Companies that want to increase their use of analytics are always looking for talent – but the hunt is full of difficulties. It starts with what to call the jobs, but it also includes who should be screening for the candidates, what skill sets are needed and what additional training should be built into the budget. And then there is the issue of keeping these talented people; they are coveted professionals. In the past 10 years, I’ve hired about 40 analysts in different companies. Here are some suggestions that will work if you are staffing a Center of Excellence or building an analytical group within a business unit:
- Don’t rely on human resources or search firms to find top analytical talent – Job descriptions aren’t quite as straightforward in the analytics world as they would be if you were hiring an accountant or actuary. There really isn’t a strong definition of a “Chief Data Scientist” or for the jobs under that person. By the time I can explain what I’m looking for to HR or a recruiting firm, I can find the person. Rely on your internal network of analysts and look to resource groups where analysts gather.
- Create a defined job path to keep your talent – Great analytic talent is motivated by intellectual challenge and content-centric goals. Companies have long had career paths within Research & Development that nurtured staff interested in creating strategic vision or managing large projects. The same should happen with analytics. If people can’t rise above the job title of analyst or statistician they will take their talents elsewhere.
- Hire communicators – Great communication skills are as important as technical and analytical capabilities. Solid analytical talent can communicate clearly and quickly what it is doing, can do, or what needs to be done. This type of talent can bridge the divide between business users and IT, between non-technical domain experts and very technical programmers, statisticians and IT experts. We don’t want to hire the rocket scientist who can’t explain what he or she is doing to the lay person. And I say that as someone who has a PhD in Physics.
- Build relationships with universities – Many university programs either train statisticians or they train engineers. It’s a narrow approach. I’ve been working with a university in Belgium to develop an interdisciplinary approach that includes a diagnosis tool to evaluate the analytics maturity of an organization and the development of its knowledge workers. We need to create a framework to develop knowledge workers. Good analytics candidates come from many disciplines. I have hired people with degrees in econometrics, statistics, finance, marketing and agronomy.
- Coach, coach and coach some more – Since it is tough to find the “perfect” analyst (even if you control the search), training is important. Many strong technical individuals with the potential to be great communicators are a bit introverted and need help learning to be assertive. We live in an extrovert-biased society, and if an analyst is working with, say, marketing; well, there are a lot of extroverts in marketing. Nurture your introverts.
Read these blog posts for related topics like the Chief Data Scientist, executive buy-in, big data and more.