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What does it mean to have “clean data”?
As we all know, your financial data provides the building blocks to calculate metrics, understand your performance, and make confident decisions about your growth. However, many companies struggle with messy data in the form of incomplete, incorrect, or inconsistent records leading to errors and confusion. Not only does this leave you in the dark about the state of your business, but it also requires hours of manual input searching for the source of errors, and a haphazard attempt at cobbling together data to make a passable analysis.
It can be difficult to understand exactly how to fix this issue—especially if you’re not sure what you’re doing wrong in the first place. However, I spoke with some of our finance experts, who help our customers clean up their financial data every day, to share some pro tips that will make a huge difference in boosting your data integrity.
It’s important to be very clear about the time period covered by your revenue. At the very least, a clear start and end date attached to each line item is a great first step to clean, organized data. For clarity, start and end dates should be separate and populated with dates in a consistent format, such as MM/DD/YYYY. Having some entries labeled “May 2022” and others “5/22” will create the need for manual, time-consuming cleanup.
Detailed descriptions or product codes that relate to only one time period are helpful during cleanup, but there can still be issues. For example, it can be difficult to systematically use “3 months” in a description field. Is this three months forward-looking or in arrears? Does it start on the invoice data or the first of the current or next month? Ensuring that dates are specifically listed can eliminate confusion and help you create your most accurate reports and metrics.
Another issue we often see is manual invoices done outside of the typical invoicing platform. Whether you prefer manually invoicing new clients or have a certain client that prefers it, manual invoices unfortunately create more opportunities to miss an invoice, apply product codes incorrectly, and have inconsistent customer data cross platforms.
If you invoice data one-time, but then a change is made to the invoice before the customer pays, or the invoice is voided, you need to let your finance team know of any changes. Whether it's a disputed charge, a service concession, or even just a timing mix-up, if you don't update your list of adjustments to apply to the invoices, your reports will not be accurate. Voiding and reissuing invoices is fine, and perhaps even more straightforward, as long as you keep track of voided invoices.
If your data is not recorded the same way between your sales pipeline and your invoicing data, calculating metrics to understand your MRR, expansion revenue, etc. will be a nightmare. Once a prospect becomes a customer, sales will continue to interact with them for renewals, upsells etc. If teams are recording customer data differently, it will be impossible to automate customer metrics tracking & invoicing. It’s crucial to have a standardized system to classify and record all customer data, regardless of who is inputting it. Better yet, invest in a tool that allows you to track the entire customer relationship from prospecting with sales all the way to invoicing as a customer in one place.
One of the biggest issues we see regarding data integrity with our customers is not taking the time to really learn how to properly use their tech stack. While software today can be incredibly intuitive, make sure to read onboarding materials and fully understand best practices. Making sure you’re filling out form fields correctly is one of the most important ways to prevent errors and incorrect reporting down the line.
While this may seem straightforward, not all revenue is created equal! As a SaaS company, you understand that recurring revenue is one of the greatest benefits of the SaaS business model. It’s reliable, predictable revenue you can count on to understand how much cash you’ll have down the line. However, you also very likely have one-time charges or service revenue. This could look like an implementation fee for a new customer, a charge for an ad-hoc project, or revenue from a month your customer needed a little extra one-time service. Whatever the situation may be, you need to make sure you’re classifying this separately than your typical recurring revenue. Certain metrics will analyze your recurring revenue while others will take into account your total revenue, and you need to be able to easily pull the data for each.
As mentioned in #4, a centralized platform is ideal for all your teams to systematically record and report your data. However, we understand that due to budget and resource limitations, this may not be a viable option. Meet across teams regularly to ensure you’re all on the same page with recording and handling customer data. Take the time to share reporting and other findings from your data with your teams so that they can see the effectiveness of their inputs. Contextualize the process for everyone by sharing how the data contributes to reports and metrics. Make sure you have a system in place to share your reports with your team and board so that your data is telling the story of your growth and efforts.
While cleaning up your data might seem like a big task, every minute you spend doing so will pay in dividends, saving you hours of backtracking, manual fixing, and frustration down the line. If you’re feeling overwhelmed, no worries! Our team of finance experts are ready to work with you to get your data in good shape. Drop us a line to start putting your best foot forward today!