The Boring Stuff

I confess I'm very much looking forward to 2017 for a whole host of reasons; some personal, some business. On the business front I believe analytics, within all aspects of resourcing, will move from being the thing the enlightened few have been doing well for some time, to the topic that is front and centre for the masses. As someone who has lived and breathed analytics for many years, this fills me with hope and joy.

However I have to confess it also tinges me with a little sadness. As we all strive to realise the benefits and insights that data can give us, and make better business decisions as a result, there is a very important consideration that we are in danger of overlooking. In the very many presentations, meetings, forums, discussions etc. that I will be involved in this year, there are three words I fear I will hear rarely, if at all, Data Quality Management (DQM).

We will all recite the truism of 'Rubbish In Rubbish Out' and instinctively know that the quality of our data is important, but how many of us will plan and execute practical steps to ensure we do something about it?

Within the world of ERP and other big ticket systems, DQM is a discipline in its own right with many highly skilled professionals working in this space. Many of us will have DQM specialists within our own organisations, but how many of us are leveraging these skills as they relate to resourcing? How many tech providers in our space are promoting DQM as part of their feature set? How many service providers in our space are promoting DQM as part of their service delivery?

Sadly it is a dry topic that is difficult to apply a direct ROI calculation to, but the indirect costs of making bad decisions based upon bad data could be immeasurable. It is a subject that very few will get excited about, and I acknowledge that I'm perhaps a little odd in finding such challenges really interesting. However I believe most of us will instinctively know its importance, and the data to quantify the size of the issue is all too readily available.

Fortunately Data Quality Management is not some dark art that can only be tackled by Jedi Masters, it is largely the application of thorough analysis skills, common sense and mostly straightforward process refinements. To truly realise the incredible benefits that analytics can bring to us, I'm hoping the data nerds amongst us are kept busy in 2017 helping organisations ensure their resourcing data is sparkly and clean.