Human capital analytics has evolved from a patchwork of studies and processes into an important organizational function. As a tool for evaluation, return on investment has evolved from an isolated activity to an important tool for accountability, driven by top executives. So what’s the connection?
Some analysts suggest any type of analysis that helps to understand, support or improve human capital programs is an analytics project. However, it is helpful to think of projects in five different, but related, categories.
1. Convert data to money. Executives need to understand the value of business measures. One of the best ways to understand value is to convert data to money. If engagement needs to increase, executives want to know the monetary value of the increase. If something needs to be eliminated or prevented, executives want to know each item’s cost to understand the magnitude of the problem. Measures such as absenteeism and turnover are easily converted. Engagement, ethics, teamwork, stress, networking and reputation may require a more advanced analytics process.
2. Show relationships and causation. This type of project requires understanding the relationship between variables and usually involves correlation and regression analysis. For example, an executive may ask, “Does increasing employee engagement increase the likelihood employees will work safely, be more productive or reduce errors?” Analysis for answers to these questions requires correlation and a causal relationship. Typical correlations include job satisfaction and retention, job satisfaction and customer satisfaction, engagement and productivity, and engagement and quality.
3. Apply predictive models. These projects are an extension of the relationship category. Typical predictive relationships in organizations include: recruiting sources predict retention, selection tests predict safety performance, and health risk status predicts absenteeism.
4. Conduct impact and ROI analysis. The most common analytics project involves calculating ROI — including reaction, learning, application and impact — for a specific human capital program. Impact and ROI studies are usually reserved for projects that are expensive, important and command executive attention such as recruiting/selection, learning/development and change management/culture. Most analytics projects lead to solutions.
5. Forecast ROI. With major projects or programs, it is helpful to understand the potential payoff before they’re implemented, and compare it with the solution’s proposed cost. Forecasting should be as accurate as possible so the forecast can be used to make decisions. If a forecast is conducted, a follow-up ROI evaluation is necessary for validation. Some major programs often subjected to forecasting are: flexible work systems, new compensation arrangements, leadership development and change projects.
ROI is the ultimate evaluation. In discussions with the executives who fund human capital programs, the focus often evolves to the ROI issue. For example, an organization has invested a tremendous amount of money on employee engagement, which is measured with a survey. Executives ask, “What is the value of having more engaged employees?” This question suggests executives are interested in the monetary value, a Type 1 analytics project.
To answer the question, engagement owners may connect engagement to an easy-to-value measure, such as gross productivity, which can be defined as revenue per employee. If engagement moves from a lower level to a higher level, the gross productivity movement can be pinpointed. This is a Type 2 analytics project. If the relationship is operationalized after testing and validation, this is now a Type 3 project.
The next question is, “So what is the ROI?” Answering this question requires comparing the monetary benefits of improvements with the fully loaded cost of the engagement solution. This ROI analysis is a Type 4 human capital analytics project. If an ROI forecast is needed before implementation, this is a Type 5 project.
All roads lead to ROI.
