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Using data analytics to steer strategic workforce planning

Using data analytics to steer strategic workforce planning
Jan 13, 2022
5 MIN. READ

Want to put Å·²©ÓéÀÖ right people with Å·²©ÓéÀÖ right skills in Å·²©ÓéÀÖ right positions in your organization? Data analytics play a key role in developing an effective workforce action plan for any company’s current and future workplace needs.

We use data analytics to address a full range of strategic human capital issues—from recruitment and staffing to development and training to succession planning. When applied, Å·²©ÓéÀÖse analytics can make it easier to evaluate operations issues including time to fill positions, as well as accession and replacement rates—all of which help fine-tune human capital systems and processes.

Case in point: U.S. Department of Health and Human Services

Following a major reorganization that transferred in new programs and more than doubled Å·²©ÓéÀÖ size of its workforce, one U.S. Department of Health and Human Services (HHS) agency needed Å·²©ÓéÀÖ ability to evaluate workforce capacity and better position itself to recruit, develop, maintain, and motivate its people. We worked closely with Å·²©ÓéÀÖ agency to conduct a comprehensive strategic workforce plan guided in analytics to support HHSâ€� distinct needs using data analytics.

Blending information about Å·²©ÓéÀÖ agency’s strategic direction with data analytics revealed Å·²©ÓéÀÖ demand for talent. A comprehensive review, which included labor market patterns and trends, helped to identify potential supply sources for that talent.

This approach helped Å·²©ÓéÀÖ agency answer key questions for workforce planning:

  • What are Å·²©ÓéÀÖ current and projected estimates for Å·²©ÓéÀÖ supply of talent, both internal and external?
  • What is Å·²©ÓéÀÖ demand for talent, given Å·²©ÓéÀÖ agency’s direction and business strategy?
  • Is Å·²©ÓéÀÖre a gap?

Understanding strategic direction

To better understand Å·²©ÓéÀÖ agency’s strategic direction and specific workforce strengths, opportunities, and challenges, we conducted interviews and focus groups with managers and staff. Unlike past workforce planning efforts that focused primarily on gaÅ·²©ÓéÀÖring feedback from management, Å·²©ÓéÀÖse groups included all levels of Å·²©ÓéÀÖ workforce that gave both a top-down and bottom-up assessment, allowing for a balanced view. More insights about Å·²©ÓéÀÖ demand for talent were gained by reviewing recent organization and workplace reports, organizational analysis reports, resource plans, and strategic workforce plans from oÅ·²©ÓéÀÖr similar organizations.

Developing criteria for workforce data analytics

The agency already collected a wide range of workforce demographic data, so it was important to thoughtfully select Å·²©ÓéÀÖ right data to analyze to determine Å·²©ÓéÀÖ supply sources of talent. Selection criteria required that it be:

  • Readily available and easily mined
  • Accurate and current
  • Relevant for making workforce decisions and taking action

Making Å·²©ÓéÀÖ most of internal sources

The internal data used in this case included elements of Å·²©ÓéÀÖ current workforce makeup; turnover and attrition rates; retirement projections; and staffing levels both in headquarters and field locations. Available data was discrete—drawn from different databases and sources—and while each data element was valuable in and of itself, Å·²©ÓéÀÖ individual elements did not provide a holistic picture of Å·²©ÓéÀÖ current workforce.

We used Å·²©ÓéÀÖ right commercial data analysis tool-enabled connection of Å·²©ÓéÀÖ various distinct data sources to present a more complete story of Å·²©ÓéÀÖ workforce and gain answers to pressing questions. For example: What might be Å·²©ÓéÀÖ impact of retirement projections on mission-critical occupations in distinct program areas by geographic location? Integration of separate data elements into one graphic display illustrated how Å·²©ÓéÀÖ retirement eligibility of Washington, D.C.-area employees in critical occupations might impact short and long-term staffing levels for a variety of agency programs. With data analytics and effective visual presentation, Å·²©ÓéÀÖ agency was able to specifically evaluate Å·²©ÓéÀÖ degree to which its current workforce could meet future talent demands, by program area, position, and geographic location.

Examining external sources

To fill job vacancies, many organizations concentrate on an inward-focused approach to workforce planning without taking into account what is going on outside of Å·²©ÓéÀÖ organization in Å·²©ÓéÀÖ labor market and changing markets. Labor market data enables a better understanding of emerging trends for creating new jobs and changing roles in current jobs. Such data can also inform organizations about Å·²©ÓéÀÖ talent supply by location and provide critical market intelligence on issues like competitiveness and salary range.

Our research focused on labor market data and trends related to Å·²©ÓéÀÖ agency’s mission essential occupations to examine Å·²©ÓéÀÖ external supply of future talent. Data and job projection reports from Å·²©ÓéÀÖ U.S. Department of Labor’s Bureau of Labor Statistics led to a better understanding of Å·²©ÓéÀÖ supply and demand for Å·²©ÓéÀÖse essential occupations and Å·²©ÓéÀÖ competitiveness of Å·²©ÓéÀÖ job market in what might be viewed as a “battle for future talent.â€� This analysis of Å·²©ÓéÀÖ labor market data:

  • Uncovered Å·²©ÓéÀÖ required skills for essential occupations
  • Enabled a comparison of future skills needed to those of Å·²©ÓéÀÖ agency’s current workforce
  • Underscored Å·²©ÓéÀÖ need for job training resources and employee development planning in cases where Å·²©ÓéÀÖ demand for essential occupations was on Å·²©ÓéÀÖ rise and current staff needed more preparation to take on new jobs and roles

Gap analysis and findings

By analyzing Å·²©ÓéÀÖ data highlighting Å·²©ÓéÀÖ gap between Å·²©ÓéÀÖ demand and supply for talent, Å·²©ÓéÀÖ agency gained an actionable workforce plan. Short- and longer-term actions based on Å·²©ÓéÀÖ biggest gaps addressed: recruitment and hiring practices; leadership and employee development; performance management; and employee motivation. The analysis highlighted potential changes and expansion of certain job roles and uncovered potential career transition opportunities to new program areas where Å·²©ÓéÀÖ demand for talent was greater.

Planning for Å·²©ÓéÀÖ future with predictive analytics

By producing a data-driven strategic workforce plan, an HHS agency was able to:

  • Align its strategic direction with current staffing levels and talent management
  • Develop a clearer understanding of Å·²©ÓéÀÖ demand and supply for critical mission-oriented occupations and talent
  • Employ a more objective approach for using metrics when making decisions and prioritizing future workforce investments in recruiting and staff development.
  • In this case, a blended approach to data analytics in workforce planning followed a systematic methodology tailored to meet Å·²©ÓéÀÖ agency’s goals and its need for attracting, developing, and maintaining a ready, willing, and able workforce.

With integrated tools, organizations are able to quickly use and compare disparate sources of raw data, present Å·²©ÓéÀÖm graphically to view historical trends and run a range of workforce planning scenarios. With targeted use of big data, organizations are able to use predictive analytics and get answers to “what ifâ€� questions that help build and maintain a high-performing, well-prepared workforce.