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Have you ever waited longer than you’d hoped for a package? You’ve experienced the proverbial “last mile” problem. A parcel zips all the way across the country, but then somehow, it gets stranded at the post office a few blocks from your home — so close, but still out of reach.
To borrow a term from the field of logistics, HR departments have a “last mile” problem, too, and it’s just as frustrating. Companies are generating more people data than ever — insights about everything from how employees work best to ways to boost retention — but that intel isn’t getting into the hands of the managers who need it most when it’s needed.
For example, let’s say a manager needs to know what kind of raise to give a valued employee. The clock is ticking. HR has relevant data, but often, it takes weeks for someone to tally industry averages and cross-reference the employee’s specifics. In a fast-moving business environment where competition for top talent is scarce, companies can’t afford such delays, which can end up impacting the bottom line.
Related: A Practical Guide to Increasing Startup Success Through Data Analytics
That lag reflects a broader sluggishness in getting people’s data into the right hands. A recent global survey found that about three out of four companies are driving business innovation with data. But less than half have created a data-driven organization, the key to unlocking insights about people, their most precious resource.
As the co-founder of a business that helps companies use people’s data to drive results, I know there’s a better way. Here’s why the last mile problem exists and how businesses can solve it to ensure timely delivery of HR data that makes an impact.
What’s behind HR’s last mile problem?
The fundamental reason HR data doesn’t travel that last mile: It’s languishing in silos.
Essentially, there’s a wall between HR and the rest of the company. Many HR departments hoard their people data, on the grounds that it’s personal and confidential. At large companies, this siloing problem even happens within HR itself. Recruiting, talent management, compliance, learning and development, compensation — all have their own data fiefdoms.
To make things worse, that data may not be very meaningful to anyone except HR pros. Even when it is shared, it often lacks context and is hard to interpret. That’s partly because it’s rife with HR jargon, not framed in the language the rest of the business speaks. Don’t know what utilization analysis is, or featherbedding, or negligent referral? You’re not alone.
Even familiar concepts like turnover rates can be confusing or misleading in the absence of context. HR might report that your department has a 10% turnover rate. Sounds terrible — but is it really? How does that compare to competitors? Is it impacting revenue or performance? The underlying problem: data is shared in the language of HR, not the language of business.
Companies that lack the ability to connect HR data with business impact risk falling behind. Over a three-year period, businesses that made sophisticated use of people analytics reported more than 80% higher average profits than their less data-savvy peers.
How to solve HR’s last mile problem
Getting over HR’s last mile hurdle calls for both a culture and technology shift.
Culturally, HR leaders need education around the idea that using people analytics doesn’t mean sharing personal information — far from it. In fact, the data in question can be readily aggregated and anonymized, so nothing sensitive gets divulged.
It’s also essential to drive home the message that HR’s contributions can and should go well beyond compliance and administration. After all, people are a company’s biggest line item and greatest resource. HR is ideally positioned to help connect the dots between talent and results.
Technology can help, too, especially when it comes to getting the right insights in the right hands. Believe it or not, many companies still rely on old-fashioned charts and spreadsheets to manage HR data. I’ve seen how this creates challenges for frontline managers, many of whom lack the time, training or inclination to sit down and crunch numbers.
The good news is that new generative AI technology is finally helping liberate that data. Using the latest tools, managers can quickly find the answers they need by asking a question in plain English. Is an employee being paid fairly? Rather than poring over a dense chart or waiting for a data analyst to weigh in, managers can get answers in real-time, with data specific to their company and the employee in question, along with industry benchmarks.
Finally, the best companies find ways to integrate people data into the rhythms and routines of daily company culture. Instead of quarterly blasts, they share insights with decision-makers on a consistent basis, whether it’s weekly or monthly. They’re selective, tailoring reports to the department or business need in question, and they put the data in context by telling the story behind it in business language. If turnover will be 10% this year, what does that number mean for the company, and how does it stack up against the competition?
Related: Using Data Analytics Will Transform Your Business. Here’s How.
The payoff for closing the last mile
When people data gets where it needs to go, fast, the entire organization benefits.
HR can now focus on the “art” of the profession rather than rote, time-consuming requests for information that can easily be handled by analytics tools. That means fewer hours spent on admin, compliance and tickets — and more time for the people who drive the business.
Managers get the information they need when they need it. For instance, they can use people analytics to find out who’s most likely to leave the company before it actually happens. Thanks to today’s generative AI tools, which many executives see as a profit booster, that’s no longer a guessing game. Ask, and you get a straight answer about individual employees’ engagement levels based on data pulled from chat, email, calendars and other workplace apps.
For the business at large, fixing HR’s last mile problem equates to a sea change in efficiency and performance. Talent decisions can be made in real time, not months (or even years) too late. Best guesses and gut instinct give way to data-backed insights. Ultimately, the ability to draw a straight line from people to business results boosts customer satisfaction, employee retention and the bottom line.
Granted, we’re not there yet. Institutional biases linger — from HR’s warehouse mentality toward data to frontline managers’ aversion to being analyzed and judged.
Wariness of AI is another potential blocker, especially in the context of privacy and misinformation — areas where the right guardrails are essential. (At my company, for example, we do ethics testing of our generative AI tools to ensure that their guidance is free of racial and other bias.)
Ultimately, however, solving HR’s last mile problem is well within reach. We have the data. We have the tools to share it safely and responsibly. Now, it’s time to get it into the hands of the leaders who need it most.
