And now on to part 3...
Step 2: Select the organizational structure
It is obvious from the outset that a business must create some type of organizational structure around a Data and Analytics initiative as it requires the full-time effort of at least a small group of colleagues. There are four choices when selecting which organizational structure is right for your company, and all of them can lead to successful outcomes.
- Business unit led - When business units have distinct data sets and scale isn’t an issue, each business unit can make its own Data and Analytics decisions with limited coordination. This approach is very flexible but will typically lead to independent silos of data. This may or may not be an issue depending upon the structure of the business units within the company and their need or desire to share data. It is possible that data independence is a key driver to success. This approach can also be more expensive if multiple teams are building their own programs. That said, the cost can be minimized by at least having a central technical platform for everybody to share. Thus, it would just be the "business" portion of the program that would differ across units.
- Business unit led with central support - Business units make their own decisions but collaborate on selected initiatives. This is a slight modification to the first approach where the business units occasionally come together on specific use cases. This collaboration is a good way to standardize certain data. Let us say, for example, that multiple business units accept customer complaints and record them. There is benefit to standardizing the codes for the set of possible complaints as well as the business processes for accepting and recording said complaints so that the metrics can be compared and contrasted across the business units. Because there is no full-time, central team identifying opportunities for and governing these collaborations, corporate leadership as well as the leaders of the various business units need to be committed to this collaboration. It is easy to miss an opportunity or for business units to diverge again over time.
- Center of Excellence - An independent center oversees the company’s Data and Analytics while business units pursue initiatives under the CoE’s guidance and coordination. This is the middle-of-the-road approach where a smaller, central team takes on the responsibility of identifying opportunities for collaboration and governing the use cases, but the business units are also allowed a significant degree of freedom through self-service capabilities. The CoE must truly be empowered by corporate leadership to serve in this governance capacity, and they also need the right approach and mindset to build a grass-roots movement of collaboration and self-service in addition to the top-down mandate.
- Fully centralized - The corporate center takes direct responsibility for identifying, prioritizing, and implementing all initiatives. In this case, business units are still involved but primarily to consult as subject matter experts on the data they use and their business processes. This approach allows the company to impose the highest level of governance, but it can be difficult and expensive to build a single team large enough to satisfy all of the data needs without becoming a bottleneck. Caution must also be taken to ensure that pursuing a "single source of truth" does not overshadow the actual, real-world needs of the business units. The program should always allow for some degree of governed flexibility.
In part 4 of the series, we will perform a proof-of-concept...