Decision Sciences COE: Make it an enabler, not just another middleman
Blog Posts:Mu Sigma
Published On: 06 May 2014
You may have heard the parable of the Blind Men and the Elephant. A group of blind men are asked to touch an elephant and then describe what it must look like. Each feels a different part – the one who touches the tusk says the elephant looks like a solid pipe; the one who touches the trunk says the elephant must look like a tree branch, and so on.
This parallels how different corporate functions see data and analytics. The CMO might see analytics as all about revealing insights and taking measurements. The CIO might see it from the perspective of Hadoop and a data warehouse-data mart strategy. Meanwhile, the newly appointed Chief Data Officer will want to focus on reducing the fragmented nature of analytics and reporting.
Each sees the value of data driven decision making, but collectively they lack a way to organize their efforts. As a result, large companies fall into the trap of applying the age old model of corporate IT to their analytics efforts – yet another middleman structure and all of its requisite baggage.
Such centralized models tend to reduce all business needs to their lowest common denominator. Often, IT and data teams aren’t close enough to business units to truly understand their needs, which leads business unit leaders to find workarounds and create their own data fiefdoms – further debilitating a company’s ability to address an ever-expanding network of interconnected problems.
So how can companies get all of these people to see the entire elephant? Consider a Decision Sciences Center of Excellence (COE.) But don’t set it up as a centralized body of analytics and reporting resources. Rather, set it up as a virtual team, spread throughout the organization, and focused on:
Driving the consumption of analytics, first by creating a consistent, semantic layer of data to increase the speed of that consumption
Identifying long-term strategic partners who will bring the interconnected approach to problem solving. These partners help ensure that business managers are not only well educated on the semantics of the data but also have business context. They will also enable standard engagement models for consistency across the organization
Creating more connections between and among business units, by evangelizing the fact that problems cannot be solved in isolation and connecting analytical partners to the business functions more effectively
Unearthing the latent demand for decision sciences within an organization, by helping business managers ask better questions and understand where decision sciences can help
Projecting the organization as pioneers in decision sciences through various internal forums and external conferences
If you’re a Mu Sigma client interested in discussing this more, or in engaging more on the subject with peers through our muLearn network, please contact your Account Manager.
But for now, which organizational model does your company currently employ – the traditional centralized approach, a more virtual COE, or something else altogether?