Moderated by Jane, a financial technology consultant at Hyperbots
Jane: Hello, everyone! This is Jane, a financial technology consultant here at Hyperbots, and today we are joined by Dave Sackett, who is the VP of Persimmon Technologies. Welcome, Dave. Thank you for joining in.
Dave Sackett: Yeah, thanks, Jane.
Jane: Let’s dive straight into it. The topic we’ll be discussing today is revenue heads in the chart of accounts. This topic is critical for effective financial management and strategic decision-making in any organization. To start, can you please tell us why structuring revenue heads properly in the chart of accounts is so important for organizations, especially across different industries?
Dave Sackett: Yeah. So what you have are compliance issues, and different stakeholders need to know revenue accounts to manage the business properly. Depending on the industry you’re in, it can vary significantly. If you’re a SaaS company, you’re looking at usage, internet clicks, etc. If you’re a manufacturing company, you have product revenue. In a service company, the revenue structure differs again. So, regardless of the industry, you may have vastly different ways to look at revenue.
Jane: Understood. What are some common mistakes or errors accountants make when creating revenue heads in the chart of accounts?
Dave Sackett: People who like data often want everything at their fingertips. They might create a revenue structure with very tight granularity, capturing every detail. But in reality, it works better to have a simplified chart of accounts and use other reports for additional details. This helps focus the audience on the right revenue and keeps everyone on target. When you have new business lines or revenue streams, that’s the right time to expand how you look at revenue.
Jane: Got it. Can you share some best practices for structuring revenue heads to avoid these common mistakes?
Dave Sackett: Yep. You want to meet with your stakeholders and figure out what your end product and reports will look like, and who needs the data. It may be for regulatory compliance or reporting to a parent company that consolidates results. Revenue tracking can be critical, especially for accounting eliminations. It’s important that everyone is on the same page when it comes to revenue, and you want to avoid overcomplicating it.
Jane: Understood. How can AI help improve the management and structuring of revenue heads in the chart of accounts?
Dave Sackett: Luckily, we’re in the age of AI, where advancements are happening quickly. AI can support you not only in creating revenue accounts but also in analyzing revenue changes, performing flux analysis, and digging into variances. So, AI has become almost a partner in accounting and finance. Focus on the problem first, then see how AI can support it. As technology progresses, AI’s ability to help will only increase.
Jane: Understood. Can you provide an example of how a specific industry, such as retail or manufacturing, benefits from an AI-validated chart of account structure for revenue heads?
Dave Sackett: Yes. I work in a manufacturing company where we make robots. AI helps us by analyzing variances and providing guidance on whether transactions are going to the correct accounts, or if revenue should be structured differently. AI can alert you if you have transactions that look incorrect based on descriptions, helping guide you in setting up revenue accounts and suggesting whether to add or consolidate accounts. It’s like having another set of eyes to assist in your accounting work.
Jane: Got it. How often should organizations review and update their revenue heads in the chart of accounts, and what factors should trigger these reviews?
Dave Sackett: Right now, I’m transitioning to a new ERP system, which is a great time to revisit revenue categorization. My goal is to keep things simple and basic, and as the business grows and new revenue streams come in, we’ll add accounts but starting with a strong foundation and adding as necessary is key. I wouldn’t recommend changing revenue categorizations frequently, but major milestones like a new compliance report or a new product or service might trigger a review. If no major events occur, an annual review, perhaps during budget planning, is a good rule of thumb.
Jane: Understood. Finally, what advice would you give to CFOs or financial managers looking to optimize their revenue structures in the chart of accounts?
Dave Sackett: Look to the future. Consider tools available today that weren’t available two or five years ago and see how they can help you. AI is very powerful now, especially with advancements in large language models. These AI systems can now really understand your business, and you can train them to support your efforts in tracking revenue.
Jane: Understood. That’s it. Thank you, Dave, for sharing your valuable insights on managing revenue heads in the chart of accounts. Your guidance will surely help many organizations optimize their financial structures and enhance their decision-making processes.
Dave Sackett: Great, thanks, Jane.
Jane: Thank you.
Moderated by Emily, Digital Transformation Consultant at Hyperbots
Emily: Today’s discussion is special as I have John with me. John is the CEO at LiveData LLC, and today we will talk about the journey of automation in the past versus now, especially in the finance and accounting segment. So, before we begin, John, do you mind telling us a little more about yourself?
John: Yeah, no problem. Thank you for having me. It’s a pleasure, and it’s a topic that I love to talk about how to automate. I’ve been involved in this field my entire career. It started with Excel sheets and figuring out how to make them work as simply as possible. As technology evolved, I was able to utilize it more. Now, running LiveData LLC, we help companies with finance automation and process improvements throughout their business.
Emily: Thank you for the introduction, John. You’ve said that you’re a firm believer in the power of automation, and over the last decade, you have spearheaded many automation projects in various organizations. Can you summarize some of the automation projects you’ve implemented?
John: Sure. The biggest projects have focused on enabling finance personnel to work on tasks that add real value instead of just pulling together reports. Initially, I built Excel models using Hyperion, analytics, and financial reporting to simplify data processing. Then, we moved to more automated processes using bots and tools like UiPath for repetitive tasks, such as invoice processing, to eliminate manual data entry. With the advent of OCR technologies, we further reduced manual intervention. Now, I’m excited to be working with HyperBots on AI automation, which is the next generation of finance automation.
Emily: That’s amazing. John, we see a lot of AI buzz today with claims of AI transforming business operations. What is your take on that?
John: The buzz around AI is justified because we can now utilize it in ways we never could before. It’s not just about making machines more intelligent but about processing all the available data both web-based and internal to provide higher-quality answers and insights. Tasks that used to take weeks can now be completed in minutes.
Emily: I agree. What have you been hearing in your peer group about the possibility of AI transforming finance and accounting processes?
John: It’s a critical time for finance and accounting to adopt technology. Historically, finance professionals have relied heavily on manual processes, but now, with the shortage of accountants and the complexity of tax laws and transaction volumes, it’s essential to adopt the latest technologies. Those who don’t adopt will likely fall behind their competitors.
Emily: From a business perspective, what impact does modern automation have compared to traditional methods?
John: Modern automation tools can go beyond just pulling numbers they can provide natural language feedback, synopsis, hypotheses, and suggest areas for further investigation. In the past, tasks like data processing could freeze your computer or take a day to complete. Now, we can get real-time, insightful feedback.
Emily: Can you give some examples of intelligent tasks that weren’t automatable before but are now possible with AI?
John: One example is the variance analysis. In the past, tools like Hyperion automated reporting but couldn’t provide insights about the data. Now, AI can analyze variances and suggest reasons, such as changes in volume or price. It can even correct data inaccuracies and highlight potential issues.
Emily: Let’s talk about invoice processing. Can you elaborate on how AI improves this task?
John: Previously, invoice automation struggled with inconsistencies and required manual data correction. Now, AI can understand invoice details even if they aren’t perfectly formatted, extracting information like amounts, tax details, and vendor names, and suggesting appropriate accounting actions. This reduces the need for human data entry and improves accuracy, allowing accounting staff to focus on review rather than data correction.
Emily: We’ve certainly come a long way. Why wasn’t this possible before, and what has changed in the technology landscape?
John: The biggest change has been the increase in computing power, enabling us to process vast amounts of data in seconds. Previously, tasks like reserve calculations could take 18 hours and weren’t feasible to run frequently. Now, we can run these calculations daily and get real-time insights.
Emily: Are there tasks in accounting that will always require human intelligence?
John: Absolutely. While AI can make us more accurate and efficient, it can also produce errors or hallucinations that need human oversight. Strategic tasks, especially those involving future planning with no existing data, will always require human intelligence and creativity.
Emily: What are the differences between traditional automation and AI-led automation?
John: Traditional automation required exact processes and rigid programming. AI-led automation is more flexible, can learn from other data, and suggest new ways to improve processes without needing explicit programming. However, we must be cautious of information overload and potential errors from AI.
Emily: What challenges do you foresee for CFOs in adopting AI-led automation?
John: There will be challenges, just like with any new technology. One major issue is ensuring data security and accuracy. AI can sometimes produce incorrect results, and if trusted too much, this could lead to significant errors in financial statements. It’s crucial to balance adoption with oversight.
Emily: How do you see AI-led automation impacting finance and accounting over the next two years?
John: Adoption will be rapid due to the shortage of accountants and the need for efficiency. We’ll see tools becoming smarter and more integrated into daily operations. Companies that adopt AI will likely experience fewer errors and greater efficiency, while those that don’t may struggle to keep up.
Emily: Any advice for CFOs who are unsure about exploring AI for their operations?
John: Start by talking to your current vendors and exploring how they are integrating AI into their platforms. Stay current by reading about the latest developments in AI. Consider bringing in consultants or experts to demonstrate how AI can benefit your specific needs. It’s essential to understand and embrace AI to remain competitive.
Emily: Thank you so much for sharing your insights, John. This discussion on the evolution of automation has been enlightening.
John: Thanks for having me.