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Let’s keep things short. Metrics are one of the most important things in Product Management. They help us to understand if the changes we are making to a product or feature are actually paying off and if we’re closer to accomplishing our goal, KPI, or OKR. But that’s not the only reason we need them, they also help everyone involved in the product answer key questions…and yes I do mean everyone. From Software Engineers to UX, it can help the whole team become more data-informed.
What I’m going to show you now is an easy framework I put together using well-known tools like How Might We (HWM), Brainstorming, and Google HEART metrics. This is meant to be done in a workshop either in-person with post-it’s or online with Miro/Mural. Of course, it needs a catchy name which is (bare with me) Data Draw Up or DDU for short. It consists of 5 steps and should take a little less than 2 hours, depending on the size of the team which should be around 7.
But first, let’s see why this is so important and how it’s helped the teams I’ve worked with in the past.
If your team is like most teams, then you’re probably the only person who keeps track of the product metrics. There might be a meeting that’s done every now and then where you share the metrics with the team but let’s be real, people usually don’t understand them or they might show interest but after the meeting is over they don’t see metrics again until the next one.
Let me say this once, it’s your job as a product manager to help everyone in your team, and the obvious stakeholders, to understand and be invested in the most important metrics.
The result of DDU is a team that creates its own metrics, shares different perspectives, and each individual member constantly checks if what they’re doing has an impact. This can be very powerful and will help you take your team to the next level, ever so close to that high performing team you’ve always dreamed of. Let’s get to it!
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How DDU works?
As I mentioned before, Data Draw Up can be done in a workshop using 5 simple steps:
Step 1: Make some HMW questions
This is the first step in getting a team that cares about data. Every one, individually, writes in posts-it’s (physical or digital) what they would like to know about the product in the HMW format. For example, “How Might We know if the user is getting all the information he/she needs from our website”.
Make sure you explain how the HMW format works and keep everything time-boxed. This shouldn’t take more than 10 minutes. It’s ideal if each person has about 3 post-its. EACH HMW GOES IN AN INDIVIDUAL POST-IT. After, make sure everyone reads aloud their own post-it’s.
Step 2: Vote your favorite
Now that you have all the questions the team wants to answer, group them all based on which are similar. When you have them grouped, you can choose one to represent the whole group and rephrase it if needed. After this is done and clear, just vote!
Each person can vote 3 times. And no, you can’t vote on the same post-it more than once but you can vote on the one you created. Remove all the ones that didn’t receive a vote and prioritize them based on higher votes. You want to have between 4 and 6 HMW’s. So you can just go with the ones with the highest votes. Don’t vote again! Keep things simple and time-boxed for máx 5 minutes.
Step 3: Categorize based on HEART metric
This is where things start to get more interesting. Make sure you understand how to use the Google HEART metrics framework. There is tons of information online. For this step, all we need to do is categorize each HWM post-it into one of the five metric types which are: Happiness, Engagement, Adoption, Retention, and Task Success. Keed this time-boxed for 5 minutes.
Step 4: Convert the HMW’s into metrics
Now that you have the post-it’s categorized you need to make each HMW into a goal following the Goals-Signals-Metrics process. You can go one by one, converting the HMW into a goal. Then specifying the signal or signals associated with each goal.
Finally, the metric or metrics associated with each signal or signals. Yes, you can reuse the signals and metrics with different goals. So following the previous example, the HMW “How Might We know if the user is getting all the information he/she needs from our website” would be the goal “User needs additional information”.
Basically, how would we know a user has all the information needed? One way is to know when information is missing. That’s how we get our goal. Now for the signal, a user contacting us to request more information or clicks on a “More Information” button are triggers or signals that tell us that a user needs more information.
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Lastly, for the metrics, this could be % of clicks on “More Information” overall page visits. Which we can interpret as the closer it is to 100% the fewer users need additional information and the better you’re satisfying that need. This is probably the activity which takes the longest, try to keep it time-boxed at 15 minutes.
Step 5: Share with your team
Great! This is the last step. Here you basically have everything you need. Now you only have to make sure to document everything (keeping it short and sweet). And make sure you implement these metrics right away. You might already have the metrics ready but if you don’t, make sure to add them to the next sprint or user story.
Also, create a dashboard in your favorite analytics tool so your whole team can see it. As advice, I would always keep the original HMW questions next to the goal/signal/metric so everyone can keep track of the questions they wanted to be answered.
Your team which usually doesn’t care much for data just created the first team metrics. Which can go alongside your north star metrics or whichever primary metric you use. Try it out and let me know your results in the comments. Remember, you’re one step closer to a high performing team.
Meet the Author
Diego Adrián Cárdenas Jorge is a systems engineer and Senior Product Manager at Quantum Talent with more than 10 years of experience in the digital tech space. He has worked in top consultant management firms, large corporations, and small and unicorn startups.
Starting out as a consultant for enterprise projects, he quickly grew a passion for digital products which led to his transition to Product Management. From a consultant to a Product Manager, he has vast experience managing large multidisciplinary teams in the development and launch of innovative products using a highly collaborative approach on-site and remote. In his spare time, he volunteers as a startup mentor helping small startups grow their business and make strategic decisions.