Looking Forward: How CFOs Can Leverage Data Analytics to Guide Their Companies

A recent Deloitte report finds high quality data is a top priority for a vast majority of business leaders, but deploying the right solutions is its own challenge. A recent webinar examines real-world examples of what digital transformation can achieve.

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As CFOs look to increase their companies’ competitive advantage in a rapidly shifting business environment, they’ll need robust data tools—including predictive analytics capabilities—to get a well-rounded financial picture of their organizations. 

Andrew Dinin, specialist leader at Deloitte, and Andrew Breimayer, consulting managing director at Deloitte, understand that need. In a recent webinar, they shared insights and use cases based on years spent implementing financial management solutions with their clients.

Still, Deloitte’s annual Human Capital Trends report suggests that many organizations have room for improvement when it comes to data management and analytics.

Breimayer, a cross-industry leader in Deloitte’s Workday Alliance practice who has been part of the Workday ecosystem since 2009, noted that 71% of the study’s respondents characterized high-quality data as a top priority. However:

  • Just 15% of respondents said they provide data to their line managers, so that they have the information needed to do their jobs.

  • Only 9% of respondents said they understand the talent dimensions that drive performance.

  • And, just 2% of respondents said they have an integrated data set they can pull from across HR and into other functions across the enterprise.

While noting that the survey results are specific to human capital management, Breimayer added, “It’s really a universal thought as we think about data analytics and why this is so difficult for organizations to identify.”

Speaking about the challenges organizations face when working with data analytics, Breimayer said most fall into four broad categories of sophistication:

  • Level 1 involves operational reporting, providing hindsight.

  • Level 2 involves advanced reporting to provide critical business insights.

  • Level 3 builds on those capabilities to provide strategic analysis, allowing for a forward-looking view.

  • Level 4 brings predictive analytics to the forefront.

Most organizations, Breimayer added, fall between the first two levels, and noted there is a “choke point” in moving beyond that tier. Doing so requires clients to manage organizational data in a way that allows them to pull ideas together and move further along the spectrum.

71% of survey respondents characterized high-quality data as a top priority, but just 15% said they provide their line managers with the data needed to do their jobs.

“If we take a look at where we've really seen success, we start with the foundation,” said Dinin, who is a Deloitte product lead for Workday Prism Analytics, Workday Adaptive Planning, and Workday People Analytics. “And the foundation really sets the stage for analytics and our data source framework.”

Dinin, whose teams also specialize in data warehousing and business intelligence architecture, shared several smart uses of data and analytics he’s encountered while working with Deloitte clients. For example:

Financial Flash Reporting

Integrating statistics and metrics from different systems into Workday Prism Analytics to satisfy financial flash reporting—which provides an instantaneous look at a company’s most important metrics—and to inform financial planning and forecasting, is one use case Dinin shared.

Business Unit Scorecards 

Another client utilized integrated external data along with different types of metrics to help produce scorecards that provide executives an up-to-date snapshot of key performance indicators, along with progress toward 12-month rolling metrics for targets, Dinin said.

Rehire Eligibility 

One Deloitte client converted 20 years of historical indicators that correlate to rehire eligibility (“What we call knockout questions,” Dinin said) from a data warehouse into a Workday Prism Analytics data source. That data was then embedded into the client’s talent acquisition and recruiting process—on the job application and the requisition itself. “So, recruiters could take a look at rehire eligibility for this candidate if they had worked at this entity before,” he added. “Embedding those indicators right into the hiring business process to allow the recruiters to know whether the candidate could move forward was very, very impactful.”

Extending Customer Accounts

Another client had utilized several different systems to hold customer-based data. They were able to use Workday Prism Analytics as a customer hub to incorporate customer data across the finance ecosystem, to enable reporting and financial processes to move forward.

Supplier Vetting 

In another example, a client was able to automate the process of checking prospective business partners against the Specially Designated Nationals and Blocked Persons List (SDN) maintained by the U.S. Department of the Treasury’s Office of Foreign Assets Control. The SDN is a list of foreign entities, companies, and individuals that U.S. entities are barred from doing business with. “So here again, embedding data directly into a business process to validate an assumption or ensure that the business process could move forward is very, very impactful,” Dinin added.

Watch the session on demand to hear Deloitte’s approach to analytics, learn about Workday Prism Analytics use cases from Deloitte’s clients, and gain best practices to help you turn your data into insight, and insight into action.

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