Analytics and data are transforming the world of talent. Now more than ever, analytics experts are able to use a company’s employee data to make enhanced people management decisions that are transforming the way they work. Unfortunately, many analytics vendors are also putting out claims about how to use data that simply aren’t true — so it’s time to get a dose of reality, put down some predictions and think about what the future could bring.
- The Allure of Dashboards and More Data
Organizations will increasingly understand the value of big data and will work to connect data sources across their organization to more effectively conduct analytics and strategically answer important business questions.
More data, however, doesn’t mean better insights. For most companies, their human resources functions already owns the data through HRIS, employee surveys, 360-degree feedback, candidate data, performance management ratings, etc. Data already exist and many practitioners will continue to have an insatiable and unnecessary need for more data. You need data to identify drivers of actual business outcomes. More dashboards do not equal greater return on investment.
- Adoption and Change Will Be Slow
Adoption of predictive analytics in HR will be relatively slow because the current analytical skill level of HR is limited. Many HR professionals understand that analytics can greatly help HR contribute more to the company’s bottom line, but the function may not have the proper skills to effectively apply analytics.
- Shiny Objects: HR will get caught up in the new shiny object of data visualization/dashboards and miss out on actual, rigorous HR analytics. They may focus on things that look cool but lack real rigor and have minimal impact on outcomes.
- Fads=Credibility Killers: Companies will apply bad analytics that will result in bad decisions — investing based on “looking” at a lot of data. This will kill HR’s credibility.
- Rage Against the Machine Learning: The race to apply automatic analytics (i.e., machine learning) will result in bad predictions because they lack rigor. Predicting human behavior is complex and difficult. So when a company starts telling you who to hire based on the font style in the candidate’s résumé, you should be skeptical.
- Learning Curve Sprint: On a positive note, HR will quickly increase its understanding of analytics and its ability to evaluate potential applications. Basically, HR will be forced up the learning curve quickly because they will be bombarded with so many different tools and applications that they will have to learn.
- A Competitive Advantage With ROI … for Some
When done correctly, analytics can help organizations solve real business problems. Essentially, the application of analytics will help HR begin making decisions and investments based on facts and data. Analytics will help them prioritize the real drivers of results (not squishy concepts like employee engagement). Data-based decisions, in general, are needed in our field, so the organizations that successfully apply analytics will gain a significant advantage.
Below is a list of reasons that will drive HR to achieve this competitive advantage:
- CEOs Asking Real Questions: Soon, CEOs will start asking CHROs, “What exactly is the ROI of all these surveys and assessments and the analytics team?” HR leaders will have to start answering the “so what” of the people investments and initiatives instead of relying on the assumption that it provides value. The only way to identify the ROI is through the application of real analytics.
- KPI Confidence: HR will stay in its comfort zone for a while focusing on turnover. Eventually, most organizations will need to start to show direct business impact on other key performance indicators, such as sales, revenue, productivity, operations and customer satisfaction.
- Bad Analytics Leads to Bad Business
Most analytics tools/approaches use very basic methods and don’t connect results directly to business results. Others are pushing new approaches based on weak machine learning and unproven algorithms. Remember that one of HR’s primary roles is risk mitigation and some of these “new” approaches introduce very real risks. Let’s explore some of the potential risks:
- Manager Mayhem: So what do you think the likely outcome will be if you give managers an individual level turnover risk metric? A manager might fire or not promote someone because they are a “turnover risk.” Can you say lawsuit?
- Affirmative Action Wins: Affirmative action lawsuits will be won in court based on a “predictive metric” with adverse impact or discrimination. This is where the machine learning component becomes risky. In this approach, correlations are sought for any and all data points. So, if a font style is a predictor of success in the résumé screening process, is it possible the algorithms might have adverse impact? Sure it is.
- Buyer Beware: Many “predictive” analytic technology companies will fail and go out of business by rushing to get unproven things to market that aren’t actually predictive These companies will fail because (1) clients will discover that bad analytics don’t actually drive success and/or (2) lawsuits. So, don’t just assume that something new and innovative will work. Be an educated buyer for your organization.
- Demand for Analytics Skills Will Continue to Grow
There is already a shortage of these skills in the job market. But, make sure you look for the right skills:
- Statistics Surge in Schools: We predict that HR educational programs will emphasize statistics and data analysis. Many programs are already starting to expand existing curriculum to include more statistical methods courses.
- Skill Set Search: Organizations hiring for HR roles will increasingly seek out candidates with these stats skills. HR leaders don’t have to be statisticians, but they must understand the application of analytics and be good consumers.
- Are YOU I/O?: Demand for I/O psychologists in HR functions will sky-rocket (this is actually already happening). I/O psychologists are experts in behavior, knowledge transfer, attitudes, aptitude and statistical methods. Essentially, they possess the perfect combination of skills for HR analytics. Predicting human behavior and performance is very difficult and complicated. I/O psychologists know how to do this.
Scott Mondore is co-founder and managing partner of Strategic Management Decisions, a human capital analytics advisory. To comment, email email@example.com.Filed under: Talent EconomyTagged with: big data, business, data, HR analytics, leadership, management, talent, workforce planning