Data analytics takes on workforce optimization

With budgets getting tighter, agencies are digging into their data to forecast workforce trends and improve decision making.

With the 2016 elections a few months away, government agencies throughout the nation are bracing for funding, program and leadership changes.

According to a May forecast by the Center for State and Local Government Excellence, the challenges of workforce management and planning are close to the top of the list of priorities agencies want to address.

Those include recruiting and retaining personnel, as well as succession planning and staff development, according to the Center, which said agencies continue to have difficulty recruiting for new positions, especially in the areas of IT, public safety and finance.

Consequently, part-time hiring is growing, with 41 percent of respondents in search of contract and temporary workers. Retirements are also on the rise, with 54 percent of respondents reporting that retirement rates were higher in 2015 than in 2014.

In confronting these shifts, the Center advocates agencies use a number of strategies, including deepening  their expertise in data analytics to forecast workforce trends and improve decision making.

Over the past decade, a handful of organizations have been developing new ways to help manage these workforce challenges now facing government.

The solutions include sophisticated analytics for workforce planning and optimization, software for streamlining access to operations data and compliance recordkeeping and innovative job-matching  tools to pick up the pace of economic development.

An eye on analytics

The Navy’s Sea Systems Command Program Executive Office Integrated Warfare Systems (PEO-IWS) wanted to shape its workforce in ways that would address its future integrated warfare needs.

Facing the challenges of an aging workforce and uncertainties about the availability of expert talent, PEO-IWS worked with the analytics software developer Decision Lens Inc. to create a recruitment and staffing strategy that factored in the reality of pending budget and manpower cuts.

The strategy helped to “create tools to help decide where we apply resources to tame complexity, avoid risks and execute efficiently,” according to the office.

Decision Lens CEO John Saaty describes the firm’s software as tool for establishing strategic priorities, selecting investments that most closely align to those priorities and then allocating resources for the “best bang for the buck.”

“The problem today is that most organizations are resource-constrained,” he said. “There are not enough resources to cover all of the mission needs, and so to understand how to allocate resources most effectively entails understanding different real-world scenarios --  whether you are in a federal organization such as the Navy, a state CIO or Department of Transportation.”

In addition to workforce optimization, the company also takes up staff allocation challenges, cases where an agency might have the funding to support a portfolio of IT projects but then not realize until two quarters out that it’s going to run out of project managers, Saaty said.

The Decision Lens concept was developed by Saaty’s father, Thomas Saaty, a noted mathematician who developed what he described as the “analytic hierarchy process.”

The idea called for putting objectives into a hierarchical format and having a group of stakeholders prioritize them through trade-offs to quantify the relative importance of one objective versus another. The process is powered by algorithms designed to optimize multiple resourcing scenarios and arrive at the one ensuring best outcomes and performance.

“So it’s not just, ‘here are the 10 things we’re trying to accomplish,’” Saaty said, “but in relative importance, how much more important is it that the Navy delivers reduced costs versus driving transformation, or whatever their objectives might be.”

The Defense Health Agency, which provides health care to the global military workforce, has been using the software to determine how best to use a relatively small budget for upgrading its worldwide facilities.

An aging facility in Surrey, England, for instance, had been drawing priority investments while the DHA installation in Landstuhl, Germany, one of the most advanced health centers in the world, was being allocated only a trickle of resources.

When the tool was used to reset DHA’s priorities to emphasize mission support, improving customer satisfaction and transforming services, officials found that Landstuhl warranted more investment and that Surrey should be closed.

The Animal and Plant Health Inspection Services has also used the Decision Lens analytics to make judgments on which of hundreds of projects to fund in while it readied the Department of Agriculture’s farm bill, legislation with implications for workforce staffing and research investment.

Lora Katz, APHIS national policy manager for the farm bill, said the Decision Lens tool offers a common approach to decision making.

“No matter what the decision you’re trying to make, what this systematic process does is force the group to develop a common set of criteria -- whether it be about selecting a person for a job… or selecting a project that would help support our mission protecting American agriculture,” she said.

“The common goal is developing a set of criteria that’s going to make a prioritization process possible.”

Today, the company’s analytics allow organizations to run out multiple scenarios and test assumptions to see how changes affect the outcomes. Saaty said he believes future innovations are likely to  bringing out predictive features and ways to accelerate the process.

Once a group has identified its priorities and the desired outcome,  we can “use our optimization algorithms in a predictive way to run through literally tens of thousands of scenarios quickly and tell you exactly what the portfolio of investments should look like and in what timeframes,” Saaty said.

It will, he said, “give you the most value as early as possible in the lifecycle for the least cost. That is coming soon.”

NEXT STORY: Tracking cancer in real time

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