Why Workforce Efficiency Isn't Just Code for Layoffs | Entrepreneur

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When we see high-profile leaders in government and industry promising to boost efficiency, the automatic association might be that workforce efficiency equals cutting jobs. But that’s rarely the case.

Across-the-board layoffs are not, in and of themselves, a recipe for efficiency. In fact, they could lead to exactly the opposite: loss of high performers or critical talent.

That said, efficiency is having a moment — and for good reason. Companies are being buffeted by new tech, shifting tariffs, flagging productivity and inflation. In these uncertain times, finding ways to get more from your people is often a matter of survival.

At its core, efficiency is a nuanced concept, but an absolutely critical one. Too many businesses fail to understand and measure it. Getting more with less requires thinking differently and using data differently, with a little help from AI.

Here’s how companies can harness data to boost workforce efficiency the right way.

1. Start with why

Before a company does anything in the name of efficiency, it should look at the big picture. The key question: What problem are you trying to solve?

Efficiency means different things to different businesses, after all. One furniture manufacturer might have a goal to produce as many chairs as possible, while another decides to focus on quality over quantity.

But too often, the de facto goal of efficiency exercises becomes cost-cutting. Laying off 10% of your employees might yield short-term savings, but in the long run, it’s exceedingly hard to cut your way to better results.

Replacing high-potential talent can cost a business up to three times the outgoing worker’s salary. When businesses factor in the total cost of recruitment, training, time to proficiency for new hires and lost productivity, haphazard downsizing often emerges as the least effective path forward.

2. Understand the people and resources you actually have

Even after working in people analytics for more than a decade, it still surprises me how many organizations are in the dark about their own workforce. Many large companies struggle even to get an accurate headcount of permanent and temporary employees across different business units.

Meanwhile, businesses continue to define employees in terms of rigid “roles,” rather than thinking in terms of “skills.” Someone’s job title might say “customer support rep,” for instance, but their underlying skillset includes product knowledge, people skills, technical know-how, etc.

At a time when tech is changing jobs overnight, smart businesses are increasingly using AI to catalog employee skills and match them to new and evolving roles. Rather than laying off that customer support rep, for instance, they’re reskilling and shifting talent to sales or business development.

This approach yields clear dividends. Besides being more than twice as likely to place talent effectively, skills-based organizations are about 50% more likely to improve processes that maximize efficiency.

3. Connect people with business results

There is perhaps no more important and overlooked way to improve efficiency than this: bringing people and business data together.

People data is all the information about what employees do, such as their performance and contributions. Business data is all about how they work — metrics like sales figures, customer satisfaction and profitability.

At so many companies, this information remains siloed. HR is entrusted with people data, while finance, operations, and sales and marketing hoard business data. Only when a company breaks down those silos by combining people and work data does a true picture of its employees emerge.

Here’s a real-life example from Cartier, the luxury jeweler. For its hundreds of stores worldwide, the company integrated people data and point-of-sale data. That let it see which locations were performing better than others, plus each store manager’s training history. Knowing which sales training got the best results, Cartier could apply it where needed to improve efficiency.

Compared to their average peers, high performers are 400% more productive. That climbs to 800% for managers, software developers and other complex roles. By pinpointing the right people at the right time for the right job, a company can avoid blanket layoffs that could end up slashing precisely the wrong people.

4. Democratize access to data and insights

It’s hard, if not impossible, to improve efficiency if you’re flying blind. To make the right decisions, people and performance data need to be accessible, not just to VPs but to the frontline managers making key hiring decisions.

This is where so many organizations fall woefully short. Historically, workforce data has either been jealously guarded or else buried in spreadsheets and scattered across multiple systems. Even basic questions require waiting weeks, sometimes months, for analysts to crunch the numbers. Meanwhile, managers have been left to rely on intuition to make time-sensitive talent calls.

Making better decisions requires democratizing workforce data, while preserving privacy and security, and that’s where AI is proving a boon. Need to know who your top performers are by location? Which managers are most effective? How does employee engagement compare to industry benchmarks?

New AI tools stitch together data across disparate systems, pulling out insights in a matter of seconds. Dense jargon and spreadsheets are replaced by explanations in plain English. And much like a human analyst, the best tools make informed suggestions about what next steps could make the biggest impact.

5. Review results and adapt in real-time

Efficiency is not a one-and-done exercise. At a moment when companies are contending with rapidly changing business conditions (Tariffs? No tariffs? Your guess is as good as mine), workforce planning can’t simply be an annual event.

The better tack here is to take a continuous approach to assessing how many workers your organization needs to support growth, ensure profitability and achieve goals.

New dynamic analytics tools help companies do just that. By tracking workforce plans against what’s happening on the ground, they let management make adjustments in real-time so forecasts are constantly up-to-date. These tools also help HR and finance get on the same page by reviewing planned, forecasted and actual headcount costs and course-correcting when needed.

Another real-life example: Providence Healthcare recently found itself looking at turnover in key roles. Using past data to make predictions, it was able to identify a group of employees where the organization would at least break even by paying them more to stay — and, in some cases, would even save money.

By using the estimated costs of turnover and calculating the cost to adjust salaries in the targeted groups, Providence saved an estimated $6 million a year.

Nor are these results unusual. Taking a more dynamic approach to workforce planning pays off. In one study, businesses with robust workforce planning boosted productivity by up to 25% over two years.

For companies in today’s unpredictable business climate, improving workforce efficiency is a very real priority. But simply slashing and burning can create more problems than it solves. A data-backed approach, with some help from AI, is a surer path to efficiency gains.

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