How predictive data analytics can help engineering & construction companies stop the talent drain
27 March 2015
Picture the scene. You have a talented young engineer who’s been with your company for two or three years, and is a high performer with a bright future in the business. You haven’t promoted them for a while, but you intend to soon. Then suddenly they resign – and move to a competitor offering a higher grade and a bit more money.
As a leader of an engineering & construction company, you probably recognise this situation all too well. Recruiting and retaining the best talent has long been a major challenge across the industry. And as economic growth gradually picks up, the signs are that the war for the best engineering talent is intensifying still further.
For example, the latest PwC Global CEO Survey found that half of all engineering & construction CEOs worldwide intend to hire more people this year – but that finding candidates with the right skills remains a key concern. In response, companies have already taken several steps to address the talent shortfall: for example, 72% have widened their search to different countries, industries or demographic segments.
But the fact is that recruiting new people is much more expensive and time-consuming than retaining the talent you already have. And while this is true in any industry, it’s especially the case in engineering & construction, where significant investment is made to train entry level talent and the best technical skills and experience are at a premium and in short supply.
The good news is that tools are now available to enable companies to stop and even reverse the talent drain, gaining competitive edge as a result. By running predictive analytics on their people data, businesses can gain a clear view of the risk factors that point to departure, and forecast with uncanny accuracy which of their people are most likely to leave. This then enables the employer to intervene to keep its best people on board.
One of PwC’s recent client engagements provided a dramatic demonstration of the powerful combination of HR data and analytics. The client asked us to help identify which of its top performers were most at risk of leaving. We analysed their data, to identify the statistical importance of a number of factors and built a predictive model based on these findings. Using this model, we were able to generate a list of people who presented the biggest flight risks.Clearly, if this sort of analysis was part of every day HR operations, they would have been able to identify this risk earlier and put the appropriate mitigation steps in place.
What’s more, the value of predictive people analytics goes way beyond preventing departures. It can help to identify which employees are most likely to be the strongest performers, and which are set to lag behind. It can also assist in raising the quality of new hires, and enable long-term workforce planning – showing, for example, whether the current talent strategy will result in a shortfall in key skills in five or ten years’ time.
So, what should engineering & construction businesses be doing to harness the power of predictive people analytics? We would suggest three steps:
First – identify a division or business unit with a pressing need for help with a people issue. Targeting a smaller population for an initial pilot will reduce the amount of stakeholder engagement required, increasing your ability to make business impact in a shorter period of time.
Second – agree the question you want to answer. For example – if you are struggling to make good quality hires, you might want to predict how long a candidate will stay in the business. If you are struggling with retaining top talent, you might want to predict who is likely to leave.
Third – develop hypotheses to test and run the analysis. Pull out key messages – the ‘so what’ – and present in a compelling way to the stakeholder audience. Getting this last bit right is the key to unlocking the value of analytics work.
As the war for engineering talent intensifies, companies need the best and latest weapons to defend their talent pool. Our experience confirms that predictive analytics is a vital part of that armoury.
