "https://research.isg-one.com/analyst-perspectives/redpanda-lowers-the-complexity-and-cost-of-streaming-and-event-data", "datePublished": "04/02/2025", "dateModified": "04/02/2025", "articleBody": "I recently wrote about the need for enterprises to harness events to process and act upon data at the speed of business. The core technologies that enable enterprises to process and analyze data in real time have been in existence for many years and are widely adopted. However, streaming and events technologies are also commonly seen as a niche requirement, separate from an enterprise’s primary focus on batch processing of data at rest. One of the reasons for this is an entrenched reliance on batch data processing products and workflows. Another is the high-level expertise that has been required to implement and maintain streaming and event processing technologies. In recent years, many software providers, including Redpanda, have set out to lower the barriers to working with streaming and event data to encourage wider adoption. Redpanda was founded in 2019 by CEO Alexander Gallego with the goal of making real-time data accessible to all developers, rather than just those with high levels of expertise related to streaming and event data processing systems and architecture. Based on their experience with existing streaming and event data processing products, Gallego and his team knew that the cost and complexity of implementing streaming and event technologies was high, presenting a barrier to adoption. They also knew that a higher number of use cases and greater data volumes resulted in increased cost and complexity, which put the brakes on real-time data processing playing more than niche role in many enterprise data strategies. ISG’s Analytics and Data Benchmark Research highlights the relatively low level of adoption of streaming data, with less than one-third (30%) of participants using streaming data in analytics. Redpanda’s goal was to create a streaming data platform that would be compatible with the Apache Kafka distributed messaging and event streaming platform without the operational complexity that Kafka was then known for. The product was initially introduced in 2021 at the same time as Redpanda’s announcement of $15.5 million in funding from Lightspeed Venture Partners and GV. Redpanda subsequently announced a further $50 million of Series B funding in 2022, followed by a $100 million Series C round in 2023. In addition to the development of the company’s streaming data platform and managed cloud services, Redpanda has also invested some of its funding in acquisitions, including the web user interface expertise of CloudHut in 2022 and streaming data integration connector developer Benthos in May 2024. I assert that by 2026, two-thirds of enterprises will require streaming and event data processes with low latency of seconds or sub-seconds to satisfy operational requirements. A key first step Gallego took to diminish the cost and complexity of streaming data technology was to reduce the resources required to deliver high-performance data processing. To achieve the desired performance gains, the Redpanda streaming data platform was written in C++, with each node in a cluster designed to be a self-sufficient single binary that natively implements the Raft consensus protocol for data management and control across the cluster. These design choices resulted in a reduced footprint compared to existing streaming and event systems and avoided dependency on Java virtual machines and external distributed coordination systems such as Apache ZooKeeper. Additionally, Redpanda implemented a thread-per-core programming model designed to take full advantage of available hardware resources (including processor, memory and disk) and avoid over-provisioning hardware to meet scalability requirements. Redpanda was also designed to take advantage of cloud object storage by default, with support for tiered storage combining cloud and local storage resources. The product also includes the Redpanda Console user interface, which is built on the capabilities acquired with CloudHut and the delivery of more than 280 pre-built integration connectors via Redpanda Connect (built on the Benthos acquisition). Redpanda is delivered as self-hosted software, as well as via a range of cloud managed services. Redpanda Cloud is available as dedicated clusters hosted and managed by Redpanda on single-tenant AWS, Google Cloud or Microsoft Azure cloud infrastructure, as well as serverless clusters hosted and managed by Redpanda on multi-tenant shared cloud infrastructure on AWS. Redpanda also supports bring-your-own cloud (BYOC) clusters, in which the data plane is hosted on the customer’s cloud infrastructure provider but provisioned, monitored and maintained by Redpanda via its control plane in Redpanda Cloud. The BYOC offering is designed to support low-latency data processing needs as well as compliance with data sovereignty, security and privacy regulations. While many cloud providers have policies that pertain to protecting data privacy, emerging data sovereignty requirements place additional burdens on enterprises to not only have reassurances about how the data is stored and processed, but control over the infrastructure used to store and process the data. Separating the control and data planes also enables an enterprise to assert more control over the performance of the data processing software and enforce multiple layers of security without ceding permissions to the software provider. BYOC can also enable enterprises to avoid cloud-egress costs that would otherwise be involved in moving data to the software provider’s environment. Sovereignty is also a concept that is associated with Redpanda’s nascent efforts to address requirements for artificial intelligence (AI), with the company looking to combine AI models with data streaming workloads in virtual private cloud environments to enable private inferencing, as well as AI lineage tracing and integration with role-based access control. Redpanda’s Sovereign AI approach is in early preview, and we anticipate further details and enhancements being rolled out during 2025. We also look forward to more details about Redpanda One, the company’s forthcoming multimodal streaming data engine, which is being designed to enable users to define data storage for each individual topic based on its unique requirements for availability, consistency, latency, safety and cost-effectiveness. In the interim, I recommend that any enterprise evaluating options for streaming data and event processing include Redpanda in its evaluation. Regards, Matt Aslett", "image": { "@type": "ImageObject", "url": "https://www.isg-research.net/hubfs/Redpanda_Lowers_the_Complexity_and_Cost_of_Streaming_and_Event_Data.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Matt Aslett", "url": "https://research.isg-one.com/analyst-perspectives/author/matt-aslett", "sameAs": "https://www.linkedin.com/in/matt-aslett/" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "research.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": "Databricks Scores Massive Funding Round, Continues to Expand Its Offerings", "mainEntityOfPage": "https://research.isg-one.com/analyst-perspectives/databricks-scores-massive-funding-round-continues-to-expand-its-offerings", "datePublished": "29/01/2025", "dateModified": "29/01/2025", "articleBody": "Databricks recently announced its Series J funding round, successfully raising $10 billion at a valuation of $62 billion. Led by Thrive Capital alongside high-profile investors such as Andreessen Horowitz and Insight Partners, the company intends to invest this capital towards new artificial intelligence (AI) products, acquisitions and significant expansion of its international operations. In the announcement, Databricks reported that it expects to achieve an annual revenue run rate of $3 billion in the quarter ending January 31, 2025. Founded in 2013, Databricks initially gained prominence for its cloud-based Apache Spark services, aimed at enhancing big data processing and creating an alternative to MapReduce. Spark was initially started by Databricks co-founder Matei Zaharia at UC Berkeley's AMPLab in 2009. In 2013, the project was donated to the Apache Software Foundation. The Spark framework includes Spark SQL, DataFrames, Spark Streaming, MLlib and GraphX. By providing robust analytics over massive data sets, Spark became the de facto way to process big data. Although Databricks’ commercial operations focus exclusively on providing managed cloud services, it has also supported the broader open-source Spark community. Over time, the worlds of data lakes and data warehouses collided. Databricks introduced the concept of a data lakehouse, adding Databricks SQL as well as open table formats. My colleague Matt Aslett has written about the importance of open table formats and Databricks’ support for both Delta Lake and, more recently, Apache Iceberg, including its acquisition of Tabular. As the years progressed, Databricks evolved beyond its initial offerings. The company’s Data Intelligence Platform is now positioned as providing a lakehouse-based environment for data engineering, data warehousing, stream data processing, data governance, data sharing, business intelligence (BI), data science and AI. While MLlib provided machine learning (ML) capabilities, the company doubled down on its investment in AI with the acquisition of Mosaic ML. Databricks also set its sights on generative AI (GenAI) and large language models (LLMs) when it introduced DBRX, an open-source, general purpose LLM, as well as supporting enhancements, driving the future of intelligent data applications. Databricks’ Unity Catalog provides a single layer for governing structured and unstructured data, as well as ML models, notebooks, dashboards and files. As a result of both its own research and development efforts coupled with its acquisition strategy, Databricks is able to offer state-of-the-art tools for enterprises aiming to build, train and deploy AI/ML and LLMs using its Lakehouse Platform. As a result, Databricks has been rated Exemplary in our Analytic Data Platforms, AI Platforms and GenAI Platforms Buyers Guides. The initiatives underline a clear strategy to support enterprises in the various stages and types of AI investments, combining multiple models and components to create high-quality AI applications supported by and integrated with the necessary underlying data infrastructure. This trend is expected to be instrumental as organizations focus on transitioning from pilot projects to scalable production systems. Our research shows that only 15% of enterprises are fully in production with their GenAI efforts. One of the company's hallmark events, the Data + AI Summit, has established itself as a nexus for industry stakeholders, offering insight into cutting-edge applications of data and AI technologies. Recently, the Summit focused on GenAI integrations, including functionalities that allow users to streamline the development of AI-based applications within the Lakehouse environment. This year, the emphasis was on announcing new capabilities like Mosaic AI Agent Framework and enhancements to its Lakehouse Platform for AI and data. The launch of Databricks AI/BI also represents the company’s entry into the self-service analytics market with two new AI-powered capabilities: low-code dashboarding and a conversational interface. Databricks also unveiled LakeFlow to bring together all types of data engineering processes into a unified platform. Building on Databricks’ acquisition of Arcion as well as its existing Delta Live Tables and Databricks Workflows functionality, LakeFlow automates ingestion, transformation and monitoring, simplifying the overall experience for data teams. Such innovations are vital as businesses continue to grapple with the complexities of managing and optimizing data pipelines across various environments. Databricks was also rated Exemplary in our Data Intelligence, Data Integration and Data Governance Buyers Guides. Shortly after the event, Databricks announced general availability of Databricks Assistant. Databricks Assistant can be used to generate code, provide help and troubleshoot errors. It can also be used to create visualizations and dashboards, although this feature is still in preview mode. In conclusion, Databricks has made significant strides from its initial focus on Spark processing for big data, becoming an industry leader that unifies data and AI under a single platform. The current push for GenAI and the substantial funding acquired provide the resources for Databricks’ continued investments. As enterprises consider their data and AI strategies, I recommend they include Databricks in their evaluations. Regards, David Menninger", "image": { "@type": "ImageObject", "url": "https://www.isg-research.net/hubfs/Databricks_Scores_Massive_Funding_Round_Continues_to_Expand_Its_Offerings.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "David Menninger", "url": "https://research.isg-one.com/analyst-perspectives/author/david-menninger", "sameAs": "http://www.linkedin.com/in/davidmenninger" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "research.isg-one.com", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script>  <script data-hs-allowed="true" src="/_hcms/forms/v2.js"></script> <script data-hs-allowed="true"> var options = { portalId: '2035844', formId: 'fa276fc9-9a16-4673-a644-1fcbedcc3c24', formInstanceId: '3969', pageId: '3884418273', region: 'na1', inlineMessage: "Thanks for subscribing!", rawInlineMessage: "Thanks for subscribing!", hsFormKey: "c968d8a5d389034af3f3262397bcfce6", css: '', target: '#hs_form_target_module_1552944263900179', contentType: "listing-page", formsBaseUrl: '/_hcms/forms/', formData: { cssClass: 'hs-form stacked hs-custom-form' } }; 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ISG Software Research Analyst Perspectives