Because business intelligence (BI) is a multi-dimensional tool – like a Swiss army knife, and because BI can be used in so many different functional settings, its value propositions for a specific company can be unclear. In fact, many business leaders with whom we have worked as business intelligence consultants have very different ideas about BI and its value proposition. Lack of clarity here can result in lack of business sponsorship and funding and lack of business engagement – both key impediments to BI success. In a previous post, I examined some of the issues that cloud the value proposition. In this post, let’s look at defining the value proposition (actually propositions, as the value varies depending on need and use) in more depth.
Why Vague BI Value Propositions are Insufficient
At the vaguest level, we have such value propositions as “make better decisions” or “make more impactful business decisions.” These run the risk of offending potential business sponsors. The business executives, managers, and analysts with whom I have dealt are successful women and men who have risen to their positions in large measure because they are effective decision-makers. While their access to information and analysis has been limited in many cases to canned reports and Excel spreadsheets, they have combined those inputs with industry experience, knowledge of their company culture, and discussions with other knowledgeable people to arrive at plenty of good decisions.
The same can be said of making decisions in the absence of “a single version of the truth” and/or in the absence of data that is readily “accessible and actionable.” So while there is nothing inherently wrong with the above generalized value propositions, the business people with whom we have worked have required a much more specific value proposition, which brings us back around to fact that BI is a toolkit, and the value proposition varies depending on what the BI team is being asked to build.
Possible BI Value Propositions
We noted earlier that “business intelligence” is a multi-dimensional tool, and different BI capabilities have different value propositions (we’ll take a closer look at the various styles of BI in a future post) :
- reporting is used to evaluate what happened after the fact, and to thereby trigger corrective actions if there is a material unfavorable variance from expectations;
- ad hoc queries, user-selected queries, and OLAP are used for such activities as deeper analysis into why something happened, creating customer segments for behavioral analysis, clustering products that often sell together for marketing purposes, and decomposing enterprise performance information by business unit, product, customer, or other relevant dimension;
- advanced analytics are sophisticated statistical and data mining techniques used to discover why something happened, particularly if simpler methods like ad hoc queries or OLAP don’t easily reveals the answers being sought;
- predictive analytics are sophisticated statistical and analytical techniques used to forecast what is likely to happen and the likely economic results;
- real-time analytics are intended for keeping a tighter rein on minute-by-minute performance of some key business process, e.g. sales or customer service, and/or to enhance such processes, such as by using BI to suggest book titles to a potential customer who has been looking at other titles; and
- performance management analytics are intended to enable strategic, tactical, and operational control over performance and to enable more cost-effective planning.
At a higher level, business intelligence and business analytics are all tools for either planning and control or enhancing the performance of an important process. That being said, many business executives, managers, and analysts we have worked with are uncertain about the value proposition for BI, and thus they hesitate to move forward with BI initiatives as aggressively as might be to their advantage. This problem can be overcome.
How to Clarify the BI Value Proposition
Essentially, leveraging business intelligence to create business value is about aligning application the BI capabilities described above with the core business processes of the firm so that business performance – and profitability – is improved. The steps for doing so include:
- conducting a BI opportunity analysis at the enterprise, functional, process, and/or program level;
- developing a concise qualitative business case for each BI opportunity that includes explicit information about which BI capabilities will be employed for what specific business purposes;
- obtain in-depth business feedback about the identified BI opportunities, including their assessments of the potential business impact of each opportunity and the relative priorities between opportunities; and
- revise the business case to reflect business feedback and finalize the value propositions for future reference.
Clarifying the BI value proposition is a straightforward process that pays dividends in the form of business sponsorship and business engagement. Further, it helps move the business intelligence initiative from being an IT-driven initiative to being a business-led initiative. This is the proper place, because while business/IT partnership is crucial to success, only business people can achieve the business process changes necessary to capture the business value of business intelligence.