Using Human Capital Analytics to Understand the Internal Customer, Before, During, and After a Crisis

This report will describe five areas of human capital where the use of data is critical in decision-making: productivity, health and wellbeing, engagement and rewards, ways of working and leading, and diversity & inclusion. Each section will describe common metrics before COVID-19, how the pandemic has changed how we collect data, and the potential long-term effects that will remain in place after the pandemic

During times of high stress, such as during the COVID-19 pandemic, there will be a sense of urgency to make decisions and a corresponding risk of acting without fully considering the consequences of those decisions. Substantial research has been conducted in decision-making effectiveness, and overwhelmingly, the research concludes that successful decision making requires the availability of information (specifically financial information) and its deployment in a variety of financial management techniques.

The target of most decisions during the COVID-19 pandemic have focused on human capital deployment – for example, how to:

· reduce staff size,

· increase staff size,

· keep employees safe from COVID-19,

· get technology to people working from home as appropriate,

· counsel employees in emotional distress,

· optimize productivity,

· get products made and delivered to customers,

· pivot the business model and associated human capital needs to stay relevant.

An accurate underlying assumption is In the absence of data, decision-making processes will be compromised. Given that most of the decisions made will impact employees and employee programs to respond to COVID-19, it is more important than ever to create and rely on human capital data. Human capital teams must be strategic in gathering and analyzing that data to inform decisions. Organizations that have base-line performance data from before COVID-19 may be positioned to better understand whether decisions made during and post-COVID-19 are achieving desired human capital performance and ultimately business outcomes. Even if base-line data has not yet been created, it is not too late to curate data from past performance so that you can “path-correct” going forward.

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