Here is an excerpt from an article written by Marcus Buckingham and Ashley Goodall for Harvard Business Review and the HBR Blog Network. To read the complete article, check out the wealth of free resources, obtain subscription information, and receive HBR email alerts, please click here.

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At Deloitte we’re redesigning our performance management system. This may not surprise you. Like many other companies, we realize that our current process for evaluating the work of our people—and then training them, promoting them, and paying them accordingly—is increasingly out of step with our objectives.

In a public survey Deloitte conducted recently, more than half the executives questioned (58%) believe that their current performance management approach drives neither employee engagement nor high performance. They, and we, are in need of something nimbler, real-time, and more individualized—something squarely focused on fueling performance in the future rather than assessing it in the past.

What might surprise you, however, is what we’ll include in Deloitte’s new system and what we won’t. It will have no cascading objectives, no once-a-year reviews, and no 360-degree-feedback tools. We’ve arrived at a very different and much simpler design for managing people’s performance. Its hallmarks are speed, agility, one-size-fits-one, and constant learning, and it’s underpinned by a new way of collecting reliable performance data. This system will make much more sense for our talent-dependent business. But we might never have arrived at its design without drawing on three pieces of evidence: a simple counting of hours, a review of research in the science of ratings, and a carefully controlled study of our own organization.

Counting and the Case for Change

More than likely, the performance management system Deloitte has been using has some characteristics in common with yours. Objectives are set for each of our 65,000-plus people at the beginning of the year; after a project is finished, each person’s manager rates him or her on how well those objectives were met. The manager also comments on where the person did or didn’t excel. These evaluations are factored into a single year-end rating, arrived at in lengthy “consensus meetings” at which groups of “counselors” discuss hundreds of people in light of their peers.

Internal feedback demonstrates that our people like the predictability of this process and the fact that because each person is assigned a counselor, he or she has a representative at the consensus meetings. The vast majority of our people believe the process is fair. We realize, however, that it’s no longer the best design for Deloitte’s emerging needs: Once-a-year goals are too “batched” for a real-time world, and conversations about year-end ratings are generally less valuable than conversations conducted in the moment about actual performance.

But the need for change didn’t crystallize until we decided to count things. Specifically, we tallied the number of hours the organization was spending on performance management—and found that completing the forms, holding the meetings, and creating the ratings consumed close to 2 million hours a year. As we studied how those hours were spent, we realized that many of them were eaten up by leaders’ discussions behind closed doors about the outcomes of the process. We wondered if we could somehow shift our investment of time from talking to ourselves about ratings to talking to our people about their performance and careers—from a focus on the past to a focus on the future.

We found that creating the ratings consumed close to 2 million hours a year.

The Science of Ratings

Our next discovery was that assessing someone’s skills produces inconsistent data. Objective as I may try to be in evaluating you on, say, strategic thinking, it turns out that how much strategic thinking I do, or how valuable I think strategic thinking is, or how tough a rater I am significantly affects my assessment of your strategic thinking.

How significantly? The most comprehensive research on what ratings actually measure was conducted by Michael Mount, Steven Scullen, and Maynard Goff and published in the Journal of Applied Psychology in 2000. Their study—in which 4,492 managers were rated on certain performance dimensions by two bosses, two peers, and two subordinates—revealed that 62% of the variance in the ratings could be accounted for by individual raters’ peculiarities of perception. Actual performance accounted for only 21% of the variance. This led the researchers to conclude (in How People Evaluate Others in Organizations, edited by Manuel London): “Although it is implicitly assumed that the ratings measure the performance of the ratee, most of what is being measured by the ratings is the unique rating tendencies of the rater. Thus ratings reveal more about the rater than they do about the ratee.” This gave us pause. We wanted to understand performance at the individual level, and we knew that the person in the best position to judge it was the immediate team leader. But how could we capture a team leader’s view of performance without running afoul of what the researchers termed “idiosyncratic rater effects”?

Putting Ourselves Under the Microscope

We also learned that the defining characteristic of the very best teams at Deloitte is that they are strengths oriented. Their members feel that they are called upon to do their best work every day. This discovery was not based on intuitive judgment or gleaned from anecdotes and hearsay; rather, it was derived from an empirical study of our own high-performing teams.

Our study built on previous research. Starting in the late 1990s, Gallup conducted a multiyear examination of high-performing teams that eventually involved more than 1.4 million employees, 50,000 teams, and 192 organizations. Gallup asked both high- and lower-performing teams questions on numerous subjects, from mission and purpose to pay and career opportunities, and isolated the questions on which the high-performing teams strongly agreed and the rest did not. It found at the beginning of the study that almost all the variation between high- and lower-performing teams was explained by a very small group of items. The most powerful one proved to be “At work, I have the opportunity to do what I do best every day.” Business units whose employees chose “strongly agree” for this item were 44% more likely to earn high customer satisfaction scores, 50% more likely to have low employee turnover, and 38% more likely to be productive.

We set out to see whether those results held at Deloitte. First we identified 60 high-performing teams, which involved 1,287 employees and represented all parts of the organization. For the control group, we chose a representative sample of 1,954 employees. To measure the conditions within a team, we employed a six-item survey. When the results were in and tallied, three items correlated best with high performance for a team: “My coworkers are committed to doing quality work,” “The mission of our company inspires me,” and “I have the chance to use my strengths every day.” Of these, the third was the most powerful across the organization.

All this evidence helped bring into focus the problem we were trying to solve with our new design. We wanted to spend more time helping our people use their strengths—in teams characterized by great clarity of purpose and expectations—and we wanted a quick way to collect reliable and differentiated performance data. With this in mind, we set to work.

A version of this article appeared in the April 2015 issue (pp.40–50) of Harvard Business Review.

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Here is a direct link to the complete article.

Marcus Buckingham provides performance management tools and training to organizations. He is the author of several best-selling books and the forthcoming StandOut 2.0: Assess Your Strengths, Find Your Edge, Win at Work (Harvard Business Review Press).

Ashley Goodall is the director of leader development at Deloitte Services LP, based in New York.