A nurse snarled at me for my 3rd repeated call on my hospital bed. 3 hours past pain medication post-surgery. I sighed… “How did they possibly hire this nurse?” After a second nurse came in later to administer the WRONG medication to me, I really started to get nervous. Lucky for me, a different shift nurse came in and my experience shifted from “get me out of here” to “amazing”. How did this healthcare organization get hiring so wrong on the first 2 and right on 3rd? They aren’t alone. Let’s face it, as a customer – anywhere- retail, call centers, when was the last time you had an incredible moment with a brand that made you a customer for life? As an HR leader and employer, shouldn’t managing the workforce and driving a better customer experience be more than a roll of the dice and luck?
In a market where the “recruiter spends on average 6.25 seconds reviewing a resume” (Susan Adams Forbes) and focuses “80% of their time on Name, Current Title/Company, Start Dates and End dates and Education” it’s no wonder the “gut feel in hiring” is LESS accurate than a coin flip. Adding volume pressure in the market with marking the 13th consecutive month more than 200k jobs were created there are more positions to fill & develop and the expectation from senior leadership to get it right.
Drive down margins. Recruit & develop the best (And learn from mistakes). Drive better customer, patient experiences. (And let’s not forget navigating the teeth gritting frustrating complexities & change in ACA and more at the same time). How can HR leaders and the businesses they support leverage insights in their changing workforce quicker, leaner, responsively and now; predictively?
Enter Predictive Analytics: The ability to take what happened in the past and find common relationships and factors (leveraging human behavior and neural networks) to model and predict the future and report back in analytics with recommendations for the future. It’s made its commercial mark in movies like “Moneyball” but the story of real depth in managing the workforce is just beginning. . Departments like Finance, Sales, and Marketing are already using predictive analytics. Now it’s HR’s turn. It’s more than past data reporting; it’s finding relationships to drive new views which like the weather report, help you forecast the future for your workforce and be considered in decision making. “People are very complex but they are not completely random. If we can get enough information about enough people in enough situations, patterns emerge that can predict what similar people will generally do in similar situations.” (Niel Nickolaison, CIO, OC Tanner)
Many HR Leaders may not be skilled in depth of analytics (much less predictive) but they do know the pressure of what the organization needs expressed by their business partners. I recently consulted with a national retailer whose CHRO, knows what it’s like to fight hard to get the seat at the table, and then find contemporary strategies to constantly prove value in that seat. It’s more than throwing “shiny software toys in the market” claiming to be “everything” at them. This organization evaluated how to drive more customer experience in ensuring their HR charter was aligned to the business tightly before they sought out expertise in the marketplace. This served as their blueprint and charter in change.
1. What does the business need for insight on its objectives from HR?
In this case of the retailer, they needed specific ally to ensure growth of the company and expanding its brand nationally while controlling costs and not adding new costs. HR needed predictive insights to support the business competitively.
2. What are the specific HR insights that HR Team needs to support the business competitively?
- Recruit the top talent and make better hiring decisions.
- AVOID hiring poor performers (this was key)
- Drive down attrition and proactively head off flight risks of High Potential with communication, career planning (ensure succession strategies in place as fail safe)
- Provide insights into new markets and talent pools with wage analysis
- Combine non HR data to provide holistic “1 view of the world” with sales, forecast and talent
3. What is the depth and domain of the predictive insights needed to fulfill the goals of HR?
Data across all of the Human Capital Domains are needed to leverage including Pre-hire Networks & Assessments, HR, Payroll, Time, Benefits, Recruiting, Talent Management, as well as neural networks and the data science analysts. The more data across the domains, with more qualified algorithms, combined with better historical modeling the better the impact with tangible yield. Better insights. Machine based learning is also key to avoid repeats of past mistakes.
The impact? Conservatively, assume this retailer can impact their attrition even minimally. “Even marginal improvements yield big savings.” Greta Roberts, CEO of Talent Analytics. “Sometimes when people hear “predictive” they think that every prediction needs to have 100% accuracy or “it doesn’t matter”. When you are predicting outcomes relating to people you look for predictions that are better than a random occurrence and better than your results today. A conservative retail example of a mid-sized retail store operation with 1,000 sales associates, and 67% annual attrition and a replacement cost of $3328 per sales associate. That’s 670 new hires a year, or about $2.2 million a year in replacement costs. Using predictive analytics to reduce attrition by just 7% – (to 60%) means they hire 70 fewer reps and save a $232,960 the first year. Additional real ROI comes when the new sales associates have a higher lifetime value, since they will last longer in the role.”
Ah ha! Now valuable data points across all of the Human Capital drive insight and pave the way for future actions. It’s making these insights actionable that makes them real. So how does an HR leader start this analytics endeavor successfully? Ask yourself and brainstorm:
1.) What am I trying to solve for the business in HR?
2.) What is the depth & domain of the data required?
a. Who can cleanse & normalize the data? (not sexy, but necessary & requires expertise)
b. Need data science support to frame algorithms and modeling
3.) Evaluate results and refine as necessary & Continue to evaluate results to change as needed in the future (behavior is not static!)
“Start with the Questions…No start with the DATA.” (Holger Mueller, VP & Principal Analyst at Constellation Research) To this point, start with aligning the charter of HR to the business objectives. It’s not about software… It IS about expertise in insight. Once you blueprint, leverage your network and learn. Reach and connect with mentors to help. Support is critical to understand how an organization can embrace predictive in HR in an agile way and drive tangible results. And you don’t want to be left behind.
So I’m back and running hard now after my health challenge, and you can imagine, filled out my health care patient survey my hospital sent me. Past tense though. They can take this historical information as a rear view window perspective. Perhaps they can predict where I am going next for my future health care? J
In the meantime, now you understand my brand loyalty to my preferred retailer. #CustomerForLife
photo credit: Wrapping one’s head around the data via photopin (license)
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