Dresner Advisory’s Fifth Annual Business Intelligence Success Index®: In the Gen AI Era, a Strong BI Foundation Is Key to Accelerating Data and Analytics Strategies
Economic forces continue to make a number of organizations reexamine and reprioritize many projects, including business intelligence (BI) initiatives. The increased cost of capital reset the bar on required levels of return from BI investments. Many projects with expected returns below an organization’s minimum internal rate of return (IRR) now get deferred or cancelled. Those with a greater likelihood to deliver high business value and ROI that exceeds IRR get escalated, funded, and prioritized.
Organizations can meet or exceed projected returns and create business value only when their BI initiatives are well designed, implemented, and operated. This reality makes a focus on BI success paramount for data leaders, who must simultaneously deliver quality and value from data and analytics.
The Dresner Advisory Services Business Intelligence (BI) Success Index®—like the companion BI Value Index®—is inspired by the many and varied economic indicators used globally by business and government leaders and their teams of analysts, economists, and researchers. Such indicators serve many functions: informing, provoking, and encouraging thought, discussion, and investment.
Success has many dimensions—too many to capture in a broad-based survey. Our survey question does not define success; individuals characterize the success of their BI initiatives based on their perceptions and considerations. This is the 10th year Dresner Advisory Services recorded data on the success of BI initiatives, and the fifth year of the BI Success Index. In 2024, the BI Success Index stands at 88 percent of organizations considering their BI initiatives either completely successful or successful.
Data leaders may want (or need) to leverage the BI Success Index in strategy discussions regarding their organizations’ implementations of generative AI. Many organizations report lower adoption rates, lower perceptions about priorities driving generative AI use and adoption, less bullishness about generative AI in general, and less need to stay on top of the latest developments in generative AI (see the Research Insight “Generative AI Smoke Is Clearing; Data Leaders Need A Game Plan”).
In these discussions, a data leader should consider her/himself as a function-neutral advocate for data and its proper use in the organization—both in “traditional” analytics use as well as part of generative AI efforts. In addition, a data leader needs to make sure senior leadership understands “the big picture” and is best informed before making critical data-related decisions regarding generative AI strategies and implementations.
This responsibility includes highlighting information such as the BI Success Index, in which a strong majority of organizations (88 percent) consider their BI initiatives successful. It also means bringing forward that the BI Value Index shows that BI initiatives with value measured by ROI achieve an average return of 10 percent (see the Research Insight “Dresner Advisory’s 5th Annual Business Intelligence Value Index®: Focus on Revenue to Deliver More Business Value From BI”).
Data leaders need to be clear in their presentation of this information that they do not wholesale reject the use of generative AI. However, optimal early-stage use cases often differ significantly from those used for BI, and many generative AI implementations can struggle with analytical use cases that are highly data intensive.
As the BI Success Index and our other data show, when properly applied and implemented, BI is a proven, business-enabling technology that delivers real business value and provides average returns that exceed the current cost of capital and most IRRs. The message that BI has a justifiably rightful place in an organization’s likely evolving data and analytics strategy likely will “play well” against senior leadership’s less bullish current perceptions about generative AI in general.
This creates a requirement to invest broadly in a BI and analytics strategy that includes advanced analytics. As organizations make these investments, data leaders must ensure that they can deliver promised returns and show value to the organization. Although the quest to deliver the highest level of success with BI is an ongoing endeavor that improves with time and experience, data leaders that take an increased focus on success and value will help to better align the data and analytics abilities of their organizations with their business needs and priorities.
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