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Advancing analytics from insight to action

Navigating the course

While HR functions have long used analytics to understand factors such as hiring, attrition, and engagement that approach is seen by Pathfinders, individuals we interviewed that are putting bold people strategies at the heart of their decisions in the KPMG The future of HR: From flux to flow report, as simply a baseline. Rather than tracking standalone metrics, they are building the value chain required to undertake relational analytics and turn existing insights into tangible action.

Pathfinders have also invested in technology and talent to ensure that insights are connected across the business so they can be interpreted accurately and acted on swiftly. Pathfinders go out of their way to correlate findings in one area to another—bringing disparate datasets together to investigate multiple, often complex underlying factors to properly understand a problem, so as to truly understand the business and their people.

The result for Pathfinders is a strong link between data and decision-making. Interestingly, for our survey respondents,1 36 percent say delivering predictive insight and business value will be a priority in the next few years. Worryingly, only 17 percent ranked analytics first when asked what they are best placed to deliver. This may explain why 53 percent are investing in analytics platforms for their HR function in the next few years, although 38 percent are not.

Workforce analytics can be used throughout an enterprise when considering human capital decisions. Which types of data do you use when making human capital decisions?

Workforce analytics can be used throughout an enterprise when considering human capital decisions. Which types of data do you use when making human capital decisions?

Source: KPMG, The future of HR: From flux to flow, November 2022

Bypass the barriers

As important as analytics is to HR functions, data quality, HR capability, and functional integration are all potential barriers to making the best use of it. Data may be unclear, unavailable, or fail to be translated from raw source to valuable insight.

From data to insight to action—navigating the rapids

According to Matt Yerbury, a workforce analytics leader in financial services, who contributed to this year’s Pathfinders research, says Pathfinders see analytics as a value chain. That value chain, in his experience, typically consists of five parts.2

The right questions

Understanding exactly what business units need to know is the first step in ensuring that analytics are produced with real commercial value.

Relational analytics

The future of workforce analytics is relational, looking at the multiple factors behind a trend, issue, or problem by combining datasets to reveal deeper insights.

Rich presentation

Setting out the narrative behind the data gives decision-makers an emotional connection to it and a clearer understanding of the actions to take.

Agile execution

Playing back findings is not the end of the analytics value chain. The next stage is to move from insight to action.

Robust data integrity

A workforce analytics team’s “license to operate” is based on trust. Employees must trust that the team is doing the right thing by them and the business, and treating their data securely and confidentially.

Ensuring that integrity will demand:


Strong data governance and ethics frameworks including a data ethics committee


Transparent communications to let people know what is being done with their data, and the governance measures in place to protect it


Careful consideration and internal conversations about how to handle the data required for each new project


Approval to use the data from the relevant data owners within the business


Using the data in an ethical way for the purpose in which it was shared, transparently, and held securely

Without that level of integrity, workers won’t feel comfortable disclosing their data, which means HR can’t provide meaningful insights. Reflections to consider:


How does people data flow in the context of wider organizational data to support decision-making?


Is there an established relationship in the HR function between data and decision-making?


How is the HR function integrating non-people data into its decisions?


Does the HR function promote relational analytics, both internally and with the business units it serves?


Are HR colleagues aware of what relational analytics is about and how they can be analyzed?


Is the HR function clear on where there are data gaps to support decision-making and does it have a connected plan across the enterprise to address this shortfall?


Can HR clearly articulate the value chain of using analytics in its decisions and how HR data then informs the value chain of the wider organization?


Does the HR function have the capabilities to maximize the analytics available to it and is it investing in those skills internally?


Is the HR function investing in the capabilities of others in the business to gather, challenge, and interpret analytics so it flows throughout operations?


Considering trends—does the HR function lead by example on this? Especially on environment, social, and governance-related metrics like diversity, equity, and inclusion?

For further reading, download the full report: The future of HR: From flux to flow


1,2 KPMG, The future of HR: From flux to flow, November 2022

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