It’s Not About D&A. It’s About Problem Solving

I’ve come to conclude that it is really not about analyzing data at all. Yes, employers must engage deeply in D&A to be competitive in this information age; yes, accounting has really always been about data; and, yes, business (that which accounting is the language of) drives the economy. Those are all valid reasons to indoctrinate the accounting field with D&A; but I believe there is a more abstract and important reason. Accountants, like never before, need problem solving skills. Business is more complex. Information is more complex. Problems are more complex. We need accountants that can solve those problems. D&A is rich with opportunities to learn how to solve problems. So, it’s somewhat convenient that this perfect storm of big data, analytics, and accounting has arrived.

Being Comfortable Being Uncomfortable

Big problems make most people uncomfortable. In a conversation with a recruiter of a Big 4 Accounting firm, I asked about the specific D&A skill set they were looking for in students. He paused, looked at me, and said, “Matt, we need students who are comfortable being uncomfortable with data.” That is now one of my unwritten teaching objectives.

Problem solving is messy and ambiguous process. It requires a tolerance for uncertainty. For the inexperienced, D&A may seem like a concrete practice. It’s not. Often its more art than science. It’s laden with assumptions, decisions, trial and error, and all before you ever begin to interpret your results to answer the question you set out to answer. The analytic approach to any given problem can have dozens of paths which are dictated by assumptions you have to make along the way. In other words, twelve different analysts could end up with twelve different results and interpretations. So, I’ve learned to ask a lot of questions about others analyses before I’m comfortable with their answers. And when I’m the analyst, I’m still learning to be comfortable being uncomfortable in the process. I can still empathize with my accounting students who want to flip to the back of the book to check their answers.

Computational Thinking

My last thought is about computational thinking. In a nutshell, computational thinking is making computers an extension of our thinking. It requires that we know how to break a problem down into parts, determine which parts a computer can handle better than us, encode those parts in a way that the computer can understand, and then interpret the computer’s response. At a high level, computational computing is everywhere today. Think social media. We can’t send a message across the world in seconds, but computers can; we just have to know how to hand that task off to them. Likewise, an auditor is not capable of checking the hundred million transactions in her client’s database for specific conditions that might indicate fraud. But the computer can (quite efficiently, in fact). The auditor just needs to know how to communicate this task to the computer.

Many claim that bookkeeping, auditing, tax preparation, and other accounting-related occupations are almost certain to be automated in the near future. If such predictions are true¹, then, in my opinion, it’s not so much about accountants being out of jobs as it is about accountants redefining themselves with better computational skills. They give the computers stuff that’s easily automated and turn around and do higher order work; and, like with problem solving, D&A is fitting teacher of computational thinking.

So I hope my D&A students (along with the entire accounting field) can learn to be comfortable in the process of gaining computational thinking skills sufficient to conquer the uncomfortable problems and opportunities our information age presents.