Leaders - How have you created a "data culture" within your team?

  • 26 February 2022
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Userlevel 2
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Creating a data driven culture is a process that doesn’t just happen overnight. I would love to hear what you (or others in your org) did to drive data adoption?

Did you hold a monthly team meeting where you shared metrics, did you give your team templates, did you make building a dashboard a part of the official JIRA launch process, did you hold a competition for the person who ran the most queries?

Any and all ideas would be appreciated!

 


7 replies

Userlevel 2
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I’m also curious if there are templates that folks use (for Heap dashboards, meeting agendas, review slide decks) that work well. We’ve successfully used After-Action reports, for example. (Download the template at that link.)

 

The AARs have been helpful not only creating a data-informed culture, but also with embracing a Growth Mindset and continually learning.

Userlevel 2
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Driving data adoption is an ongoing and quite honestly never-ending process, if you want it to be successful over the long-term. We started from square one both with Heap and an introducing the overall concept of what it means to use data to inform business decisions. We have utilized a few different ways of weaving data into the everyday fabric from holding open Office Hours to using a dedicated Slack channel, to having countless one-on-one chats with business partners about what Heap can do for them. Heap, as a tool, is a big part of the process; however, what can be even more important is that the users and interpreters of the data truly understand what they are seeing and their recommendations are sound. As the lead analyst for this tool, I have been very active in educating users on how to read a funnel versus a graph, or how to create insightful business questions that are measured by informative metrics. I often ask the question “why” as in “why do you need to know that piece of information - what is it going to teach you about your product/service/user?” People often latch on to ‘vanity metrics’ or metrics they think will make them look good - something like ‘time on site’ or ‘time on page’. These metrics as standalone numbers can be extremely misleading - it all depends upon the interpretation. 

This type of analysis is not in most people’s wheelhouse, so for that I try to be a point person and sounding board for those who are trying to incorporate data into their overall analysis. The company has grown incredibly over the last two years and I am still one person, so the more I can educate people to be able to do things on their own, the better off everyone is in the long run. My advice is to try a few different things and then discover the one or two ways that best suit your company structure. 

Userlevel 1
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I appreciate your focus on the outcome, @BurpeeNinja -- your focus on the why

I’d love to hear your thoughts and ideas on how to make what you are expert at more accessible to others for whom analysis is not in their wheelhouse. Beyond training and enablement on Heap, how do you educate your internal customers to approach problem solving and think like you? Inquiring Heaple want to know!

Userlevel 2
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@Wendy J that’s a great question which extends well beyond Heap as a product, but more around how to ask smart business questions that can be answered with insightful data-driven results. In order to use Heap or any digital analytics tool, you need have a basic grasp of how to ask questions and what data to use to inform your answer. It sounds really simple, but in reality, without this solid foundation, your analytics “house” will crumble. Heap is that foundation upon which we can build our hypotheses and subsequently, our recommendations for optimization.

For many people the idea of identifying a “problem” is foreign - they just want to know “did I get more visitors?” That’s not the problem, so getting people to understand that in order to influence visitors to engage with your site, you need to ask yourself “what is it I want visitors to do?” Should all visitors be asked to perform the same task, or should you have designated user journeys that will satisfy different needs? Many times, Product Owners have not thought about the “why” and they just want to know the “what happened?” and think that looking at a table of numbers is going to tell that story. Unfortunately, it’s not that easy and instead we need to understand the whys behind the data.

Heap gives us the opportunity to be more insightful about what the data is saying and enables us to come up with problem statements and hypotheses upon which we can base a test or a new feature implementation. It is not my goal to get business owners to think like me, or even to think like an analyst, but more to get them to think about data at the start of a conversation and not as an afterthought. 

Userlevel 2
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“… how to ask smart business questions that can be answered with insightful data-driven results. In order to use Heap or any digital analytics tool, you need have a basic grasp of how to ask questions and what data to use to inform your answer. It sounds really simple, but in reality, without this solid foundation, your analytics “house” will crumble. … For many people the idea of identifying a “problem” is foreign...” I could not agree with this more, and in all honesty, I was one of them, so I started reading/listening about how the scientific method is applied in the business world. I think people default to vanity metrics because it takes a more time and effort to think about, let alone answer, the “why” - even more so if you never learned how to ask “smart business questions.” Thank you @BurpeeNinja for your incredibly thoughtful responses on this thread.

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I can only echo what has already been said - it is an ongoing process to implement, maintain and improve upon. I am currently implementing a data-driven decision making process in my workplace, largely based around the RICE framework to help assist with prioritisation of features, tailored to the specifics the organisation need. This is slow going as I get the - now - distributed Product Management team onboard to recording down the raw data for analysis later. This is being one in parallel with other metrics initiatives I’m pushing for, others around more straight-forward things like user retention, onboarding etc. The fun bit is going to be correlating all of this down the line to understand spikes, trends or changes in behaviour. 

Userlevel 3
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Agree with most of what’s been said. What I’d add is that you can really foster culture of data driven decision making by leading by example. Don’t wait for others in your organization to  set goals, create reports and do analysis. Do it yourself first, and teach others by doing.

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