Behind all great big data strategies is a great editor

Published November 27, 2013   |   

What do Oscar-winning movies, the perfect Christmas card, and a great analytic strategy all have in common? They’re all byproducts of great editing. Editors are often unsung heroes of masterpiece productions, and your big data analytic strategy is no different. In my college days as an Organizational Leadership major, I wrote a lot of thesis papers. This is where I learned the value of having a great editor. My college had a free editing service where English professors would offer suggestions on how to improve your paper. I used them for every single paper, and in every case, my paper was clearer, more concise, and more collegiate. I’ve carried this best practice into my professional life, and it has served me well. With all the authoring I do, I never publish an important document without having an editor review it. Surprisingly, I don’t often see editors on data science strategy teams – this is a big mistake. To make the most effective use of your data science team, employ the skills of a professional editor.

Editors for leadership and management

Just like you have experts in leadership, management, and of course analytics on your data science team; you must have experts in communication. Editors articulate thoughts and ideas into effective communication media, and there’s no strategy or data science team that doesn’t need this. So, without a specific role to play this part, editing often becomes a group exercise among your most expensive and least appropriate resources. I’ve often seen managers unofficially anointed to this thankless role, and even if they are good, wouldn’t you rather have them managing the team? Worse yet, the manager’s draft now goes up to the leaders who must now spend their time in edits instead of setting the course. This is a gross misuse of valuable resources. With relatively little additional expense, hire an editor to worry about content – they’re the experts.

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