This Small Business Innovation Research (SBIR) Phase II project seeks to refine an algorithmic approach and develop prototype software for workforce optimization with a focus on diversity planning and management. This project is expected to achieve the following four major objectives: 1) further enhance and extend the core technology created during Phase I and endow it with added capabilities that will be valuable for marketability as well as effectiveness; 2) enhance external communications - the software must communicate effectively with the user and database systems. In Phase I, rudimentary communications were established. During Phase II, the system will be greatly enhanced to allow for more effective use; 3) develop software as a service architecture - for greatest market penetration, the software will be deployed via the web. The system architecture will be redesigned to accommodate this requirement; and 4) perform alpha-testing - internal and external testing is critical to releasing a high-quality product. The Phase II research will strengthen the technical aspects of the product while significantly improving its ease of use, producing a system ready to enter the market.
The commercial applications anticipated for the software system are to first enhance the performance of workforce diversity planning and then evolve to supporting the optimization of the entire workforce. The technology is expected to have a significant impact on the broader inclusion of under-represented talent in the workforce. We also expect the technology to lead to improved organizational performance by enabling better decisions in recruitment and retention of all employees. The software will permit an organization to model and simulate critical patterns between policies, programs, initiatives, as well as other factors such as practices and compensation. The impacts of this research include the potential to: 1) design a more effective approach (simulation/optimization) to diversity planning and workforce optimization, increase workforce diversity, capabilities, and performance; 2) support a significant social and economic initiative; 3) become appealing to attract investments as it significantly increases return and minimizes risk in diversity and workforce planning; 4) add to the body of knowledge in human resource management and decision sciences that may be leveraged to permit additional research and development.
Project Outcome Report SBIR funding from the National Science Foundation enabled OptTek Systems, Inc. to design and develop software for Strategic Workforce Planning. The original focus for the software was to support diversity planning but based on feedback from companies selected as prototypes, the software scope expanded to encompass enterprise strategic planning that includes diversity. We currently have two customers and are now marketing the software to more organizations. The following description provides an overview of the software. OPTFORCE OVERVIEW OptTek’s software for strategic workforce planning, OptForce, is based on a bottom-up approach to predicting talent behavior patterns. The simulation technology focuses on accurately predicting individual decisions based on demographic characteristics, as well as work-related and external stimuli. Individual behaviors are then aggregated into cohorts of interest so that large-scale effects can be analyzed. This approach is fundamentally different from traditional top-down or trend-based approaches used by most workforce planning tools in the market, and produces more statistically reliable results based on a careful model calibration and verification procedure. In addition to improved accuracy, OptForce enables the evaluation of the impact of alternative programs, benefits, and hiring practices on employees based on their unique set of attributes, the work environment, and the state of the economy. OptTek’s optimization system takes this process one step further, by enabling the planner to identify the best set of retention and recruitment programs, policies, benefits, etc. that are most likely to achieve the organization’s goals within budget. OptTek’s simulation optimization system provides an accurate predictive tool combined with a decision support system for producing optimal workforce performance. OptForce is unique in many ways. First and foremost, it is the only workforce planning tool on the market based on simulation and optimization. Because of that, the level of insight, accuracy and reliability that is delivered by the tool is unparalleled. It is also one of the only tools on the market that empirically measures the impact of HR programs on your workforce and can show a detailed view of how your workforce changes over time given a particular set of interventions. This allows our clients to determine the right portfolio of investments to make in order to achieve their goals. But OptForce can do much more than this, and can answer questions such as: How to tie workforce plans to long-range revenue targets and forecasts – and what to do if the forecasts change How to determine the resources a business unit will need based on how much revenue it generates How to achieve results at lower cost without sacrificing quality or service How to determine the best way to deploy or re-deploy resources across the organization How to deal with an aging workforce, competition for limited talent, and other scarcity / surplus concerns How to address changing government regulations This is just a sample of the insight that OptForce can provide. OptForce is also unique in that it projects answers based on client facts, and not just assumptions and benchmarks. It shows clients how confident they can be in the answers it provides, and helps frame the relative risk of decisions for the decision-makers. On a very practical level, it easily allows clients to examine multiple scenarios and determine the best options to meet their goals, and helps clients understand how to navigate the current turbulence in the economy. Most importantly, the application continuously learns and can re-calibrate itself to further improve its predictive capabilities based on new data and history that is introduced. No other tool on the market can do this and both the methods embedded in the tool and the tools itself are patent pending.
