Does your organization have a high PO percentage, but you spend time on the back-end matching all those PO’s to receipts and invoices before paying them or chasing people to enter receipts, manually keying and clicking? Learn how DataServ’s "touchless" invoice processing will save you time and money, while dramatically reducing errors and manual labor.
View the webinar to hear Jamey Biegener, DataServ's Director of Software Product Management, talk about how:
You can select 2- & 3-way invoice matching
The solution is tailored to match your business needs
Analytics allows you to see exception trends to eliminate them
Click the link below to view the webinar, or scroll down to read the transcript.
Tom: Hello, and good morning everybody. Thank you for joining us today. My name is Tom Fischer and I am the director of marketing at DataServ. And I want to welcome you to our webinar today on enabling AP continuity with touchless invoice processing. Our learning model has certainly changed in recent times, given at home restrictions and what COVID has done to our working style. So we are glad to have you at our webinar and interact with you in this way. We know we need to learn in different ways these days and we are hoping this will great event for you. A quick housekeeping note: all attendees are currently in listen only mode but we encourage you to please ask questions any time using the functionality of Go To Webinar. You’ll see an area to ask questions. We’ll be monitoring that throughout the webinar today, and answering questions as they come up. And certainly we’ll have questions at the end as well.
1:00 We are recording today’s event and we will send you a copy of that after this is over so you can refer back to the information. The topic of AP automation is certainly an important one today given that we all have remote work and business continuity is more important than ever. But we also want to highlight the advanced nature of automation and the role it can play to deliver completely touchless ways to process invoices. And so we’re going to touch on both those topics today.
1:35 Before we start, let me just mention a little about DataServ. DataServ offers Accounts Payable and Accounts Receivable solutions that drive automation, drive savings, efficiency, and visibility to your organization. We place a high value on our client service. We have users around the world. And we love that so many of our clients stick with us for 10 years or more. It’s an indicator that we really value those deep relationships and partnerships that we have with our clients. We deliver a tailored approach to make sure client’s successes are being met. You’ll see on the next slide a partial list of some of our logos of clients who work with us. What I want to mention there is all of the best practices from each of these clients is based into our solutions. When clients are working with us, there’s value coming from how all clients have used our services and our SaaS based solution continues to evolve. That’s really it for me. I’m going to turn things over now to Jamey Biegener who is the Director of Product at DataServ.
3:00 Jamey: Hello! Just a quick introduction of myself. I’ve worked at DataServ for about 16 years. Worked in a lot of different roles at the company. And have actually been implementing some automation around AP and the matching process specifically since I started. So things have come a long way in the last 16 years regarding automation and I’m excited to share that with you today.
3:30 Here are some, according to Ardent Partners’ survey that they ran, some top challenges in Accounts Payable. You can see here that the number one concern is the high percentage of exceptions that AP has to deal with on a day to day process. And we know that AP deals with both exceptions on the purchase order side as well as invoices that aren’t related to purchase orders. But for this presentation let’s focus on the PO process and specifically matching. So when we are talking about matching we are taking the invoice, the purchase order, and sometimes the receipt of goods to make sure that the invoice is ready for payment and all things match up.
4:45 Obviously, in a perfect world there wouldn’t be any exceptions. But we know that there are quite a few exceptions that occur during this matching process. For example, sometimes vendors aren’t putting information on the invoice so the PO number isn’t present, and AP will have to chase that. Or sometimes the PO number is wrong. Sometimes they go to match to a PO and it’s closed, it’s already been used. Price discrepancies occur. Quantity discrepancies. Many companies we work with have some issues with receipts getting entered in a timely manner. And sometimes we see the invoices bill differently than things were ordered.
4:45 We’d like to take a little poll, and see of our audience here, what is your company’s biggest invoice matching exception.
Dawn: We’re going to go ahead and give you guys a few seconds to pick your top challenges. I’m going to go ahead and close the poll and I’m going to share these results with you. And it looks like we’ve got invalid/no PO here.
6:45 Jamey: That’s really interesting from the survey. Let’s talk about what we can do there, in all these areas actually. We are going to dive into this automated matching process service and explain a little bit about how it works, how it can work better for you, and what kinds of benefits and value you can get from automating this process. I’d like to start by asking another poll question. We’d like to hear from you how automated is your matching process. Not AP as a whole, but specifically your matching process. How much automation do you believe you have in that area. Everybody can fill that out.
Dawn: Alright great, I’ll go ahead and give you guys another few seconds. I’m going to go ahead and close the poll, and I’ll share those results with you. It looks like we’ve got a dead tie between 1-25% and 26-50% at 38% each.
Jamey: OK. So it looks like we have a lot of room to help this audience with automation. OK so let’s talk a little bit about defining automated matching. What does that mean? That can mean a lot of things to a lot of different people. You’ve probably heard words like touchless, straight through processing. People throw that around a lot when talking about automation, but there is a process to making this better. It’s not a one and done type of arrangement. And of course the goal of automated matching is to successfully match your invoices for payment while reducing the number of times that a human has to intervene with those invoices.
9:25 So, when we take a look at automation, it’s pretty obvious that gone are the days when automation meant taking your paper and turning it into a digital document. DataServ has been doing document processing in AP for a very long time. When we first started processing invoices, we were looking at about 10% email vs 90% paper. In today’s world we are the opposite. We do get some paper still that we process for our clients, but the majority of it has switched to email. There have been times that I’ve talked to some of our clients and asked about their automation, how automated are they? And I think some people interpret automated as we get our invoices digitally. But often times what we see is that ends up with a manual process where people are printing those email invoices. The point of this diagram here is to show that there is a lot more technology in use today to make automation successful. You can see in the middle here that we are using artificial intelligence, smart workflow that can route things appropriately based upon what happens to documents, and then looking at analytics. Really understanding the data behind what happens to your invoice processing so you can make changes and improvements and really drive down the number of exceptions that you experience.
11:25 So this might seem like a dream to some people. When you look at these industry averages and best in class amount of invoices that some companies are not having to touch. But these numbers can be achieved. Imagine if you only had to touch and manually work one out of every ten invoices that came in. Think about the impact that could have to your business process and other goals that your department could work on.
12:00 So let me talk a little about DataServ’s approach to matching automation. DataServ is Software as a Service, which means that we have a common code base. So our matching process, when we make improvements to it, those improvements benefit every one of our clients. Everyone can take advantage of the improvements, modifications, and changes that we make to our process. We have a goal to create as few touches as possible in the process. Exceptions are exceptions. The process is not intended to completely remove every exception that happens. But how can remove the day to day work and data entry that the AP team is working with so we can focus on driving down the number of exceptions and making improvements in that area. We also believe that invoices should go directly to the person that can solve the problem. We see a lot of times with companies’ process that they end up routing things to AP to try to figure out where they go, and oftentimes AP ends up in the middle of a process that they’re not actually solving the problem, they’re just in the middle figuring out who needs to solve the problem. So really try to get it to the right place and get that solved. Also we really believe in a partnership with matching automation. This isn’t something you can turn on and walk away from and expect to get 90% of your invoices to match. We’ll talk a little bit about how we do that.
14:15 We also see this automated matching as something that happens before these invoices get into your ERP. So this is an upfront, pre-ERP matching process. We understand that some people have automated processes in their ERP already around matching, and we would not suggest that this is replacing that. But it is an enhancement that so we can make sure that data that is transferred is clean and matched appropriately and it will flawlessly go through your ERP instead of stopping for exceptions.
15:00 So this is a diagram of the DataServ AP process as we see it holistically. I want to focus in on our digital mailroom. Our digital mailroom is where we are able to streamline invoice data that comes from multiple sources. We don’t care if it’s paper, fax, email, EDI, and yes in the past, we’ve even gotten invoices written on napkins. We are able to take all of those sources and streamline the process to capture the data form those invoices from OCR and some AI to really learn and improve that process. And again, I want to reiterate that we are a SaaS organization, so across all of our clients, our system is learning how those invoices look and where data is on them, and that is across our whole client base. If it is able to recognize certain data for a particular invoice that our vendor that multiple clients use, then everybody is getting the value of improvements in OCR for those invoices. I also would like to point out that we do have a human validation step. Many of our competitors that produce OCR data have the actual end users doing the validation. We actually do that ourselves before that data is presented and used in your system. So the end result is we’ve got clean data that we can use for matching to PO and receipts data that comes from your ERP.
17:20 So again, the benefit of automated matching and taking advantage SaaS is that you will start to see value immediately. There isn’t a big learning curve to start over. You make look at some solutions where you are setting up OCR templates yourself and trying to collect the data off of that. There is no learning curve around that because we are already doing that today. We also have proven matching logic to really hone in on accurate matches at the line level. So we’re looking for exact matches. And then if it can’t find an exact match it may use broader logic to find the match where we incorporate tolerances on both price and quantity. It will attempt several iterations to try and find the appropriate match. Our solution has statistics on the success and the exceptions, and we really believe that that’s where the focus needs to be with the automated matching process so that you are able to pinpoint how to improve the process to get better results. And again we partner with you to continuously review that and help make the process more efficient. I also want to point out that we are ERP agnostic. We don’t only work with Oracle or only work with JDE. We have worked with over 30 different ERP systems and have interfaces for most of the common ERP systems.
19:30 Some of the things that I wanted to point out is DataServ, as SaaS, we believe we’ve got about 80% best practices built into our solution. But we know that users are going to want to be able to change some of the things. So everybody has their unique process, and over time we’ve learned to understand what variances people want to tailor in our system. A couple of those items are here. For example, we often see companies that do both 2-way and 3-way matching. So we work with you to determine when to apply which type of matching. We also believe that when 2-way matching happens, just between the PO and the invoice, that someone should probably approve that that invoice should actually be paid. So we can set it up so that it routes those invoices to the requestor, and have them confirm that they did in fact receive those services. Tolerances again we can apply at the header and the line level. And we can look at tolerances with both quantity and price. I mentioned earlier that we prefer routing those invoices directly to the person that can fix the problem. So we work with you to take that PO information and really figure out for each type of exception who should receive that invoice so that it can get resolved.
21:30 Tom: Jamey, we had a question about tolerances. Could you maybe cover again what we mean by tolerances and how people apply those?
Jamey: Absolutely. Most ERP systems are going to have a tolerance set for when you match an invoice to a PO. We would prefer to have the same tolerance because we don’t want to be having a higher tolerance in DataServ and then we transfer data to you and it would bounce out of your system. But the tolerance you can apply is based on a percentage or a dollar amount, or a combination of the two. So it could be that you are willing to pay a unit price that is 1% higher than what the PO said, but it can’t exceed $5 difference. So there are different tolerances you can set based on the different 2 and 3-way matching. 2-way matching you may see more of a tolerance on a header level, as long as the total amount on the invoice is within 1% of the open PO amount you are OK with paying it. So when we go through our matching process, we first attempt matches without a tolerance. We are looking for exact matches. And then we include the tolerances to find the right match.
23:30 One of the questions I asked up front was about your receiving process. Companies don’t often know how long it takes on average to get receipts entered into the system. But visibility with something like this, we can provide analytics to share that with you and show you how many of your invoices are bouncing out with a no receipt exception. One of the things we let you tailor is the number of days to check for receipts. Sometimes people have amazing receiving processes and they are entered the same day things are received. But typically we see about 3-5 days to get receipts entered. So we may attempt the matching process for a number of days before we bounce it out as an exception.
24:35 I’ve mentioned a couple times that success with automated matching is a joint partnership. It is between you, your vendors, and your automation partner, and in this case we are talking about DataServ. There are things that each of these parties can do to increase your matching success. Some example here: changes to your processes may be reviewing your internal procedures. Looking at the PO process, the receiving process like we just talked about, and really making sure that there are good standards in place around those processes so that automation can be adjusted to make sure that process works. Same thing with the vendors. It was interesting to see that so many people struggle with the vendors not putting the right PO number there or not putting a PO number at all. This is something that we assist with. DataServ, when we onboard a new client, we provide what we call a rapid adoption kit, and we do help give information that you can share with your vendors about what to do, how to properly invoice you so that they get paid the most efficiently. Generally, when you share with them that you are going to start automating your invoice processing and the PO number is critical for their payment, they’re going to want to comply so that they can get paid.
26:40 Tom: Jamey, if I could chime in there really quickly. When you talk about changes to the vendor process, I think you’re saying we’re not asking everyone to have their vendors follow an exact template that DataServ requires. There’s still flexibility, right?
Jamey: I’m glad you stated that. Correct. We do not say you must submit a PDF. But we do point out why they would want to put a PO number on an invoice. Thanks, Tom. DataServ is very flexible in how we get invoices and process invoices. We do not require a specific format and thanks for pointing that out. The other method is changes to the DataServ process. So we have a lot of different configurations that we can pull different levers to help you succeed. The whole goal is to increase the number of invoices that flow through with zero human touch. That’s what we are trying to achieve.
28:00 DataServ systems also provide analytics. So as exceptions occur, we are really able to dig in and look at the different types of classified exceptions. Here’s an example of what our analytics would provide. What I’m showing on the right hand side, if we were to drill into that 15% of the exceptions have no receipts, I can drill in and see on the right hand side, of that 15% of receipts what’s the breakdown by location there? I can really start to hone in on, our north branch is contributing to half of our no receipts. So maybe we need to take a look at their receiving process and determine how we can make some improvements on that. This is one example. This isn’t the only example of analytics that we provide. It’s a very powerful tool to really dig in and find specific vendors, specific bottlenecks in the process. But that is all part of the partnership that we have. We do not recommend going in and making a bunch of changes before you start. We suggest that you follow our best practices and our proven logic and see what exceptions fall out. And really get a good feel for what type of exceptions are happening in your system. I think a lot of people think they know. You can probably sit and think of a terrible vendor that causes you problems every time you sit down to do your work. But it’s interesting over time how trends can develop and you get a different picture of what’s really happening with your process.
30:15 This isn’t everything we have in our toolbox, but I wanted to highlight some things that over time we’ve really learned can help improve the automation success. So we talked about the number of days to look for receipts. Sometimes people start where they just try the match, and if it doesn’t work it bounces out as an exception. We help you understand how long it is taking for those receipts to come in on average and we’ll help you adjust that number of days to try so that you’re not having to deal with the no receipts problem. We also work with you to adjust tolerances. And we can really help you understand the different types of matching. I want to pull out an example of one of our clients. They were an Oracle shop and they insisted on having receipts entered for everything. So all of their invoices with a purchase order, they required receipts to be entered. And we were getting very low match rates. Like 3% of their invoices were matching, and this was because no receipts were entered. For a long time this company really took it upon themselves saying we just don’t have a good receiving process. But when we really sat down and talked about what kinds of invoices these were, these were invoices that are services. And I started asking questions like, what triggers a receipt to be entered into the system for this type of invoice. What we discovered is that it was getting the invoice into possession was what triggered them to enter receipts. Well when you move to an automated process and upfront capture of information, you cannot be successful with touchless processing if getting the invoice is what tells you put the receipts in. So we really talked about how can we implement a 2-way matching process here, and once it matches to the PO, then it goes to that requestor that purchased it and they can confirm that the invoice should be paid, and when they do that, that’s the 3rd component of control to close out the match. By changing their process in that way, they were able to move from a 3% success rate to a 50% success rate just by applying a 2-way match where it was appropriate.
33:45 So that’s one example of how we’ve helped a client improve their automation. A big change for their AP team and really freed them up to work on other things. WE also have the ability to implement some quantity and price adjustments. We see a very common theme with some of our clients is some vendors will end up billing in a different unit of measure. They may bill you per thousand. So we can set up some automation rules to automatically adjust the invoice data to work with your PO data to get a good match. We can do some reversals of unit prices and quantity. A lot of times when someone is looking to do an amount only PO, you have to work within the configuration of your ERP system. When a PO is set up as an amount only, you may put in a price of 1 and a quantity of the total amount of the invoice. We see this sometimes, and we are able to accommodate some automation around helping that type of PO match to invoices. And another common thing that we see is vendors like to put their own part numbers on the invoice instead of your part numbers. And when you are trying to do automation, that is difficult because you are looking at the part number as part of your automated match. We have done some cross references for clients where they’re able to tell us their part number and the vendor part number, and then we can apply each of the part number to get the right match. That helps with really controlling the data and getting the accuracy of the match.
36:00 Tom: Jamey, we had a question. How do you handle purchases where there is no PO?
Jamey: That’s what we apply non-PO workflow. This is where we do upfront capture of invoices, route that to the appropriate approver. We can apply default coding. We can set up routing rules so that certain vendors always go to certain people in the system. There are ways to accomplish less touching of invoices when there is no PO. We do have solutions for that, we were focusing on the PO piece for this process. Anything else, Tom?
Tom: I think there’s one more question. Sometimes we get multiple PO’s listed on a single invoice. How do you handle those?
Jamey: That is a very common thing. I think it’s painful for a lot of our clients to process those types of invoices. We have the ability to capture PO number at the line level and apply matching to multiple PO’s on the same invoice. That’s our standard logic that we can apply that multiple PO process, if necessary. We usually ask and talk through how many vendors do that. Because if it’s one vendor you may not want to capture that PO number at the line level for everything. There may be other ways to address that. But if there’s a good amount of vendors invoicing you that way, it’s a great thing to add in there.
Tom: Thanks. I know we have a variety of organizations represented on the call today that are listening in. We talked about sometimes the physical purchase. Are the ways we can help with a service oriented purchase that an organization might make. In terms of that receipt part?
Jamey: That’s exactly what I was talking about a little while ago about our client who we moved to 2-way matching because they were trying to do a 3-way match on services. Since there isn’t a physical receipt of inventory or a physical thing, what’s triggering their receipt is the invoice. If you’re trying to automate you need to do that upfront capture first. When you do that, the person that bought the service is not getting the invoice until it bounces out as an exception. We really try to facilitate NOT making that an exception, and the way we do that is to match it to the PO with a 2-way match and then route it to the person that purchased it so they can say yes, I received this service and we should pay this invoice. There are a lot of different effects behind that as far as how the ERP is configured to deal with those types of PO’s. But there’s some automation that we can do to meet those criteria.
Tom: Thank you.
40:20 Jamey: OK. A lot of times when people have talked about automation in the past, I think sometimes people are scared. We’ve heard concerns about losing your job or what’s gonna happen to all of the exceptions and things that we deal with. It’s really not something to be afraid of. It ends up being an opportunity. An opportunity to repurpose the skill set of the AP team. And really focus on improving the exceptions instead of spending the time dealing with all of those invoices that just work. So we really encourage taking a look more strategically at AP and figuring out the best way to really look at trends and make great process improvements so you can start working on other value tasks like discount management, spend management, and really working with your vendors to improve the speed of the payment process. So now that we’ve talked about automation and what it means to automate your matching process, I wanted to ask again how automated you believe your matching process is now that we’ve talked through these activities.
Tom: I’ll ask a question that’s come through since we’re getting towards the end of our time, what percent of data that comes through is reviewed by a human? I think they’re talking about the intake part. Is it only data that AI finds a problem with?
42:30 Jamey: Great question. The answer to that is yes. The way that DataServ runs that process, we go through OCR, AI runs rules, and processes those invoices. And then those that encounter errors or don’t pass validation, those are the ones we will be looking at and applying human eyes to. We also use master data from our client systems to do some of the data validation. So we’re able to recognize right away if the PO number is invalid or if the vendor is invalid and we have a lot of checks and balances in place that we use for that.
Tom: Thank you. I do have another one for you, Jamey. It says my team in the warehouse doesn’t always enter their receipts right away because they are so busy. Will these all kick out as exceptions.
Jamey: I love that question. At first, when you start a process like this, you really start to see what falls out. Like the analytics I showed there is going to show you what your biggest exception process is. And we help you pinpoint and focus on bringing those exceptions down. With the receipt example, we’d be able to show you what locations or what warehouses are having that issue. Hopefully by talking about it and understanding your internal process that you have around receipts getting approved, those things can improve. We can also understand how many days we should look for those receipts. Because if we have it set to 3 days, maybe we should move it to 5 so that more things get processed and matched without becoming an exception in that area.
Tom: Here’s a million dollar question: what percent of invoices will automatically match? What’s your exact number, Jamey?
45:10 Jamey: You can’t really answer that question across the board. We showed some statistics up here about best in class is getting up about 90% match rate. Our philosophy with DataServ is we start you out, when we first initialize a client, we start to see between 40-50% of their invoices going through touchless. And that’s right out of the gate, because you’re receiving some of the benefits of the SaaS component. But over time by tweaking things and working together and partnering around your exceptions, we can start to see between 80-90% match rates flowing through without being touched by a human. That’s really our goal. Every client is slightly different. Your businesses are different. Your internal processes are different. That’s why we really believe in partnering with this process to get you the most success.
Tom: I’m thinking back to the slide that you showed about the analytics that showed reasons why automated matching isn’t occurring. That’s probably the one to watch to see how that number can continually be improved upon from all parties’ perspectives.
Jamey: Absolutely. We incorporate that data regularly with our conversations with our clients so that we keep revisiting and keep trying to make improvements to those exceptions.
Tom: Jamey, do you have any final thoughts as we wrap up and come to an end here with our webinar?
Jamey: I found it interesting that once we talked about matching and about how we apply that, it looks like people increased how automated they were. But there’s always more to automate in this technology world we live in, things are changing fast. It’s exciting to see how this can be applied. Particularly the analytics portion to help people improve their processes over time.
Tom: Thanks, Jamey. And with that I will wrap up our webinar and thank everyone for your time and for attending this morning. We appreciate that. And as a follow-up you will hear from DataServ with a recording of this event. But if you have any questions at any time feel free to reach out to DataServ or Jamey about this specific aspect to automating AP, in terms of getting those invoices processed as touchless as possible. We’re excited. We’ve seen a lot of clients improve their processes in that regard, and we hope to share that story with you again. Thank you everyone and we hope you have a great Tuesday.