The size of your organization, the magnitude of the opportunity for improvement, and the number of potential opportunities to focus on will all be factors in the way your OKRs are working. If there’s a mismatch between the scope of the OKR and the product, team, or outcome it is designed for, it’s unlikely to be effective. The good news is, there are some tips to help you get it right.
In a large organization, it’s tempting to implement a broad, high-level OKR and then break it down into pieces that each team can focus on. That can work, provided it is written in a way that gives teams clear guidance and can be broken down in a way for teams to contribute effectively.
As an example, let’s consider a large organization that wishes to improve the customer experience. Many teams can contribute to this, and each team has several choices around how they could contribute. The company has identified that measuring the customer experience can be done by considering revenue, but only from customers who have renewed (the assumption being that renewal implies the customer is happy with the service they’re receiving).
Improve the customer experience
Increase revenue from customers who have renewed for a minimum of 12 months from $880k to > $1m MRR by end of the year
High-level OKR = broad in scope, difficult to affect, scoped over a longer period
First of all, as a high-level OKR, this has been set to last for a year, as it will take a while to achieve the desired outcome, and cannot be easily affected within a quarter. This type of OKR is not an ideal way to make small improvements and allow for changes in approach, but it’s a good way of aligning teams around a goal.
For teams who are contributing to the company OKR, it’s important to consider what they can affect, and ensure there is time to pivot if success isn’t easy to achieve with the chosen approach. In this example, the teams should be considering quarterly (or even monthly) OKRs in areas they can directly affect, with more achievable and measurable key results. Remember from our Lesson 1, that the best OKRs refer to leading indicators so we know we’re affecting important KPIs.
To break this down, each team thinks about how they can make a change, and measure the results, which they also feel will affect the company’s OKR. The support team identifies that customers are frustrated with password resets and integration setups, and feel that reducing that frustration is likely to increase renewals. The product success team identifies that customers cancel their subscription as they find the user interface difficult to use, and so they avoid using the product.
The resulting team OKRs might look like this
Reduce the number of support tickets around common queries
- 10% reduction in password reset tickets in Q3
- 10% reduction in integration-related tickets in Q3
Increase adoption of product A
- Increase % of monthly active users from 10% to 10.5% by end of Q3
Team level OKR = Specific in scope, short period
Now that we’ve covered how to manage OKRs in a larger organization and within a team, let’s try mapping it out! Take some time to reflect and try answering the following questions:
- What problems are you currently facing as a team and within your organization?
- What team OKRs could you put in place to take those problems?
Good measurement is fundamental to the success of OKRs. It’s important to be confident whether your activity has made a difference, and also which activity you’ve tried during the period you’re measuring. There are a few ways you can ensure that your key results are tied directly back to the work you’ve done.
- Ensure you have a good set of baseline measurements before you start and know how you measured them so you can replicate them.
- Be confident that you understand which levers are likely to affect those metrics before launching into any work which may affect them. Note those levers for future reference.
- Keep track of when changes are implemented, so you can see a correlation between a product/service change and the resulting metric change
- When planning your work, stick to one change at a time so you can be confident in why your metrics have changed
By following these rules, you’ll be able to confidently state the outcome of the work you undertake. Product management is a scientific discipline, where we develop hypotheses and use data to prove/disprove them.
It’s often better to focus on % figures instead of absolute numbers as KRs, as percentages are harder to game and tell a better story of what the quality is at that point in the funnel. Let’s face it, you may flood the top of an eCommerce funnel with traffic, and will probably see more overall sales come through, but there is always a possibility that conversion will drop as a result. A more sustainable approach is to understand what kind of traffic provides the best conversion so that you can invest your PPC budget in the traffic most likely to give you the best return.