The right analytics can save companies millions and help them see the road ahead (and the opportunities that exist there) more clearly -- if they have the right tools, if they maintain a relatively sane information technology (IT) environment, if a broad range of decision-makers know how to use analytical tools, if...
This string of conditionals adds up to a formidable obstacle. And one of the largest obstacles preventing companies from harnessing greater advantages from their analytics capabilities is what Lavastorm Analytics CEO Drew Rockwell describes as the "great data divide." On one side of the divide, you will find relatively few companies with quick and easy access to all the data necessary to immediately fuel all of their analytical engines.
On the other side resides the vast majority of companies who must contend with data that is "increasingly fractured and allocated into separate departmental silos within an organization," notes Rockwell. He recently took time to respond to questions about valuable analytics-related opportunities, obstacles impeding the adoption of continuous monitoring and auditing, and the changing nature of financial planning & analysis (FP&A) functions.
Eric Krell: Today, the corporate finance function can apply analytics to so many different business processes and challenges, including revenue and profitability management, business performance management activities and even risk management activities like fraud prevention (and more). What do you generally see as some of the most valuable analytics-related opportunities for corporate finance functions today?
Drew Rockwell: First, I'd definitely point to analytics around accuracy. The accuracy challenges that finance is seeing, and indeed many other industries, are getting bigger because of the growing complexity in service delivery chains and supply chains. This becomes more and more disintegrated. The challenges are also amplified as technology allows for greater segmentation and pricing flexibility, especially as data volumes and variety grow. With this, potential problems are hidden in individual data records or even fields within records. Keeping this in mind, independent validation is becoming more important to ensure accuracy.
Second, deeper analytics around risk are also a valuable area for the finance world. Fraud and security, for instance, are far more dynamic than ever before and finance departments need the flexibility to adapt to these as they continue to evolve in both style and complexity.
Further, I'd say that analytics around financial optimization are hugely valuable. Financial departments must ask: Are our bills accurate? Are our payables accurate? Are our accruals correct? Are our tax payments correct? We've seen finance departments find millions of dollars in a single analytic, but as data volumes grow and rules become more complex, they are discovering these opportunities using Excel and manual inspections samples.
Applying analytics to fraud prevention and internal auditing seems like a no-brainer, but continuous auditing and monitoring has not become as pervasive as many experts expected, at least not yet. What do you see as some of the barriers to overcome if organizations are to fully harness the benefits of audit analytics?
Rockwell: One of the biggest challenges may be what we call the "great data divide," where data is increasingly fractured and allocated into separate departmental silos within an organization. Often, this information is not even accessible by the people that need it the most. This divide can largely be attributed to the limitations of spreadsheets and traditional business intelligence platforms. In almost all cases these were implemented years ago when data was more stagnant, smaller and less varied -- before the age of "Big Data," if you will.
But while these sorts of solutions haven't really evolved since then, the requirements of the data that they're processing has changed significantly in just the past few years alone. Because of that, organizations need to consider how new data sources increase the performance demands on analysts and on their organizations. Today, when it comes to business performance and analytics, there is a requirement for greater flexibility, speed and control.
An insufficient supply of these three dynamics can wreak havoc on organizations' ability to govern, optimize and ensure compliance for key processes that affect revenue flow and risk if they don't have a foundation architecture that is built to support them.
How have you seen organizations work through these obstacles?
Rockwell: Most organizations are catching on to the fact that they really need to keep up with their data in order to truly capitalize on it. I've seen businesses go about this in a few ways, one of which includes centralizing complex calculations and validations by building consistent platforms to replace regional spreadsheets and samples. They're also redefining internal audit from a sample-driven approach to 100 percent inspections, and putting in place the tools to do that. Last, they're really bringing risk forward -- trying to prevent issues rather than to simply "catch" problems. They're doing this by getting involved with new product and system introductions before they go live -- thus avoiding any unnecessary complications.
A few years ago, FP&A was identified in the general business press as one of those select "Hot Jobs of the Future" professions. Today, it seems like analytics -- and to some degree, even FP&A -- has moved into almost every business function and process. What type of impact is the growing use of analytics throughout the enterprise having on FP&A functions and professionals?
Rockwell: FP&A is now tied more closely to every business aspect and, because of that, organizations are looking to leverage analytics more and more. The use of more analytics often means training employees on how to use these tools, which means more time and money invested. But analytics are evolving so that executives and business analysts -- not just IT teams -- can become proficient in the tools themselves.
This is largely due to tools that enable end-to-end visualization of the data and the analytical paths taken to arrive at various conclusions. Why is this important? Because when it comes to answering questions from within the data, most employees don't speak the language (e.g., SQL or complex Excel macros) required to conduct complex coding or decipher a monthly financial report. As such, manipulating, exploring and understanding analytics have lacked factors like transparency, trust and ease-of use. Clearly, they won't be running to the nearest Best Buy to buy these analytics tools, but the fact is that this data and the results gained from analyzing it are now accessible and understandable beyond the IT department and more pervasive throughout organizations, including FP&A.