The assumption has always been that pay and, to a lesser extent, benefits, were the only variables to which most people in the workforce paid attention and were therefore the only ones on which companies needed to focus. It also helped that such metrics were captured in audited financials, which made them easier to manager and compare with others.
It was hard to argue if you were paying less than competitors but delivering superior results. And if you were paying more but delivering superior results, well, at least you could justify it for a time. At least until the ROI police arrived from the CFO's office and began demanding a reduction in the denominator, that reduction generally being people.
People might be an organization's most valuable asset, or so the hoariest business cliche goes, but when the CEO's compensation is on the line, more 'strategic thinking' is called for.
So it has come as both a revelation and a relief to learn that when it comes to designing compensation systems for the lean, mean contemporary organization, there are many more variables in play. At many of them dont cost much. If anything.
And even better, with more sophisticated analytical capabilities available, it is even possible to build them in, rather than creating an ad hoc nightmare that resided in an obscurely named file inside some manager's laptop.
The post-industrial service organization requires a broader set of skills, more responsibility and greater commitment to corporate strategy than they did in the past. As the following article details, those factors can now be identified, measured and managed. There may be objections from traditionalists, but what does that even mean when some of the most significant advances in corporate value creation are seven years old? Big data is creating opportunity for some who recognize it - and opportunity costs for those who do not. JL
Rachel Silverman reports in the Wall Street Journal:
Take it from the quant geeks—money can't always buy workers' love.
Companies armed with an array of analytic tools are changing the way they pay and keep their workers. Some of these data-driven findings seem counterintuitive: Rotely paying workers more may not be enough to prevent defections. The key may be a flexible work schedule, or simply a nicer boss.
Companies have for decades collected pay data about the industry and rival firms. But the analytics movement is going beyond simple comparisons and making much more complex decisions possible.
For example, a company wondering how to keep workers from jumping ship might gather data on retention rates, job satisfaction, work-life balance and career progress for hundreds or thousands of workers.
It then can build a model—controlling for such factors as employee tenure and pay relative to peers—to tease out causes of attrition, and whether a pay bump would make a difference.
Such predictive analytics "absolutely will change how people get paid and the structure of their compensation—how much is fixed, how much is variable, how much is here and now versus how much is backloaded," says Haig Nalbantian, a senior partner at consultancy Mercer, a unit of Marsh & McLennan MMC.
One of Mr. Nalbantian's Mercer clients, a large regional bank, had high turnover among its customer-service representatives and other front-line positions.
The bank gathered data on turnover, promotions, job changes and external pay to create a statistical model predicting why workers quit. Though the bank had used frequent pay raises to keep staff, the results showed that raising pay across the board by 10% might only shave a half point off the turnover rate.
Workers felt dissatisfied, not underpaid. More rapid job changes, even without promotions or corresponding rises in pay, made it much more likely that high-performing employees would stay, Mr. Nalbantian says.
Relatively few companies, especially smaller firms, do such deep analyses.
A recent study of 560 organizations by Mercer and human-resources professional association WorldatWork found that most companies—some 95%—remain focused on benchmarking pay, while 43% use some form of predictive modeling.
Number-crunching is easier said than done. Some human-resources departments lack the statistical talent to design and run, say, a multivariate regression analysis, which examines numerous data streams. A number of enterprise software vendors say they provide tools to automate data collection and calculations, but human intelligence is usually necessary to tease out which data are meaningful.
And companies can develop "analysis paralysis," spending so much time playing with models that they're unable to make decisions, warns Mollie Lombardi, vice president, human capital management at market-research firm The Aberdeen Group. Even the most carefully designed statistical models don't always match reality or fail to capture the real reasons behind a problem.
Caesars Entertainment Corp., the Las Vegas casino chain, likewise made counterintuitive discoveries when it set out to determine the effect of pay on retention. After analyzing pay and employee-engagement scores for about 5,000 workers who left the company, Caesars found attrition was as high as 16% for corporate employees who earned less than the midpoint of their salary range, says Sean Phillips, who directed the effort for the company.
Bringing an employee's salary up to the midpoint, the analysis found, reduced attrition to 9%. Going higher than the midpoint, it turned out, had no benefit.
With these insights, the company can now be "very surgical" in giving pay raises to its most prized workers, says senior vice president Emily Gaines. She can now identify high-potential employees at risk of leaving the company. Meanwhile, she can also make the case against paying others far above the midpoint.
Sometimes the numbers show that a pay plan doesn't pay off. Facing high turnover for early-career consultants some years ago, managers at accounting firm PricewaterhouseCoopers wanted to try a deferred-compensation plan, but had no proof it would work.
With the help of Alec Levenson, a workforce analytics expert at the University of Southern California, the firm found that touting the long-term financial benefits of staying at the company, along with finding ways to improve work-life balance—not deferred compensation—would lead to better retention.
0 comments:
Post a Comment