4 Digital Skills Every Finance Manager Needs to Maximize Business Growth

The year was 1956. A young, Hungarian man had immigrated to New York City after a life of facing some of the worst atrocities of history in the wake of World War II. But the man wouldn’t let that experience define who he was. He’d stepped into the world of finance, working at a merchant bank over in London. Now, in America, he was set to become a trader through F.M Mayer. His name was George Soros.

In time, Soros became one of the most successful and influential investors of the 20^th and 21^st centuries. He predicted the stock market crash of 1987 and became known as the man who broke the Bank of England by shorting the pound sterling and earning a profit of $1 billion. His philanthropy organization Open Society Foundations has given away $32 billion to good causes.

But none of this success happened overnight. Soros didn’t rely on just one skill. He tapped into his philosophical background to come up with an investing framework that worked for him. He kept up to date with trends and changes in the financial sectors. He analyzed data, remained open to differing perspectives and constantly iterated his approach.

Soros’ story is a shining example of how financial professionals can grow through constant learning. And in today’s business world, digital know-how is a must for financial managers. It’s especially important given how the profession has been historically fearful and slow to embrace digital skills. 

Let’s explore four key digital skills every finance manager should know to maximize business growth (and follow in Soros’ footsteps by betting on yourself and growing your career). 

AI and machine learning in finance cover everything from chatbot assistants to fraud detection and task automation. By automating financial processes with AI, finance teams can streamline tedious tasks (saving lots of time and resources) and dramatically improve the customer experience, as they don’t have to wait for long periods of time to get their deal approved. 

Digital transformation in the financial world is well and truly underway, with the global market predicted to be worth $1009 billion by 2025. So, financial managers really can’t afford to sit on the fence about the value of technology. 

Matthew Debbage, CEO of the Americas and Asia for Creditsafe, makes a compelling case for why it’s time to embrace digital transformation in finance: 

“Over the last few years, many companies have been increasing their investment in digital transformation. Digital technologies and processes offer so many benefits, including increased productivity and reduced costs. And it’s usually the CTO, CDO, CIO and/or CISO who lead the digital transformation charge. These are all roles where technology and automation are critical and embedded into every process from the start.

But the finance profession has historically been slow and hesitant to adopt technology into their roles and processes. This is a profession that, in many cases, still uses Excel sheets to maintain its ledgers and manage its debt collection.

Rather than relying on a physical ledger, using a digital ledger management tool means you can get a full and accurate view of your cash flow. So, you know exactly how much sales are coming in, how much cash is going out as well as which customers have paid their invoices and which ones haven’t.”

The benefits of doing this include:

• Collecting money faster from customers
• Reducing the risk of bad debt
• Increasing your cash flow to pay for expenses and have a buffer against financial uncertainty in a recession

Then there’s the upshot of automating your credit decisioning process, especially when there’s a lot of back-and-forth decisions to be made between finance and sales. Nobody likes friction or miscommunication. The easier that is to take away, the more likely you are to make better business decisions because the emotion has been removed from the process. 

Plus, you can reduce the number of touchpoints needed to research the financial history of a prospect and close the deals that are going to make you more profitable. While the customer gets a more efficient onboarding process, you keep your cash flowing. Everybody wins with the right technology.

“Data is everywhere.” How many times have you heard that? Well, you might think it’s an exaggeration, but it isn’t. As of 2021, there were 79 zettabytes of data generated worldwide. By 2025, more than 150 zettabytes of data will need analysis.

With so much data, finance managers are going to have to do some wrangling. (No, we’re not talking about cattle or sheep here). This is all about data wrangling and it’s actually a similar approach to the animal variety. Finance managers need to have a clear view of all data that’s collected and stored internally so they can make sense of it all. 

But bad data is one of the biggest killers of business growth. What I mean by this is that incorrect or outdated information stops you from connecting with customers and being able to make accurate cash flow forecasts. It’s duplicate data that you’ll waste precious time and money fixing. It’s incomplete data that stops you from having clarity on your processes.

So, what does bad data look like in action? Imagine you want to introduce a new service to your customers but don’t have all the necessary data to understand their pain points and problems. You launch the service and find out it’s the wrong fit. Now, you’ve lost money, time and potentially damaged your credibility and lost customers, further impacting your cash flow. 

The solution here is data cleaning. When you remove low-quality information, you can focus on the high-quality data that gives you more insights into your customers. This involves getting rid of irrelevant details e.g. baby boomer customers within a category or Gen Z customers when you’re targeting the latter. It’s fixing structural errors like naming conventions e.g. N/A and Not Applicable so categories aren’t mislabeled. 

I also want to stress that the most effective kind of data wrangling is when you have the right data. It’s not just about relying on your ERP and CRM systems and hoping for the best. I asked Matthew Debbage for his opinion about ERP systems and data quality. He raised some great points:

“In many instances, ERP software isn’t correctly implemented across all functions, which leads to internal errors and failures. Another problem with ERP software is that businesses don’t properly integrate their ERP software across their entire technology stack. This happens because legacy systems are so outdated that they can’t communicate and integrate properly with ERP software. And that leaves companies stuck with data quality problems that often lead to misinformed decisions that expose their business to financial, legal and compliance risks.

Let’s also not forget that ERP software doesn’t always have important metrics you need to manage your cash flow, such as accounts receivable (AR) metrics. Without these metrics, companies are left with a huge blind spot that could put them at risk of increasing their DSO (days sales outstanding) and reducing their cash flow significantly.

It doesn’t help that 61% of late invoice payments occur because of incorrect invoices. And that’s happening because finance teams are relying on their ERP software as a catch-all for their data needs. But that software is missing vital information about your customers’ financial health, ability to pay invoices on time, outstanding debt, credit score, credit limit and other information that’s needed to make the right decisions for the business.”

Even though finance professionals deal with numbers every day, they’re not always the most astute at interpreting large amounts of data and putting it into the context of how it affects the business (both from a risk and growth perspective). Gartner research shows that when considering all the decisions made across an organization, a lack of skills in data literacy can cost a company as much as 1% of revenue. This is one area you need to address and close if you want to mitigate risks and grow a business long-term.

Put into a credit risk context, data literacy isn’t a nice-to-have skill. It’s a must-have. Why? Well, first there’s the financial cost that poor data has on businesses. And it’s a lot. In fact, Gartner estimates that businesses lose $12.9 million a year due to poor-quality data. So, it goes without saying that finance managers must have the strategic mindset and technical skills to understand and contextualise the key data points that directly impact cash flow and profit. Otherwise, they’ll find it hard to future-proof the business against risks.

For example, when vetting potential customers by reviewing their business credit reports, you’ll want to pay close attention to credit scores, credit limits, DBT scores, percentage of payments that are past due (and the corresponding dollar amount) and other payment trends. Any discrepancies or red flags could indicate that they are a habitual late payer and could be on the verge of bankruptcy. When you’re able to analyze this data in the context of the risks it poses to your own business, you can make quicker and more effective business decisions to save yourself a lot of pain and money later on.

An important takeaway here is that data literacy and digitization are two sides of the same coin and one can enhance the other. To gain a better understanding of how this works, I asked Dmitry Svolap, CCO & Co-founder of upSWOT, for his opinion. He said, “There’s absolutely no way to manage finance without technology today. For finance professionals, data is one of the most important tools and assets in doing their job. It’s essential to keep all information up-to-date and to have a clear picture of your company’s finance health and growth capabilities. It’s also critical in identifying and preventing your company from being exposed to risks. Without data, finance teams are flying blind and the potential risks are likely to increase.

But there’s another benefit to leveraging technology – it can help finance teams do their jobs better. Let me explain how. By automating invoice processing and creating payment calendars (by each customer), your finance team will know exactly when and to whom they should send payment reminders to. And if they use software that lets them build in workflows for this, they can do it in a single click – meaning payments can be collected faster and your company’s debt burden could be reduced.

Of course, technology can also help your finance team save so much time by presenting your financial data in a digital dashboard. For instance, your team can merge your ledger data with credit risk data so you not only get the full picture of your own company’s financial health, but you also see how long it typically takes your customers to pay their invoices and how much money they owe in past due payments.”

Historically, the finance function tends to be isolated from other departments. This is for many reasons. For instance, other departments might see the finance team as just a final stop when approving budgets or deals. 

It could also be that the finance team doesn’t actively collaborate and communicate with other departments to help them understand the company’s financial and credit policies as well as what risks and threats could hurt the business. As automation and AI will simplify and improve once-manual tasks, it will also require finance teams to evolve and become more than just ‘number crunchers.’

In our ‘Sales vs. Credit Control Battle’ study, we found that credit risk apathy between sales and finance teams could cost a business up to $4.8 million per year. Let’s look at that another way. If you have a company with a 20-strong sales team and half of them lose $200,000 a month due to prospects failing to meet the credit policy, you’re losing $24 million a year.

This kind of risk shows that partnerships and teamwork are essential. Financial megastar George Soros is a prime example. In 1969, he and his business partner Jim Rogers set up an investment fund together that went on to become The Quantum Fund, which by 1980 was up to $21.5 billion in assets. He and Rogers worked well together, but they differed in their approaches. Soros wanted to hire extra staff, while Rogers wanted to stick to the two-man operation.

After parting ways, Soros continued to manage the fund but even he wasn’t immune to financial risk. In 1981, The Quantum Fund took 23% in annual losses and he eventually delegated the business to outside managers and other teams to pick up the slack. 

Another great partnership case study is the story of Warren Buffett and Berkshire Hathaway. Before it was a multinational conglomerate with a market capitalization of $500 billion, Berkshire Hathaway was a struggling textile company. Then in 1965, Buffett and his investment firm purchased enough stocks in the company to take over and it wasn’t long before it became one of the world’s largest holding organizations.

The reason Berkshire Hathaway was able to grow so successfully was that Buffet afforded a lot of autonomy to the managers of the subsidiaries that sat beneath the parent company banner. This attitude was passed down the chain to other departments and a culture of collaboration was established. 

Digital skills are worth their weight in gold for financial managers. But it also requires an awareness of not being stuck in your ways. Refusing to adopt new tech and the latest financial processes isn’t just going to hurt business growth; it will limit your career growth and advancement opportunities.