Part 9 in the “Continuous Accounting Action Plan” series
So far in our series, we’ve discussed various steps to execute a continuous accounting action plan, from quick wins to big wins, controls to analytics. Like any finance transformation journey, people and process play a major role. It’s about having the vision and courage to step back and look at an existing process and ask if it really is the most scalable and efficient process going forward, while also challenging the finance and accounting team not to simply settle for the status quo.
But moving towards continuous accounting requires technology. Depending on your organization, your people, and your processes, different technologies may help your transformation toward continuous accounting. Let’s discuss three areas you might consider investigating: automation, scheduling, and monitoring.
Automation: basic and advanced
The term “automation” is bandied about often. But what’s changed in recent years is the complexity of tasks that can be automated. Let’s break it down to clarify basic and advanced automation.
Let’s start with the basics. A calculator is an automation and, stepping up, so is a spreadsheet. But basic automation in this context is all about automating rote, repetitive tasks. Many journal entries are done manually; by leveraging technology they can be automated. Consolidation calculations can be automated, including reconciliations, eliminations, and essentially any calculation that is done every period for the close process. It’s all about implementing purpose-built functionality that is designed to automate specific, repetitive accounting tasks. The difference with this level of automation from years past is that accounting can easily configure the rules themselves, rather than relying on consultants. Manual spreadsheets should be replaced with software that is designed for automation of accounting processes.
Then there’s the more advanced automation stuff. This is where technologies like machine learning (ML), predictive analytics (PA), and artificial intelligence (AI) come into play. They don’t simply apply one-size-fits-all logic; instead, they can look at prior decisions, patterns in data, or results and make decisions based on what they have learned. Historically, a data scientist might be employed to develop algorithms or do sophisticated analysis on data sets. Today, with better, faster access to bigger volumes of data, much automation comes out of the box. It’s all about anticipating outcomes. You can use predictive algorithms and machine learning to assess the likelihood of future outcomes and steer your business in the right direction. Again, depending on your organization, your people, your processes, and your requirements, the possibilities of these advanced automation tools are limitless.
Scheduling: supervising automation
Long gone are the days of scheduling tasks using batch scripts or simply time-based scheduling. Think of today’s scheduling technology as almost like an “automation supervisor,” overseeing tasks, deciding what should be performed next, considering dependencies, and then kicking off those tasks based on what needs to happen next. Today’s scheduling technology provides a cockpit where accounting can watch how the overarching schedule is proceeding, such as the financial close.
Modern scheduling is visual, and it enables accounting to make changes to the process at the end of or during the period. It enables accounting teams to change the actual overarching process itself and the sequencing and dependencies. It’s an essential tool for moving to continuous accounting.
Monitoring: putting accounting in the driver’s seat
Automating and scheduling at scale used to be much harder to do. The process often required IT and consultants to get everything set up and working properly. The two technology capabilities we’ve discussed help accounting achieve them without creating baggage and maintenance. But the old way of automation used to come with another problem: lack of visibility in the process, which often doesn’t provide reporting and analytics on the health of the process. This issue causes a lack of ability to identify opportunities for improvement. Often the results were buried in log files, email alerts, or simply not even logged at all.
Modern monitoring technology changes all that. At a granular level, it supports audits by recording the output and history of all tasks performed (and who did them) to ensure tasks don’t fall through the cracks – which is especially important if the organization is undergoing finance transformation. However, monitoring is also vital for continuous improvement. Coupled with reporting and analytics, it can provide a clear perspective into opportunities to improve, such as whether the corporate close is often delayed waiting for a certain local-entity file, and in turn, where the delay is in that entity’s close. Monitoring provides accounting with the toolbox needed to understand the integrity of the process and to identify and make the case for where to apply continuous improvements.
Beyond accounting: How FP&A can apply a continuous approach
In the next blog, we’ll be covering how a continuous approach can be just as readily applied to common financial planning and analysis (FP&A) activities. We’ll also examine how accounting and FP&A can partner to build a data supply chain, continuously flowing data from accounting to model, and plan on the results.