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Politics and Provisioning
Is your BI initiative a democracy, a meritocracy, or an oligarchy? Is the tough analytical work done by everyone, by anyone who can master it, or by a small group of the quantitative elite? This decision is key to your organization's BI strategy and to how it organizes its analytical capability. I don't think there is a single answer that applies to every firm, or even a single answer for any particular organization. I'm pretty sure, however, that thinking about the question is important.
Two Cheers for Democracy
Since we ostensibly live in a democracy, let me first take up the virtues and vices of democratically organized BI. The great virtue of having everyone engaged in analytical decision-making is just that - everybody is engaging in it. If you have somehow managed to bring BI to the people, it means that your organization has achieved the kind of analytical culture and highly distributed data environment to which many would aspire. Of course we would want everyone to use data-based decisions, control groups, statistical models, predictive models, etc., if we could pull it off. Right?
Well, maybe. But with a democratic approach there's a possibility that some people will get in over their analytical heads. They'll produce spreadsheets with errors (one study suggests that 20 percent of spreadsheets have them), violate statistical assumptions, and create new versions of key corporate data elements. If you seek multiple versions of the truth, you may well get them with a fully democratic approach to BI.
At least a couple of companies have embraced the democratic approach, and are trying to upgrade the skills of their employees by having them swim frequently in the information river. Thus far there have been no reported drownings. Irving Tyler, CIO of Quaker Chemical, has been providing the results of data analysis and reporting through email alerts for several years to company employees. He believes that the more information users are delivered, the more it begins to shape their ability to solve problems and make decisions on information rather than intuition. He is also beginning to work with other Quaker executives on how the organization makes key decisions.
At the telecommunications firm Verizon, the CIO's objective is to create a similar change in analytical culture. Verizon and other firms arising out of the "Bell System" have long been analytically oriented, but decisions were generally made slowly and were pushed up the organizational hierarchy. CIO Shaygan Kheradpir is attempting to change this culture through continual exposure to information. He created a form of continuous scorecard in which hundreds of performance metrics of various types are broadcast to PCs around the company, each occupying the screen for 15 seconds. The idea is to get everyone - not just senior executives - focused on information and what it means, and to encourage employees at all levels to address any issues that appear in the data. Kheradpir feels that he is beginning to see signs of cultural change from the use of the scorecard.
The Next Step Up-Meritocracy
A more uppity version of democracy would involve allowing - or at least encouraging - only those who are analytically qualified to actually do a lot of analytics. This would deliver many of the benefits of full democracy, while preventing some of its shortcomings. Of course, to make it work an organization would need to make systematic efforts to upgrade and assess the business intelligence competencies of its people.
This is the underlying idea behind the "business intelligence competency center," which seems to be an up-and-coming concept. I recently saw a 2005 BetterManagement survey suggesting that almost a quarter of organizations already had such a BICC, which surprised me a bit because I don't see them that much in organizations. Having a BICC doesn't necessarily mean that the organization has a merit model in mind, but the idea of improving competency at BI does seem to have a meritocratic ring.
A BICC could do lots of things, but if it were particularly focused on creating more capable data analysts and decision-makers, it would do at least some of the following:
- Make high-quality data available to those who need it;
- Assist BI users in the analysis and interpretation of data;
- Train users on BI tools and techniques.
These are, in their order of preference, what the BetterManagement survey respondents said people needed within their organizations. So maybe the BICC's time has come.
Elitism Rears Its Ugly Head
When I studied about 20 organizations that were serious about competing on the basis of their analytical capabilities, in almost every case I found some degree of BI oligarchy in place. That is, the companies had a group of analytical experts - one called them "Ph.D.s with personality" - whose job was to create new algorithms, solve difficult analytical problems, and embed analytical decision-making into systems and processes. It's unlikely, for example, that a "single echelon, uncapacitated, nonstationary inventory management algorithm," employed by one analytical competitor I studied, would be developed by an amateur under a fully democratic BI regime. Among the highly analytical competitors I found, these central and somewhat elite groups were increasingly being viewed as a critical resource in taking analytics to the next stage.
There are two logical alternatives for the organizational home for these high-powered analysts. One would be the business function that is the primary competitive thrust for the organization. For example, Harrah's keeps most of its "rocket scientists" in the marketing department, because customer loyalty programs are the primary orientation of its analytics.
The other logical home is in the IT function. Such analysts make extensive use of IT and online data, and they are similar in temperament to other IT people. Some of the analytical competitors where analytical groups report to the office of the CIO include Procter & Gamble, the trucking company Schneider National, and Marriott. Procter & Gamble, for example, has recently consolidated its analytical organizations for operations and supply chain, marketing, and other functions. The new group has almost 100 specialists in statistics, experimental design, operations research, and other specialized skills. The consolidation will allow a critical mass of analytical expertise to be deployed to address P&G's most critical business issues.
Of course, there is no need to pick only one model. I expect that the best firms in the future will have elements of all three. They'll give lots of people access to data for their own analyses, they'll try to upgrade and certify BI skills in order to create some "meritocrats," and for highly specialized analyses they'll have an oligarchy of quant jocks. Even in these hybrid environments, however, it may be useful to know which model is an organization's primary focus.
Tom Davenport is professor and director of research, Babson Executive Education, Babson College. He can be contacted at tdavenport@babson.edu.
Tom Davenport is Professor and director of research, Babson Executive Education, Babson College. He can be contacted at tdavenport@babson.edu.
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