Analytic managers and consultants like me are responsible for getting things done; data scientists, on the other hand, value brilliance over deadlines. As much as I love working with very talented analysts, this is the most frustrating part of my job.
Notwithstanding their analytic disposition, everyone — including your data scientists — wants to succeed. In order to do so, they need to be concise in their speech, in their writing, and even in their approach to solving difficult problems. Here are my seven best tips for making that happen.
1: Analyze the impact
At the onset concision is very uncomfortable for analytics, and they’ll need to rationalize it for themselves before they change their de facto behavior. So when in Rome, do as the Romans by conducting research on the benefits of concision and the costs of not being concise, and then preparing analysis (which you should check two or three times — remember, you’re dealing with people who can spot a hole in analytics a mile away).
In my experience, you can double or triple productivity when your team effectively practices concise behaviors. You’ll need the numbers for your specific situation to make it relevant. High-level studies are interesting, but it becomes impactful when the analysis is brought into their reality.
2: Communicate the need
Armed with your analysis, let them know your intentions — you can do this formally or informally, depending on the organization’s structure. I like the informal approach because it’s better for engagement, but do whatever you feel works best. This should be an engagement (which implies dialog and discussion), not a communication. Listen to their feedback and concerns, and make it clear you understand. If they don’t voice any concerns, they’re either not listening or not internalizing the message’s implications. Continue the dialog until they stop head-nodding and start sharing.
3: Teach them this skill
Work with your team coach, HR, or an external consultant to design a program that teaches concision. The facilitator should be familiar working with analytics, because they are a special breed when it comes to this type of instructional design. You’re asking analytics to learn something they won’t initially be good at, and it takes finesse to navigate through this dynamic.
4: Show them how
Once your analytics have guidelines, they’ll want to see it modeled in exemplars. The analytic manager on a data science team should be the paragon of concise behavior. Shorten one-hour working sessions to 30 minutes and eliminate status meetings altogether. When documents are created or reviewed, focus on communicating the most information in the least space, with the question, point, or thesis within the first few sentences.
5: Help them build
I suggest encouraging analytics to read a well-written newspaper like The New York Times or The Wall Street Journal. The email alerts I receive from The Wall Street Journal are usually 100 words or less do a great job of communicating breaking news within a few seconds.
6: Offer them feedback
Be encouraging and supportive, not critical or condescending. Analytics are especially sensitive to skills they can’t quickly master, so give them time to grow, and they’ll eventually come around.
They won’t do it right for some time, so here’s where you have to be very careful. Criticizing an analytic for rambling or producing a tome when a brief will suffice should be avoided. Even when it’s in the spirit of improvement, highlighting any shortcomings should be done with care. In this situation, ask them to produce a more concise version, and be specific.
I once had a data scientist give me a 50-page PowerPoint of all words. My feedback was that it had a lot of great content, but I’d need a two-page process visual to call it done.
7: Give them kudos
When you see analytics exhibit concise behavior, make a big deal out of it. Constructive feedback should always be done in private, but exemplary behavior should be well publicized.
Leaders should support analytic managers in this effort — even a handshake from a higher-up is a big deal to most people. Everyone appreciates kudos, but more importantly, when analytics see their peers getting rewarded, they take notice.
Be concise, and coach your analytics to do the same. Enough said.