The most common and risky mistake when using these techniques is to ignore a lack of clarity:Lack of clarity on the inputs for your OKR definition: You need to have your vision, strategy, customer insights, and roadmap in place to be able to estimate your next contribution to your success.Lack of clarity on the goals of your OKRs: Do you want to measure performance, enable more focus, and get the team more autonomy?

Most Common (underestimated) Mistakes

“Outcome over output” is a well-known claim in product management. Output OKRs(Objectives and Key Results) are said to be rather shallow, not inspirational and are likely to block learning opportunities. The key results should give a holistic picture of the objective, capturing the objective from as many perspectives and levels as possible. This will give more space to come up with the best solution(s), but also requires more confidence and skill from the team.

There Are No Right or Wrong Key Results

<ul><li>Mind that there are no right or wrong OKRs, just different dimensions (with relating consequences) that you as a team should be aware of.</li><li>Be aware of unclear aspects of your OKR inputs as well as the goals you want to achieve.</li><li>Consider using output-driven OKRs as a helpful tool to establish a product discovery practice.</li><li>Set up regular check-ins – on the team and company level.</li></ul>

Key Takeaways

Based on the consequences of the key results, OKRs can be separated into three different types:<ul><li>Impact-ish OKRs: a high-level expression of the company’s strategic priority expressed through a result/metric.</li><li>Outcome-ish OKRs: a change in human behaviour that creates an impact on a department level. It can be validated through the “how might we” test.</li><li>Output-ish OKRs: a completed activity that aims to create a change in behaviour and has an impact on a team level.</li></ul>

The Three Types Of OKRs

Categorising your OKRs like this will likely not be enough for actually working with them on a day-to-day basis. A second layer should be pointing out the likelihood of the aimed change. This can be measured by a concept that has been around for a while:<ul><li>Leading indicators are more difficult to spot since they require insights from actual user behaviour.</li><li>Lagging indicators: are easier to spot (e.g. user growth, revenue) but are often unresponsive and hard to change from a company perspective.</li></ul>

Adding the Dimension of Leading/lagging Indicators

Most product teams review goals in hindsight to see whether they have succeeded. But what if you could not just assess what you’ve already done but prioritize your actions along the way?A few takeaways from an extensive workshop:<ul><li>There are no right or wrong key results.</li><li>Adding the dimension of leading / lagging indicators.</li><li>Most common (underestimated) mistakes.</li><li class="ql-align-justify">Using output-driven key results to establish a product discovery practice within the company.</li></ul>

Measuring Progress For Product Teams

Output key results for Product Discovery are a bit controversial since they are easy to misuse, but can be helpful for teams that struggle with prioritizing discovery work and/or discussing its progress. Metrics like “number of winning prototypes” or “number of opt-ins to user testing” can help make Discovery become a more sustainable practice.

Using Output-Driven Key Results to Establish a Product Discovery Practice Within the Company

Product Management coach and author Tim Herbig took ProductTank Amsterdam through a hands-on workshop to provide insights on how teams can measure progress through outcome OKRs.