Three Critical Distinctions in Success with Business Intelligence in 2020

1. Success with business intelligence relates powerfully and directly to an organization’s ability to act on BI-derived insight. Armed with insights from business intelligence data and analysis, organizations can make better decisions and create new business value, which in turn also helps to maximize the value of their BI investments. In 2014 we began studying “Action on Insight,” our methodology for measuring how well organizations put BI data to use beyond passive reporting/observation. We asked survey respondents to rate organizational Action on Insight according to the following characteristics: Closed-loop processes for action – information is shared, teams work to process and act in a timely fashion; no formal boundaries Ad hoc – informal action on insights across functions Uncoordinated action (sometimes at the expense of others) Insights are rarely leveraged Our 2020 study reveals that an organization’s ability to act on BI-derived insights is a significant cause leading to success with business intelligence. Organizations with closed-loop processes reported they are “completely successful” more than 60 percent of the time and at least “somewhat successful” more than 85 percent of the time. The assessment of “complete success” drops to less than half among organizations with ad hoc / informal action on insights. Organizations with uncoordinated action on insights are much more likely to fail than to succeed. And among organizations that rarely leverage BI insights, almost 90 percent of our study respondents rated their BI efforts as “somewhat unsuccessful” or “completely unsuccessful.”

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2. An organization’s success with business intelligence leads to use of fewer BI tools. This year’s survey of BI consumers finds an increase in the number of different business intelligence tools in use. Generally and as we would expect, the number of tools in use increases with employee headcount. Since 2013, our studies reveal considerable fragmentation in the number of business intelligence tools in use by organizations. In 2020, the number of organizations using one tool decreased and the use of three, four, five and 10 or more tools increased. A likely cause of the increase is the expansion of BI to more departments or silos in an organization. Our study found two significant success effects regarding the number of tools in use. Thirty percent of the survey respondents reporting their organizations are successful with business intelligence use just one BI tool. In contrast, respondents reporting they didn’t know how many tools are in use in their organizations also were the most likely to rank their BI efforts as unsuccessful. This suggests that one cause of success in BI is a greater strategic focus. When the top executives or a BI Center of Competency (BICC) drive a business intelligence program, they ensure a more strategic focus, which usually leads to consolidating BI tools.

3. The state of data in an organization – and users’ trust of the data – correlates with an organization’s success with business intelligence. We asked survey respondents to rate the state of data in their organization according to the following attitudes and behaviors: Users view data as “truth” and a common view of enterprise data is available with common application of data, filters, rules and semantics. A common view of data is available; however, users use parochial views and semantics to support specific positions. Consistent data is available at a departmental level; conflicting, functional views of data cause confusion and disagreement. Multiple consistent data sources with conflicting semantics and data; information is generally unreliable and distrusted. Analyzing this year’s respondent data reveals that when organizations view data as “truth” and have common rules and semantics, they are almost 10 times more likely to rate their business intelligence efforts as successful. In contrast, the majority of organizations with multiple, inconsistent or conflicting data sources say their business intelligence is “completely unsuccessful.” Even when organizations have consistent data at the departmental level but conflicting functional views of data, they are 70 percent more likely to state their business intelligence programs are “somewhat unsuccessful” or “completely unsuccessful.”