The opinions expressed by Entrepreneur contributors are their own.
Have you ever waited for a package longer than expected? You’ve experienced the proverbial “last mile” problem. A package hurtles across the country, but then somehow gets stuck at the post office a few blocks from your house: so close, but still out of reach.
To borrow a term from the logistics field, HR departments also have a “last mile” problem, and it’s just as frustrating. Companies are generating more data than ever about people – insights into everything from how employees work best to ways to increase retention – but this information 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 it often takes weeks before someone can calculate industry averages and cross-check employee specifics. In a rapidly changing economic environment where there is little competition for top talent, companies cannot afford such delays, which can end up impacting their bottom line.
Related: A practical guide to increasing startup success through data analytics
This delay reflects a broader slowness in getting people’s data into the right hands. A recent global survey found that approximately three in four companies are driving business innovation through data. But fewer than half have created a data-driven organization, the key to gaining insights into people, their most valuable asset.
As the co-founder of a company that helps businesses use people’s data to drive results, I know there’s a better way. Here’s why the last mile problem exists and how companies can solve it to ensure timely delivery of impactful HR data.
What’s behind HR’s last mile problem?
The fundamental reason why HR data doesn’t travel the last mile is that it languishes in silos.
Essentially, there is a wall between HR and the rest of the company. Many HR departments hoard their employee data, as it is personal and confidential. In large companies, this silo problem also occurs within HR itself. Recruiting, talent management, compliance, learning and development, compensation – they all have their own data fiefdoms.
To make matters worse, that data may not be very meaningful to anyone except HR professionals. Even when it is shared, it often lacks context and is difficult to interpret. This is partly because it is full of HR jargon, not framed in the language spoken by the rest of the company. Don’t know what usage analysis is, or duvet, or negligent referral? You are not alone.
Even familiar concepts like turnover rates can be confusing or misleading in the absence of context. HR may report that your department has a 10% turnover rate. It sounds terrible, but is it really? How does it compare to competitors? Does it affect revenue or performance? The underlying problem: Data is shared in HR language, not business language.
Companies that lack the ability to connect HR data with business impact risk being left behind. Over three years, companies 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
Overcoming the final HR hurdle requires both cultural and technological change.
Culturally, HR leaders need to be educated on the idea that using people analytics does not mean sharing personal information – far from it. In fact, the data in question can be easily aggregated and made anonymous, so nothing sensitive is disclosed.
It is also essential to convey the message that HR’s contribution can and should go well beyond compliance and administration. After all, people are a company’s most important line item and greatest asset. HR is ideally positioned to help connect the dots between talent and results.
Technology can also help, especially when it comes to putting the right information 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 front-line managers, many of whom don’t have the time, training or inclination to sit down and crunch the numbers.
The good news is that new generative AI technology is finally helping to unleash that data. Using the latest tools, managers can quickly find the answers they need by asking a question in plain English. Is an employee paid fairly? Instead of focusing on a dense graph or waiting for a data analyst to intervene, managers can get answers in real time, with data specific to their company and the employee in question, along with industry benchmarks.
Ultimately, the best companies find ways to integrate people data into the rhythms and routines of everyday company culture. Instead of quarterly releases, they share information with decision makers on a consistent basis, both weekly and monthly. They are selective, tailoring reports to the department or business needs in question, and putting the data in context by telling the story behind it in business language. If revenue is 10% this year, what does this number mean for the company and how does it stack up against the competition?
Related: Using data analytics will transform your business. That’s how.
The reward for closing the last mile
When people’s data gets where it needs to go, quickly, the entire organization benefits.
HR can now focus on the art of the profession rather than time-consuming, repetitive requests for information that can easily be handled by analytics tools. This means fewer hours spent on admin, compliance and tickets and more time for the people who lead the business.
Managers get the information they need when they need it. For example, they can use people analytics to find out who is most likely to leave the company before it actually happens. Thanks to today’s generative AI tools, which many executives see as boosting profits, it’s no longer a guessing game. Ask and get a direct answer on individual employee engagement levels based on data pulled from chat, email, calendars and other workplace apps.
For the business at large, solving the last-mile HR problem equates to a seismic shift in efficiency and performance. Talent decisions can be made in real time, not with months (or even years) of delay. Best guesses and instincts give way to data-backed intuitions. Ultimately, the ability to draw a straight line from people to business results increases customer satisfaction, employee retention and profits.
Of course, we’re not there yet. Institutional biases persist: from HR’s warehouse mentality towards data to front-line managers’ aversion to being analyzed and judged.
Distrust of AI is another potential obstacle, especially in the context of privacy and disinformation, where the right guardrails are essential. (At my company, for example, we perform ethical testing on our generative AI tools to ensure their guidance is free of racial and other biases.)
Ultimately, however, the solution to HR’s last mile problem is within reach. We have the data. We have the tools to share it safely and responsibly. Now is the time to put it in the hands of the leaders who need it most.