Data Leadership Challenges I Failed At So You Don't Have To! PART III

Avoiding the mistakes I made as a data leader!

Welcome back and happy Valentines day! 🌹

This is the third and final instalment in Data Leadership Challenges I Failed At So You Don’t Have To!

In this series I’ve been looking at challenges I faced in my data career that I ultimately failed to overcome and what I would do about it today!

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1. Failure to educate stakeholders on data concepts

🏔 Challenge: Low levels of data literacy are not uncommon among non-data stakeholders. This can make communicating even the simplest of data very challenging. But instead of acknowledging the need to help those stakeholders to better understand, it was easier to simply complain that our stakeholders are just dumb 😒.

📉 Impact: When stakeholders fail to grasp insights that are being shared with them, it becomes impossible for data analysts to gather momentum and gain buy-in for insights or data initiatives. That’s bad for the data team and for the business overall.

👨🏼‍🎓What I learned: Having since been involved in data literacy programs and training, I’ve come to realise that the level of understanding is often times far lower than we data professionals appreciate. Even the basics of reading charts are not always there - yet that is the key tool we use to communicate with the business.

🚀 Today’s Approach: As quickly as possible, I would look for ways to evaluate the data comprehension of my stakeholders. Through interviews, surveys and even the use of tests, I would try to understand where the gaps lie.

Then, resources permitting, I would embark on a program of data literacy education across the business, so that people are able to grasp the fundamentals at the very least.

2. How I failed to handle data tool adoption

🏔 Challenge: Data teams love to invest in data tools. It is a tangible representation of our work and our abilities. We love them - particularly dashboards. But, that’s not always true for stakeholders. In my experience, we put a tonne of work into data tools in the hope that the business will use them…but they rarely engage them at the level necessary to extract value.

📉 Impact: A whole lot of work done by data teams is wasted and data teams fail to demonstrate their value to the organisation.

👨🏼‍🎓What I learned: For the most part, tool adoption is low because we do a terrible job of understanding the needs of our stakeholders. We often build solutions in these tools hoping that out stakeholders will find value in them. This is not how it works.

🚀 Today’s Approach: As much as you may hate to hear this, stakeholder facing data tools are largely overhyped and unnecessary.

(might be about to receive a cease and desist from some SaaS sales guys)

While I’m all for dashboards and self service analytics, we need to make sure that what we are building for stakeholder will actually help them to solve a problem they have. Having them tell us what they want and then building it for them is not going to work either.

To get this right, we need to ‘creep and go’. We should start out with minimal access/reporting and see how they get by. If they come asking for me, then that’s when we provide more.

Inundating them with reports and dashboards and unlimited access is unlikely to result in the desired outcome.

That’s it for this week and for this series!

If you’d like to check out the first 2 parts of Data Leadership Challenges I Failed At So You Don’t Have To - you’ll find there here:

⚡️Whenever you are ready, there are a few way I can support you: