Have you ever waited longer than you hoped for a package? You've experienced the proverbial “last mile” problem. A package makes its way across the country, but then somehow, it gets stuck at the post office a few blocks from your house—so close, yet out of reach.

To borrow a term from the field of logistics, human resources departments they also have a “last mile” problem, and it's just as frustrating. Companies are generating more people data than ever before—insights into everything from how employees work best to ways to promote retention – but this intelligence is not getting into the hands of manager who need more when 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 for someone to tally industry averages and correlate them with employee specifics. In a fast-moving business environment where competition for top talent is scarce, companies cannot afford such delays, which may end up affecting the bottom line.

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This delay reflects a wider slowness 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 fewer than half have created a data-driven organization, the key to unlocking insights about people, their most valuable 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 the timely delivery of HR data that makes an impact.

What's Behind HR's Last Mile Problem?

The fundamental reason why HR data doesn't travel that last mile: It is languishing in silos.

Basically, there is a wall between HR and the rest of the company. Many HR departments hoard their people's data on the grounds that it is personal and confidential. In large companies, this problem of silos also occurs within HR itself. Recruiting, talent management, compliance, learning and development, compensation – all have their own data fiefdoms.

To make matters worse, that data may not be very meaningful to anyone but HR professionals. Even when shared, it often lacks context and is difficult to interpret. This is partly because it is filled with HR jargon, not adapted to the language spoken by the rest of the business. Don't know what usage analysis is, or featherbed, or careless referral? You are not alone.

Even the concepts known as turnover rates can be confusing or misleading in the absence of context. HR may report that your department has a turnover rate of 10%. It sounds terrible – but is it really? How does it compare to the competitors? Does it affect revenue or performance? The fundamental problem: data is shared in the language of HR, not the language of business.

Companies that lack the ability to connect HR data to 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

Overcoming the HR last-mile hurdle requires a cultural and technological 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 easily aggregated and anonymized, so nothing sensitive is revealed.

It is also essential to send the message that HR's contributions can and should go beyond compliance and administration. After all, people belong to a company the largest item in the line and the greatest resource. HR is ideally positioned to help connect the dots between talent and results.

Technology can also help, especially when it comes to getting the right knowledge into the right hands. Believe it or not, many companies still rely on old-fashioned charts and tables to manage HR data. I've seen how this creates challenges for frontline managers, many of whom don't have the time, training or inclination to sit down and crunch the numbers.

The good news is that the new Generative AI technology is finally helping to 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 paid fairly? Instead of poring over a dense spreadsheet 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 standards.

Finally, the best companies find ways to integrate people data into the rhythms and routines of the company's daily culture. Instead of quarterly bursts, they share insights with decision makers on a consistent basis, whether weekly or monthly. They are selective, tailoring reports to the needs of the department or business in question and putting data into context by telling the story behind it in business language. If the turnover is going to be 10% this year, what does this figure mean for the company and how does it stack up against the competition?

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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 instead of simple, time-consuming requests for information that can be easily handled by analytics tools. That means fewer hours spent on admin, compliance and ticketing — and more time for the people running 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 one profit booster, this is no longer a guessing game. Ask and you'll get a direct answer about individual employee engagement levels based on data pulled from chat, email, calendars and other workplace applications.

For the business at large, fixing the HR 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 increases customer satisfaction, employee retention and the bottom line.

Granted, we're not there yet. Institutional biases persist—from HR's warehouse mentality toward data to frontline managers' aversion to analysis and judgment.

Beware of AI is another potential blocker, particularly in the context of privacy and disinformation—areas where proper guardrails are essential. (At my company, for example, we conduct ethics testing of our AI generation tools to ensure their guidance is free of racial and other biases.)

Ultimately, however, solving HR's last mile problem is quite achievable. 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.