The Evolving Role of the Tax Department (from a Tax Technologist’s Perspective)

Tax technologist and CSC Corptax^® Senior Manager Jason LoBrutto works closely with tax departments every day—giving him a first-hand look at the tax department as it changes over time.

How has the tax practice evolved over time, and where do you see it going?

Jason LoBrutto: My first job was at a large, multinational company. The VP said when he was my age, hundreds of people made up the tax department. They did ledgers by hand, used calculators that spit out paper ribbons, entered data on typewriters, and bound and mailed stacks of paper to the IRS. A few months later, they would find out if the return was accepted.

Now, the process is digital. We pull in ledgers through APIs or other structured formats, automatically pre-populate amounts, review within applications, and file forms electronically. You know your return status within hours.

Plus, today, taxing authorities want things fast. The volume of data we must manage is huge, and tax departments are asked to do more. Tax automation is a big part of making that possible.

Where do I see the tax practice going? I see greater automation and more analytics—letting software do more of the rote preparation and tax accountants doing more of the fun stuff, like researching, strategizing, and thinking creatively. Software is great at following rules and logic—a big part of tax prep. But people excel at interpreting rules, doing analytics, and thinking creatively.

What else do you see driving the evolution to technology?

Jason: Lower cost, ease of automation, and accuracy. Historically, the tax department has been seen as a cost center, so there’s a drive to reduce expenses while increasing productivity.

Take the cost of data storage for instance. Twenty years ago, terabytes of cloud data storage required millions in upfront costs based on hardware and storage expense, implementation, IT support, and so on. Today, it’s as easy as engaging Microsoft or Amazon or Google and setting up a cloud architecture at a nominal cost. Heck, most folks have cloud storage working seamlessly on their phones.

Then, you take workflow automation applications like Power Automate, Power BI, and Alteryx that let accountants automate processes without needing programming skills.

Next, you have the accuracy component. People can inadvertently transpose or mistype numbers during data entry— computers don’t make those mistakes. Structured, validated data follows rules error-free, time after time, day after day.

And circling back to lower costs, technology also helps tax departments get more done with the resources they have.

We’re hearing more about data science—how does that technology influence tax?

Jason: Data science matters because statistics are a key field of knowledge. But unlike standard statistics where you find causation and correlation, data science emphasizes prediction and action. It allows you to explore complex aspects of data analysis like algorithms, machine learning, structured prediction, and neural networks.

Looking at a tax scenario: hundreds of weekly notices come into the department at all hours via a cloud storage drop box. Machine learning and optical character recognition read them instantly. Algorithms using prior human data automatically classify them without human intervention: what’s high priority, low priority, etc.

They parse and save the data and make it searchable and accessible at any time. They assign metadata like uses, vendors, amounts, year, month, day—you name it. This saves countless people-hours, and it’s mistake-free.

Algorithms can also take massive amounts of data and find useful correlations a tax accountant would be hard-pressed to see. For example, looking back on data since 1995, the neural network could conclude that during times when unemployment numbers reach X%, revenues drop by Y%, Z% of the time. That finding may influence how Tax creates its forecast.

Where would a department just starting out with technology begin? 

Jason: Start simple and start small. Find processes to automate that are manual, time-consuming, and repeatable.

For example, let’s say before you import your trial balance data, you always do five things. You can create an automation to do those five things as soon as you drop that file into a folder. Or better yet, let your automation pull in the file, apply the five steps, and deliver newly formatted data.

You can further streamline by automatically notifying people when files are ready for further work or review. And you can make data easily accessible to people who need to see it, instead of storing documents offline on computers or in email.

Further, centralizing data simplifies collaboration and lets you easily access it for your data science tools. It also provides security, version control, and backups.

Any more suggestions for those starting their tax technology journey?

Jason:  Stay positive—Rome wasn’t built in a day!

Make sure you test, test, test—I can’t stress that enough. Come up with all potential scenarios and test them with your automated process. Throw as much as you can at it to ensure you’re getting the same result with automation as you would by hand. Then, once you’ve set up rules and thoroughly tested results, trust the computer. That said, occasionally spot check, and don’t be afraid to tweak.

If you want to accelerate the process, you can always consult with business process experts. They work with tax departments to identify areas most likely to generate the biggest time and cost savings.

What does the future look like for people with a traditional accounting background vs. a technology background?

Jason: A traditional accounting background without technology gives you key concepts but not how to fully utilize data or use tools to drive efficiencies.

A technology background may provide those tools but doesn’t concentrate on tax accounting concepts and end results, like why a number times a percentage isn’t always the right answer because of ever-changing tax laws.

So basically, you’ll need to wear both hats. Tax accountants won’t be expected to program an app from scratch or build out a machine learning algorithm, but they may need to know more than adding v-lookups or index formulas to an Excel model.

Low-code applications such as Power Query, Alteryx, and Power Platform now exist to make complex actions more user-friendly. As those tools get more powerful, understanding how to use them will become more of a must-have in a tax department, than a nice-to-have.

I’ve gone through this myself. Over the years, I’ve taught myself new tools and skills through online courses, webinars, and other resources. So much is available today—it’s easier than ever to learn and make yourself more valuable.

Can tax practitioners expect to use today’s tax tools in the future?

Jason: Well, within the past 25 years, we connected with people on Myspace and rented movies at Blockbuster, right? What you think of as the standard way of doing things now may be completely obsolete within a few years. Tax accounting tools are no different.

Excel will always be in the picture—it’s ubiquitous in the industry. But more and more tax departments will embrace tax technology for the reasons we’ve discussed, keeping up in the tax world, getting more done, seeing and communicating what your data can tell you, and so on.