So you’re a small business or a team within a larger business.  You have hiring responsibility for your team and some level of P&L responsibility.  You’ve heard for the past 5-10 years nothing but “data, data, data,” and “information overload,” and “competing with analytics,” but you don’t know where to start.

(Or, you know someone who is in the above situation and you forward this post to them so they can read it in the first person!)

To keep the blog post short, let’s keep to why, who, and how.

Why hire a data analyst?

Why would you hire a data analyst?  Because they have the power to make your life easier, your team smarter, and your business more effective by filling gaps in most information workers’ skillsets.  Data analysts are used to working in the trenches, resolving real information issues and getting you to the first horizon, the hallowed “One Version of the Truth.”  I cannot describe in words the power of everyone on the team working from the same set of assumptions, not just for historical “truths” but also for granular forecasts.

The right data analyst can then take you beyond the truths into predictive analytics, they can drive relationships out of messy data by eliminating noise.  They build better business cases, and they implement statistics actively to drive tangible business results.  If the “why” is still a question, comment below, and maybe we can tease out additional posts.

Who do I hire?

I am biased.  I think that your first hire should come out of a data shop within a well-respected consulting firm.  I cut my teeth at A.T. Kearney, and even though I am out of the game now, there are many who had similar training to me, and KPMG has a similar shop.  In fact, many consulting firms are running to catch up, and their high-flyers should all be in scope.  Find a Manager in the group, one who managed teams, managed projects, sold work, hired analysts, gave talks at schools.  These people are out there, and you can get them.

When you interview them, ask them to lay down a vision for how they would work with your team, which problems they would prioritize.  Tell them about your team and engage in a meaningful dialog.  You would be surprised how many leaders are out there, and you need one.

But make sure that the person with whom you are speaking has the soft side and hard side covered.  Probe to make sure the person does in fact understand the business impact of the projects on which they worked and is not just running numbers and analysis sake.

So then what (the How)?

Once you bring someone in, you have a simple deal to make.  You need them to demonstrate value in the immediate term by starting small and delivering something meaningful.  But your end of the bargain is executive support.  Your new data analyst will require your patience if business processes need changing.  You may need to tell one of your finance guys that they do in fact need to abandon an Excel-based forecasting system in favor of working with your new analyst to build the forecast assumptions into the new process that everyone can access.

It isn’t an easy transition to being a data-savvy organization, but your competition is trying, so you may as well get on it, and hopefully the brief advice above is a noble start.

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