This probably comes as no surprise to you, but today's best HR strategies have a lot to thank Brad Pitt for.
Not only does he adorn the screensavers of thousands of desktops in offices all around the world, but Brad has the ability to make just about anything look cool.
Including predictive analytics, believe it or not.
In the 2011 blockbuster film Moneyball, playing the role of Billie Bean, Brad and his team portrayed the use of predictive modelling and data sets to predict the potential success of baseball players in the US to great effect.
Moneyball tells the true story of how statistical models influenced Major League Baseball, but in truth, predictive analytics tools aren’t exclusive to baseball, nor are they even new techniques.
For years now, your bank has used forms of predictive analytics software to evaluate your credit risk when applying for a loan. Your local weather app on your smartphone uses similar analytical techniques to tell you that it might rain in two weeks from now.
The truth is, it’s not just the financial services who should be using predictive analytics to improve their strategies and offerings. Some of Silicon Valley’s finest have begun understanding big data sets on their own employees to improve and optimise their own HR strategies.
In an age where people data seems abundant in just about every workplace, understanding and using data has become an essential role of every HR team.
Predictive analytics might not help us understand what next week’s winning lottery numbers may be, but it goes a long way to future-proofing any business.
If your HR department isn’t using data analytics to inform their strategies, here are 5 reasons why they should:
1. Hire the right person
Often the greatest puzzle to any HR department is finding the right person for the job. Having great employees who excel at their job is the magic ingredient every HR department searches for.
Laszlo Bock, the former Senior Vice President of People Operations at Google revealed in his 2015 book that the most important instrument of Google’s HR department was statistics.
The interview process at Google HQ is often fully automated, with candidates asked solely computer generated questions designed and fined tuned to find the tech giant the perfect candidate for every role.
Google evaluates their answers and generates statistics on the candidate that not only qualifies/disqualifies them from the role but allows Google to predict the probability of the candidate leaving the role in the future.
2. Boost productivity
Finding the right employee is often only one piece of the puzzle for HR teams.
Once the right employee is successfully onboarded within the company, HR will need to find ways to maximise that employee’s potential and success within the business.
Step forward predictive analytics.
Using predictive analysis, managers and HR teams are able to monitor and predict future outcomes like general performance, employee progress, failures and so much more.
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3. Upskill your team
One of the best uses of predictive analytics on scale is predicting where your teams will develop skills gaps in the future.
Mexico’s ministry of energy has been trialling a predictive analytics model that defines their workforce planning strategies for several years now.
Their goal when embarking on such an extensive data collection drive has been to locate critical skill shortages within their oil and gas department both now and in the future.
Staff with the right skill sets in the right positions will be able to provide cleaner, optimised energy pipelines for the future.
Identifying and predicting skill shortages isn’t exclusive to large operations like the Mexican energy department, however.
Los Angeles based learning group, YoiCorp, provides training solutions for local businesses that integrate predictive analytics into the workplace making training more contextual for new hires.
Predicting skill gaps and plugging them without any noticeable drops in performance is a great asset to any organisation.
4. Improve employee engagement
For so many businesses, measuring and predicting future employee engagement scores is tricky business. In truth though, this is where the effective use of data analytics shines.
Measuring key employee engagement metrics through online solutions, surveys or even personal engagements can offer valuable insights to businesses going forward.
The ability to predict the impact changes like new strategies, office improvements or working hours have on critical employee engagement metrics helps define future strategies and even the manner in which leadership within an organisation communicate and engage with their fellow employees.
5. Retain Your Key Talent
Each year, businesses around the globe invest enormous amounts of resources in identifying, onboarding and training their staff.
It becomes even more expensive for those with high staff turnover rates.
As a result, more businesses than ever are turning their attention towards regression models and predictive analytics to analyse their organisation's data and identify any areas impacting staff turnover rates.
Highlighting talent at risk of leaving and even the conditions driving them towards the exit door allows business to address any potential issues and hold onto their best employees.
Predictive analytics can be an HR game changer
We’ve only listed 5 reasons why applying solid data analytics into your HR strategy makes sense, but in truth, there are many more reasons.
Ultimately HR departments can save, or earn, their business millions in revenue each year by using historical data to predict staffing outcomes.
The ability to predict how employees will perform and the impact of future people policies means that HR is in a better position to help inform managers and leadership to make better decisions to improve employee engagement and staff retention.
What’s become clear, is that predictive analytics is the way forward for HR.
Does your HR department use predictive analytics to inform their strategies? Feel free to share some of your experiences in the comment section below!