data matrix

Better Workforce Planning: 3 Fixes for Data Glitches

There's a four-letter word on the lips of workforce planning professionals everywhere--data. Reliable and comprehensive data is crucial to workforce planning effectiveness, yet data issues are among the top challenges planning teams face. (And perhaps cause for the use of more colorful four-letter words.)

A new report from i4cp, Workforce Planning: Data Choices for High Performance (download a complimentary summary report now), explores the data frustrations workforce planning teams face, and it highlights some of the differences that characterize organizations that outperform their counterparts in the marketplace (based on revenue growth, profitability, market share and customer satisfaction).

The business and workforce planning professionals who participated in i4cp's recent Strategic Workforce Planning Survey confirmed that data problems are multifaceted, challenging planning teams in a variety of ways. Planners have many questions; these are three of the most compelling:

  • Can we access the workforce data we need?
  • Is our workforce data accurate?
  • Do we know how to interpret the data effectively?

Accessing data isn't easy

Organization-wide data access issues posed the greatest stumbling block for workforce planning teams, and that held true for high- and not-so-high-performers alike. Specifically, technologies that fail to share data effectively are impeding workforce planning progress -- and probably other business imperatives as well.

Workforce Planning Data Challenges

"Technologies that don't share data effectively across an organization make the production of analysis manual and time-consuming," observes Michael LeBrun, workforce planning & analytics manager at Toyota Financial Services, a provider of finance and insurance products to Toyota and Lexus dealers and customers across the U.S. He explains that manual systems add continuity and efficiency challenges because they require a high level of reconciliation to ensure data integrity.

Think that manual data collection is a thing of the past for most companies? Not so. Thirty-seven percent of survey respondents from HPOs said their workforce planning teams lacked access to automated workforce data. Even among those with automated data, nearly half said it wasn't integrated across the organization. Clearly, manual systems remain entrenched in many companies.

Of course, manual collection issues assume that organizations actually track data needed for workforce planning in the first place. That isn't necessarily so, either: Nearly a third of high-performers admitted that an overall lack of data affected their organizations' workforce planning capabilities.

Toyota Financial Services' data mart solution
LeBrun and his team overcame data-sharing and collection issues by creating a data mart (a centralized database) to consolidate information from disparate systems. Establishing a single data collection and storage point allowed his team "to begin creating an environment for direct access to post-reconciliation and real-time information." While he expects a new HRMS will further strengthen data capabilities, LeBrun says "the data mart will still need to fill the analytical gaps in the system."

Planners question data accuracy

If data does exist and workforce planning teams are able to access it, the next hurdle is accuracy. A third of survey respondents admitted that their organizations' workforce data wasn't reliable. i4cp's recent report, HR Analytics: Why We're Not There Yet, confirmed similar findings: about one in four respondents said they lacked confidence in their HR data, and nearly one in five said their organizations had no controls in place to assure data accuracy.

Accuracy extends beyond the is-it-or-isn't-it-correct conundrum. It also speaks to consistent understanding of data. Are definitions (what constitutes turnover, for example) uniform from one organizational department or function to the next? Getting buy-in for consistent definitions of data is often a fundamental step for workforce planning teams, challenging them to build and nurture cross-functional relationships.

Chubb's data accuracy solution
At the Chubb Group of Insurance Companies, an insurance and risk management provider, senior talent management specialist Brent Weiss takes care to ensure data accuracy. "I typically keep all of my data unrolled on the raw data spreadsheet and then do a lot of summarizing analyses on other sheets," he explains. "Similarly, in SPSS I would never transform an original data field onto itself -- I'd keep the original intact and create a new variable so I have the original record that I can refer to later if needed."

To ensure accuracy, Weiss encourages cross-functional collaboration and consistency in workforce data, too. "I always share the unrolled data with the business just so they can verify that the data is correct," he says. "It helps build credibility for the [workforce planning team's] analysis when managers feel confident in data accuracy."

The final piece of Chubb's data-accuracy approach is what Weiss describes as "a data cleaning effort" to identify and reconcile inconsistencies, duplicate entries, and other issues.

Workforce planning teams need data interpreters

Collection and accuracy questions about workforce data complicate planning teams' jobs. But there's more: Even if planners can get the information they require and the data is accurate, they need skills to organize, analyze and interpret the data. Moreover, workforce planning teams need competencies that enable them to perceive the stories behind the numbers and present them in ways that compel action. It's that final storytelling piece that connects the dots, empowering leaders to apply workforce planning outcomes to positively affect business decision-making.

Unfortunately, forecasting, analytical and statistical abilities are lacking on many workforce planning teams, according to i4cp's research. Further, teams say they have difficulty enlisting members with those capabilities -- the very skills needed to maximize the value of accurate workforce data.

i4cp's data interpretation solution

Creative and insightful interpretation of workforce planning data begins with team members who possess strong data-related competencies. Based on its workforce planning research, i4cp recommends these actions to help teams build their skills:

  • Assess existing skill sets of planning team members to identify capabilities and gaps.
  • Design learning opportunities to enhance the team's forecasting, analytical and statistical skills.
  • Recruit (internally or externally) new team members who possess advanced analytical and data-related skills.
  • Establish a development plan to deliver ongoing training in data-related skills and the latest practices in workforce planning

More information on data issues in workforce planning and the metrics high-performance organizations use in their planning initiatives is available to i4cp members in Workforce Planning: Data Choices for High Performance. Non-members are invited to download the complimentary summary report.

Carol Morrison
Carol Morrison is a Senior Research Analyst and Associate Editor with the Institute for Corporate Productivity (i4cp), specializing in workforce well-being research.