Moderated by Sherry, Financial Technology Consultant at Hyperbots
Sherry: Hello, and welcome to all our viewers on CFO Insights. I am Sherry, a financial technology consultant at Hyperbots, and I’m very excited to have Shaun Walker here with me, who is a seasoned internal audit leader with a wealth of experience in driving risk management, compliance, and governance initiatives across diverse industries. Thank you so much for joining us today, Shaun.
Sherry: Today we’ll be talking about handling sales tax verification for invoices with multi-destination shipments. To get us started with the interview, how do Hyperbots handle invoices with line items shipped to different destinations?
Shaun Walker: It’s an AI tool that treats each line independently. It identifies and extracts its unique destination address from the invoice with the shipping details, and this allows it to apply specific tax rates based on where each item is shipped. For example, if office furniture is shipped to New York and IT hardware shipped to California, Hyperbots will process each one separately and ensure that the correct tax rate is applied based on the destination.
Sherry: What role does state and local tax information play in Hyperbots’ tax verification process for multi-destination shipments?
Shaun Walker: State and local taxes vary widely. Hyperbots pulls data from data dictionaries for each destination and references both state and local tax rules. For instance, if New York has an 8.875% combined state and city tax rate for certain goods, and California has a 7.25% state rate, Hyperbots applies these distinct rates accurately for items shipped to those locations, ensuring compliance with each jurisdiction’s tax laws.
Sherry: To dive deeper into the topic, can you explain how Hyperbots manages the categorization of each line item for tax purposes when items are shipped to multiple states?
Shaun Walker: It categorizes each line item based on its product type and applies relevant tax rules to each destination. For instance, a software license delivered digitally to Texas might be exempt, whereas computer hardware shipped to California would be taxable. Hyperbots reference these tax distinctions and apply the correct tax treatment.
Sherry: How does Hyperbots address tax thresholds in different states for multi-destination shipments?
Shaun Walker: Some states impose tax collection only after certain purchase thresholds are met. Hyperbots track cumulative purchases to each state and apply tax once the threshold is reached. For example, if California requires tax only after $500 in cumulative purchases, Hyperbots will monitor the total spend per California and begin applying tax once the threshold is met.
Sherry: How does Hyperbots verify and correct any tax discrepancies for invoices with multiple shipping destinations?
Shaun Walker: Hyperbots verifies each line item’s tax application independently and flags discrepancies if the tax code doesn’t match the destination’s requirements. For instance, if a vendor applied a flat tax rate across all items shipped to different states, Hyperbots would detect this and recommend the correct rate for each location. This real-time validation minimizes errors.
Sherry: Could you summarize the main benefits of using Hyperbots for tax compliance on multi-destination shipments?
Shaun Walker: Hyperbots offers end-to-end automation. It ensures compliance with state and local tax laws for each destination without any manual intervention. It accurately categorizes and applies tax rates for each item, reducing the risk of error, saving time, and preventing compliance issues. For example, if an invoice has items shipped to three different states with unique tax rules, Hyperbots handles these seamlessly, delivering accuracy across all jurisdictions.
Sherry: Thank you so much for that insightful conversation, Sean. It’s clear that Hyperbots is quite the tool for robust handling of sales tax verification for invoices with multi-destination shipments.
Shaun Walker: Absolutely.
Moderated by Mayank, Marketing Manager at Hyperbots
Mayank: Hi, everyone I am Mayank, the marketing manager at Hyperbots. I am pleased to have Claudia Mejia on the call. Claudia is the managing director at Ikigai Edge. Thank you for joining us today. We are here to discuss the level of visibility companies should provide to the vendors during the invoice processing workflow. Let’s start with the basics. So why is vendor visibility in the invoice processing workflow important for a company’s financial operations?
Claudia Mejia: Hi, Mayank, thank you for having me. Well, it’s very important, because it impacts vendor relationships in any company. We want to make sure that our vendors are content, and for that, we need to provide efficient processes and make sure that processes align with the terms set with the vendors. So we just need to make sure that the process remains smooth and timely.
Mayank: Awesome. So basically, there are two primary approaches to vendor visibility: full transparency versus high-level updates. Could you explain these two approaches?
Claudia Mejia: Full transparency means you communicate to the vendor the stages of the invoice process, from the moment it’s received, through reviews, approvals, and finally payment. The vendor knows exactly where they are in that process. However, high-level status is more about giving them key updates, like “We’re in the review stage” or “You’ll be paid on this date.” It doesn’t delve into all the details, just gives them a sense of when they can expect payment. Ultimately, vendors want to know when they’re going to get paid.
Mayank: Awesome. So, what do you see as the primary advantage of providing full transparency to the vendors?
Claudia Mejia: It’s about trust at the end of the day. Transparency builds trust, and that’s crucial in any organisation, especially in vendor relationships. When you’re transparent, it reduces the number of inquiries you might receive from vendors. If you have a system in place to provide that information, it also saves time for the team processing invoices since they deal with fewer inquiries.
Mayank: Got it. So, what are the potential risks or downsides of this full transparency approach?
Claudia Mejia: Well, there’s always a balance. Full transparency can lead to information overload, exposing processes to vendors that might not need to be shared. This could reveal vulnerabilities in your systems or processes. Sometimes it’s just unnecessary to show all the details. There’s always a balance between what the vendor needs and what they don’t need to know.
Mayank: Got it. Conversely, what are the benefits of sticking to high-level updates?
Claudia Mejia: It minimises the effort required from the team to process the invoices. The key is to communicate around important milestones. As long as you fulfil the terms of the contract, that’s what matters most.
Mayank: Got it. Do you think there’s a risk of vendors feeling dissatisfied with high-level updates due to a perceived lack of transparency?
Claudia Mejia: Honestly, I haven’t seen that in my experience. As long as communication is clear and expectations regarding terms and payments are laid out, most vendors are satisfied. Issues tend to arise when you go beyond those terms and fail to explain a delay in payment. Being proactive when you can’t meet the terms is key. Otherwise, I’ve found that vendors generally understand the process as long as it’s efficient.
Mayank: Got it. So, in terms of communication and collaboration, what methods do you recommend to ensure effective interaction with vendors regarding invoice status?
Claudia Mejia: One effective method is having a vendor portal. Through the portal, vendors can view their invoices and where they are in the process. Of course, this requires a system that tracks those stages. Alternatively, providing key milestones, making sure you meet the terms of the contract, and offering clear lines of communication—such as a contact person, phone number, or email address—are essential. Vendors should always have someone to reach out to for inquiries and like I said, be proactive. If there’s an issue with payment, let them know in advance.
Mayank: Got it. Finally, how can AI play a role in making the invoice processing workflow more efficient for both companies and vendors?
Claudia Mejia: AI can automate many tasks that are currently done manually. AI can automatically send notifications and, through predictive analytics, anticipate certain events. AI can handle standard inquiries via chatbots, providing information that doesn’t necessarily require human intervention. Ultimately, it’s about making sure vendors have the information they need, whether through AI or by speaking to a person when necessary. AI can streamline processes significantly, but there will always be situations where human interaction is needed. AI won’t solve all our problems, but it can definitely make processes more efficient.
Mayank: Totally agree with you, Claudia. Thank you for sharing your insights. It’s clear that balancing transparency with efficiency is key to maintaining strong vendor relations while protecting the company’s interests. Thank you so much, Claudia, for your time. It was really insightful.
Claudia Mejia: No, thank you very much. Thanks for having me.
Mayank: Thank you.
Moderated by Sherry, Digital Transformation Consultant at Hyperbots
Sherry: Hello, and welcome to all our viewers on CFO Insights. I am Sherry, a financial technology consultant at Hyperbots, and I’m very excited to have Claudia Mejia here with me, an experienced finance and operations leader, with over 15 years in finance, operations, project management, and driving businesses towards efficiency, innovation, and strategic growth. Thank you so much for joining us today, Claudia. Date format variations in financial documents can lead to significant challenges in global operations. Let’s delve into this topic with a focus on understanding the issues, best practices, and how AI can help. Could you explain how date formats vary across different financial documents and regions?
Claudia: Hi, Sherry, thank you for having me. Yes, this is an important subject, especially now with the era of AI. I think let’s explain a little bit about how the formats are different across regions. In the United States, we usually use the format of month, date, and year, while in Europe or Latin America, they use the date, month, and year. In Asia, they use year, month, and day. So with all these variations of format, it’s complicated for people in general who manage documents. Data entry becomes complicated and is prone to errors. It’s important to make sure there’s standardization because these inconsistencies can create issues with accuracy and all kinds of consolidation problems.
Sherry: And before we move on to best practices, let’s touch upon the obstacles. What are the primary challenges organizations face when dealing with these variations in date formats?
Claudia: Well, there’s the risk of misinterpretation, right? I can interpret one format as the month, the year, or vice versa. This creates not only payment process issues, but also contractual, legal, and compliance issues. The first step is understanding how we’re going to interpret formats and how we can standardize them in a way that the whole company, especially global companies, can execute properly.
Sherry: From your experience, can you share any real-world examples where date format issues caused significant problems?
Claudia: Yes, for example, in a global company, let’s say a vendor in Europe sends an invoice to be processed using their format. They might put the date first, then the month, then the year, like 8/7/2024. In the United States, we might interpret that as August 7th, while they meant July 8th. This creates late payments, penalties, and issues with cash management, which is crucial for any company. It’s important to ensure there’s standardization across all regions to avoid such issues.
Sherry: To overcome these challenges, what best practices do you recommend for managing date format variations in financial documents?
Claudia: One standardization that’s widely used is the ISO 8601 format, which follows year, month, and day. This eliminates ambiguity. It’s also important to create validation rules in financial systems to correct issues before invoices and documents are fully processed. Training everyone who handles documents, including contracts, is crucial. Educating vendors about the formats your company uses also helps establish standard practices.
Sherry: Since AI is the future, how do you see AI playing a role in addressing these challenges?
Claudia: AI can detect and monitor date formats, automatically correcting them. As systems learn, AI can catch errors before data enters the financial system. AI can also address issues like when people accidentally enter the wrong year, for example. It can correct these mistakes automatically, which is something humans often miss.
Sherry: What are the potential risks if an organization fails to address date format inconsistencies?
Claudia: If companies don’t address this, they risk missing payments or deadlines, which damages trust with vendors. This can create compliance issues, complicate audits, and waste time resolving unnecessary problems, adding no value to the company.
Sherry: Could you share some insights into how AI-driven solutions are currently being used to manage date formats in global financial operations?
Claudia: Many companies use OCR (optical character recognition) to capture data, which is a machine learning technology. AI can learn and predict potential errors, helping to mitigate issues before they arise. AI can also correct problems before the data enters the ERP system, ensuring accuracy.
Sherry: Makes sense. Looking forward, how do you see the role of AI evolving in managing financial document processes, particularly concerning date formats?
Claudia: AI will drive efficiencies in data capture and system learning for document processes. Companies adopting AI will see increased automation, with AI capturing, correcting, and pushing data into ERP systems without human intervention. Human checks can still be incorporated, but AI can handle most tasks end-to-end, which wasn’t possible before because the technology wasnt advanced enough to learn independently. AI can bring great efficiencies and accuracy, but companies must also maintain proper controls.
Sherry: Thank you so much for being here, Claudia, and for sharing your insights. It’s clear from this conversation that addressing date format variations is crucial for maintaining financial accuracy, and that AI offers promising solutions to these challenges.
Claudia: Thank you very much, Sherry, for having me. It’s always a pleasure.
Moderated by Riya, Digital Transformation Consultant at Hyperbots
Riya: Hi, everyone! This is Ria, and I’m very excited to have Mike join us on call today. Mike is a CFO consultant and strategic advisor to many privately held organizations. The topic of discussion for today is goods versus services and the similarities and differences between them when it comes to purchases. So to start off, Mike, would you share your thoughts on the key differences between purchasing goods and services in a typical organization?
Mike: Sure. Thanks. Yeah. So let’s focus on that. It depends on the size of the organization, a big company versus a small company. But let me focus on the general process and how the goods and services differ. The goods would be more on tangible property, where you need to have a specific quantity, specific price, and specific quality of the product you require. It depends on whether you’re buying the raw material or you’re buying the machinery or equipment. It all depends on whether you’re buying for a fixed asset or an inventory. What services would be different? It’s more on the intangible nature, like consulting services, temporary labor, or high-level consulting. It depends on the expertise required, and the level of people needed. The goods are more tangible and measurable, while services are milestone and delivery-based, often tied to hours or retainership agreements. These are the main basic differences between goods and services.
Riya: Got it. So in terms of terms and conditions for procurement, how do they differ between goods and services?
Mike: For goods, as I said, you need specific quantity, quality, and specifications. When you purchase something, you need to ensure that you have specific quantities and specifications, including delivery timing and any maintenance if you’re buying fixed assets. Services can include follow-up services, installation, or after-sales support. On the services side, it’s more about expertise, confidentiality, and deliverables. Milestones and performance levels need to be clearly outlined, including time and labor-based or lump sum agreements. These are the key differences in terms and conditions for goods and services.
Riya: Got it. So would you like to explain when it comes to pricing? How do the considerations differ between goods and services, especially when you’re negotiating with a vendor?
Mike: Goods pricing is largely market-driven. It depends on market rates, supply and demand, and the economic environment. Bulk purchases often allow for negotiations on price and discounts based on payment terms. Services, on the other hand, depend on labor costs and expertise. You negotiate hourly rates or lump-sum fees based on the level of experience and type of service provided. These are the key differences between pricing for goods and services.
Riya: Okay, so could you elaborate on how the approval processes differ when purchasing goods versus services?
Mike: One commonality between goods and services is the need for cross-functional collaboration. For goods, purchasing raw materials, for example, requires operations, procurement, finance, and legal departments to work together. Services, on the other hand, may involve less cross-functional approval, especially for specific departments like legal services, which can order on their own under certain thresholds. Generally, services may involve fewer approval channels if the department has the budget and authority.
Riya: Got it. How does the receiving process differ between goods and services? And what challenges does this present?
Mike: Receiving goods involves matching the goods received with the purchase order and ensuring quality and specifications are met. You also need to match the goods receipt with the purchase order and invoice. Some goods may require testing or verification, especially with machinery or equipment. For services, the process is different as there is no physical product to receive. It may involve verifying hours worked for contractors or ensuring milestones and deliverables are met. This presents challenges in verification compared to the more straightforward process for goods.
Riya: Thank you. So, Mike, would you like to explain how purchase orders play a role in both goods and service procurement? And how does that differ?
Mike: The purchase order is critical for both goods and services. For goods, the purchase order details specific quantities, descriptions, and timing. For services, it’s more descriptive and outlines the type of service and terms. Services may use blanket POs, where a general budget is set, and departments draw from it as needed. In both cases, the PO serves as a formal document for procurement.
Riya: Thank you. So would you like to explain how invoice processing differs between goods and services? And what are the best practices in this area?
Mike: For goods, invoice processing involves three-way matching: the purchase order, goods receipt, and invoice. You ensure that what was ordered matches what was received and invoiced. For services, it’s a two-way match, between the purchase order and the invoice, as there’s no goods receipt. If contractors are involved, you can also match the time cards with the invoice. For other services, you ensure the department head approves the invoice based on milestones achieved. These are the main differences in invoice processing between goods and services.
Riya: Got it. So, Mike, how does vendor onboarding differ for goods versus services? And what should organizations really focus on?
Mike: For goods, you need to assess the vendor’s reputation, certifications, and production capacity. Supply chain reliability and logistics are key considerations. You want to ensure the vendor can meet your material needs without causing delays. For services, you focus on the vendor’s expertise, reputation, and the quality of their workforce. In both cases, you need to ensure the vendor can meet your organization’s specific requirements.
Riya: Thank you, Mike. So that brings us to the last segment of the interview. What role do you see AI playing in streamlining procurement for both goods and services?
Mike: AI can play a significant role in automating workflows, reducing human intervention, and improving accuracy in areas where companies don’t have sophisticated systems in place. AI can help with compliance, predictive analysis, and market data insights. It can assist in real-time data sharing with vendors and create dashboards to track purchases, vendor performance, and inventory levels. AI can offer customized solutions to streamline procurement processes for both goods and services.
Riya: Thank you, Mike.
Moderated by Emily, Digital Transformation Consultant at Hyperbots
Emily: Hi, everyone. This is Emily, and I’m a digital transformation consultant at Hyperbots today. I’m very pleased to have Niyati join us today, who is the co-founder and VP of AI at Hyperbots. Today, we’ll be talking about invoices, their peculiarities, and the different nuances. Specifically, why is it not so trivial for AI to understand them? So Niyati, let’s start with the basics. What makes invoices peculiar?
Niyati: Thanks, it’s always great to be talking to you. What is an invoice? An invoice is the main document or the mode of communication for any accounts payable process or AP process. These invoices contain information about what payment needs to be made between a vendor and a company. It includes addresses, identities, goods or services that are being invoiced, and, of course, the amounts and other related information.
Emily: That’s quite a lot of information, right? All of this is usually put in a single format. So it’s all very structured, and the invoices look the same, correct?
Niyati: No, not really.In fact, an invoice by nature is unstructured. Every vendor may have their own way of representing an invoice. It’s not only about how it’s laid out on the page or multiple pages; it’s also about the format in which it may be communicated. Sometimes it’s via email, a scan, a PDF, or even an Excel sheet. An invoice doesn’t have to follow a specific structure as long as it communicates the necessary payment information and the details of goods or services being transacted.
Emily: So this would also vary across industries, right? Can you give me an example?
Niyati: Sure! Let’s take the example of a software company. Maybe they’re renting office space. The invoice between the office provider and the software company will likely include the number of seats, infrastructure costs, and similar details. However, they probably won’t have invoices for transportation costs. On the other hand, if we talk about a manufacturing firm building machinery, their invoices might include transportation costs for different parts of the machinethings like weight, transportation charges, and other associated costs. So, depending on the nature of the business and the industry, invoices can vary significantly.
Emily: Got it. So, industry verticals have a huge impact. Now, can you explain the part of the invoice that contains the actual amounts and item details? What’s challenging there?
Niyati: That’s a great question. Line items the part of the invoice that lists what’s being invoiced for are core to the document. They show things like I gave you 100 apples at this rate, and this is the cost. Line items can also define product codes. For example, an electric bulb manufacturer might offer different types of bulbs, and the line item would define which specific bulbs were delivered. It can also include things like labor charges, such as a service invoice saying, Service provided by person X at rate Y for 30 hours a week. The AI needs to understand that each type of line item has different unit prices, net amounts, taxes, or discounts. The tabular format of these line items determines the final amount or transaction between companies.
Emily: So an invoice will just have one table, right? Can’t we build models to understand that single table?
Niyati: Not necessarily! An invoice can have as many tables as needed. For example, I might decide to show basic goods in one table, additional charges in another table, and vendor identity information in a third table. Someone else might combine all this into one table, or display vendor information as text, the items in a table, and fuel charges as a subscript. So, there’s no rule about just having one table in an invoicethere can be many.
Emily: If I understand correctly, then the industry, document format, and layout of the line items all make invoices quite complex for AI to interpret, right?
Niyati: Exactly. Invoices are semi-structured business documents with a mix of well-written language, codes, and numbers all together.
Emily: What about the small subscript text often found in invoices? Is that important, and can AI models understand it?
Niyati: Yes, it is important. Just like when we sign things online without reading the fine print and later realize we’ve agreed to monthly charges, subscripts in invoices are critical. They can cover things like payment terms, penalties, discounts, or conditions that have already been agreed upon. However, understanding them is hard for AI. AI needs specialized models because subscripts can be tiny and difficult to read, and standard OCR (Optical Character Recognition) struggles with that. You need enhanced extraction capabilities for the AI pipeline to first read the subscript text. After that, the AI needs to interpret the details like if a payment term says a penalty applies if not paid by the due date, and interest is charged monthly, AI has to calculate all of that.
Emily: I get the part about discounts and penalties, but isn’t text extraction from invoices something OCR already solves?
Niyati: OCR does help, but only to an extent. It’s an established technology, but it’s not always adapted to every scenario. For instance, OCR might struggle with crumpled paper or tables that aren’t read left to right. In some invoices, information like the invoice ID is written vertically rather than horizontally. Just like humans need to tilt their heads, AI needs to do the same. Standard OCR won’t handle that well, so there’s still some work to make it usable for finance and AP processes.
Emily: I didn’t realize there were so many practical challenges involved, It seems like even just reading an invoice requires expertise.
Niyati: Yes, exactly! That’s why it’s so interesting. Out of curiosity, let’s say I have a really advanced AI that solves all these problems. Would invoice understanding be easy then? Not quite. You’d still need a finance-minded perspective or expertise to fully understand invoices. Let me give you an example: If I show an invoice to a layperson, which is similar to showing it to an AI that doesn’t understand these nuances, certain things won’t make sense. For example, if there’s a term like “1% 10, net 30” on the invoice, it may look like a code. But to an accountant, it means if you pay within 10 days of the invoice date, you get a 1% discount. If not, the full payment is due in 30 days. So even if the AI is good at reading the invoice, it still needs to be trained in these kinds of accounting-specific interpretations.
Emily: Wow, after hearing you describe all these challenges, it sounds quite overwhelming. At the same time, it’s really exciting to see AI solving these problems for finance teams.
Niyati: Absolutely! The technology is finally at a point where we can build specialized models to tackle these challenges. It requires out-of-the-box thinking, experimentation, and intelligent product design, but we’re getting closer to solving this in a way that saves time and money for businesses.
Emily: Thank you so much, Niyati. It was wonderful chatting with you and hearing your enthusiasm!
Moderated by Sherry, Digital Transformation Consultant at Hyperbots
Sherry: Hello and welcome to all of our viewers on CFO Insights. I am Sherry, a financial technology consultant at Hyperbots, and I’m very excited to have Shaun Walker here with me, who is a seasoned internal audit leader, with a wealth of experience in driving risk management, compliance, and governance initiatives across diverse industries. Thank you so much for joining us today, Shaun. We’re going to discuss some important aspects of closing purchase orders and how organizations can improve this process. Now let’s dive right in. Before we talk about the best practices, I wanted to first start by asking you about some of the most common challenges you encounter when closing purchase orders.
Shaun Walker: Sure. So in my experience, some of the main things would be invoices not being matched, there being partial deliveries, items being returned, sometimes discrepancies between goods not received, purchase orders, and often there may be difficult workflows. Depending on the amount or the dollar value of the invoice, there may be several different people that have to approve before getting to the final.
Sherry: Adding on to this challenge, how do unmatched invoices contribute to POs remaining open for extended periods, and what strategies can be used to address this issue?
Shaun Walker: One thing is being able to automatically match those invoices. Having a system implemented that does it where it’s not a manual process and speeds it up. Also, performing regular audits or reconciliations will also make the process more efficient.
Sherry: As we are already talking about strategies, what best practices can be adopted to manage blanket POs and ensure they do not remain open longer than necessary?
Shaun Walker: Being able to track receipts is one thing. Also, having clear end dates for blanket POs would be really good for closing them out in a timely manner.
Sherry: One of the most commonly faced problems in the industry is regarding service POs, which often face challenges in the receipt process. How can organizations effectively manage and close service POs?
Shaun Walker: One thing they can do is integrate a service receipt process within their ERP system. Depending on the company, they’ll have different ERP systems and functionality. However aligning those systems will allow for PO closure, and that will help with the process.
Sherry: About yet another obstacle, how can a lack of diligence in PO creation affect the PO closing process, and what steps can be taken to improve this?
Shaun Walker: A couple of examples, there might be difficulties or complications with closing POs, different delivery, and invoice staging. One of the things that we can do is implement standardized templates and have a detailed approval process, and that’ll enhance the accuracy of the POs as they’re being created.
Sherry: Since AI is taking the finance industry by storm, I have to ask, what role does AI play in improving the PO closing process? And what specific AI applications have proven effective?
Shaun Walker: The great thing with AI is it’s able to somehow predict the future. It can look at data and potential issues. With AI, we can optimize workflows, and create automatic matching, and automatic reconciliation as well.
Sherry: From your experience, can you share some examples of how vendor performance issues have impacted the PO closure? And what strategies can mitigate these issues?
Shaun Walker: Sometimes when products are being delivered, they might be delivered in incorrect quantities, or even if it is the right quantity, it might not be delivered at the right time. Having systems in place that track these things for you, creating less likelihood of human error, is the key to improving the invoicing process.
Sherry: Makes sense, Shaun. What recommendations do you have for organizations or our viewers looking to streamline their PO closing processes and reduce the number of open POs?
Shaun Walker: The main thing is looking at their ERP system to see if there are any updates for optimization. Having a system in place that can perform reconciliations, update workflows, and automatically match these invoices will increase the overall efficiency of the system and the invoice processing in an AP department.
Sherry: Thank you so much for such an insightful session, Shaun. Your views on such notable concerns in the industry are invaluable for organizations looking to enhance their PO closing processes.
Shaun Walker: Absolutely. Thank you so much.
Moderated by Sherry, Financial technology consultant at Hyperbots
Sherry: Hello and welcome to all our viewers on CFO Insights. I am Sherry, a financial technology consultant at Hyperbots, and I’m very excited to have Mike Vaishnav here with me, an experienced finance executive with experience in global operations, strategic leadership, and a proven track record in driving results across finance, M&A, controllership, and corporate strategy in diverse industries. Thank you so much for joining us today, Mike, to discuss the challenges and strategies for matching invoices with blanket purchase orders. First, could you briefly explain the key differences between a blanket PO and a specific PO?
Mike Vaishnav: Sure. Thanks, Sherry. The blanket PO is used for ongoing purchases with a predetermined amount or quantity. It is open for a specific period of time or amount where you’re going to receive goods, but there’s no perfect quantity or fixed price. The amount is set, but the exact quantity for each purchase may vary. A specific PO, on the other hand, is tied to a one-time purchase with a fixed quantity and amount. You know exactly what you want to order, and it ensures that the exact amount of goods or services will be delivered. For example, with a blanket PO, you might decide to buy 1,000 units over the next six months for $100,000. The quantity can come in multiple deliveries, and you would match the quantity received against the PO, such as 100 or 200 units at a time. Another example of a blanket PO is for consulting services or projects. You might set up a blanket PO to cover a specific project with a set budget, including services like legal or audit fees. Payments are matched against the progress of the services rendered. A specific PO, however, is for ordering a specific quantity of goods in a one-time or limited purchase.
Sherry: And given the open-ended nature of blanket POs, how do you approach the matching of incoming invoices with these POs?
Mike Vaishnav: Matching can sometimes be tricky with partial deliveries, but you need to match the delivery of the product or service to the PO. For product-based blanket POs, it’s relatively straightforward you receive 100 units, and you deduct that from the total PO amount. For services, it depends on the deliverables and how the service is invoiced. If it’s based on time, such as contractor hours, you can match the timecards to the PO but service-based blanket POs can be more challenging to match than goods, where quantities and delivery schedules are clearer.
Sherry: And how do you track the cumulative spend and quantities against a blanket PO to ensure the limits are not exceeded?
Mike Vaishnav: There are various ways to track this. One method is using a cumulative tracking system within the accounts payable function. The accounts payable team monitors what goods have been received and how much of the PO has been used. This allows for continuous monitoring of the remaining quantities and amounts, ensuring that invoices don’t exceed the PO limits. Some companies use integrated systems to track this automatically, while others may use add-on solutions or manual tracking to ensure compliance.
Sherry: And what role do tolerance levels play in the matching process for blanket POs?
Mike Vaishnav: Tolerance levels are crucial. They set the acceptable range for discrepancies in price or quantity, determined by the company based on the materiality of the item. Some products may have higher or lower thresholds depending on their nature. If the variance is within the tolerance level, say 5% plus or minus, the system can approve the invoice automatically. However, if the discrepancy exceeds the threshold, it requires further review and approval.
Sherry: From your vast experience, could you describe the approval workflow for invoices that exceed the set tolerance levels?
Mike Vaishnav: If the invoice exceeds the set tolerance levels, it triggers a workflow for approval. Based on the company’s workflow, it will route the invoice to the appropriate person for review, following the approval hierarchy and limits. If the variance is minor, a lower-level manager might approve it. However, if it’s significantly higher than the threshold, it escalates to higher-level management or even executive approval. The rationale behind the variance must be justified, whether it’s due to contractual terms or other factors like the vendor shipping more to clear out their inventory.
Sherry: Since AI has taken the finance industry by storm, I have to ask, how can AI enhance the efficiency of matching invoices with blanket POs?
Mike Vaishnav: AI significantly enhances the efficiency of matching invoices with blanket POs. It can analyze and flag discrepancies that require manual intervention by predicting potential mismatches based on past trends and patterns. AI can also streamline the process with ERP systems to match quantities and flag issues in real time, helping catch errors more quickly. It also speeds up workflow approvals, enabling faster resolution of any problems and ensuring compliance through predictive analytics.
Sherry: And since we’re talking about efficiencies, what are some best practices you follow to ensure effective matching of invoices with blanket POs?
Mike Vaishnav: First, establishing a robust process is key, whether through an ERP system or using AI-based tools. Regularly reviewing and auditing the PO matching process helps identify any discrepancies early. Clear communication with vendors is also essential. Discrepancies often arise from mismatches in received quantities or incorrect invoices. Timely reporting, reconciliation, and monitoring of open POs to address why they haven’t been matched yet are also critical.
Sherry: Finally, how do you ensure compliance and control in the process of matching invoices with blanket POs?
Mike Vaishnav: Compliance is ensured through strong processes. Setting up proper tracking and tolerance levels, implementing approval workflows, and following internal policies help maintain control. Regular audits, reconciliations, and system-based controls further ensure that blanket POs are handled efficiently and accurately. AI can assist in monitoring for unusual activity and ensuring that any issues are addressed promptly, improving overall compliance.
Sherry: Thank you so much for these insights, Mike. This has been a very informative discussion on the complexities and strategies for managing blanket POs.
Mike Vaishnav: Thank you. Nice to be here.
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.
Moderated by Niyati Chhaya, Co-Founder at Hyperbots
Niyati: Hi everyone, good morning, good afternoon, and good evening. I’m Niyati, Co-founder and AI Lead at Hyperbots Inc. Today, we have Mike Vaishnav with us, a CFO, consultant, and strategic advisor to many privately owned organizations.
Before we delve into our discussion on how AI complements ERP systems, Mike, could you introduce yourself?
Mike Vaishnav: Thank you, Niyati. I’ve worked in Silicon Valley for almost 30 years across diversified industries in various roles, including controllership, FP&A, treasury, tax, investor relations, and operational roles. In my last two CFO positions, I managed fund, IT, legal, HR, and procurement functions. I’ve covered all aspects of finance and operations in different industries.
Niyati: Wow, that’s a broad range. Today, we’ll address our topic in three broad categories: the efficacy of ERP systems, how AI and ERP work together, and the actual integration of AI into ERP systems.
Niyati: You have been part of several large and medium-sized organizations. What kind of ERPs and business processes have you worked with?
Mike Vaishnav: I’ve used both small ERPs and large ERPs like Oracle and SAP. I’ve been involved in every module for ERP, including procure-to-pay, accounting, sales, and inventory processing. I’ve implemented ERP systems globally over the past 20 years.
Niyati: What gains do you see in companies through effective ERP implementation?
Mike Vaishnav: Key gains include process automation, process improvement, audit trails, and data security. ERPs provide detailed analysis and streamline financial information, moving away from manual processes.
Niyati: What are the challenges despite effective implementations?
Mike Vaishnav: Challenges often arise during data migration and integration with old systems. Proper testing and documentation are crucial to ensure successful ERP implementation. Companies should conduct parallel test runs in a test environment for about two to three months to ensure data accuracy before going live.
Niyati: Let’s now discuss how AI and ERP systems complement each other.
Mike Vaishnav: AI is complementary to ERP. It provides add-on solutions that make data analysis more effective. While ERP systems collect and process data, AI enhances the ability to make timely and informed decisions, especially in mid-size or small ERPs that may lack advanced data analytics capabilities.
Niyati: Can you give an example, like invoice processing?
Mike Vaishnav: Sure. In large ERPs, the entire procure-to-pay process is automated. However, mid-size or small ERPs might lack such automation. AI can automate processes like opening and approving POs, providing real-time answers to specific queries, and creating customized dashboards for different departments. This enhances efficiency and privacy.
Niyati: Why is it better to use AI to complement an existing ERP rather than upgrading to a bigger ERP?
Mike Vaishnav: Upgrading to a bigger ERP is a complex and costly process. AI add-ons can enhance the existing ERP’s capabilities without the need for a complete overhaul. This approach is more efficient and less disruptive.
Niyati: Where will the budget for AI come from?
Mike Vaishnav: Companies need to work smartly, balancing their budgets. AI can help automate high-volume transactions, improving accuracy and timeliness. In the long run, AI provides better return on investment by enhancing process and operational efficiency, ultimately adding to the bottom line.
Niyati: How should a company assess the need for AI in its various use cases?
Mike Vaishnav: It’s case-by-case. AI is customizable, so companies need to evaluate their specific requirements, budget, and departmental needs. SMBs, in particular, can benefit from AI add-ons to enhance their existing ERP systems.
Niyati: Do you see ERP vendors integrating AI modules themselves?
Mike Vaishnav: Some top-tier ERP vendors are incorporating AI solutions, but mid-tier and lower-tier ERPs are slower to adopt these technologies. AI can help enhance these existing systems, especially for SMBs.
Niyati: When does it not make sense for organizations to adopt AI?
Mike Vaishnav: For companies with low transaction volumes or extremely small operations, AI may be unnecessary. In such cases, manual processing by a single person might suffice.
Niyati: To summarize, AI is a good friend to finance professionals, complementing ERP systems. While AI will not replace ERP, it enhances the capabilities of ERP systems, especially for SMBs and mid-tier ERPs.
Mike Vaishnav: Absolutely. AI adds significant value to ERP systems, making processes more efficient and helping companies make timely decisions.
Niyati: Thank you, Mike, for sharing your insights on how AI complements ERP systems.
Moderated by Emily, Digital Transformation Consultant at Hyperbots
Emily: Hi everyone, good morning, good evening, good afternoon based on where you are. I’m Emily, a digital transformation consultant at Hyperbots, and today I have Mike Vashnum with me. We are going to discuss a practical toolkit to bring efficiency in accruals. But before we get into details, Mike, would you like to introduce yourself?
Mike: Sure. Thank you, Emily. I’ve been working in Silicon Valley for about 30 years and have had the opportunity to work in a diverse range of industries. I’ve been fortunate enough to touch every aspect of finance, including controllership, FP&A, treasury, tax, and investor relations. In my last two roles as CFO, I also managed non-finance and operations departments like legal, HR, IT, facilities, and procurement. So, I bring a very diversified and wide-ranging experience in finance and operations.
Emily: That’s great, Mike. I have divided this session into two parts. In the first part, we will discuss the current accrual landscape, and in the second part, we’ll dive into AI and accruals. So, for the first part of this discussion, Mike, I’d like to ask you to highlight the importance of expense accruals for companies and how they generally impact financial reports.
Mike: Absolutely. Not just expense accruals, but any accruals are essential for a company. If you look at basic accounting principles, you have to match the revenue with your costs. If you’ve booked the revenue and incurred the cost but haven’t received the invoices or bills, your profitability will be inconsistent. One month you might show higher profitability because of lower expenses that weren’t booked, and the next month you might have all those expenses catching up, but no matching revenue. This mismatch doesn’t present an accurate picture of profitability. By accruing expenses for which you haven’t received invoices, you match your revenue with the associated costs, giving a more accurate representation of profitability. This is crucial for investors and analysts to ensure the company’s profitability for a specific period is correct.
Emily: Understood. Based on your experience, Mike, what is the current process used in companies for accruals?
Mike: Different companies use different processes. Most accrual processes are manual because you have to collect information from respective departments. I would categorize accruals into inventory accrual and expense accrual. Inventory accrual can be automated in sophisticated ERP systems, where goods received notes allow for booking received but not invoiced items as accounts payable. Expense accruals, however, are very manual and time-consuming. Accountants typically send emails to department heads to check for pending invoices and services rendered. They also look at open POs to follow up on whether services or expenses have been incurred. Despite some ERP systems offering recurring accruals, accurate accruals still require manual processes and a lot of back-and-forth communication.
Emily: Can you also share the categories of accruals and how does the reversal happen?
Mike: Sure. As I mentioned, there are inventory and expense accruals. Expenses can vary depending on the company’s size and nature. The reversal process is necessary to avoid duplication of expenses. When you book an accrual at the month-end and then receive the invoice in the following month, you don’t want to double-book the expense. So, the best practice is to book the accrual, reverse it, and rebook it at the next month-end.
Emily: Can you highlight the pain points in the accrual process?
Mike: The main pain point is the manual process. Collecting data, ensuring the accuracy of accruals, and coordinating with various departments are time-consuming tasks. Ensuring all necessary accruals are booked correctly is critical because auditors will not accept general accruals they need specific purposes and processes.
Emily: Thank you, Mike, for explaining accruals and the current landscape. In the next section, we will cover AI and its role in accruals.
Mike: Sure, thank you.
Emily: Welcome back, Mike. Thank you for taking us through the current landscape of accruals. Now, let’s discuss the role of AI in accruals. What role does AI play in accruals, and can you provide some examples to help us understand it better?
Mike: Absolutely. AI can tremendously speed up the accrual process. While ERPs can handle many tasks, AI enhances them, especially in communication. For example, AI can look at open POs and automatically send messages to the respective departments asking if services have been rendered. This eliminates the need for human intervention. By setting AI to check for open POs on specific days, it can collect and follow up on all necessary information automatically. Let’s take the legal department as an example. AI can send automated messages to attorneys asking if services have been rendered, which replaces the manual process where accountants send emails and wait for responses. AI can also help with inventory by identifying received items that haven’t been invoiced and processing those accruals. Essentially, AI can handle the communication aspects of accruals, ensuring accurate and timely data collection without human intervention. This streamlines the month-end close process, allowing accountants to focus on analysis rather than data gathering.
Emily: That gives me a clear vision of how AI helps in accruals. Thank you so much, Mike.
Mike: You’re welcome. I’m looking forward to seeing AI develop further to make the accrual process faster and simpler, ultimately allowing more time for analysis and less on data gathering.
Emily: Thank you, Mike, for being a part of this discussion on AI and accruals. It was great having you here.
Mike: Thank you. Glad to be here.
