As we’ve discussed on this blog before, technological changes and economic variables are putting more and more pressure on marketing teams and businesses in general to justify strategies and quantify results with data. The problem with data is that data, in its simplest, just-collected form, is completely raw. Knowing that 10 of your leads this month came from Ohio doesn’t really tell anyone anything about how well you did or how you should run your business going forward. Is that number high or low when compared with how you’ve done in that state in the past? How does it compare to other states? The point is data needs a context before it can have meaning and be useful.

Here’s the problem with everything I just said, though: The person who manages the data collection often isn’t the person who is best qualified to place the data in a useful context. There’s a data integration process – from collection, to management and filtration, to analysis, to action – that relies on technology and systems, and someone has to maintain those systems (usually IT). But, IT isn’t the department actually needing/using the data (that would be marketing and/or sales). At some point, the data baton needs to be handed off, and figuring out how to do that is the real challenge for businesses.

We all have a pretty good idea of what traits we like to see in new employees. There’s a laundry list of cliché adjectives nearly every manager at some point is guilty of pulling from when putting together a job listing. We want our candidates and future employees to be dynamic, motivated self-starters with a passion for whatever their specific role will entail. The point is we know, almost to a fault, what we’re looking for in an employee.

Well, any human employee, that is.