Wanted: Analytics for Finance and HR

The old trope about business forecasts being outdated the second they are published has been around for decades, and it usually is received with a shrug or nod of agreement. But advanced analytics are disrupting the traditional forecasting model, and soon the notion of planning for the future in functional silos with limited data will be a thing of the past.

Cloud technology enables sophisticated and reliable modeling based on multiple sets of data, including third-party contextual data. An organization can now easily visualize what its future could look like—as well as multiple potential options for planning for that future.

If you work in finance, this means you and your team probably need to improve your ability to work with HR teams to support growth initiatives. Specifically, you will need to invest in the right technologies and develop more analytic skills so that the right talent and skills will be in place when needed.

HR analytics maturity varies

It’s important for finance to collaborate with HR because personnel costs often are a business’s highest expense, and hiring/retention plans often are based on financial forecasts. Fortunately, HR as a function is already experienced in analytics, and many HR teams use data not only to describe what has already happened, but also to predict future outcomes—such as which recruits may be most successful and which employees might be at risk of attrition.

In fact, in some ways, HR is ahead of its financial peers, based on a study of 1,510 HR and finance executives that Oracle conducted in late 2018.

HR analytics maturity ranges from “novice” status (i.e. We are able to determine which questions to ask) to prescriptive (i.e. We know what is likely to happen and what to do about it). Between those ends of the spectrum are diagnostic analytics (i.e. What has happened?) and predictive analytics (i.e. What will likely happen?).

HR professionals see themselves as fairly advanced, even if others disagree. About half of survey takers said their HR teams are highly skilled at using analytics, and more HR respondents reported using prescriptive and predictive analytics than finance respondents.

Additionally, more than 90 percent agree that:

• They can predict future workforce needs
• They can predict turnover in critical roles
• They have real-time career development insights

Despite this confidence, HR teams face challenges in collaborating with finance. Cultures and skills, rather than technology, pose the largest hurdles in HR-finance collaboration among those surveyed.

Analytics technologies and skills must be top priorities

HR practitioners might not be able to address these challenges on their own, but one area they can improve is communications about their analytics capabilities. The survey revealed a mismatch in assessment of analytics capabilities between HR practitioners and HR executives. Practitioners reported widespread use of predictive and prescriptive capabilities, but only 37 percent of executives said they have observed HR teams using these advanced types of analytics. Other research has found a similar gap in finance, with professionals ranking their own data skills much higher than senior leadership.

At the same time, 53 percent of HR pros still are using Excel spreadsheets for analytics. Cloud enterprise software is the No. 1 tool used, but spreadsheets come in second.

Spreadsheets might seem “easier” because of familiarity, but they are notoriously inaccurate and can weaken the quality of data used for decision-making. This downside is validated by what respondents said was the most difficult task to perform using their current analytics tool: “Making good decisions based on trusted data.”

Clearly, the future requires more sophisticated, cloud-based applications. 

Artificial intelligence (AI) is another area to focus on. AI is now HR’s No. 1 tool for talent insight, and the use of predictive insights is set to increase in the next 12 months.

• 52 percent of survey respondents use AI for modeling their talent pipeline.
• 53 percent use AI to identify at-risk talent with attrition modeling.
• 75 percent use AI to predict high-performing recruits.

AI makes it easier for HR and finance to collaborate because they can identify common goals based on objective, data-driven insights.

Jump the barriers to collaboration

HR and finance already partner on a wide range of strategic business analytics, from modeling workforce planning to attrition to productivity and the best areas for investment.

To capture the real power of analytics, though, both finance and HR professionals will need to sharpen management skills related to analytics and not just generation and review of data. The No. 1 analytics skills gap for HR that the research identified is “acting on data and analytics to solve issues,” while the No. 2 gap was “cultivating quantitative analysis and reasoning skills.”

C-level leaders and board members also have a role in improving HR/finance collaboration. HR respondents said the No. 1 barrier blocking this collaboration is a short-term focus on quarterly performance rather than future strategy. Lingering organizational silos and mismatched skills development also are hindering collaboration.

While HR and finance already work closely together, everyone involved still has work to do to keep these two functions in lock step as the use of analytics spreads and matures.

Get the full survey results. Download the research.