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.

The post Building the data academy: Identifying students first appeared on Stringfest Analytics.

I’ve self-published a number of Kindle e-books as part of my blog. This has been one of the most challenging and rewarding parts of the blog. A few lessons: 

1. People love free content… I had heard that one of the best ways to promote a book on Kindle is to mark it for free a few days after release. At first, I dismissed this. I am going to price this book at under five dollars, I thought.Who wouldn’t buy it? Boy, was I wrong. The day I set it for free, my ebook launched to #1 in the Guitar section of the Kindle store (for free books). A small accomplishment, but it was incredible to think that all over the world, people were going to check out my first book. It felt like getting angel investors — for free!
2. …but only if they’d pay to get more. One source of traffic I really overestimated was my personal social media. I thought that sales and reviews would come flooding from friends and family. But they are not this book’s tribe.Most of my social network couldn’t care less about buying a first guitar. Why would they check out my book, even if it’s free? On the other hand, people who had never heard of me downloaded it: folks from guitar forums, Facebook groups, etc. If I publish a second (paid) book, they would be more likely to purchase than even my closest friends. I learned here that I can’t depend on everyone to buy my product — I have to find the right audience.
3. Getting reviews is hard. Now I know why every podcaster I know ends with a request to “please review this show!” Come to think of it, even I haven’t reviewed some of them — and I’m a daily listener. How much less likely, then, for someone to review my obscure debut book. Related to the second point, getting reviews comes down to finding your tribe.
4. You are not a one-man show. My first objection to trying a Kindle book was “I don’t know how to do all that design work!” Turns out there are people a click away who do know. From cover to proofreading, ebook assembly is a collaboration. This showed me that to accomplish things, I don’t have to know how to do everything — I just need to find the right people.
5. Writing is fun. I attended a liberal arts college where some classes required 60+ pages of writing per term. Fast forward a few years and it would be rare to write that much in a year now (emails excluded). I was afraid that after college, I would not have an outlet to write. Now I found one that extends far beyond a rural Michigan campus.

Posting this short ebook on the Kindle store has taught me a lot. And it’s great when lessons come the fun way.

Photo courtesy of Gratisography.com

The post What I’ve Learned from Self-Publishing first appeared on Stringfest Analytics.