Last year I discovered an interesting faction of the American Accounting Association that was focused on Big Data. When Big Data first came out, I characterized it just the newest buzz word for business intelligence. Attending last year’s Accounting IS Big Data conference really opened my eyes to the potential to leverage Big Data and how accountants are the key to unlocking its benefits.
This year’s Accounting IS Big Data conference was held on Sept 15 & 16, 2016 at the San Francisco Airport Marriott Waterfront. The majority of attendees were accounting professors from around North America, but there were also a pretty good contingent of accounting practitioners from public practice (mostly Big 4) and a few from business and industry. The Ted Talk style opening session provided a great frame of reference for the role of accountants in Big Data. Here are some highlights.
Big Data is Really About Better Decision Making
Raef Lawson, VP of Research & Policy, Institute of Management Accountants, stated that their research shows that most data initiatives fail to deliver value, and they found that the primary cause was the lack of data analysis skills in the finance department. Your first reaction is probably, “wait in the finance department? Isn’t big data an IT thing?” You’ve hit the crux of the problem, a lot of times big data is owned by IT. However, just as we saw with business intelligence initiatives, IT alone cannot help organizations realize the value from their data. That’s because while IT is good at dealing with the data, applications, and systems that manage the data, the true value comes when data is transformed into information and insights are extracted to drive better decision-making. This is the domain of accountants.
Cory Hrncirik, Group Finance ManagerEnterprise and Partner Group, Microsoft, described this role well: “As an analyst I had to be able to merge all that data together and glean some meaning from it.” “Data is the new currency.” He shared a visualization of how data is transitioned to information and then turned into action (see Diagram: How We Use Data to Take Action).
Cory also cited Microsoft and IDC research that showed that there is a $1.6T (yes trillion) opportunity for companies that better leverage their data by turning it into action. As an example of the opportunity he showed us aMicrosoft Power BI dashboard that analyzed all of their customer churn based on the number of support calls. With that data he was able to show that for the overall US, if a customer had to call support 4 times, there is an ~35% probability that they would lose that customer, and then by the 8th call the probability is increased to ~95%. He was also able to drill down and show us that however in California, the risk was much higher and that the ~95% risk of customer loss actually occurred at the 4th call in California. So if you set a performance standard of solving the customer’s problem within 4 calls (the overall trend), you risk losing a lot of your California customers. Since different areas of the country have different churn rates, you could potentially optimize your support function to ensure that you are resolving support incidences within the appropriate customer tolerance for their area—essentially optimizing the use of your resources and reducing the risk of customer loss.
Big Data and Data Quality
You can only make better decisions if you have high quality data. This is often the domain of internal auditors (yes again accountants). Doug Anderson, Managing Director for CAE Solutions, The Institute of Internal Auditors (IIA), spoke about the role of internal audit in looking at the risk associated with the use of data for risk quantification and financial measurements. I think of this as applying all those financial statement assertions like completeness, accuracy, etc. to an organization’s internal data. (I wrote a whitepaper for the AICPA that explained and expanded on this concept as Business Information Risks in 2009. Email me at firstname.lastname@example.org if you’d like a copy of the whitepaper.)
Doug continued explaining that internal audit is also looking at how is data being used, structured, and leveraged. He provided the following considerations about uses of data:
- Responsive or convenient? Are you using only data that is convenient and easy for you to obtain? Or are you really getting the data that is responsive and best represents the state and impact of business decisions?
- Complete or available? Are you working with the complete set of data or only what is available? Is the data set actually representative of the whole population? How can you get access to a better data set?
- Causation or correlation? Are you looking at the things that actually cause events to occur (i.e. business drivers) and are you correlating the appropriate data sets to look at cause and effect relationships or build your data models and algorithms?
- Ethical or barely legal? Have you considered the ethical implications of the data that you are using? Are you using it in a way that doesn’t violate regulations? For example, are there any non-discrimination or potential privacy risks associated with the data that is being used?
So accountants, whether part of the finance department or internal audit, are prime candidates to help answer a lot of these questions and ensure that data is of high quality and being used in the “right” way.
Big Data, Risk Analytics, and Audits
The other opportunity for Big Data was in providing non-financial data and meta-data on an organization’s operations. These can be used to quantify risks and provide indicators for when there is a change in an organization’s risk posture. The customer churn analysis (risk of customer loss) that Cory provided above is a great example of using a non-financial metric (number of support calls to resolve a problem) to drive prediction of a non-financial event (loss of customer), which then has a financial impact (loss of future revenue).
Doug also mentioned that internal audit is trying to figure out how best to leverage risk indicators as part of the internal audit function too. Representatives from PwC and EY also described how Big Data is being incorporated into their advisory and assurance services. Jason Guthrie, Senior Manager, EY, provided his perspective of the audit of the future (see Slide: The audit of the future) which described how technology could be used to automate routine audit tasks—allowing humans to focus on application of judgement and professional skepticism.
Risk management and compliance are part of an organization’s corporate governance function, so yes again are part of the accountant’s domain rather than IT; and auditand assurance are definitely accountant domains.
Big Data Opportunities for Accountants
Whether you’re an accountant or not, you’re probably thinking: “yea right, the accountants I know can’t do all this stuff.” And you’re probably right—most current accountants are not ready to take on these opportunities. However, we’re still at the infancy of the Big Data wave and there is time for accountants to ready ourselves to ride this wave rather than being washed under.
As you can probably tell from the way I’ve described the
opportunities above, especially if they come from the audit background, accountants have a very strong base to build upon and develop their data analysis skills. Accelerating accountant excellence in information technology has also been a passion of mine and during my three-year tenure as the Chair of the Information Management and Technology Assurance (IMTA) Executive Committee of the AICPA, my fellow committee members and I rallied around a vision of enabling basic IT competence as part of the “regular” CPA rather than as a specialist discipline. This trend had already been identified by the AICPA’s CPA Horizons 2025 research where technology was removed as a CPA core competence and shifted to be part of the CPA baseline.
Roger O’Donnell, Partner, Global Head of Data & Analytics, KPMG, proposed that accountants are potentially primed to be the next set of data scientists. Okay, that might be a stretch he admitted, but he said that accountants are in a good position to look at how we acquire data, ensure that it is of high quality, and then analyze it and present it visually. KPMG feels so strongly about this that they collaborated with both the Ohio State University Max M. Fisher College of Business and the Villanova School of Business to provide a KPMG Masters of Accounting with Data and Analytics, and they fully-funded 50 “Top Talent” students in pilot classes at both schools.
Accountants Can Easily Learn Big Data
As a professional educator within the accounting profession, I’ve foundthat data modeling and business intelligence concepts are easy for accountants to learn and quickly put into practice. There are specific opportunities for quick value realization using more data analytics within financial planning & analysis (FP&A), and both external and internal audit. So if you’re an accountant that wondering if Big Data is something that you can learn, my answer is definitely YES.
Stay ahead of the wave and start learning about Big Data now. This will help you drive more value at your organization (think about the $1.6T opportunity) and also help open upward career opportunities. If you’re not sure how to get started, don’t hesitate to contact me at email@example.com.