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Hertz understands the havoc that data errors can cause.
Back in 2014, the rental car company found upwards of $46.3 million worth of errors in its 2011 statements. Emerging from a range of sources--from uncollectible fees for damaged vehicles, to doubtful accounts and miscalculations--the errors came with serious repercussions. Hertz not only saw a 9% decrease in stock prices but their CFO resigned shortly after.
Still, that's chump change compared to the data mistakes the Bank of America found the very same year.
Also in 2014, the bank found miscalculations in its 2009 acquisition of investment firm Merrill Lynch. As it turned out, Bank of America had overstated its capital position by $4 billion. Again, stock prices plummeted in the aftermath.
Mistakes happen. These big business examples are proof enough of that. But they don't always happen without consequences. They're not the purview of big businesses alone, either. Small and medium-sized businesses (SMBs) are just as susceptible to the common pitfalls of data analysis--and the repercussions can be just as difficult to deal with.
So what can go wrong for SMBs when the data isn't right?
Whether the result of human error, undefined processes, lack of collaboration or a range of other issues, there are plenty of examples of businesses getting their financial data wrong. Mistakes are a normal part of doing business, after all. But those data mistakes can have a ripple effect if you don't catch them, which can have lasting effects for business owners and operators.
That's not just the case for big names such as Hertz and Bank of America, either. With smaller teams and less-defined processes, small and medium-sized businesses can easily find themselves affected too. The resulting errors may not make headline news, but they can affect your bottom line, create inaccuracies in your financial statements and impact your reputation with customers and employees.
So let's look at some of the things that can go wrong for SMBs when the data isn't right.
A lack of collaboration and communication between team members can make duplicate data and data omissions more common than you'd think. That's especially the case in situations where multiple invoices have been received for a single charge, or multiple team members are manually entering data in different versions of a spreadsheet. But if you don't catch them, those duplicates and omissions can trickle down to impact your balance sheet, income statement, tax statements and more. To keep things running smoothly, then, it's critical that you trust your data is right--and when you can't, you waste time double and triple checking your numbers. That requires extra resources, leaving less time to spend strategizing toward your growth goals.
Omissions and duplicates add their own form of chaos. But what happens if a whole formula accidentally gets overwritten and every calculation that relies on it is wrong? It can be harder to catch errors like these, yet they can have more far-reaching effects, leading to multiple errors throughout your financial records. Putting more defined processes and centralised systems in place can help ensure they don't happen in the first place.
Too many spreadsheets can make it difficult to keep your data straight--and to be confident you're working with the most recent version. When there's no single source of truth, especially with multiple team members making changes, you risk pulling up an outdated version or accidentally leaving a colleague's hard work behind while you add your own updates. Having a central database can help ease this issue and make things run more smoothly, with a single source of truth.
Processes such as budgeting, forecasting and scenario modelling rely on accurate data if you want to get them right. If the data's wrong in the first place, or if you're using outdated numbers to fuel your perspective, you're at risk of getting things wrong--meaning you won't be as agile for your future needs as you could be.
Working in finance for a small or medium-sized business may already mean you're spending most (or all) of your time on traditional accounting duties. After all, your team is only so big and vendors, suppliers and employees need to get paid, financial statements have to be prepared and your overdue receivables need to be followed up on--among a list of other tasks. When you also need to spend time looking for data errors and dealing with any repercussions of those you didn't catch, there's even less time left over to spend on FP&A and the strategic planning that will help you in your business goals. Getting your data right, then, frees up time to get other things on the right track as well.
So how do you make sure you have the data right, avoiding those all-too-common pitfalls in data analysis so that you can get on with business? Here are a few tips:
The right data is critical for all businesses, no matter what size they are. If you're part of a small or medium-sized business, getting the data wrong might not cost you billions of dollars, but it can be damaging all the same. In fact, getting the data right in SMBs can be even more important--because, unlike big businesses, you don't have the luxury of large reservoirs to back you up if something goes wrong. The future of your company is reliant on data: to secure funding, build your customer base and keep building toward your goals. Without accurate data, you might not have a growth plan at all.
Getting the data right, then, is critical. So why not make it easier to avoid the five major pitfalls in data analysis going forward?
