As we have discussed in our two most recent posts here and here, data analytics can be a powerful tool that allows companies to determine whether they are spending their compensation budgets in the best possible way. This, in turn, opens up a variety of options for companies when it comes to managing that compensation budget, whether that involves keeping costs the same, cutting the compensation budget or making strategic increases to that budget.

A company looking to keep costs steady might use data analytics to reallocate the existing compensation budgets in ways that will improve business performance. In another situation, a company that needs to cut costs can use analytics in order to identify the potential impact of their compensation cost-cutting decisions in order to avoid unintended consequences of those decisions. Finally, companies that believe that additional compensation investments will increase business performance can use data analytics to identify the size of the necessary increase and to make sure its impact is focused on the right things.

“HR bringing that kind of information to a dialogue with the CFO is very important,” says Wendy Hirsch, a principal with Mercer’s workforce strategies group in Milwaukee. “You can articulate where an organization is currently and which of these three scenarios makes the most sense for the organization.” Once that compensation budgeting decision is made, companies can rely on ongoing monitoring of compensation and total reward spending using a business intelligence platform or dashboard that tracks key metrics.

But that is only the beginning. CFOs can work with HR and compensation professionals to improve the presentation of this information. “Although compensation professionals are used to analyzing data, they may not be as practiced in using more advanced analytics to tell a story with that analysis,” says Hirsch. “This is not about providing reams of paper and piles of tables and charts and graphs. It requires the ability to sift through that data to find and explain the key story in a compelling way.” It is this insight that gives senior management what they need to drive decision-making and action plans.

At this point, these analytics should be viewed as the result of a cross-functional effort. If the effort is limited to HR, any resulting recommendations may not be considered broad enough to guide strategic decision-making. However, if the CFO and other senior executives participate and contribute to this effort, the resulting analytics and insight are more likely to be viewed as far-reaching and relevant. “Just like evaluating capital investments or marketing dollars, companies can turn the same lens on their people costs,” says Hirsch.

Hirsch urges companies to take an evolutionary approach to data analytics in order to prepare the audience for receiving this insight. “Companies should work on bringing the organization along gradually to make sure that they can consume the information that is being produced,” she says. That could start with benchmarking before moving on to correlations and simulations and, ultimately predictive analytics.