Managing your analytic human resources either has or will soon be the most simultaneously humbling and gratifying experience in your management career. If you have hired and trained well, these people are smarter than you are. They will beat you hands down in any argument involving logic and systematic approaches to solving business problems. To most of them, you are the idiot who sold your soul and went in to management. If you don’t have a technical background, then you can be forgiven as one of those who simply never knew better; but an engineer or senior analyst turned manager? From their perspective: God have mercy on you.
Your first mistake: They attend too many meetings. A meeting can be one of the most productive places for a decision-maker, project manager or someone for whom coordinating tasks and aligning work streams is key. But for someone whose job it is to tease out nuanced insights and information from gigabytes of data or to innovate new ways to model a particular business process, a meeting is at the bottom end of the productivity spectrum. You’d be better off sending them outside to get some fresh air and sunshine. Train the management hair on the back of your head to bristle a bit the next time you see your best analysts sitting in a meeting, especially if it’s a so-called ‘status’ meeting; they probably don’t need to be there.
Next mistake: assume your motivations are their motivations. What motivates you: a chance at the next promotion, money, recognition, expanded responsibilities, high-profile business trips, or an A+ rating on your next performance review? Those motives have value, but very few if any of these things will be of great concern to your analyst. For an analyst who finds the deepest satisfaction and meaning in their work, his or her pursuit is truly the exploration of an analytical world in aspects like models, techniques, new and old methods and data insights. Respect that your motivations are not theirs and find out what theirs are. Sure, everyone says they want the “A” but only because they think asking for a meaningful, challenging and inspiring work environment sounds a little off the charts. In other words, your staff is more likely to ask for what they think they can get versus what they really want. You might be able to give them what they really want.
How do you never go wrong? Get everyone to the training courses of their choice. For someone who has proven to themselves that sharpening the mind leads to pleasure (personal satisfaction, compensation, recognition) there is no greater reward than to have the chance to do some more mind sharpening.
Training is one of the most inexpensive, high-leverage benefits you can provide to your analytics team. If your staff is more senior and should be doing the training, encourage them to write and publish or get involved in their local professional society chapters. If you have a master’s or Ph.D. in a technical discipline, there’s a certain mystique and prestige to getting published. Banish any scarcity mentality you might have that says training and publishing only makes resources more valuable and accessible to outside companies and competitors. It’s true, they do. But an even quicker way to run off an analytic resource is to not train them. Err on the side of caring for your staff. If you get the reputation of having good analytic professional development, the talent will start to find you.
In the black and white world of data analytics there is gray. Any management advice you get that sounds counter-intuitive is probably good advice for your analytics staff. For example, fully utilized does not equal fully utilized. Let’s say you have 120 hours of work to spread among yourself and two other analysts next week. Easy math says each person gets 40 hours of work. That’s fair right? Yes, that’s fair but not correct. You’re paying these people to think, you should be thinking high leverage.
The best way to leverage the most gray matter is to not load it down with administrative matters and busywork. In our math problem, you should be taking on 50-60 hours and dividing the remaining 60-70 between the two analysts. This gives them time to think. Face it, your thinking is simply not as valuable dollar per hour when compared to theirs. This thinking time (and ideally it should be more than five hours per week) is innovation time. Innovation is born of creativity which almost always gets suppressed when there’s too much to do. The innovations will start small, like automating a weekly or monthly report; it’s up to you to provide the vision that challenges larger innovations, game changers for your business or decision support function.
Thinking time gets especially beat up when analytics teams are put in the same business units or paired closely with operational teams. The latter is successful when heroic, last-minute efforts are made to push something through production. Most ops teams pride themselves on meeting tight deadlines under unforgiving and impossible circumstances. Teams that run on process, high adrenaline, late nights and venti bolds with an extra shot don’t always speak the same language as an analytic job shop that mimics a middle age craft guild more than a modern day manufacturing line.
The next thing to be sacrificed under unrealistic timelines is quality control. No time to check the data, just email it as soon as the report finishes. Everyone’s been burned by that one. The analytic manager must run interference and create compromise when meeting a deadline encroaches on delivering value to the organization that pays you to do so. Indeed, poorly managed and rushed analytics can increase the risk to an organization.