Workforce Analytics Translates Rich Raw Data into Actionable Information

Most business organizations have a bounty of data available to them, and this is definitely true of healthcare organizations, who have rich resources from patient records to payroll to EHR records. As The Harvard Business Review writes, “The vast majority [of organizations] readily acknowledge themselves as ‘data-rich and information poor.”

Records may be stored in systems that don’t talk to each other, or they’re kept in a program whose analytical and predictive functionality is limited (Microsoft Excel is a common culprit here), or the data may lack enough “structure” to use.

However, if your organization can parse those piles of data to make use of them, the results can be spectacular. Beckers Hospital Review reports, for example, that intelligent scheduling platforms can analyze workforce data with enough sophistication to produce accurate staffing forecasts up to four months in advance. One company that implemented such a solution saw up to 7% year-over-year savings in labor spend, and “time savings of 7-15 hours per manager per pay period.”

Such benefits aggregate. Technology research and analysis firm Forrester Research says, “Predictive analytics can have a multiplicative model on the bottom line.”

But where do we start? How do we improve your workforce efficiency?

That question is always the starting point. Don’t approach healthcare workforce analytics from the standpoint of basic data management – that is, merely capturing, storing and presenting raw data. Instead, you want to leverage that data to produce beneficial outcomes.

Thus, it’s crucial to start with the goal in mind. Given that labor is the biggest spend in most health care organizations, you might want to take the time upfront to understand your situation and your workforce.

For example, is time- and labor-intensive scheduling an issue? If your managers spend an average of two to three hours daily on core staff scheduling to the exclusion of patient care, then yes, it’s an issue. Fortunately, a problem like that is prime territory for workforce analytics.