I didn’t have to wait very long in my career to realize the powerful impact that data training and improved data skills can have on employee retention. In fact, I saw it firsthand after graduating as an industrial engineer when I started at an aerospace company. 

My manager asked me to take over a team in a liaison role between operators and leadership at a manufacturing plant. The majority of my time and experience there was to be spent providing data training for operators on data-centric tools and technologies, and how to use technology to support their work. 

Whatever I’d been expecting, I had to reset my expectations pretty quickly. The operators felt jaded about technology, specifically that it was coming to take their jobs away. They were proud of having rotary phones at home, and they had a stern, negative view about data. I had to find a way to get them involved by highlighting the insights they could generate. When I showed them how to collect data about their day-to-day performance – not having scrap, not having rework – and how it contributed to their quarterly merit-based bonuses, they got on board. Employee retention went up, because they were able to see how their individual impact contributed to the bottom line.

Tapping the power of client and employee data
When I started at my current role at a global business and technology consulting company in 2020, I saw the use of data in the same way but in a very different setting. My new employer is intent on making an impact using data, but this extends in two directions. We help companies become more data literate, data driven and increase their efficiency with data, but we also use some of those same client measurement systems as part of our employee retention strategy. Here we go beyond aggregated numbers to break retention down by sex, race, and a number of other demographic descriptors.

One interesting metric is what consultants call time on the bench, or time that is not spent working on billable client projects. We track this quarterly, and it hovers in the five percent range. By tracking it, we are able to confirm who might be over-tasked and who has an opportunity between projects to grow in their roles. Data leaders shouldn’t look at non-billable work as downtime, but really time that employees can use to deepen their data training and take their own careers up a notch. 

It's also critical to keep a pulse on employees’ mental and physical health, especially after the past two years. In an industry where 70- and 80-hour weeks are common, my company commits to no more than 45 hours a week for employees. They understand that we have lives and other commitments outside of work, and they welcome that. Our effectiveness is not measured by the percent of time that we’re on a project, it’s measured by our total impact in the organization: client projects, internal programs, networking, certifications, and lunch and learns. These metrics are used for recognition as well as promotions. 

Three ways to improve retention right now
Here are a few strategies for reengagement and learning that have made a difference in both hybrid and on-site settings in our company and helped us to retain employees.

  1. Use data to understand your internal opportunities. Where do your employees stand on their role and career right now? Have you asked them lately? It’s easy to field surveys to uncover how your employees feel about your company. Quantifying these metrics will help you determine how much engagement or training may be missing. You could be doing a stellar job hitting your bottom line, but employees may feel that they’re just robots or that their work has no impact. 
  2. Launch core initiatives that are mutually beneficial. At the moment I'm a team lead for something called The Amazing Cert Race. It's a group of 150 different people of which I'm managing 15. The idea is to see which team can earn as many certifications as possible, all paid for by the company. And rather than launching a massive external hunt for new solution architects, we created internal boot camps where employees are training to fill the open spots we have now. I see both efforts working to actively reengage people, which of course improves retention. 
  3. Align training with goals. One of the casualties of training programs I see is that they try to use a one-size-fits-all approach when granularity is called for, or create generalized, generic situations that don’t match up to real-world messiness. Learning in virtual environments can feel safe and cushiony, but when your employees enter settings where data quality is less than ideal and infrastructure is barbaric, it’s hard to draw on idealized lessons. So vet your training as you would vet a client deliverable.


Retaining for today and tomorrow 
Data doesn’t stand still, and neither do generations. Today’s aspiring data leaders want to feel valued, and to add something of meaning to the world and their company. In my experience with older generations, they’ve been more heads-down in their attitude about work. These days I think people are more internally motivated and we may not have the external drivers and motivators that other generations do, and we need to take this into account in our employee retention programs.

All of these factors – culture, demographics, generation, continuous learning – play a role in creating a thriving data culture. It’s up to us as data leaders to use whatever is at our disposal to show how they can come together and create a place where colleagues not only want to stay, but recruit by the example of their happiness and engagement.