Workforce Analytics Optimizes Human Capital
Most companies spend copious amounts of time evaluating the performance of their investments in areas such as R&D, capital equipment and even sales and marketing, but they never analyze investments into what is probably their greatest area of expense: human capital. For services firms, this may comprise 85 to 90 percent of total costs, workforce analytics and even for manufacturing firms, human capital costs are often twice as high as other capital costs.
The last few years have been strategy-altering for companies struggling to survive in the recession, as many have been forced to reevaluate the basics in order to run lean and stay ahead of their competition. Cost sensitivity has been a core survival tactic. In that type of environment, can your organization afford not to pay attention to human capital costs? The issue is no longer whether to focus on the returns of investment in human capital; it is how to measure it.
Traditionally, workforce-related decisions have been subjective and involved little involvement from IT. The lack of easy access to data, combined with the dearth of in-house analytical resources become a barrier to more objective decision-making in workforce planning and management. With more organizations feeling the increasing need to quantify workforce costs and benefits and integrate workforce initiatives into their overall financial planning process, many organizations are paying increased attention to this type of analytics work. Any organization, regardless of size, that agrees with any of these statements could benefit from taking a data-driven, analytics-based approach to its human capital strategy:
Hiring expenses are on the rise due to increased or unanticipated employee attrition.
Even though employee turnover seems to be low, the people leaving are top talent.
Umbrella retention strategies are in place but not generating the desired results.
Substantial budget outlays for training are made, but management is unsure which areas to focus on.
Hiring budget is across several channels and vendors – but management is unsure which ones are cost-effective.
Operations centers struggle with staffing at an optimal level to meet service-level commitments.
Performance and talent management could benefit from more objectivity in the process.
The ultimate objective is to sync human capital strategy with business strategy.
Organize, Structure, Analyze and Optimize
Getting started is often the most daunting part. The first step is to identify all the relevant data. A typical progression is: organize, structure, analyze and optimize.
Many organizations find themselves with employee data, hiring data, compensation data, training data and contact center data sitting in isolated and incompatible platforms. The journey toward data-driven decision-making in workforce management starts with organizing the data sources in accessible data warehouses and data marts. This is followed up with structuring the information around established metrics and key performance indicators that help provide an understanding of the pulse of the HR organization.
A snapshot view of the metrics measured against industry benchmarks can identify areas of improvement, whereas tracking trends over time shows early warning of problem areas. For instance, if trends show seasonally low attrition rates around the holiday season, a sudden spike around the months of November/December should trigger further exploration into the matter. Tracking such trends also helps address issues proactively – if seasonal trends show higher attrition during certain periods, human resources can plan ahead and boost retention and recruiting efforts in the preceding months. A monthly dashboard with an organization’s top KPIs is an excellent way to keep a health check on the workforce and the performance of the HR organization. Those KPIs should be related to the top HR functions, such as resourcing, compensation and benefits, operations and business support.
Customer Analytics Parallels Workforce Analytics
Performance gaps identified through the regular reporting of such metrics or deviation from past trends often trigger the need for more advanced and sophisticated analysis. The advancements made in statistical and econometric modeling, and optimization in the areas of marketing, credit risk and finance can be easily adopted and applied to modeling workforce issues. It is appropriate to consider an employee as a customer in an internal environment. Hence, all the analytics that apply to a customer life cycle can easily be applied to an employee life cycle – from acquisition, to growth, to retention, to post-attrition to reacquisition.