Digital transformation of finance unleashes analytical minds

The digital transformation of finance is like all automation: an effort to speed up and standardize manual processes. CFOs can lose their jobs if they don't get the essential processes right, such as moving invoices and closing the monthly books. But once a firm digital foundation is laid, finance departments can become strategic advisers to the CEO by harnessing more advanced technologies, such as analytics and AI.   

For 11 years, Dan Fletcher has had what he calls a "side seat" to the technical and business challenges of CFOs, including the digital transformation of finance, as a consultant focused on improving the performance of companies owned by private equity firms. He became CFO of Host Analytics, a provider of SaaS corporate performance management and financial analytics based in Redwood City, Calif., when his employer, Vector Capital, bought the vendor this past January.

Fletcher shared his views on the digital transformation of finance in his company.

What do you think digital transformation of finance really means?

Dan Fletcher

Dan Fletcher: The fintech that's used by finance has a really unique impact on the organization holistically, because everything flows through [it] from a data and decision-making perspective. Fintech can influence cross-functional partnerships, compensation and incentives that can influence how decisions are made ... and the processes through which work is completed across the org, how outcomes are measured and how the results of the business are communicated.

It's really the lifeblood of the business. Perhaps 'hub' is the best word I can use to describe what I think of fintech as in both its current iteration and as it will evolve.

What technologies are central to the digital transformation of finance?

Fletcher: The way I break it down is by function, workflow and process. You've got all these finance processes, such as procure to pay, and then you've got everything from reporting and budgeting and forecasting, from invoicing all the way through to cash.

The question, of course, is why automate? There are multiple reasons. No. 1 is speed. These processes, when they're done in [Microsoft] Excel, are done offline and largely manually by the team. It takes time. So, speed and accuracy.

The second would be the professionals in the finance and accounting function are often some of the most highly educated, sophisticated and intelligent and ambitious professionals in the organization. The less time I have my team bogged down in manual tasks and doing account recs in Excel, the better, because then I can turn those high-powered guns on to really value-additive activities, like decision support.

The last would be either cost takeout or future cost prevention. At a company the size of Host Analytics, we've got a nice team in place here, a nice solid accounting team and finance team. And because of what we've done in the back office, I think we could double the size of our business without adding a single additional head to our finance and accounting team.

Some say the next frontier in the digital transformation of finance is the analytical side, including financial modeling, advanced analytics and AI. What do you see happening in the industry or your company?

Fletcher: There's analyzing your own data -- being able to consolidate clean data that your team can trust and access quickly -- whether you're pulling it into reporting from a Host perspective, or whether you're pulling it into modeling and running scenario analysis on it. That's kind of step one, and I think we as an industry are there.

We've built the functionality with all the connectors into ERP systems such as NetSuite and Sage Intacct, and pulling that into solutions like Host Analytics or even a BI [business intelligence] tool like Looker. We're able to very quickly consolidate, gather and trust our data, and parse it and use it to make decisions now or to run scenario analysis and forecast the future. We can continue to evolve that.

Manual tasks are being slowly automated away, and there's no doubt that the tasks remaining are largely nonmanual, or certainly require a higher level of skill and intelligence.

The next frontier is predictive analytics. There are different parts. No. 1 is: Are we able to access data that is correlated to our business and, therefore, be smarter when we're forecasting or making decisions? That may be macroeconomic data, it may be industry trends -- you just need to find those correlations. It may be the price of oil, depending on your industry.

The other piece of that would be writing code -- algorithmic code that's not relying on humans working in Excel-like solutions ... into which we can input our base data. Then, it runs its secret sauce, whether that's an algorithm or some other complex code, and then outputs data that is useful to us. That is the part of the business, part of the automation, that I think we're still working on.

How far could the use of robotic process automation go?

Fletcher: It can be applied to almost any of those various workstreams and functions in the finance org. I'm not trying to get rid of humans, [but] I'm not naive enough to say it doesn't remove some demand for human labor in the market.

Reporting is a real pain, as any finance professional knows. And because of our system, reporting is essentially automated, except for the commentary, the MD&A [management discussion and analysis]. That may be somewhere in the future -- automating that commentary. But, right now, it's the human touch.

The marriage of operations and finance has long been a goal of corporate performance management. How successful have Host Analytics customers been at achieving synergy and coming up with something that's greater than the sum of the parts?

Fletcher: If you're a company that has a lot of inventory, and you need to do constant, vigilant analysis of inventory level and SKU level and profitability, our software and software of adjacent technology in this space can be very valuable. You pull all your data into a data lake or a data cube, and you provide pretty deep, high-powered resources ... to help analyze it. One example might be if you're a building-products distributor, and you've got thousands upon thousands of SKUs -- we're talking 30,000 SKUs -- and your ops group doesn't have the type of resourcing to constantly stay vigilant about profitability.

Finance can access the same data lake and build what you might call an economic contribution margin cube, allocating costs across to different product lines and different SKUs, so that we really get a sense of that long tail -- the products that we're selling and aren't providing a lot of margin to us. And then there's an opportunity to rationalize those SKUs, or to at least negotiate better pricing on them with our vendor partners.

What you've described sounds like it puts some demands on the skill sets of finance people. How big an issue is reaching this higher level of predictive analytics to do sophisticated things with operational and financial data?

Fletcher: Institutions of higher education and the AICPA [Association of International Certified Professional Accountants] and other stakeholders in educating our finance and accounting professional workforce [are] eventually going to have to step up. The manual tasks are being slowly automated away, and there's no doubt that the tasks remaining are largely nonmanual, or certainly require a higher level of skill and intelligence.

Finance professionals are going to need to be very adept and very flexible at [handling] large volumes of data and pulling out the insight, and then on the back end of that -- and this is often overlooked -- being able to communicate that to the stakeholders.

You can do all the greatest work in the world as a data scientist or as an FP&A [financial planning and analysis] professional and pull out your insights, but if you don't have the political savvy and the communication skills to bring that to the proper executive, be able to win them over and be persuasive enough to provide or prompt action, then your skill set is largely going unutilized.

Have CFOs become more strategic? How has their relationship to IT and the CIO evolved?

Fletcher: When you think about the responsibilities of the past, they were largely defined as maintaining regulatory and statutory compliance and reporting, analyzing and reviewing financial data, financial performance and, of course, preparing budgets and monitoring expenses and cash flow -- all that core stuff. And, of course, all the processes that underlie those functions: payroll, [travel and expense] approvals, etc. Those are our bread-and-butter activities that the CFO and CFO team still have to execute at a high level.

The modern CFO ... is the strategic partner to the CEO. They may be expected to identify and execute value-creation opportunity. They may be the owner of [mergers and acquisitions]. They're often the center of business intelligence, not just an owner of the financial results, but of the intelligence derived from those results. And they're expected to interface with the organization both vertically and horizontally to implement a finance mindset.