How should a PM’s performance be evaluated?
In a recent post, I argued that one cannot consistently measure the intrinsic dollar value created by a Product Manager.
Here are the performance metrics that can be set for different PM roles.
The following common set of measures (not in any order of priority) can be safely used across different role types –
- Customer satisfaction – Has the customer satisfaction trajectory improved? It is a critical job of the PM to make the customers happy irrespective of what type of PM they are. Note that, customers can be external or internal depending on the type of PM role.
Metrics like NPS, Direct customer product feedback rating, and customer escalations post-launch can be used as performance measures.
There are exceptions to using customer satisfaction as a performance measure. These are cases of strategic tradeoffs where compromise on customer satisfaction metric is agreed upon within the company at a given point in time.. – e.g. Monetization as a priority can result in some customer dissatisfaction. But the limits should be clearly drawn and agreed upon by stakeholders.
- Insights – How many useful & actionable insights did the PM generate? The insights can be about the customer, business, technology, environment, or competition. Note that the emphasis is on the phrase “useful and actionable”.
- Execution – Did the PM ensure that the product was conceptualized and launched in a smooth manner? In case of blockers beyond his/her direct sphere of control and influence, did the PM bubble up the issues proactively?
Now let us dwell into specific measurements for each role in addition to the ones mentioned above.
- Growth/Optimization PM – Revenue, P&L and customer count can be used in firms where PM fully owns the levers to impact them. Otherwise, Product funnel metrics are good measures to use. Examples are conversion rate, activation rate, engagement rate (assuming engagement levers & related budget are owned by the PM), etc.
- Scaler PM – Depending on the context, the measures can be – Automation percentage, scale supported (in terms of customers or transaction volumes), number of use cases enabled, feature adoption, etc
- Experimenter PM – Customer adoption is a good measure. A couple of subjective measures that are very useful are – a) Was the launch a bare minimum to experiment (MVP)? b) If the project failed, did we fail fast (consuming minimal resources and time)?
- Platform PM – Measures like Products (or customers) onboarded, platform coverage, and cost savings due to platformization can be used.
General guidelines:
- The measure should be under the sphere of control or influence of the PM. For example, revenue cannot be a goal for a PM if she doesn’t have a say in pricing or the sales/marketing teams don’t report to her.
- When a metric is impacted by multiple levers some of which are not in the PM’s control, it is important to break down the metric to match the ones that are in the PM’s sphere of control. For example, customer NPS gets affected by pricing, support quality, etc, so using a derived metric like “Detractor % with product as the reason” can be used to measure PM performance.
Note: Skills (prioritization, research quality, etc) and attributes (e.g. ownership, leadership) relevant to the role can be added to the evaluation but those are input parameters to performance/outcomes and hence not covered in this article.
