Where do we start?

This is one of the most common initial questions asked by executives when we lay out findings after conducting an assessment of a customer's data analytics architecture and IT organization. It can feel overwhelming. But when you have the right framework it doesn't have to be.

The way we prioritize efforts is through a business prioritization matrix. This gives a clear, concise view of the long term analytics roadmap and should guide efforts for future weeks, quarters, and years.

It's simple—as we interview business and IT stakeholders and executive leadership, and dig deep into systems profiling data and finding the gaps, we assign a metric for what we deem to be the 1) technical feasibility and 2) business value of conducting each of the potential projects we uncover. Plotting these on a simple 2-by-2 matrix gives a great visual on where to start and how the roadmap should progress.

Start in the upper right hand quadrant. Knock out the efforts that should provide real value, and that you know are realistic to achieve. Find and execute on the quick wins to keep momentum up. Keep the quadrant a "living" document, updated over time to reflect changes to the business. Potentially build a cross-department committee to gather input going forward to plot out new initiatives on the matrix.

As outside experts coming in to assess organizations, Analytics8 is in a great position to objectively prioritize efforts across multiple departments. Often, there are huge redundancies across departments that stakeholders may not even be aware of.

As simple as this exercise may seem, I'm shocked how often this is seemingly new to organizations or different from how they're currently prioritizing their data analytics efforts.

Drop me a comment if you're currently using a prioritization matrix in your organization or perhaps going about this differently. I'm curious to hear about what's working (or not) for you!