At our September event, we welcomed a panel of experts:
Some of the big themes to emerge highlight the opportunities and challenges around putting predictive workforce analytics into action.
Predictive analytics make for better strategy
Bold organisations embrace predictive analytics to achieve breakthrough performance. Take an example from Formula 1. Analysis of live data from cars helps drivers understand the likely impact of their decisions as different race scenarios evolve. Powerful software runs millions of possible strategies for each two-hour race – giving drivers a degree of insight they could never achieve with pure brainpower. Predictive workforce analytics does something similar – helping businesses make better decisions on people strategy than they could make with instinct alone.
Analytics give us experience beyond our years
Experience improves our judgement. In situations we’ve encountered before, we understand how different courses of action might play out. So is experience just another way of saying we recognise patterns? And what if we could share that experience with the whole team? With predictive analytics, we can. Access to analysis gives every team member better information about where different courses of action might lead and helps them make smarter decisions on optimising performance.
Learning from data-driven product design
Sensors in products now routinely send back data to manufacturers on how the product is being used. This data informs future product design so customers get something better with each new version. The same principle can help HR teams deliver better support. Workforce data can reveal how a strategy is performing, while predictive analytics can help HR professionals look ahead and understand how subtle changes to strategy can help the business achieve better results.
Spread your data net wide…
On the day Sam Allardyce lost his job as England head coach despite his 100% match record (one game, one win), we understood how misleading a single data point can be. Data from more sources, including sources beyond the organisation, makes insight more accurate.
Despite this, HR often depends on HR data to monitor and predict employee performance, ignoring the trail of data signals employees leave behind them as they work. KPMG monitors over 8000 different signal types to get clearer intelligence on performance. Using data from many sources, we can predict accurately which employees will leave their jobs within the next 90 days – and, within the first three months of an employee joining, the likelihood of them becoming a future star.
… but not too wide
More data is good, but not all data. Businesses, HR professionals, even Formula 1 teams must focus on data that can help answer specific questions rather than going on a general data trawl. The key question must be: how can we get maximum insight from minimum data?
Organisations seeking new data sources must resist the lure of dramatic data that seems to tell an easy story. It’s vital to make a careful appraisal. If the data supports what we already believe, it’s all too easy to suspend critical judgement and forget to ask: can we trust the data?
Data doesn’t deliver certainty
Data doesn’t make decisions – and it doesn’t deliver certainty. It helps people make decisions based on a better assessment of probability. This truth often comes up against unrealistic expectations in the boardroom. Many business leaders want certainty – and they want it fast.
The reality is that it takes time for organisations to get their data in good enough shape for meaningful analysis. And it takes time for HR teams to build or find the capabilities they need to add value through predictive analytics. As a result, HR professionals at the top table face the challenge of reframing expectations for the leadership team.