While some companies and employees may worry about the impact of analytics on measuring productivity, it's hard...
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to deny that analytics can be an effective tool for workforce management. It can help workers understand how they spend their time and how to become more efficient, and it can help companies understand how to apply resources to a project, or where to send technicians to service a customer account and when.
Workforce management is the practice of allocating staff resources most efficiently -- whether to a task, a project or for hiring more generally. Historically, the science of workforce management has been a guessing game, and it can benefit greatly from the realm of human analytics, which helps to quantify and measure the most efficient use of human resources.
These kinds of staffing allocations described above have less to do with monitoring workers' habits and productivity than they do with optimizing processes, logistics and number of staff applied to a project. But that's not to say concerns about Big Brother aren't valid, or that companies need to reassure workers that human analytics information will be used responsibly to optimize business operations, rather than peer into employees' tasks.
Companies may be hesitant to use human analytics in workforce management. But analytics can be a guiding light in evaluating and improving human performance. Here are some ways analytics can help organizations optimize the enterprise workforce.
Human analytics can help identify and acquire the best talent, then motivate and retain that talent once they're on board. This philosophy is called total rewards.
An optimized enterprise workforce begins with employees who are capable and effective from the start, then made better by analytics-driven processes and decision-making. The first step is attraction: presenting talented people in the marketplace with a compelling employment scenario that will not only encourage them to come aboard, but also to stay long term.
So, first, analytics can help organizations hire for specific skill sets, train and retain workers, and identify how to make them productive and efficient on the job. Notably, applying analytics to workforce management has proven benefits. A 2007 Harvard Business Review article noted, "Those organizations that invest more in talent management significantly outperform their competition across every measure of business -- including earnings per share, gross profit margin and market capitalization per employee."
In addition to increasing revenue and productivity, with analytics, it's possible for organizations of all kinds to create compensation packages that are role-specific within industries that are designed to attract not only specific talents, but specific personalities. Bringing new employees into the enterprise and having them stay is as much a question of personality fit as ability, and analytics makes it easier to get that right upfront.
Analytics can open a new door. Techniques like regression analysis can now isolate subtle performance indicators to generate new success metrics, and historical data can be cleaned up and mined for trial runs of those new metrics before they are deployed. Put simply, it's easier than ever to identify opportunities to reward employees for improved performance. And that reward can keep them motivated.
It's also easier to retain employees with analytics. Descriptive analytics -- in particular, a technique called principal component analysis -- can be used to define employees in social terms. It shows which sort of person performs most effectively with a team, who works best alone, as well as deeper traits, such as what style of leadership a particular group would be most responsive to, or even what group-meeting format might yield the best results for a team tasked with generating creative solutions.
An organization can expend effort to create an environment in which workers fit in well and feel positive about their surroundings, which helps retain employees. When people enjoy not only their work, but their co-workers and environment, they are more likely to stay.
This is just the beginning of what analytics can do to optimize an enterprise workforce. Finding and keeping good people is certainly the right start, but much more is possible. Analytics can be leveraged for effective teaming, measuring business impact of employee effort more accurately, teasing out the true drivers of performance and choosing between competing courses of action. Any one of these is an undertaking as rich as attracting and retaining good employees. These points underscore the idea that analytics is becoming an indispensable human resources tool within the enterprise workforce.
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