In the last few years, you’ve probably heard terms like “employee retention analytics” and “ people data analytics” bandied about online. It’s far too easy to get bogged down with jargon.
Predictive analytics will indeed change the business world irrevocably. You need to adopt this technology soon to stay innovative and competitive. A few of the ways predictive analytics can help your HR team level up include:
Finding patterns in employee micro-behavior to predict and prevent burnout.
Gauging the success of long-term people strategy, and showing evidence and data from within their own company to lend quantitative support to the value of investing in employee engagement.
Providing internal statistics and determining what works and what doesn’t within their own company and with their team.
But where do you start? In this post, we'll outline real-world examples of how companies are using predictive analytics to re-engage their teams and stay ahead of the curve. Don't let your business fall behind - read on to discover the power of predictive analytics.
HR SaaS and HR analytics in talent management for distributed companies
HR needs visibility into how their teams are doing in a remote world because it’s difficult to take the “temperature “ of a room if there is no physical room. To do this, HR needs to turn to analytics to prove their value and justify their employee experience and wellness initiatives to higher-ups.
Sending out pulse surveys is not enough anymore, and frankly, it hasn’t been enough for a very long time. They’re plagued with sample bias. Employees eager to respond to them may not reflect the mindset of the whole company. It’s possible that employees are not truthful in pulse surveys, fearing that a lack of anonymity might affect their jobs.
With these anxieties in mind, HR Teams are turning to data mining and people analytics to revamp their people strategy. Pre-COVID, there was already a growing call for cloud-based solutions and people analytics in the HR SaaS Industry. The global HR advisory services market is forecasted to expand from $81.45B in 2021 to $ 87.32B in 2022, with a CAGR of 7.2%.
It’s undeniable that the transformative effects of remote work have spurred this staggering growth in the HR SaaS Industry.
20% of new hires quit within their first 45 days of employment
HR Managers want to increase their team visibility and handle their employee metrics to stay competitive during the ongoing Great Resignation. It is expensive to hire new employees and even more costly to refill the same positions repeatedly.
These aren’t new problems, but the disruptive transition to remote work and the Great Resignation make companies feel a tighter squeeze. HR needs the tools to manage talent in the new normal. Unprecedented challenges often require unprecedented investment to address them.
Statistics like the ones below are becoming the go-to justification for investing in employee engagement and talent management solutions:
20% of new hires quit within their first 45 days of employment.
26.6% of Gen-Z employees plan or anticipate getting a new job in the next six months.
Many remote-first companies are turning to software solutions rather than hiring consultants. Decision-makers know what they’re looking for and don’t need outside experts to say that employee engagement is the metric to watch.
Distributed and remote-first companies don’t need a consultant to gather the data. Remote Managers already know they have all the data they need because their teams communicate and collaborate through data-collecting technology. What Managers don’t have is the technology to condense all that data into useful, actionable analytics, so that is where predictive employee engagement analytics comes into play.
What Is Predictive Employee Engagement Analytics?
Wowzers, let’s start breaking down this 25-cent word.
First, what is predictive analytics?
According to SAS, Predictive analytics uses data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to provide the best assessment of what will happen in the future.” HR SaaS Solutions now take the principles and ideas above and apply them to employee engagement.
Predictive Employee Engagement Analytics finds patterns in employees’ micro-behavior to gain insights about their engagement levels. The goal is to predict and prevent turnover, burnout, and undesirable retention and find the best solutions to these problems.
The most common use-case of predictive analytics is identifying employees at high risk of wanting to leave a company so that the HR team can design interventions to re-engage those employees. This type of people analytics is a significant step up from descriptive analytics that an Excel spreadsheet could spit out.
Predictive analytics and data science help HR find correlations between employee activity and behavior and the impact of employee engagement initiatives. These analytical insights allow decision-makers to gauge the success of their long-term people strategy. HR can then show their employers data to lend quantitative support to the value of investing in employee engagement.
The HR Team won’t have to rely on external statistics about employee engagement. Instead, they can show their employers evidence and data from within their own company, which will be more persuasive. Statistics from outside your organization can only tell you so much, as your employee engagement issues are as unique as your team.
Why Do You Need Predictive Employee Engagement Analytics?
You need predictive analytics to ensure sustainable retention and engagement in your remote-first company. Tracking employee retention with descriptive HR analytics and engagement with surveys is not enough in the new normal because they often analyze what is too late to fix.
HR is often stereotyped as stifling innovation, rigidly applying outdated practices, and wasting company capital. This isn’t true, and with hard numbers generated from well-integrated predictive workforce analytics, HR can finally prove the naysayers wrong. Rather than adopting statistically successful methods drawn from industry experts, you can finally determine what works and what doesn’t in YOUR company and with YOUR team.
Your culture, goals, values, and team are unique to your company, so you need a surgically precise, tailored people strategy based on in-house quantitative insights. A one-size-fits-all strategy taken out of a handbook or from an influencer will inevitably amount to making investments and decisions that are not right for your team and don’t meet your goals.
In this time of change in the world of work, companies and HR teams cannot waste time and energy treading water. Predictive Employee Analytics can save remote, distributed, and hybrid teams money and improve multiple business metrics.
For example, Hewlett-Packard (HP) used HR data mining to create a “Flight Risk” score for every employee. They based this score on numerous variables, including salaries, performance, and promotions. This predictive metric saved HP $300,000.
Also, Best Buy found increasing employee engagement by just 0.1% led to increased profits of $100,000 for a brick-and-mortar location.
A Hypothetical Example of How Companies Use Predictive Analytics
Are you trying to learn how to predict employee attrition? Want to understand the on-the-ground benefits of employee engagement analytics?
Let us paint a scene for you. There is a B2C SaaS company that sells tax/personal finance software designed for tech freelancers. Let’s call it ExampleCo.
ExampleCo has 100-plus employees and has had trouble keeping entry-level talent for more than a year. ExampleCo’s voluntary attrition is high, and productivity is down. Plain, old HR Analytics tells them the when and who but not the why. It tells them what you already know, giving them no options to help their disengaged employees. People are leaving, and it is affecting ExampleCo’s bottom line. They’re not even at square one at this point.
Predictive employee engagement analytics is a different story. Predictive people analytics could tell them that software developers are more likely to quit than other employees. Analytics points out that a warning sign for impending resignation is the growing response time for emails and Slack messages.
ExampleCo now knows who is disengaged and why. They can then address these employee engagement issues with a targeted people strategy. ExampleCo can vary software developers’ work or invest in their wellness and personal development. With enough data and quality employee analytics, they can compare different employee engagement strategies over time to determine what works best for their remote team.
What Companies are Doing With the Data
Unsurprisingly, some of the most popular findings in HR analytics are the statistics around healthcare use and employee absences, as the US Army and National Australia Bank both discovered.
The US Army has been using HR analytics not just to help improve the lives of its soldiers but save them. They discovered that attrition during basic training was costing them a staggering $400 million to $600 million annually. The further analysis helped them understand that for soldiers, who lead incredibly disruptive lives due to frequent deployment in combat zones, Post-Traumatic Stress Disorder (PTSD) was a known but often unpredictable side effect. The Army performed an analysis of recruits' healthcare utilization and found a link between higher healthcare use and lower resilience and emotional assessment scores, which could lead to PTSD in the field. PTSD obviously has great personal and financial costs associated with it, and the Army was able to use this knowledge to manage better the expectations and needs of the soldiers in training and prior to deployment.
Using HR analytics, National Australia Bank discovered that its workers were hoarding their allowable leave days each year and it was costing the bank AU$20 million. On average, workers were using only 18 of their 20 days, leaving two days that were carried forward to future years, resulting in potentially large payouts to employees who left the company with accrued and unused days. They found that 50% of its liability was held by 20% of its top offenders -- the same people who also had the highest number of absences due to illness. The bank then pressured these workers to begin taking 105% of their allowed time off, resulting in a more rested workforce and considerable cost savings.
Innovative HR Analytics for Better Business Model
When companies start mixing their HR analyses with business plans, new and innovative approaches to business begin emerging. In sportswear giant Adidas' case, they wanted to use their findings to help increase employee engagement levels and revamp how management, communication, and departments worked together. Adidas believes they are driven by three core pillars: data, metrics, and the employee experience, which provides them with insight into "employee behavior, skill-sets, and talent." Adidas' commitment to the company and employee betterment started by combining a business strategy with a people strategy, a practice that is not owned by HR but instead by the whole company.
As Adidas' senior manager of people analytics, Stefan Hierl points out, "Both employee and customer experience should be approached in the same way...People are a business’s most important asset.” By creating a positive experience for employees, they intend to create a trickle-down effect that will result in increased customer satisfaction. Regular employee engagement and feedback opportunities are encouraged, measured, and compared against regular customer satisfaction analysis, giving them a truly big picture of their business and an ability to spot trends up and down.
US Bancorp is the fifth largest bank in the US, and when they decided to move their HR analytics team to work alongside their business strategy team, it was a big and unprecedented move for the bank. As Jennie Carlson, the EVP of Human Resources at Bancorp notes, the bank has a strong commitment to advancing and developing talent from within. Their desire is to create a positive employee experience that will get passed along to the bank's customers, and they want to be at the forefront of driving trends in their mid-level market share.
To this end, US Bancorp's HR department still regularly solicits and collects employee engagement surveys -- however, the information is now strategically analyzed through a different, more customer-centric lens. The result is better recognition of employee and customer trends that will help drive and improve both the employee and customer experience.
And finally, a process that sounds like the premise for a sci-fi movie and is perhaps the most intriguing approach to collecting and analyzing employee information: gaming company Riot Games is the creator of the 30-million-user computer game, League of Legends – a Tower Defense-type game where teams of players compete to capture a flag and destroy an enemy base.
Almost accidentally, Riot Games began to determine employee suitability based on how employees, who all have profiles in the game, work together as part of a team while playing the game. Players communicate with one another through written in-game chats, and the game's creators have found that while playing, people show surprisingly true-to-life behaviors as they would in real-life situations. If they show high levels of teamwork, sportsmanship, and camaraderie, they are likely to also have those traits in the real world. Alternatively, if they have a tendency toward "toxic" behavior, it will come out most often in the form of "homophobia, racism, sexism, and hate speech" during the chats.
Understandably, such behaviors can negatively impact other players on the team (and in the office). Riot Games' analysis has shown that a new player who encounters a toxic team member is 320% less likely to come back a second time. Further analysis showed that 25% of their own employees who had been let go in the previous 12 months displayed an unusually high level of in-game toxicity.
Riot Games then turned their attention to current employees with the same traits and worked with them to overcome their toxic behavior, some of whom were appalled when confronted with their in-game behavior. As a company high on Fortune's 100 Best Places to Work For list, Riot Games is committed to ensuring an excellent work environment for its people. They have now implemented similar analytical exercises for potential job candidates and are working with MIT to see how their research and processes can help create high-performing teams elsewhere.
How to Measure Employee Engagement with Analytics Integrations
A people analytics strategy to successfully boost performance management needs access to all the tools your team uses to work together.
You don’t need to be a data scientist to know that people analytics can’t measure what it can’t see. HR professionals need to be comfortable with HR SaaS having visibility in other tools like an HRIS, G-Suite, and Google Calendar.
Remote managers worry constantly about the costs of their workforce management, their high attrition rate, and the quality of their employee benefits. They fear the lack of visibility that digital barriers create will damage their overall business strategy. They’re right to worry. People Analytics can solve this problem, but they need trust in the process and complete onboarding, adoption, and integration to work.