The most cumbersome part of any close process is gathering the data needed to accurately report on month-end, especially when that data is stored across disparate systems. If conducted well, month-end close is an intricate balance of accuracy and timeliness, especially when dealing with pressure from the finance team to deliver results as soon as possible so they can generate projections and forecasts, or when pressured to hit close benchmarks of 5 days or less.
If you’re like most accountants, you find yourself caught in the same vicious cycle every month. It looks like this:
Sound about right?
This approach leads to challenges further down the road and doesn’t hit Accounting’s goal for timeliness and accuracy. The typical month-end close process frequently doesn’t deliver accurate, compliant results, making audits more challenging. Auditors put pressure on Accounting to defend the numbers and show their work. However, this is difficult because the numbers are in dozens of spreadsheets, and there is no way to cleanly showcase the calculations that went into the final numbers. If auditors find a mistake in your numbers, you need to restate them, which isn’t a great way to manage perception to investors and the board.
Manually reviewing and reconciling transaction data when dealing with high volume is tedious, time-consuming, and frequently error-prone, leaving little time for tracking discrepancies in the data. This process often leads to accounting burnout. To address these challenges without overburdening yourself or your team, you must first solve your data workflow problem to deliver accurate month-end on time, alleviating audit woes and pressures from your Finance team. Below, we’ll explore some potential strategies to help you improve your data processes and ease reporting.
Here are some strategies that can help you manage and consolidate your transaction data to ease month-end:
One way to ease data challenges is using a centralized data warehouse to aggregate transactions from multiple systems. Data warehouses are unified storage systems that enable you to aggregate and analyze data. For example, if you process transactions in your Apple App Store, Stripe, and PayPal, you can pool all of this data in a data warehouse and analyze it in one place. Within the data warehouse, you can perform necessary month-end close tasks, like applying rules on top of the data to adhere to compliance or reconcile transactions. In addition, you can use data warehouses to conduct historical data analysis to track trends and behaviors over time.
Unfortunately, data warehouses also have significant drawbacks that you need to consider before you leap in. While great for aggregating data from multiple sources, data warehouses are primarily built for analytics, not accounting. Frequently, data warehouses overwrite historical data if new data comes into the system. Moreover, data warehouses are often inaccessible by accountants, requiring a deep understanding of SQL queries to extract the data you need out of the system. Architecting the data warehouse to suit your business needs can also suck up valuable IT resources and put an extra burden on IT to maintain the system to integrate new systems and incorporate new product lines.
To use the data in the data warehouse, finance teams usually opt for a business intelligence add-on or third-party system to help them visualize the data or create reports they need for month-end.
A business intelligence (BI) solution can help you organize and visualize transaction data within your data warehouse or from disparate systems. With a BI solution, you can establish relationships between related datasets, set up reconciliation reports across different types of transactions, and view all of your transaction data in a tabular format so it’s easy to digest. Once the transaction data is aggregated in the BI system, you can then use it to create dashboards like a journal entry report or view cash outflows and inflows in the business.
While a BI tool can help you centralize your data and report on it, one of the things it may not be able to do natively is standardize your data to a singular reporting currency. Some BI tools need information on the currency conversion rate through an API, data file, or other source to do so. Moreover, setting up your BI solution for Accounting needs requires support from an analyst who is well-versed in connecting data sources into the system, setting up complex formulas, rules, and relationships between the data points, and maintaining the system. As your business grows and you add more products into the mix, you’ll need to constantly update the system to account for new products and accounting rules.
Another way to manage the data process internally is to set up a process using spreadsheets and detailed documentation outlining your month-end close process and transaction rules. In this documentation, you can outline how data needs to be organized in source transaction systems and in which format to make it easier for Accounting. For example, you can suggest custom fields within a payment processor for when returns or disputes come in. Then, you can designate a member of your team to comb through returns and map them to the original payment throughout the month so that reconciliation is easier. You could also establish a weekly reconciliation process to speed up the process at the end of the month.
In addition, you could also document policies and controls the team must follow while they prepare for month-end. These policies can include information on compliance rules that must be applied to different transactions as part of the reporting process. Once you have the documentation in place, you can train the team to follow a close checklist stored in a workflow or project management tool to ensure everyone on your team follows the process, approvals, and steps to get there.
Unfortunately, while it may seem that a checklist and documentation will get you to a seamless close process and help you get ahead of your data process problem, the challenge of consolidating the data in one place in a standardized format remains. Even if you try to stay on top of your reconciliation process or fill in the gaps in your data continuously, given the large volumes of data in your systems, you'll still be left behind. Since the process is relatively manual, creating a workflow and documentation still doesn’t eliminate the risk of human error. You may think you’ve filled in all the data gaps or appropriately reconciled the data. However, you may still accidentally forget a chunk of data during consolidation.
Consolidating transactions, especially when dealing with millions of rows of data, can feel like an impossible challenge. There always seems to be a snag in the process, and you can never be too sure that you’ve captured every transaction flowing through your business. Moreover, despite seemingly appealing solutions like data warehouses, BI tools, and workflow solutions, the process doesn’t seem to get less manual. There are no real guardrails to trust that the data you’re accounting for is accurate and complete.
The best way to address these challenges is through automation, which can help you consolidate, standardize, and enrich your transaction data with crucial details and relationships in one place. What is the name of the automation solution? Leapfin. Leapfin helps Accounting teams transform transaction data from multiple sources into unified accounting records and balanced journal entries.
Leapfin offers several features that can help you standardize and enrich your data:
The first step to data consolidation is ensuring it lives in one centralized location. Leapfin automatically integrates with systems like payment processors, order management systems, billing systems, and mobile app stores. Leapfin also imports all relevant transaction data into its centralized, easily accessible repository.
Complex transactions, like payments and returns or payments, disputes, and chargeback fees, are frequently the most challenging to reconcile. What if the data isn’t reconciled correctly or appropriately linked to the initial transaction? This can lead to multiple downstream effects like inaccurate journal entries and difficulty defending the number to auditors in the future. Furthermore, depending on where transactions come from, transaction data may not have crucial details necessary for reporting, such as the type of subscription a customer purchases, monthly or annual, or the product type. This lack of detail makes it nearly impossible to report data with 100% accuracy.
This is why Leapfin enables accountants to create enrichment rules: to ensure that data contains crucial details necessary for accounting and to generate accurate, complete, balanced journal entries. With data enrichment rules, Accounting teams can create and manage rules to transform raw transactions into accounting-ready records by adding rules:
Turning transaction data into reportable records is often another close challenge at the end of the month. Even if the data is reconciled, linked to related transactions, and converted into the reporting currency, it must be stored in a standardized, accountable format to ease subsequent steps of the close process, like recognizing revenues accordingly in journal entries. To address these challenges, Leapfin offers the Universal Accounting Record, which displays every transaction in a unified, customizable format.
With the Universal Accounting Record, users can view everything they need to audit the transaction and answer questions about transaction details:
With Leapfin, you don’t have to worry about errors in your data consolidation workflow or how to standardize your transactions into a reportable format. We can automate that for you and every step in your month-end close that comes after, including journal entry reports, subledger creation, data analysis, and more.
Ready to consolidate your transaction data and automate the rest of your month-end close process? Request a demo today.