Now that organizations run on data, any mistakes in that information can have serious consequences that spread across departments.
Take financial reports as an example. If the metrics in those reports are off in any way, it gives decision makers a skewed perspective of enterprise performance. Ideally, the errors won’t lead to any disastrous decisions, but they could.
Avoiding such incidents isn’t easy because when errors creep into the data, they’re hard to recognize, and even harder to remove. As a result, they tend to linger and propagate, spreading misinformation and misunderstanding wherever the dubious data gets used or shared. Depending on the error, executives and department heads (or anyone else who relies on the reports) may have a wildly inaccurate understanding of performance.
The only way to avoid the risk of bad decisions is by keeping errors out of the data. When errors aren’t present, they can’t propagate. With the absence of errors as the goal, it’s important to consider where data errors come from and how they spread throughout the organization. The answer typically comes back to simple human error.
User Errors are Data Errors
Whenever humans handle data, they have the potential to mishandle it. That’s why experienced typists still make keystroke errors. It’s also how accountants and finance professionals inadvertently allow errors to end up on reports.
Finance professionals frequently pull data out of an ERP, transfer it into Excel, slice and dice the information, and adjust the underlying formulas, all manually. At any step in the process, there’s the risk of information being miskeyed, cut off, or left behind. When you consider that accountants often have to build complex reports on tight deadlines, it’s clear how errors end up in reports.
Whenever systems require users to manually manipulate data and adopt a hands-on approach, they produce more data errors as a result. The opposite is also true. Systems that remove humans from the equation where possible help prevent data errors, which leads to better reports and smarter decision making. For those kinds of systems to work, though, having a single source of truth (SSOT) is mandatory.
SSOT and Automated Reporting
With an SSOT in place, significant human error is removed from the data management process. By contrast, when people rely on multiple data sources, which may or may not have been cross-checked and verified, errors are almost inevitable.
Automated reporting based on an SSOT removes humans from the report generation process almost entirely. Users simply define the information they want to report on, and then automation scours the SSOT to collect, integrate, and analyze that information.
When machines are manipulating the data and working from a common repository of facts, there’s minimal risk of typos, “eyeball” errors, or mental lapses causing mistakes. Automation proves ideal for the kind of high-volume, high-precision work that performance reporting requires. Additionally, by automating most of the work of reporting, accountants can focus on other things besides data management.
Building an SSOT isn’t easy, which is why automated reporting is essential. With a dedicated financial reporting tool, companies instantly turn their data into a cohesive, comprehensive, collective asset. Rather than searching for what they need, users simply request what they want and can trust that they’re getting exactly what they need from a unified, common data source.
The team at insightsoftware is pioneering new approaches to performance reporting. In addition to eradicating data errors, we aim to make reporting easy enough so that it’s an optimized asset at every company. Facilitating an SSOT is a big part of what we do, which is why we created a whitepaper exploring the subject in depth. Download your free copy here.