Director Credit and Accounts Receivable,
Thank you for joining a session on why you need a tech-driven approach to resolve FMV deductions actions faster. Today our speaker is Jacob Wetzlar, Director of credit and they are at Danone. Jacob is an experienced business professional with a diversified background that includes sales, receivables, payables, account balancing forecasting and financial analysis (giggles) that was a long list and now that the housekeeping is out of the way Jacob the stage is all yours.
[0:32] Jacob Wetzlar:
All right, thank you guys can hear me okay. All right. So a lot smaller stage. So if we don’t walk off of it here, but I’m grateful for the opportunity to speak thank you guys for coming out. I know it’s right before lunch. We’re just talking about I think before lunch is better than after lunch. So hopefully you guys are hungry, you will stay awake. And hopefully, I won’t keep you too long and we can go have a good lunch. But yeah, I’m going to talk about kind of our deduction process that we have Danone, and it’s really going to be from our perspective. So I know there’s a lot of people from different industries. So it is going to be more from the food and beverage perspective.
But hopefully, you can still relate to those who are from different industries. And some of the stuff that we talked about can apply some of the stuff that I’m going to talk about, we don’t have in place yet. But there are things that we’re looking forward to in kind of our next evolution as we go through our journey as well. So, again, from a perspective of the food and beverage industry, what is unique about our deductions that may be different from some of the other industry. So we have some numbers and this is taken from a consulting, which, you know, Jessica Butler, I know she’s on some sessions. This is the industry part that she puts together. But one of the biggest things that I wanted to point out and note here, that unique maybe to the food industry, or the food and beverage industry, is the fact that we have a lot of trade-related to deductions and ask the majority of the deductions that we receive, versus the non-trade-related deductions that we see in the other industries.
So really the point that I want to drive home with this and what I’ll talk about more is these traits Related deductions are deductions that we expect to happen. So they should be pretty straightforward because we know they’re going to happen, we’re expecting the customer to take it, there’s an agreement in place for the customer to take these for the most part. And that’s the majority of our deductions that we have. So even with that, though, it still requires a lot of work to be able to match it against promotions, and, and a lot of time spent on these deductions to make sure that they are valid, but the majority for us are trade-related versus non-trade related deductions. So just some quick numbers to kind of ground ourselves and level set I guess, with what we’re dealing with. It didn’t own with regard to these trade deductions. So yes, about 85% of them roughly all the deductions we receive are trade-related, of that 85 % the majority of them are valid, this number is probably even a little bit low. I think we identify some as invalid and in further research, they actually validate that we put 90% here are usually valid, which means 10% are invalid deductions, and those invalid deductions are the ones that require are a lot of manual work.
But those are also very important ones because those are the ones that we can bring money back into the company and so we wanted to highlight those right now. And this is continuing to evolve and improve. But we estimate at the time this presentation was done as it’s taking about 45 days and DDO is deductions days outstanding. So just a measurement of how long it takes from once we get the deduction to actually validate it, and then clear it and close it out. So we’re at 45 days roughly. And that’s something that’s a number that we continue to try to drive down and something that we keep here our team on is to try to drive that down. So just that’s where we’re coming from an unknown perspective. And I guess I should back up a little bit. I don’t have slides on this, but I like to think that everybody knows about the unknown, but maybe people don’t know about the unknown if you’re from the US. You may know better as Danone, Danone yogurt, so said, for the most part, a dairy company but also we have a lot of plant-based products as well. So if you go to the store and you see activity, or Waco so those are lightened fit to Good, those are our products. So next time you’re in the store, I have four kids that need to be fed.
So think of our products as you have you buy your yogurt, so, so I appreciate that. But we also, a couple of years ago, we acquired a company called White wave, which makes silk milk, so delicious product, horizon dairy, a bunch of others as well. So we’ve got really into the plant-based side of the business as well. So again, very heavy in the dairy and alternative dairy and plant-based products. So just as we say, to know, and I don’t have a very good French accent, but that’s it we are a French-based company so that’s where the name comes from. So I don’t even know if I’m pronouncing it right, but Danone is how I’ve always called it so.
[4:42] Jacob Wetzlar:
Alright. Alright, so some of the things that I just wanted to cover in this session really quickly, just…deduction management is really trying to find the value and find that needle in the haystack that’s out there with these deductions. Maybe and then we’ll start getting to some as the presentation is called getting some of the technology So maybe why some companies don’t automate or some of the challenges with or challenges that there are out there with automating deductions, how automating deduction process can reduce complexities, how it can help resolve some the collaboration issues that we have as there’s a lot of different touchpoints and people involved with deductions management, and then going into a little bit the AI around deductions and what’s possible with that.
[5:23] Jacob Wetzlar:
So again, finding the needle in the haystack, and as you know, as working with HighRadius to put this presentation together, and some of the next slide I actually, as I was preparing this to come in here, I realized there are some sentences in here and into the next slide specifically, I don’t necessarily agree with but I didn’t have time to change it, but I’ll explain it a little bit more too. So with this, and the part that I don’t necessarily agree to is that that bottom piece where it says time and effort lost on valid disputes and what the message that I don’t want to give here is that even though valid deductions and like I said we expect our customers to take a lot of deductions, it’s not time wasted. I mean, that’s the biggest role that we play in deductions management is to be able to process those valid deductions, validate them and get information back to the business to the sales team so that they can get an ROI on their investments that are making with their trade spend. And that’s a huge portion of the money.
So I don’t like the word that its time and effort lost because that is a very important part of it. But really, when I talk about the needle in the haystack, what I wanted to focus on more is around those invalid deductions, being able to do some things that maybe require a little bit more work, but also have some good return. So you know, in the past in our department, one thing that we’ve always been proud of is we’ve been able to bring money back into the company’s we’ve been a revenue-generating department, which there’s not a lot in a business that actually generates revenue. But we’ve been able to be proud that, you know, by February or March, through deductions that we were able to bring back, we can pay for ourselves, and we don’t actually cost the company money and we’ve been able to, we’ve been trying to help all of our department to understand that and to realize that so they can be proud that they’re bringing money back to the company. We’re paying for ourselves. So anyway, similar to the numbers that I showed earlier.
So out of all the deductions that we get, we have a small piece that we just-auto right off. So we have different tolerance limits based on a dollar amount based on the type of deductions that we’re not even going to look at. So we’re going to go ahead and take care of those, what’s left, the majority of them are valid, we still have to do the work to understand to validate them, but also understand where we want to clear them to we have a portion that’s invalid out of that portion that’s invalid that’s the money, we’re trying to get back and recover and bring money back into the company. And that’s where really if we can change the way that we look at those ones that are valid, that is still very important to get that back to the business, but focus more on that stuff that we can generate revenue and bring money back into the company.
So and maybe this is a bad title here instead of why organizations don’t automate their deductions or just put it more as challenges the company faced and trying to move to automate deductions and changed more than higher-value work. So first of all, it’s a very complex process. There’s a lot of effort required in that. And I’ll go in a little bit more with that. But then also collaboration. And so again, there’s a lot of departments and places and people that are involved with this, that we have to collaborate with. And they make automation a little bit more challenging. So some of the complex processes, and I realize now I have the 90% number or 10% number in this a lot, so I apologize for that.
But really, it’s just trying to get through a large volume of deductions. And again, even though those trade deductions, we expect to happen we still have to research all of them in order to decide if they are valid, and where they should clear and so at Danone we cleared a line item levels so we really want to understand the products that the customers are deducting for so that we can clear that level and be able to get the information back to the business to understand how they sell on the activity at work during or close to other things. So we are breaking down deductions to the line item level requires a lot of work. So every almost every deduction we have to look at and actually break out. So a very complex process with that. The other thing is, in order to do that, we have to look at the backup. So being able to get the documentation in order to see what the deduction is, the products that it’s relates to getting the back end, which is a challenge on itself is we can’t do anything in the process until we actually have that backup or that documentation.
[9:20] Jacob Wetzlar:
And then each customer seems to be very different. So you know, at first, as we thought about automation, we would have to basically write rules for every single customer in order to get the automation working, and everybody’s different. So and it’s not just that every customer acts differently. Our sales team seems to promote very differently with each customer as well. And so not only do we have customers behavior that’s different across the board, but we have salespeople who promote differently across the board as well for different reasons. And so the uniqueness causes of a very challenging situation in order to try to automate this and especially write rules around it. And again, going back to the collaboration, so being able to involve sales in this cash application, collections logistics, shipping customer service. There are so many parts of the company that touches upon deductions that collaboration plays a big role in this. And again, another challenge in automating through so being able to have real-time visibility into the production process where the deductions are in their production lifecycle, what we need in order to resolve them, where we’re at, that’s a big, big part of it as well, that we have to figure out and there’s a lot of people that play into that. So really making sure that we touch all the points that we need to, it’s very time-consuming. And very, it makes automation very challenging.
So what I want to do here, and I don’t really have a good slider presentation of this, but I just wanted to kind of talk about where we’re at in Danone in our production management process. So right now we do use the HighRadius deduction module. We also use cash application. So, course deductions all start with a cash application. So we have a lot of automation built into that’s something that we were very able to easily get some automation in there to have a lot of rules to apply the cash to create the deduction. After that point, then it goes into the production module. And we have some data agents to some other things built in a place where we’re trying to automatically get that backup and that documentation attached. So, customers that have portals, HighRadius is going out, grabbing that backup attaching it to the deductions, customers who send their backup in by PDF or Excel. That’s all coming in. So the idea that we’re trying to achieve is that as a specialist sits down to start clearing the deductions, the deductions created and the backups already there. But then after that, right now, it’s a pretty manual process.
So I’ll go into it a little bit more. We’ve tried to automate what we’ve could, but it hasn’t worked really well, in the state that we’re in right now. So a lot of it we have some customers where the specialist is actually printing out the backup on a piece of paper, you know, they’re breaking it out, and they’re trying to decide what pack rips it goes to we have, you know, two screens and now people are using their laptops, so they’re, you know, getting sunburned by other screens that they’re getting and they’re trying to go through it all just to try to figure it out of how to break this up. So it’s still a very manual front process for us. And then if we run into any snags with it, so we’re trying to do as much work as we can so that sales can focus on actually selling our product. So if we go in there, we try to look for rates, dates, pack groups. And if we can find a promotion that matches that, then we’ll go ahead and match it. If not, we send it to our sales team to try to get them to look into it. Did they just forget to put a promotion and they forget to change something is an invalid, are they gonna come back and tell us that and that’s where our process really stops and really drives our DDO or that measurement up a lot is because we have to rely on now another department to get back to us. If it’s the logistics related, the same thing, we research it as much as we can, then we have to send it on to our logistics team to validate it to POD to figure out what’s going on. And again, that stops the whole process.
And then it all comes back to us to hopefully try to close these out. So right now it is where we are trying to automate as much as we can. We still have a lot of manual processes that we go through in this. So where we’re trying to look in and I will We’re not there yet. It’s something that we’re just exploring. So some of this is still very early on in the process of trying to really advance that technology. I attended the Hershey session a little bit earlier today, and it sounds like they’re a little bit further on, then then we are in this process, but we’re kind of on the same journey. So the idea is, is now instead of just relying on some of the standard rules to automation is really looking into AI or that artificial intelligence to help us resolve this. So really having the AI look at our entire set of deductions, deciding whether it’s trade or non-trade, once it decides that then use historical data to try to figure out what to do from there. So can it find certain things based on the history and how deals were cleared, that is going to be able to apply things to promotions, or deal with the logistics side and really identify for us and help to prioritize the high-value stuff versus a lower value?
So some of that lower value stuff from like, $1 standpoint makes up a lot of quantity. But if we have a high confidence level in the system is doing what it should we just want the system to automatically clear those. And then we don’t have resources actually touching that piece of it. And it’s probably prioritizing that high-value stuff or some of the invalid deductions. So that’s where currently the team is focusing on. And we’re not dedicating resources to some of that lower value stuff. And that’s what this slide is just trying to point out is that the AI will help assist in identifying and prioritizing for us those deductions and what they mean. So this next slide, I didn’t realize that Hershey had this exact same slide. So I’m not plagiarizing. I like chocolate too much to plagiarize this but this is the exact same slide they had. So if you attended that my thunder is gone now already, but this is the idea that in such a HighRadius like this, so but so this is where we’re at with them right now.
So a lot of it is so HighRadius went through and they looked through a lot of our historical data and how items were cleared to be able to figure out how AI can help us out and you can see some of the numbers there on the bottom of it. But really the idea with it is this is that the artificial intelligence will look at our historical data, how certain characteristics of deductions were cleared against those sort of characteristics of promotions, it will be able to create algorithms right rules, and then make recommendations to where different promotions, those deductions should be clear to. And then based on how we, we actually end up clearing that deduction. It could be what was recommended, which is good, or it could not be what was recommended. And then we’ll kind of go back to the system will actually learn from what the recommendation was versus what actually happened and go back and changes our algorithms and change its rules.
So that’s constantly improving, continuing to improve. Now, a couple of years ago, we tried to do this automated deductions with HighRadius and we were able to do it a little bit with some of our certain customers that were very complex customers where they put contract numbers on their deductions. They put other things that he did way identified it then we wrote rules. We had our sales team make sure that they put contract numbers on their promotions. And if the contract numbers match, then the system would match those up and clear for us. It was working well for a little while. And then sales forgot to put a contract number in their sales forgot to put everything in there, and then it all broke. But then, so we kept on having to refine these rules. But then we also switched our planning system, our trade promotion system, sales did and then it all broke.
So it was a lot of work to constantly try to keep these rules up to date, and then any change that sales did or anything that they did, we would have to go back and rewrite our rules. And so we basically, we gave up on the automatic, because we are spending way more time trying to keep these rules up to date than actually having a resource go in and try to clear in bulk and do some other things. So the advantage with this artificial intelligence is that it’s going to hopefully keep up with all those changes that are going on and those differences that are happening so that now we don’t have to dedicate resources to try to keep up with the rules and all the changes that are going on. And honestly, right now I’m glad we didn’t invest in continue to write the rules because we just found out that we’re going to change our trade planning systems again. So what of all broken again, so but some of the…Yes. So some of them out of the data sample that HighRadius pulled, they were able to identify 20%, which is not the, you know, a number that we like to get up, but it’s still a great number and some savings that we were trying to get. So based on no work that we did on our part, just them running their artificial intelligence on the set that we already had without making us making any improvements or any difference, they were able to match 20%. And then out of that 20% 79% or 80%, were actually accurate.
So their algorithms and rules are working on that 20%. So that’s good news for us and very encouraging that this process can work for the way that we do business and make a difference for us. So again, just some other numbers on the sample that the HighRadius pulled for us. So we focused on our three top customers, and again over a certain timeframe. They looked at historical data and what was going on. And so you can just see from the different colors here, we did a lot better on our blue customer, we don’t want the customers that are green in our yellow or orange or gold, whatever. So out of this one that identified about 1000 deductions on the blue customer, of those thousand about 650 actually had different line items. And again, we wanted to break out by line item, what was going on 500 of those automatic, which is a pretty good percentage. And then out of that 550, about 522 of it actually matched accurately. So again, a very good percentage of accuracy related to what it was able to auto-match. So again, very encouraging for us and you can kind of see the green customer not so good as far as the number of deductions but still right now will take any improvement. And again, this is without any work on our end, to try to help improve these numbers. But it’s still time savings that we can have that those deductions again that we expect the customer to take that we know they’re going to take that we can have the system do some of this stuff force and I’m not dedicating resources to us. The other thing is, when we were, we were going in and trying to manually update all the rules. We only did it on our top customers, because those words, the ones that had the biggest impact, we had a lot of small customers that we just didn’t even touch at all, because of it would take a lot of time and then a lot of maintenance to keep. But with artificial intelligence, our hope is that we’ll be able to go through every customer that we have and be able to have the system write rules for us and do this historical trend for us and be able to identify different rules and opportunities to automate.
So again, just some numbers here for the timeframe that they looked at about 6000 deductions in total. 1000 had deductions with line items is able to auto-match 100 of them. And then the accuracy rate was about 600. So, you know, it’s still something that, you know, we want to try to improve that but basically we’re able to use the artificial intelligence to have rules and try to auto-match for every single customer that we have. So we can touch our entire customer base, not just our, our large ones. And again, this slide is maybe a bit of an eye chart with a lot of numbers and words and stuff. But, but really, the idea is, if you look at the colors is, is just trying to point out that, you know, one of the things that it can do for us is just prioritized. So really the idea is with the green bucket here is just showing some numbers that, you know, that is kind of a high volume, about 16% of it, but it only makes it in dollar amount less than 1%. So those ones really, if we can trust the system to do that, we can just go ahead and auto clear that I don’t have to have anybody working on that piece of it. The ones in the red, those are ones that that is a high, you know, relatively high volume, but also a high dollar. So that’s where I want my team focused on so I can eliminate a lot of their work to focus on what’s in that red bucket. Those are the ones that potentially are invalid that we can bring money back. Those are the high dollar ones. We want to make sure it cleared accurately so we can get that information back to cells.
And then the idea with the yellow ones are just those ones. You know, maybe we don’t need to spend as much on that, we want to just a quick review to make sure that they look good. But we can still prioritize the time and maybe not spend as much effort with that. So really trying to just change the way that we look and be able to free up time in order to focus on what really adds value to our organization. So the collaboration issue, as I talked about, and, you know, just the question here is, “can we address the collaboration issue with both the right set of people and technology?”. So automation is great, but it’s still people still need to be involved with it, especially in communication with other organizations and other departments and some of that human communication. So one is, hiring the next generation of the deductions team and I had a presentation yesterday where I talked about this a little bit, but we’re really trying to change the team that we hire those specialists that we bring into clear deductions. So I actually started out as a deduction specialist with Danone when I was going to college. It was a great job and I don’t mean to sound disrespectful, but I was there so I can say that but it was great as a college student because I could, I went to school at night, and I was brain dead and I came into work and I could just not think about working clear deductions, it doesn’t take a lot.
So it was, it was very good from that standpoint that I didn’t have to think really hard, I could just clear deductions and rest my brain a little bit and then go back into it. But really, we want to change that mindset that we don’t want just people coming in and processing transactions, we want the system to do the transaction work for us. And we really want to focus on being able to shift people to some of the higher value stuff and some of the more communication talking to sellers working with logistics, those numbers that I showed earlier, those percentages really focused the team on trying to drive those percentages up. And then where we can auto automate the correspondence and more what I mean with that is there still needs to be some human element to that correspondence and being able to collaborate with the other teams. But can we get all the documentation faster? Can we bundle stuff easier? Can we send stuff off a lot easier, so we’re not having time spent trying to gather information, gather documents, so we can send that off a lot faster and then follow up with that human touch.
So, being really more on that next generation is in our business where we’re growing a lot, there’s a lot of focus on, especially the plant-based products. So we have a lot of growth, we’re spending a lot of money, trying to promote our products. Now that you guys are all going to go out and buy Danone products, I got to deal with those deductions as well, which is great. But we want is the myth is not that this growth is we need to go out and hire more people, what we want to do is be able to get the systems to work more efficiently for us and automate a lot more so that our growth is not compensated by additional resources, but compensated by automation and technology within the systems. And so a lot of that is yes, we have to deal with some of that change management with the people. And I won’t go into that too much. But we’ve got to get the current people that we have on board with this kind of change their mindset to look for ways that they approach their job of what can they do differently in order to try to get their auto rate percentages up?
What can they do differently and try to get them to do less of just a transactional work and more of some of that higher value-added work? So, just in the summary of the kind of where we’re headed with automated deductions, and again, we’re just starting this journey, we still have a long way to go with that. But really trying to get where we can go back to that deduction lifecycle and track each deduction life, being able to understand where we’re at in the production process, being able to get the information back to the business of where we are in those deductions, being able to auto process a lot of those trade deductions. Again, those are ones we’re expecting the customer to take, we know they’re going to come it should be pretty easy to match those up, prioritize and focus the team on where they need to focus on being able to automate the correspondence, being able to gather the backup, which is this other piece here, so that when a specialist comes in, everything’s ready for them.
So really, as much as we can just, you know, overall focus the team on doing what adds more value to the company, bringing them the money in but then accurately and with confidence, know that those trade deductions are being cleared correctly. So the information is given back to the sales team. So again, we’re not there yet. It’s the start of our process. We appreciate the partnership with HighRadius to try to do this with Danone and automate where we can. But that’s kind of where we’re at from our perspective. So we have a few minutes for some questions. I know I went through stuff quickly. But any questions for the next few minutes?
Hi! I was just curious on the side where you said that you had 20% Auto matching and about 79% or so were accurate. For the 20% or so that were not accurate? How did you find out about those? Was there some kind of alert in the system?
[25:34] Jacob Wetzlar:
So the way that they did is for us, this was actually all after the fact. So these were deductions that had already been cleared. They just looked at our historical data around their models. So they basically said, Hey, this is the stuff that you cleared during this timeframe. If you were living with artificial intelligence, we would have been able to match 20 and we would have got 80% right. So right now we’re just in that phase where it was kind of in the past if that makes sense.
So, how are you going to do that? in the future? So when the AI runs, and you have, you know, 5% that you find out, okay, that’s actually not valid. How are you going to make sure that that part that the AI doesn’t find that you find it? Because you still need to go to college?
[26:20] Jacob Wetzlar:
Yeah. So I mean, it’s something that I saw, it’s still in the working process. So I may not know the answer Exactly. The way I kind of envisioned it is that at first, we’ll work sort of on an exception basis. So we’ll see what the system is going to predict that it should match. We’ll make sure we agree with that until we can get a good confidence level. And then we’ll get to the point where we feel good about what it’s matching at. And then we’re only going to deal with the exceptions. So ideally, it would just be truly on that exception basis. Let’s see what it can do. But again, we’re not truly there yet, so may change a little bit, but that’s kind of what I envisioned.
Hi, quick question. What is the tolerance level you were talking about? auto resolving deductions. I don’t know what the dollar amount would be or it’s based on certain like non-trade reason codes or it’s a trade it’s this much.
[27:08] Jacob Wetzlar:
Yeah. So we do it is based a little bit on the type of deduction that comes in we have different tolerances based on that. So it does depend a little bit but yeah.
A lot like let’s say for shortage in damages. Non-trade do you?
[27:24] Jacob Wetzlar:
So so for us it’s we go at $750. Okay, right now to set is honestly something that we continually look out to make sure that that’s a good one right now. That’s what it is, but okay.
And do you use them for trade? Do you use outside the system for that, as well, you were talking about trade finances uses some other system or-
[27:44] Jacob Wetzlar:
Yes, we have a trade planning tool that our sales team goes in and they create the promotions in there and then that integrates into HighRadius and so our deductions go into HighRadius or sales planning tools there as well and HighRadius is where we match them up, but there are multiple systems that they integrate into HighRadius.
So her question was a nice segue into mine. So if you have a trade promotion tool outside of HighRadius, and it matches in HighRadius, is it auto clearing back to that trade promotion Are you do in duplicate closures?
[28:20] Jacob Wetzlar:
Now? So it’s pretty much automated, I guess. So we actually when we match it in HighRadius since things back to our earpiece system to actually close out the deduction, that it also sends data back to our trade planning system in order to record the spend as well. So it’s nothing that we do on our end, we just match them in HighRadius, and then it kicks off these interfaces that the record was called out in our earpiece system. Yeah.
There’s plenty of running for me. Yeah, that’s good.
[28:49] Jacob Wetzlar:
Work up your appetite.
Maria Froman who’s a bush, I have a question about your organization structure. What is the split of roles and responsible abilities between the deduction team? And for example, the team members on the logistic side who are actually looking into the issues you’re raising, or for example, between the deduction team and the customer service team, which is also obviously working with the customers and receiving some of the claims come into them.
[29:20] Jacob Wetzlar:
Yeah, let me know if I don’t answer your question exactly. But so the way that we work is, so we fall under finance. So we’re, you know, fall under that finance piece, and then our customer service and of course, the logistics all fallen in the supply chain piece of it. So we have, there are about 50 people total in my organization that we handle is the shared service center. And so when we find those deductions, we send them off to our logistics team who validates it with pod and everything else. And there’s a handful of people on their side who actually validate it. If it’s valid, they send it back to us, we match it with credit if it’s invalid, they send it back to us and we try to collect it. So they’re the ones that try to validate that piece of it. Customer Service, you know, again, a different department will assign deductions and HighRadius to them as well. And so, you know, I don’t know if I’m answering your question exactly. But where we do have that split? That’s where a lot of that collaboration comes in and sending those deductions and that information back and forth between the different departments.
That makes sense. Yes, yeah. The trade off-trade promotion.
My just a quick follow up to that question. You said you’re sending it to HighRadius. Are you using the correspondence tool within a high radius then to manage the workflow back and forth, the email communication, what would typically be email communication and everything.
[30:39] Jacob Wetzlar:
So we are not using the correspondence packets as much with that piece. We’re actually so our sales team as well as our logistics team, we actually give them access into a radius so they have a username and password of their own. We’re just assigning ownership. So we have the owner and the processor to them. So we’re actually changing I guess it’s the process or not the owner we’re changing the processor to those salespeople are Those logistics people into their name. They receive an email anytime something’s assigned to them. And the expectation is that they are going to log the entire radius. Look at the notes, everything else we have with that, do something, note it and then assign it back to us.
Perfect. Thank you.
[31:17] Jacob Wetzlar:
All right. All right. Thank you.
Thank you very much.
[0:00] Anchor: Thank you for joining a session on why you need a tech-driven approach to resolve FMV deductions actions faster. Today our speaker is Jacob Wetzlar, Director of credit and they are at Danone. Jacob is an experienced business professional with a diversified background that includes sales, receivables, payables, account balancing forecasting and financial analysis (giggles) that was a long list and now that the housekeeping is out of the way Jacob the stage is all yours. [0:32] Jacob Wetzlar: All right, thank you guys can hear me okay. All right. So a lot smaller stage. So if we don’t walk off of it here, but I’m grateful for the opportunity to speak thank you guys for coming out. I know it’s right before lunch. We’re just talking about I think before lunch is better than after lunch. So hopefully you guys are hungry, you will stay awake. And hopefully, I won’t keep you too long and we can go have a good lunch. But yeah, I’m going to talk about kind of our deduction process that we have Danone, and it’s really going to be from our perspective. So I know there’s a lot of people from different…
HighRadius Integrated Receivables Software Platform is the world's only end-to-end accounts receivable software platform to lower DSO and bad-debt, automate cash posting, speed-up collections, and dispute resolution, and improve team productivity. It leverages RivanaTM Artificial Intelligence for Accounts Receivable to convert receivables faster and more effectively by using machine learning for accurate decision making across both credit and receivable processes and also enables suppliers to digitally connect with buyers via the radiusOneTM network, closing the loop from the supplier accounts receivable process to the buyer accounts payable process. Integrated Receivables have been divided into 6 distinct applications: Credit Software, EIPP Software, Cash Application Software, Deductions Software, Collections Software, and ERP Payment Gateway - covering the entire gamut of credit-to-cash.