Data-Driven Decision-Making Is Transforming HR


A recent post on the Management Concepts blog addressed the impact of data-driven analytics on the nature of human resources staffing. The focus on analytics and rising expectations about the potential benefits of big data is ratcheting up pressure on chief human capital officers (CHCOs) to expand the ability of HR to apply quantitative analysis to support decision-making. In terms of HR staffing, it’s likely to be transformative:

Introducing analytics to the Human Resources Line of Business (HRLOB) will require HR personnel with a set of skills that has not traditionally been part of the human resources function.


The post cites five key skillsets that increasingly will be sought in HR personnel:

  • Business acumen
  • Research/hypothesis design
  • Statistical analysis
  • Data reduction
  • Evaluating and presenting results of analysis

The ability to tie HR data and study results to core organizational performance metrics will be critical for successful implementation of HR analytics. While it’s one thing to design a research study, gather data, and analyze the results, making those results compelling by linking them to key performance indicators that are of interest to senior executives has not typically been in HR’s area of expertise. This skill requires business acumen.
Effectively using analytics to drive decision-making requires carefully formulated questions and a specifically designed data collection and analysis strategy that will yield actionable information. Therefore, HR practitioners need to understand how to design research studies to explain events within their organization. Additionally, the ability to calculate and appropriately interpret key statistical metrics such as measures of central tendency, as well as more advanced analyses such as correlations, t-tests, and analysis of variance, will be essential in correctly interpreting the results of analytic efforts. While there are countless tools available for managing large data sets, some effort and skill are still required to clean and filter noisy data streams so that analysis can focus on the best set of available data. Consequently, data reduction skills will be increasingly valued.
Along with performing the studies, HR personnel will need to be able to review the analyses performed by others and translate the results into useful and useable visual displays. This presentation skillset will be especially important for HR leaders who may not actually perform analyses, but will be the first-line consumer of analytic studies.
On another front, Human Resources Executive Online notes that one area strongly emerging from use of analytics is talent forecasting. Talent forecasting is a growing field where data-rich software is leveraged to help HR leaders better understand and address the supply-and-demand challenges within their organizations. The article cites five ways that talent forecasting is transforming recruiting:

  • Predictive analytics proactively pinpoint problems.
  • Recruitment must become part of integrated talent management.
  • Faster speed means quicker hires and less wasted time and resources.
  • Increasingly, big data will inform strategic workforce planning.
  • Talent acquisition is the single most important factor for revenue growth and profit. 

The author Lisa Hartley concludes: “These five advantages showcase how talent forecasting can provide human resources with data that will make long-term planning and the allocation of resources easier. Clearly, talent forecasting is much more than counting the number of employees—it's about understanding the business you want to be and using the technology we have today to find and deliver an effective workforce.”
This is data-driven food for serious thought.

Posted by Lisa Rickard, Senior Manager, Product Marketing for HCM at Epicor


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