Page 54 - GCN, Aug/Sept 2017

MANAGEMENT
Facing the challenges of an aging workforce and uncertainty about the availability of expert talent, PEO-IWS worked with analytics software developer Decision Lens to create a recruit- ment and staffing strategy that factored in the reality of pend- ing budget and manpower cuts.
Decision Lens CEO John Saaty described the firm’s software as a tool for establishing strategic priorities, selecting investments that most closely align with those priorities, and then al- locating 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 [understanding] how to allocate resources most effectively entails un- derstanding different real-world sce- narios — whether you are in a federal organization such as the Navy [or] a state CIO or Department of Transpor- tation.”
In addition to workforce optimiza- tion, the company also tackles staff al- location challenges.
For instance, an agency might have the funding to support a portfolio of IT projects and only belatedly realize that it’s going to run out of project managers, Saaty said.
Saaty’s father, noted mathematician Thomas Saaty, developed what he described as the “analytic hierarchy process,” and it forms the basis of the company’s approach.
The process involves putting ob- jectives into a hierarchical format and asking a group of stakeholders to prioritize them through trade-offs to quantify the relative importance of one objective versus another. It is powered by algorithms designed to
“The problem
today is that most organizations
are resource- constrained...and so [understanding] how to allocate resources most effectively entails understanding different real-world scenarios.”
– JOHN SAATY, DECISION LENS
optimize multiple resourcing scenari- os and arrive at the one that ensures the best outcomes and performance.
“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 military workforce, has been using the soft- ware to determine how to make the most of a relatively small budget for upgrading its worldwide facilities.
An aging facility in Surrey, England, for instance, had been drawing prior- ity investments while the DHA instal- lation in Landstuhl, Germany — one of the most advanced health centers in the world — was getting only a trickle of resources.
When officials used the tool to reset DHA’s priorities to emphasize support- ing the mission, improving customer satisfaction and transforming services,
officials found that Landstuhl warranted more investment and Surrey should be closed.
The Agriculture Department’s Animal and Plant Health In- spection Service used Decision Lens analytics to make decisions about which of hundreds of proj- ects to fund while it prepared the farm bill, which has implica- tions for workforce staffing and research investment.
Lora Katz, APHIS national policy manager for the farm bill, said the Decision Lens tool of- fers a straightforward 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 [of] protecting American agriculture,” she said. “The common goal is developing a set of criteria that’s going to make a prioriti- zation process possible.”
The company’s tool allows organi- zations to run multiple scenarios and test assumptions to see how changes affect the outcomes. Saaty said he be- lieves future innovations are likely to focus on predictive features and ways to accelerate the process.
In the future, once a group has identified its priorities and the desired outcome, it can “use our optimization algorithms in a predictive way to run through literally tens of thousands of scenarios quickly and tell you exact- ly what the portfolio of investments should look like and in what time frames,” Saaty said.
It will “give you the most value as early as possible in the life cycle for the least cost,” he added. “That is coming soon.” •
46 GCN AUGUST/SEPTEMBER 2016 • GCN.COM