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
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