Every field relies on data, from accounting and finance organizations to startups and factories. Business plans, strategies, and major decisions are made based on data collected and managed over a certain period of time. Finance departments rely on vast amounts of data, all managed in Excel spreadsheets. The importance of data accuracy is clear, especially in this field, and yet it is still allowed to be subject to something as uncontrollable and unpredictable as human error. One mistake hidden in thousands of rows of data can influence bottom line numbers and official reports in public companies, and mislead important insights. It is no wonder that professionals in the finance industry are concerned.
The real issue is, there is no good alternative to Excel, and finance departments, organizations, and professionals will continue to use it.
While data can be collected and calculated using algorithms and automated programs, there is still quite a lot of human intervention along the way. Files are shared with and edited by different people within an organization, making it very difficult to track the most updated file. Many changes are made by employees and not computer programs, which introduces the element of human error once again. The finance department usually needs to collect and manage this data from various source, and with the volume involved, finding one mistake is near impossible.
When it comes to financial statements, with calculations upon calculations that rely on data from different locations, one mistake can make a significant different to the result.
Excel is a powerful tool with obvious benefits (i.e. flexibility, VBA, ease of use, etc.), and while there are significant issues with regards to data integrity, that does not mean that an alternative to Excel needs to be found. Organizations need to understand the issues that they are facing and find solutions that address each and every one of those issues, including tools and best practice guidelines for company employees. In this article, we introduce a few guidelines that can help companies significantly reduce errors and improve data integrity.
The larger the organization and the more people work on the same data, the higher the chances of making mistakes. Data is shared and edited throughout the organization, and this can quickly lead to lost and wrong data due. Monitoring and tracking spreadsheets and their most updated versions at all times can prevent this and significantly reduce the risk of errors. While this can be done manually, larger organizations would benefit from a technology solution that can make this process more efficient and reliable.
Preventing access of certain files to unauthorized personnel is not only about security and protecting private data. It also helps avoid situations in which someone opens and edits, or erases, important data from spreadsheets by mistake. When managing large amounts of data, it is important to define who has access to which files in order to increase security and improve data integrity.
Assuming only authorized personnel can access the data, and management knows what the most updated version is, there is still a matter of ensuring that all changes are approved. These changes include both direct changes made by a user, or changes to formula results. Being able to see who made what change, and at what time, can help detect errors as they occur instead of further down the line, when it is much more complicated.
The EUC (End User Computing) landscape refers to the integration of non-programmers in the data management systems. It is important to document and constantly update all EUCs. The more information that can be provided, the lower the risk of errors. Examples include data owner, dependencies, risk level, department, lifecycle stage, etc. This helps managers and decision makers within an organization to identify what spreadsheets, data, and applications require their attention based on priority. It also provides an opportunity to identify and embed best practices to improve EUC and data management. For example, changes on important spreadsheets should be approved before accepted, either by another employee or using automated review processes to look for anomalies.
These types of frameworks are also a great way to ensure compliance with industry or government regulations.
When data integrity is compromised, it is almost exclusively a result of human error. Manually ensuring data integrity and accuracy is not only impossible when dealing with large volumes, but it leaves organizations still vulnerable to human error. Automation in the review and management processes can mitigate risk and save organizations in resources and man hours.
Throughout the stages of data collection, management, and review, there are many ways to use technology solutions to automate the entire process and make it more efficient.
Spreadsheets aren’t going anywhere in the foreseeable future, and that doesn’t mean companies and organizations need to settle for unreliable data. DataRails provides an Excel-based platform that allows organizations to manage, share, and control their spreadsheets without changing the Excel experience, while ensuring data integrity and reducing the risk of errors.