If you’re a customer insights (CI) or analytics professional, the questions below may sound familiar to you. I hear them from leaders of business insights teams of all kinds, from quant to qual, digital analytics to database marketing, customer analytics to voice of customer, market research to competitive intelligence, campaigns to customer service, behaviorial to predictive, B2C to B2B, CPG to pharma – you name it:
• “I lead our [name the insights area[s] here] team. We’re struggling to get our business and operational areas to take action on insights – heck, sometimes we don’t even know what happens to the insights we provide. How do we change this?”
• “Our insights teams work in silos that have built up over the years. The teams are good at what they do. But how do we pull together and combine our different flavors of insights to get more customer understanding? How should we organize?”
• “I’ve been asked to re-organize [or, I’m new and I’ve taken over] our insights areas. I need to give a presentation to the C-team about what I’ll propose. Any ideas on a framework I should use?”
The pressure is on, bigtime, for firms to get more value from their substantial investments in people and technologies for driving insights. Our research shows that the return on the investment doesn’t seem to be where it should be. For example, in 2016, data and analytics pro’s reported that still only 49% of business decisions are made using quantitative information and analysis – as opposed to subjective factors such as experience, gut feeling, or opinions (up 3 percentage points from 2015).
CI pros know that there’s need for change – that’s clear from the questions they ask. And they also want to know: is reorganizing the way to go? Is centralized best? Decentralized? Research shows that CI follows one of three organizational models: dedicated (decentralized), centralized, and center of excellence (CoE). Typically, CI teams with higher customer obsession maturity operate in a CoE model.
Each of the 3 models have their upsides and downsides. For example, a centralized / corporate shared service CI team may appear to be lower cost, but almost never is. Why? Because, for example, since one CI team is focusing on a range of business lines, the CI pros often don’t have capacity to provide customized solutions. The business then views them as inexpert or unresponsive and may go rogue and seek outside help. In a large, global organization, one-off rogue research and analytics projects going on across the organization can add up to a lot of expense that’s relatively invisible, as it’s hard to track.
CI Centers of Excellence can vary in their organizational approach and still provide value. For example, a firm may have a combination of whole teams of CI pros residing in the CoE in some analytics and insights-generating areas, and in other cases, a small number of CI pros within the CoE providing support to individual business’s dedicated analytics areas. An effective CoE provides governance, program management, and best practices expertise and support firmwide. The downside of a CoE is that people in the center need hard-to-find (and retain) skill sets. For example, CI pros don’t necessarily develop or focus on, along with their analytics expertise, key program management skills such as best-practice internal communication and change management, and have those skills peppered around in a CoE is critical.
