How to Prioritize when Everything is High Priority: the Data-Driven Approach

Post was originally published on April 2020 and has been updated in March 2023 for relevancy

At a company where data is core to business, to help make data-driven decisions, I recommend the following 5-step prioritization approach, which builds on the RICE prioritization method, to determine which initiative to move forward with.

Step 1: List all possible initiatives you're considering, from pie-in-the-sky to the short-term.

Step 2: Decide what the timeline to deliverable is, e.g. next quarter, next board meeting, etc.

Step 3: Score each item in the list on the following 4 attributes, each on a low/medium/high scale:

- Impact: Expected business impact -- in profit/savings or towards mission
  - Note: If it solves an (internal/external) client pain point, how does that translate into business impact?
- Confidence: Data availability
- Effort: Timeline to deliverable, including feasibility in hitting the timeline specified in Step 2
  - - This includes considering whether the solution is a product/service that already exists and that you can buy (e.g. the "build vs buy" consideration). Especially if the deliverable won't be core to main product/service the company's offering, consider the "buy" route.
- Interconnectedness to (or dependencies on) other products/projects [Hilary Mason]? e.g. How much easier the other initiatives will be if this one is done first? [Harvard Business Review]

Step 4: Sort according to those that score high on business impact, breaking ties with those products that are more interconnected.

Step 5: Discuss results of Step 4 based on the other attributes to determine the next initiative.

Step 6: Repeat all of the above towards the end of the timeline (specified in Step 2) to plan the next phase, e.g. potentially quarterly.

Keywords: Data products, prioritization, productivity