Not everyone in your organization wants or even needs to be a machine learning engineer, but they still have a role in how your organization works with data. That’s the of the point of the data academy: it’s about up-skilling the staff you have to take the first steps in building a strong data culture.
If you start to read my series of posts on building the data academy, you’ll see me repeat the claim that most organizations have more data talent than they know or use. This staff may have skills, opinions and ambitions in how to use data at your organization, but need the training and the buy-in to do it.
These are the candidates who you want to enroll in your data academy, and this is what they might look like:
Their expectations gap is wide
Data analysts and scientists spend intense amounts of time learning and honing their craft, whether through formal education, self-study or online bootcamps. These individuals may have the impression that working with data in an organization should be rewarding, if not even enjoyable.
However, many organziations just aren’t ready to support much of an analytics strategy. They may look for an entry-level data wonk to patch the holes with his better-than-average spreadsheets, but this is not a sustainable strategy. Employees like this will continue to up-skill themselves, then ultimately jump ship.
If your best and brightest data professionals keep leaving, there is likely a wide gap between expectations and reality in working with data at your organization. Rather than have your top data talent put themselves through a bootcamp, then leave, why not put this talent through your own bootcamp? This will help narrow the gap between expectations and reality, and increase retention.
They know there’s a problem, but…
Some of your future top data talent isn’t top data talent yet, but they do know that times are a’changing in your organization.
Take a look at Amazon’s 2025 workforce development program press release. Do you see how many times “data” is mentioned?
Your top candidates for a data academy may have nothing to do with data, yet. They do recognize how automation and analytics could transform their line of work. It’s somewhat enticing to them, but they have no idea how to future-proof their roles for it.
Rather than these individuals trying to future-proof themselves, how about giving them resources to do it, which by implication will future-proof your organization?
The analytics myth-busters
Domain knowledge is indispensible to a successful analytics strategy, so much so that your future top data talent may even be those who claim they “can’t do math.”
These individuals will be encouraged to learn that analytics isn’t so much about number-crunching as it is about framing problems, charting processes, and implementing strategies. Doing this well requires as much business acumen as it does spreadsheet ju-jitsu. “A’s” in high school math is not a pre-requisite and could even be meaningless to success.
So, think holistically about your business when identifying candidates for the data academy. If you don’t incorporate those with a strong grasp of your business model, the academy will fail because it will not have a strong basis in domain knowledge.
What’s next?
From your underwhelmed data analyst, to your automation-anxious foreman, to your math-phobic operations manager, the analytics academy takes all kinds. But finding the right talent is just the beginning.
To learn more about building a data academy, check out my series of posts. You can also contact me directly or schedule a free initial consult call.
Leave a Reply