Cheryl Metzger wrote a three part series on data and the role it plays in business and I think it is fantastic. All three articles are excellent, but I think her third installment is the one my readers will care about the most. That piece is about hiring data analysts; it is relevant to job seekers and those looking to transition to an analytics related career, and she hits on some points I would love to expand on.
The article highlights three key personality traits and soft skills that data leaders share. They are a love of learning, the eagerness to adopt new tools, and problem solving tenacity. The first two are obvious, but I think there is a nuance to tenacity that I think readers should be mindful of.
Tenacity and grit are important of course; someone who gives up easily when things get hard will never make it in the world of data. But what distinguishes great data professionals from decent ones is how they press forward when things get tough. When the first, second, and even third solutions do not work, does the person keep trying the same approach or do they re-examine their hypothesis and assumptions before re-starting the analysis? The best data leaders attempt to understand what went wrong and try a modified approach before expending more effort.
Tenacity has yet another nuance for a data leader, and that is in being creative to find new ways to solve problems. Countless times analysts bemoan, “This would be so simple if we only had XYZ data!” Unfortunately XYZ data does not exist. The best analysts will figure out a way to combine a few data sources to replicate it, or find another variable which works well as a proxy, or build out the capability to measure XYZ and incorporate it in future iterations.
Cheryl highlights a couple of items that should encourage analysts already working with data and job seekers who would like to start working in a data related field. A McKinsey report predicts a significant shortage in both people who work as analysts and people who manage analysts and business units that need their insight.
Analysts currently working in industry should be excited about the fact that the demand for managers with analytical skills will far exceed the supply. That means there will be more, and better paying, opportunities for advancement. Those individuals should begin working on their business and management skills as soon as possible. Many analysts are never seen as potential managers because they are thought of as too focused on data, not understanding of the business as a whole, and not being able to lead other employees. For those individuals, take the time now to learn and demonstrate those skills to the max extent possible.
Current managers and individual contributors have an opportunity as well. Fluency in data is more important than ever. With a significant shortage of talent at the analyst level, the ability to promote current analysts is limited. Many managers without significant experience in analytics will be required to manage the people performing analytics. More importantly, the design and implementation of strategies and tactics to improve the business based on those analytics need to be run by managers who understand what the data is actually saying. For individuals who do not have an analytical background, understanding things like what the analysis can and cannot tell you are vital to job performance. Learning to do even simple analysis will start the path that sets you apart from those who do not put forth the effort.
The end of the article holds the key to achieving results from analytics. She highlights this issue when she writes, “Analytics should not be seen as an end in itself, but as a path to action.” Too many organizations and individuals fail that test. I believe that is one of the reasons that some managers are distrustful of data, or unwilling to invest in high quality analytics. Too many analysis efforts fail to deliver on their promise because they are not begun with the end in mind. Analysis is only worth the effort if the insight it provides can drive action. Countless companies produce beautiful and complicated dashboards and analysis but without a clear view of what action they will drive. A basic Excel spreadsheet analysis that drives clear action is vastly superior to a machine learning model whose predictions cannot drive action that will improve the business.
Businesses have been moving towards a more data driven approach for years. Some are light years ahead of others, but even the firms that lead the way will continue to expand their analysis capabilities. Changes produce opportunities for those who see them coming and put in the work to take advantage of them. It is not too late to broaden your skill set to take advantage of the continued data driven evolution.