The pace of BI tool consolidation projects increased in recent years and now sits at an all-time high level, with 36 percent of organizations reporting plans to consolidate business intelligence (BI) tools. Organizations reporting high degrees of success in their BI initiatives more frequently plan and successfully execute BI tools consolidations.
By promoting and guiding their organizations through refinement of their portfolios of BI tools, data leaders can reduce costs and deliver greater returns from BI investments. Although organizations most frequently cite cost reduction and ease-of-use improvements as the main drivers for this work, our most recent data show additional drivers increasingly present, including alignment with strategic direction or corporate standards, improved functionality, and desire to remove unused shelfware. The latter represents the fastest-growing driver of tool consolidation in the last year.
Regardless of the rationale, data leaders acting on these drivers and actively managing their tools portfolios through appropriate consolidation efforts gain significant benefits. Organizations that achieve greater success in their BI initiatives also more frequently report that they consolidate BI tools, indicating that active management of BI tools (including consolidation efforts) plays a role in achieving overall BI success.
Of course, the tools alone do not create success (see the Research Insight “BI Tools Longevity Data Show Right Fit, Better Skills, and More Experience Lead to Greater BI Success”). Data leaders and their teams also must cultivate skills and experience with the tools and work to increase data literacy of the user community. The right tools supported by these human-centric characteristics are key to optimizing the success of BI programs.
Data leaders increasingly will need to focus on cultivating the BI tools portfolio with an eye toward maximizing BI program value. This means regularly assessing the return on investment (ROI) from BI tools—that is, whether the value derived exceeds cost for the BI programs that use these tools. In addition, identifying tool redundancies, unused tools, and non-standard tools could identify tools to remove or replace.
Data leaders that collaborate with key business stakeholders to drive BI program success will be most effective. This means encouraging those business leaders to help in communicating clearly to their user communities the rationale for tool changes and consolidations. It also requires business leaders to make the necessary investments in time and resources to improve skills and data literacy among their people. By prioritizing high-profile BI programs whose lower levels of success result from tools-related challenges, tools consolidation efforts can rapidly increase the value derived from and created by these programs.
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