Data Product Wheel

I have been fortunate in my time as a data analyst to work in an analytics team in a Product Business Unit. From this I gained exposure to product management practices and the huge benefits and overlaps that an analytics team can gain by taking on a product mindset. Time and time again I witness analysts focussing on the analytics and then wondering why the stakeholder didn’t respond or take any action from their work. The key for generating action from analytics is for analysts to take on a Data Product mindset. I have simplified this into 4 stages of a Data Product Wheel.   

1. Discover 

Before any work starts, it’s essential to understand the problem that is trying to be solved. Stakeholders are notoriously bad at giving requirements. What they request is often not what they really need to solve their problem. The Data Product team’s first job is to uncover the problem we are trying to solve.  

2. Analyse 

As part of the analytics phase, I like to take on concepts of Agile as part of the product mindset. By iterating work through team leads, peers or stakeholders, the end outcome can evolve to be more relevant and actionable. 

3. Customer Experience 

I’m a big believer in making life easy for the end user. This could be something as simple formatting changes to make the insights easier to read – e.g. 1.8m is easier to read than 1845952 – or something more complicated like providing a call to action by telling the stakeholder what to do with the insights, i.e. don’t make the end user do the hard work to figure out what the next steps are.   

4. Sell 

Selling in this context is ensuring you gain value for your work, i.e. ensuring it gets used or drives action. Selling can take many forms: it can be checking in with stakeholders at all parts of the build to maintain the buy-in from the stakeholder by iterating work with them; it can be in how the end results are delivered to the end user, i.e. could an email be lost in the stakeholder’s inbox or does the stakeholder prefer pre-reading before a presentation of the results?  

Taking on a product mindset can be a big culture change for a team. It can require people to move out of their technical comfort zone and into softer skills. It’s important to remember analytics is a team sport, especially if you want to scale your business. It isn’t necessary that one individual has to complete all steps but to more work as part of a team and draw on individual strengths. As with all new changes the most important thing is to try, give things a go, know your strengths and know when to ask for help. 

A common misconception when coaching the product mindset is that every task now doubles in delivery size as we now have to allow for 3 extra components to deliver. However, this doesn’t have to be the case. By iterating work earlier in the product development, it can reduce the amount of additional work created by aligning with the stakeholder earlier. The data product mindset doesn’t mean that every analytics task has to turn into a big task. It’s about adopting concepts relevant to the size and urgency of the task. Sometimes a senior leader just needs a quick number.