Which is the best model for Institutionalizing Analytics: Centralized, Decentralized or Federated?
Blog Posts:Mu Sigma
Published On: 28 December 2011
If you hang around Mu Sigma (or this blog) long enough, you’ll hear us refer frequently to the notion of Institutionalizing Analytics. That means making analytics a part of your ongoing business processes – weaving it into decision making across the organization.
There’s no doubt that institutionalizing analytics leads to better decision making – but there are three different options for doing it: creating a Centralized analytics function, creating a Decentralized analytics function, or a Federated approach.
Which is best for you? The answer, I’m afraid, is “It depends.” Each has its pros and cons. There is no “one right answer”.
Some factors to consider include:
Company size: Smaller companies may have an easier time with a centralized model, primarily because good analytics talent is so difficult to find. Centralizing the group will enable you to use resources more efficiently.
Degree of diversion within the organization: Let’s face it – any organization with more than one person has politics. If politics are rampant at your company, you may be better off with a decentralized or a federated approach.
General pace of the business: If decisions need to be made quickly, avoid a federated approach, which tends to be the most time consuming.
Availability of analytics talent: It’s well known that there is a serious shortage of analytics talent, at least in the U.S. If you have trouble finding and keeping analytics talent, consider a centralized approach. Mu Sigma also provides an extended arm to ensure bandwidth, industry expertise and scalability on the fly for big projects.
Need help determining the best approach for your organization? Send me an email.