Taking lessons from KM to influence business intelligence pervasiveness

Evidence-based decision-making is spreading rapidly throughout commercial, non-profit and public sector organizations. That trend is driving the need for more insightful, more accurate and faster decision support solutions built on business intelligence (BI) and data warehouse (DW) tools, analytic applications and related services. The recession has spurred organizations to examine the way they retain customers, spend capital and operating budgets, and comply with regulations. However, over the long-term, BI solutions will continue to be applied to optimize a wide array of processes and support an expanding pool of users.

An increasing number of organizations are making BI and analytics functionality more pervasively available to all decision makers inside and outside the organization, including executives, staff employees, managers or suppliers. In pursuit of pervasively available BI, organizations should focus on the five key factors that a recent IDC study found can be directly influenced to increase diffusion of BI. Those factors were found to be statistically significant to directly impacting the diffusion of BI technology and fact-based decision making throughout the organization and include:

  • the degree of training on the data, tools and analytic techniques;
  • the prominence of data governance;
  • the design quality of the BI solution;
  • the prominence of a performance management methodology; and
  • the involvement of non-executive management in promoting the design and use of BI solutions.

Although interest and investment in BI solutions are growing, we would not anticipate organizations investing in those solutions unless there was some belief that they would eventually benefit from them. The evidence, as shown in the following examples, of the impact of BI on competitiveness and performance is growing.

  • In 2003, IDC released the results of a study, entitled The Financial Impact of Business Analytics, that evaluated the ROI of business analytics projects at 43 leading organizations in North America and Western Europe. Each of the resulting case studies was accompanied by in-depth ROI calculations, which showed, for the group as a whole, a median ROI of 112 percent. Across all of the projects, the benefits attributable to technology accounted for only 4 percent of the total return. In other words, 96 percent of the benefits were in the productivity and business process enhancement categories.
  • Latest IDC research, conducted in 2008, suggests a statistically significant link between analytic orientation of an organization and its competitiveness. Analytic orientation is one of six key indicators of pervasive BI. The case for quantifiable benefits is made even stronger in difficult economic times. Although the focus on improving decision-making processes may not have a direct correlation with economic activity, the specific BI and analytics projects undertaken by organizations do change throughout economic cycles. For example, over the past 12 to 18 months, most organizations have switched from over-weighting their investments in technology, processes and people for new customer acquisition, to cost cutting across all business processes, as well as servicing existing customers to prevent them from churning. As the economic cycle improves, the BI focus is likely to migrate again to supporting new business development.

Pervasive business intelligence

Pervasive BI results when organizational culture, business processes and technologies are designed and implemented with the goal of improving the strategic and operational decision-making capabilities of a wide range of internal and external stakeholders. Pervasive BI means more than just putting BI tools into the hands of more users. Although the degree of internal use is important, so is the degree of external use. Internally, more pervasively available BI solutions lead to greater accountability by all employees and greater consistency in performance management. Externally, relationships with suppliers and partners can be strengthened through effective sharing of key performance indicators (KPIs).

Further, internal use of BI solutions is usually segmented among information producers and information consumers. Although that distinction is beginning to blur, the percentage of users in the former group, also known as power users, is another key indicator of pervasiveness of BI. IDC has identified a total of six quantifiable indicators of pervasive BI, which we’ll be discussing in greater detail in upcoming reports and articles.

Organizations embarking on or continuing their path toward pervasive BI need to decide how to allocate their scarce human, capital and IT resources to tasks and projects that have the biggest impact on increasing the diffusion of BI throughout their organizations and to external stakeholders. IDC has identified five key factors as having the strongest influence on BI pervasiveness. Those factors include:

  • Degree of training is a factor that consists of the satisfaction level with training on the meaning of data, the use of BI tools and the use of analytics to improve decision making.
  • Design quality refers to the extent to which users’ expectations about the speed of adding various BI solution components by the IT group are met.
  • Prominence of governance refers to the existence of and the importance of a data governance group and associated data governance policies to BI system design or enhancement initiatives.
  • Non-executive involvement consists of the level of non-executive management’s involvement in promoting and encouraging the design and use of the BI solution at the organization.
  • Prominence of performance management methodology is based on the existence of and the level of importance within the organization of a formal performance management methodology.

Those factors need to be addressed by a combination of technology deployment, decision process changes and changes to organizational behavior. From a technology perspective, organizations must consider an increasingly broad spectrum of tools and applications that support or automate decision making processes.

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