In this webinar, GBS expert, Tony Saldanha shares the P&G digital transformation journey during his stint in the company. He talks about how organizations can leverage technologies like AI & ML and be successful in the fourth industrial revolution.
In this webinar, GBS expert, Tony Saldanha shares the P&G digital transformation journey during his stint in the company. He talks about how organizations can leverage technologies like AI & ML and be successful in the fourth industrial revolution.
In this webinar, GBS expert, Tony Saldanha shares the P&G digital transformation journey during his stint in the company. He talks about how organizations can leverage technologies like AI & ML and be successful in the fourth industrial revolution.
Tony Saldanha:
All right. Hey, good evening. It’s wonderful to be back here in Radiance. It just keeps getting bigger and bigger every year. I think you guys are going to need to hire or rent out the airport next time. But congratulations to Sashi and the HighRadius organization. About a month ago many newspapers had this article about how a hotel in Tokyo that was run by robots had fired about half of their robots. Right. I don’t know if you guys had the opportunity to stay there or maybe see this online.
Video:
Henn-na Hotel means a strange hotel in Japanese. And it’s certainly bizarre. There are a mechatronic velociraptor and a female android. To check you in. Different robotics now, humanoid robots are on hand to act as desk clerks and a concierge. And if you don’t want to deal with human waiters, you can get hot dogs and rice balls from this vending machine. Meanwhile, water robots developed by Sharp are ready to carry your bags to your room where a facial recognition camera system eliminates the need for a key. Once you’re settled in your room, you don’t have to feel lonely because you can chat with this little guy or girl.
Tony Saldanha:
Now, this is striking because, among all the news of how robots are taking over human jobs, this was the article that gave us all hope. Like, you know, maybe we can take our jobs back. But in any case, the interesting thing about this is, I want you to actually go the opposite of all of the lessons the news media learned from this, which is that it is actually possible for you to be successful and very successful with A.I. In fact, I would go further and say, I promise you, if you do it right, you will be successful and you will all be heroes. OK, Secondly what I want to do is to actually show you real-life examples of stuff, not like the hotel cool crazy stuff but actually a day to day work in large corporations. That is actually happening. OK. So that’s essentially my pitch here today. And like I said, I had the opportunity of essentially doing some of that through the last three years of my career with Procter and Gamble, where we took global business services and I.T. organization about two and a half billion dollar organization and essentially at some point in time had to face up to the issue of what’s coming, what’s next, where is the world headed and how can we actually go ahead of that? And that’s really the challenge that I’m going to share with you about. And what we actually did was take 10 X disruption opportunities. So not a 10 percent improvement, a 10 times improvement. And we ran about 20 or 25 different projects, which you see up here. And we’re talking about some of them later. Starting with the top you will see things that cut across finance, things that cut across the supply chain. IT, HR is some of the work that I did included with HighRadius was what’s the future of accounts receivables. Right. But as you can see up there, you know, you can do it. What’s the future of master data? What’s the future of marketing or what’s the future of retailing? So on and so forth. Right. And those are some of the examples from my journey. But before I go any further, let me step back a little bit and give you a little bit of a glimpse of, you know, what I hope to cover. I’ll do a few introductions and then I want to kind of talk a little bit about why we’re all here talking about disruption and transformation. Then we’ll go into the P&G examples and then I promise I’ll come back and talk about how I think you can all be heroes. Okay. So if that works.
Tony Saldanha:
Let me start with why I think this Japanese hotel staff failed? The reason they failed is that they actually decided that they wanted to be on the edge. They wanted to make a statement. They wanted to stand out among the hotels. Right. And AI is a technology that’s in its infancy. You know, it was still like children there. Okay. The wrong lesson to take away from this is while we’ll wait until it grows up. Don’t do that. Because like with real children, you know, you can’t basically say, I’ll just give bullets to a fully formed child, it doesn’t work that way. You actually have to start from scratch. And yes, in case some of you guys are wondering, that’s me a long time ago. You know, a very, very long time ago when I actually had black and curly hair and stuff like that, that was the peak of my handsomeness. Ever since then, it’s been in complete decline. And so that’s the reason why I use that particular photo.
I had the opportunity, as it was mentioned during the introduction of a wonderful career with P&G, I happened to be on the leading edge of many of the developments of the I.T. and chip services industry, including setting up the first shared services for P&G in the Philippines in 1993. And then, you know, being associated with a program managing the outsourcing of two-thirds of I.T. and shared services, a 10 year, a billion-dollar deal in 2003 of acquisitions and divestitures with the Gillette Company. And then running these operations in every region of the world. And finally and most importantly for this talk, you know, really coming to the realization that with digital and A.I and everything else that’s changing. I was going to have to undo everything that I had done over the past 24 years because it is not sufficient for you to be the best in class amongst large companies.
Our real competition, P&G GBS and IT were considered the best in class, which is all fine, but our real competition is no longer Unilever or other large companies. It is the startups and startups that have a cost structure which is half of ours and agility which is ten times ours. And so we would actually have to figure out what is the future of shared services in IT and processes like AR are across the industry. So, anyway, that’s a little bit of my story there. I mentioned Procter and Gamble. I don’t want you to take away the wrong impression of the quality and quantity of my hair. P&G products are much better than that. I promise you. In fact, I guarantee you that if I hadn’t used head and shoulders, I would have had no hair. But you know, I’d be happy for you. What you have, I guess. But anyway, the lesson I wanted to take you guys to take away from that was that again, this is the context of a large company. Seventy-five different countries, large operations and stuff like that.
Tony Saldanha:
So I mentioned the dilemma that we had about three years ago, which is what do you do next? Once you have, for example, wall to wall S.A.P for finance and supply chain and order management and HR across the world, one standard, one operation. Right. Until we actually reached out and talked to a hundred different entities because we were sure that this was not the pinnacle of success. We knew you know, we knew all the mess that we had. Despite the fact that we had common systems and stuff like that. So they had to be the next generation. And as I said, we set out to actually create that for the industry. So I set up an organization called Next Generation Services. We invited seven or eight large companies. So the H.P ‘s, the Ernst & Young and so on and so forth to actually become a part of this, put in money and resources. And then we worked with about a thousand different startups through our connections with the venture capitalists. And then we took specific areas, accounts receivables, supply chain planning, payroll, so on and so forth, then set out to actually create 10x disruptive kinds of capabilities.
The reason why that’s important is, I promise you that even as you sit here and listen to Shashi talk about how the world is changing around us. It’s humans plus machines. There is a part of us that gets so immune to reading this day in, day out that the gap between realization and action never really gets bridged. OK, so what I like to do, and I beg your forgiveness for the next five minutes is try and connect the dots on why all the things that you hear in the media are not just important, but it is very urgent for you to figure out what you’re going to do about it.
OK. So you saw a version of this earlier today when somebody talked about the singularity. The thing I want to point out to you is for a thousand dollars by 2023, you’re going to be able to walk out and buy the computing capacity of a human brain. I don’t know about you, but that is absolutely amazing, it’s mind-boggling. A human brain is a fantastic organism. It is a miracle of nature, if not a higher power. And to be able to go and buy the capability of that for a thousand dollars is absolutely crazy. But it gets worse or better depending on where you come from. Because 20 years after that, you’re gonna be able to go out for a thousand dollars and buy the capability of all the humans on earth for a thousand dollars. Now, If you are a board member or a CEO, you have to be thinking about what my organization plans five years and 25 years from now. How many people are there? How many thousand dollar computers am I going to have? This is happening. This is real. And oh, by the way, you see this in the way the stock market values companies because five of the top 10 companies in the world are tech companies. And don’t kid yourself.
Tony Saldanha:
You work for a tech company today. You might be working for DHL or Procter and Gamble. I’m sorry, but you work for a tech company because of not just five out of the 10. That does not include Alibaba and Amazon. So 7 out of the 10. And guess what? Eight years ago, it was 1 out of the 10. So this stuff is changing before our eyes. It’s changing the nature of every work process, for example, supply chain Zara. Deliver us from design to retail within two weeks. How do you go design a dress and get that in all the stores within two weeks? That’s why I said, our competition is no longer, you know, other peer companies, it is the startup, it is the small companies. That’s why we’re all digital companies. And it’s not just a supply chain. The way products are designed and delivered is changing before our eyes. Xiaomi basically sells a different phone every week. I’m not talking about software upgrades. I’m talking about quite literally significant changes from week to week. Again, this isn’t a hypothesis. This is in the future. This is the stuff that happens. And by the way, this isn’t just changing in one or two companies or one or two industries.
You know, you have data that basically says 40 to 50 percent of service type roles across many industries are going to change dramatically over time. Right. And if you think that this is only stuff that happens at work, that’s not true. This is the stuff that also happens in your personal life because, In about eight years, 10 percent of all wealth management is going to be done by man plus machine. Now wealth management, so managing your investment and stuff like that is an affluent person’s kind of game and they kind of tend to go with the human touch. I wonder why, and to have that be disrupted by having a combination of man plus machine do that is a little bit like replacing your admin assistant with a robot. That’s pretty amazing. And that’s not just your personal life. It’s also sort of society, because if you look at the next piece of data there, In about 10 years the ability, the literacy of a computer in the US is going to be better than 24 million people in the US. Now, you already kind of knew that because for driverless cars to read signs on the highway and understand them. They would have to be pretty smart anyway, right? But to have computers be more literate than 24 million people in our own country is absolutely crazy in the next 10 years.
Tony Saldanha:
So when I talk about the fact that this is urgent, that this is here, this isn’t just, you know, the next release three years from now on some software, that is really what drove us three years ago at Procter and Gamble to say, oh, my God, we can’t be sitting on the sidelines waiting for this stuff to happen to us. We have to be in this. It’s a question we have to ask ourselves. So if A.I is kind of like creeping everywhere. What do we do? Perhaps we just go suck up to our future bosses overlords. You know, that’s an option. That’s a pretty smart kid. I mean, she’s sucking up to her future overlords already. But no, that’s not the key message I want you to take away, the message I want you to take away, You know like I said, you have to be ahead of the game. You are going to be ahead of the game because you have more information than, you know, most people around on what’s going to be possible, and you have context. There is absolutely no reason to be either overwhelmed or worse still, concerned or afraid about this change because this change has happened through humankind over and over again.
It is the fourth industrial revolution. The first three were steam engine electricity and computers. The fourth basically takes all of the evolution of computers and applies that to mechanical, physical, medical and all of the fields. That’s why this is a little bit of a confusing subject because, you know, when people talk about the digital revolution like I was talking about this to my 85-year-old mother, she was like, oh, that’s boring stuff. I had a digital watch in nineteen eighty-five. Now, this is a little different. Right. So that’s why it is confusing. But don’t be confused, we’re in the midst of an industrial revolution. And it’s affecting everybody around us. Don’t get misled by software people or hardware that basically brand everything, digital transformation, and disruption. It’s very simple. If you think about it, digital disruption is the evolution from the third to the fourth industrial revolution. If you succeed, you have successfully disrupted yourself and others, and transformation is your project. Digital transformation is the project journey to take your work in your enterprise from the third to the fourth.
When you start to think about this in that context, then you’re knowledgeable enough to not be swayed by people that want to sell you digital disruption. Nobody can sell your digital disruption. The only people that do it are you, right? And obviously, as I said, everybody wants it right. Because you have to thrive and survive the industrial revolution. And by the way, this isn’t just a blue-collar job issue, as it was with the first three industrial revolutions. This is a white-collar job. One of the examples that my organization worked on was, we worked with a startup that was able to ingest contracts. Really, really big contracts, about six-inch thick contracts and understand them and then tell us which of the clauses, the red line at which of the clauses were not in compliance with P&G, policies or procedures. Better still, it has the ability to also tell us if you want to negotiate those here are three other areas that you might want to give in order to do that. When I saw that I went home and called up my sister who was a lawyer, immediately and said, hey, guess what? You know, your job is toast. But that is so true. It’s not just blue-collar jobs. It’s white-collar jobs as well. And by the way, it’s not just collar jobs. It’s also things like medicine.
Video:
Schroeder creates nanoparticles, each marking a unique barcode that carries a specific medication. These nanoparticles are then injected into the blood and into the malignant tissue penetrating through miking fissures that do not exist in healthy tissue. The nanoparticles then discharge the drugs within the tumor cells.
Tony Saldanha:
Why is this digital transformation? It is because these nanoparticles are actually programmed just like driverless cars to get to specific coordinates in the body. Okay. This stuff is all around us. You see it all the time. Here’s an example from my, you know, hometown city of Cincinnati. This is a tweet from the police that says shooting in Evandale, which is a locality victim, lied until confronted with evidence from a ShotSpotter. ShotSpotter is this technology that triangulates in real-time from the sound on cameras around the city and dispatches police in real-time to those locations. Okay, now that’s understandable in New York and maybe Houston and, you know, London. Well, we’re talking Cincinnati. Cincinnati is the town that Mark Twain said when the end of the world arrives, I want to be in Cincinnati because Cincinnati is 20 years behind the times, right? This is Cincinnati. This stuff is all around us. So then the question, as always, is, you know, a little bit like anything IT. Right. How far is this right? Is this like the next version of, you know, Microsoft or SAP or HighRadius software, it’s gonna solve world hunger. And then this happened. So this was 2015.
Like I said when we started on this journey and I went out and was talking to about 100 different executives, and one of those I was talking with, I wanted to meet with was the CEO of a startup. His name was A.J and we were playing, you know, schedule tag over email. You know, he said, you know, how about this date? I said I’m not available this week. How about next week? And he said, fine, you know, clopping. And any who I assumed was adamant. Right. And then Amy did her magic, as you can see from the bottom of the slide there. You know, she gave us some options and my admin picked a date and so on and so forth, which is a very boring story. Until you click on Start AI and you figured out Amy is a robot. Now, read that email again. When I said I’m not available next week on the 10th of April, none of the options that were produced were for that week that I was out. OK. Think about the most personal services. The most sensitive services for a CEO administer. And three years ago, you had Amy doing this. Obviously, we have to do something about this stuff. Right. So that’s when we got into it.
Tony Saldanha:
All right, how do we disrupt our own operations? Because if we don’t, somebody else will. And that’s really where these 20, 25 projects that I talked about came in. So what I’m going to do, I won’t have time to go through all of them. But I want to give you a flavor of what’s possible today. All right. With three or four examples, the first one most relevant for HighRadius, because they were involved in co-developing this with us, was using AI for claims management. Now at P&G, we have about 400 people across the world on AR. Most of the stuff that they do is claim management, disputes management. We’re fairly well organized on stuff like cash application and, you know, figuring out creditworthiness. So that’s actually the small FTE in our organization. The bigger FTE is actually disputed. So we sell a thousand dollars worth of stuff to Wal-Mart. Wal-Mart ends up paying us $900. And then you basically say, hey, you know what gives here? And they say, well, that’s all the goods that we got. And then who’s got the truth in there? Right. Is it the trucking company that dropped a few cases somewhere, you know? Did we send the wrong stuff there? So that’s really what disputes are all about. So he said, fine, you know, we had done some work early on with a startup in Silicon Valley, which sounds very, very fancy for a two-person group that was just data scientists. And then we brought some of that along with HighRadius. We basically scaled it. And at the end of that, we were able to predict with more accuracy than our existing AR people, whether a given dispute should be adjudicated in our favor or the customer’s favor. And this is something that’s, you know, being used for a couple of reasons right now.
So again, this stuff is possible. It doesn’t need data and stuff like that. So don’t wait. You have to get your act together to do some of this stuff. So don’t wait too long. But this stuff is possible. Right. Here’s another example. So this is a little bit like Freeda. But, kind of take it to the next level. So P&G has about 800 people in call centers where I mean, if you buy one of the P&G products, you know, a Pantene shampoo, you basically call the 1 800 number behind it or, you know, the e-mail. And this is all over the world, actually 800 people. Now, the job of those poor people is actually very tough because one minute you get somebody that says, hey, is the ingredient for dye, ethyl oxide, whatever in shampoo, sustainably sourced in Indonesia. And then, you know, the next call is, hey, my baby’s diaper keeps leaking in. What’s the problem? Right. And so how do you know across a hundred and different brands, how do you even keep track of all of the answers? And so typically what happens in these is, if it’s an easy answer, they basically type it in, you know, and give a response if it’s not your follow up and you call up later on stuff like that.
So what we did was two sets of artificial intelligence, one which was a voice to text a little bit like you saw Freeda do, except the thing that we did here was we decided to make it interesting and we started with Chinese to English because that was our test. So even as the call came in, like Freeda, instead of the agent typing in all of the details, it kind of auto-populated. So instead of spending his or her time typing, they were focusing on the consumer. The second piece of A.I was actually then taking that question and querying the back end systems to say what’s the best possible answer? And if it was an e-mail, then you didn’t even ban it, basically even crafted the response. We didn’t send it because we didn’t want a robot talking to a consumer at that point. But, you know, and again, this is the stuff that is again in use in China, in the UK and parts of the US. Right.
Tony Saldanha:
So, again, the stuff is real. Another example. So if you are, driving down the highway and you feel a little hungry, you basically say, Hey Siri, where’s the nearest ethnic restaurant near here? And then Siri basically tells you, all right. You know, here’s whatever the nearest Thai restaurant is. OK. Siri can essentially look at different sources of data. Right. Obviously address locations, translations of ethnic equals, tie, you know, so on and so forth. Right. On the other hand, if you have a new higher joining your company, how many different systems do you think you have to go into to enroll them? Security payroll, employee number in our training, so on and so forth. Right. And that’s perfectly understandable because those are standalone systems, so what we said is fine, we’re going to use consumer technology in the corporate world. So how about you have one agent that negotiates with all of the systems at the back end? But the employee can basically just say, I’m moving from Singapore to Cincinnati. You do whatever you need to system. So essentially in the way that works is you create a little bit of a master virtual assistant that then negotiates with the backend system that, you know, kind of puts all of that together again, stuff that’s possible.
Actually, in the break out earlier in the afternoon on the blockchain, they were talking about the work that Maskin and IBM had done to essentially put global shipment information. So if you’re importing raw material from China in all into one blockchain. So we were part of that about two or three years ago, except that we were a little crazy and said, OK, that’s cool. But, you know, can we make this bigger? Can we make it 10x? So we said if you have all of this information, you know your contract, how much you’re supposed to pay to the supplier, you know, if it was in port for so many days, you know how much you paid customs and stuff like that. Why would you ever want to receive an invoice? Because that’s just paperwork. So he said, let’s play around with auto invoicing. So you don’t need any of these systems because, If you have real information and it’s supposed to be the immutable record, which everybody agrees to, then no paperwork. Yeah. So again, we’re kind of testing that in fifteen different lands across the company at this point in time.
But again, these are examples, I wanted to share with you examples of stuff that’s possible where you can actually say. I want to change the way my organization works, right? And the question as always is when you hear all these stories, it’s like, cool, yeah, but you know, I’m starting from here or here, how do I get there? And what I wanted to share in the next few slides is learning from all of those hard years that gave me the gray hair on where to get the start and where to make mistakes and not.
Tony Saldanha:
All right. So the first thing. Don’t do it. Don’t piss off your overloads from the future. No, I’m just kidding. OK. The first thing, as professionals, is to understand where you are in the journey on financial services. You know, maybe your organization is still in the stage of managing chaos or maybe it’s at the stage where we are already starting to get to AI-based algorithms. Right. It really doesn’t matter. Everybody is kind of going through that journey. Yeah. The one thing I will tell you is, unlike Proctor and Gamble, you are not going to take 20 years to go from one extreme to another. Yeah, you don’t have to. You can leapfrog from any point to any point there in about two to three years, but you have to understand where you are in the journey first. The second thing you have to do is then be aware of what’s happening around you. So I pulled out this information on trends in the generic financial world. I couldn’t get that for AR alone. But maybe this is more useful for you guys as leaders. And you can see that many of the topics that were talked about in the conference, Blockchain. You know, so on and so forth. Right. It is already recognized as a trend. And you know that. And you have to be, you know, very, very clear about how some of these are going to impact you. Right. Including AI. And this is the key. This may be the most important slide that I can share with you. The mistake most leaders make is they say we are here. You know, some of these companies are here. I have to focus on it. I have to build my foundation. I have to get my data ready before I go there. Bad mistake. I learned this from Google when you know the benchmarking of 100 companies.
Google has a 70- 20- 10 formula. They have 70 percent of the resources working on current operations, 20 percent on continuous improvement and 10 percent on disrupting themselves. Now, your ratio doesn’t have to be 70- 20- 10, when I did this stuff at P&G, it was probably more like eighty nineteen points nine and point one. And I’m not joking. It was probably like point one, all of the stuff I was talking about was not expensive stuff. But you have to think three tiers because you have to think of how I won today? And how do I win tomorrow? And if you don’t think that way. If you think linearly, Then you are going to take 20 years to get there and that’s 20 years that you don’t have. The other thing that I can share with you is some of the most innovative companies, certainly, Amazon, Google, Samsung are examples.
They make the ecosystem work for them. Right. So this is an example from Samsung on the connections that they have with academia and other supplier companies and so on and so forth, that Procter and Gamble, I basically went to those seven large companies, HP and others, and said, give me your people, you know, or at least take some of the billing that you do for us and help redirect some of that into innovation. I don’t care whether you are a multi-billion dollar company or a multi-million dollar company. You have an ecosystem around you. Put them to work, put it to work. Have the ability to essentially take a small fraction of your resources. Point one percent maybe to keep track of what’s happening. Next, most importantly. Look after your people. Technology grows exponentially. People’s capability grows linearly. If you don’t recognize that in the next few years, you’re going to end up with a bigger problem because you’re going to have to then replace not just your technology, but you’re gonna have to replace your legacy people, which is a terrible term.
Tony Saldanha:
Again, just like the 70 -20- 10, you have to have investments in your people. And then even if you do all of that, there is this data that 70 percent of all digital transformations fail and they don’t need to fail. They fail because of this Alice in Wonderland type thing that happens. I don’t if you guys remember from Alice in Wonderland, Alice in the Cheshire Cat, where Alice says, hey, which way do I go? The Cheshire Cat says, What? Depends where you want to go. She says I don’t really know where I want to go. Then he says, Fine, go anywhere. Right. And it sounds funny, but that’s essentially what happens with technology and what processes in most organizations. When you say I want to digitally transform, it’s like you talking about my mother’s digital watch or you’re talking about surviving the third and fourth industrial revolution. Which is really in the book and some of the stuff that I know, I have some flies out there. The biggest learning that I’ve had is real digital transformation takes not creativity, but discipline. You have to be extremely disciplined about where you want to go and how you want to get there. Right. And if you do that, then I promise you, as I said at the outset. You have all the reasons in the world where you can be heroes because this stuff is not rocket science. This stuff is something that you can do. Anybody can do it. Because it’s been done before. If you can have a robotic admin assistant if you can have AI judge whether a claim is more valid. Another. If you have camel racing to be done by robots, then you can certainly transform your organization. And I wasn’t kidding about the camel racing being driven by robots if you’re interested. Take a look at this.
Video:
Camel racing is an ancient tradition in the Arab world, but mechanical jockeys used today have only been around for a decade or so. The jockeys weigh about six and a half pounds. They come equipped with a walkie talkie, so the camel can take directions and a small whip, which is activated by remote control. There you go. Thank you very much. Don’t leave yet. The night is still young. We have a few more instructions on what’s going to happen next so that. Do we have some time? OK. Questions. Other than where’s the nearest bar? For tough sorry, you go.
Audience:
Hi, I was actually very interested in this line about how you used blockchain to track Damaris shipments all the way down to the invoice. Could you explain how that came along? Who sponsored, was it P&G that came up with it or was it, Damaris, that you’re trying to resolve for. And what was the benefit that you got out of it?
Tony Saldanha:
Yes. So the short answer is the actual construction of the network. You know, working with the government, customs authorities and all that kind of stuff and giving the data and you would never have I mean, that’s not our business. Right? So for all of the stuff I was talking about, we always took stuff that was happening somewhere in the world. But in a standalone silo, I call it the Lego blocks and we assemble those Lego blocks and then we put cement around them to actually create a new vision. So in this particular case, that Lego block, which is convincing the various governments and Port Authority to actually use blockchain was done by Maersk and IBM. So we were starting to get information, except they were trying to sell us information. It’s like you can see in real-time where your goods are. And I was like, yeah, what am I gonna do with it? And then we said, well, wait a minute. We have about a billion and a half dollars of stuff, you know, at any given point in time through the year in transit. And no, actually, that’s not true.
One and a half billion dollars was actually not just the stuff in transit for raw material, but, you know, some of the finished goods as well. And then we said we have quite literally thousands of entities involved in there. And our estimate was there was about a 40 percent loss of costs because when somebody says, hey, you know, in Abuja, in Nigeria, you know, we paid such and such money to the customs authorities, they give you some very sketchy paperwork. All right. And so what you do is you have people that manage other companies that validate whether that’s true. All of that’s losses. Right. So we basically said, all right, cool. You know, cut out the middleman. Oh, sure. Oh, yeah. Now, that’s right. I’m sure you may be able to get some of these from HighRadius as well. Happy to share. OK. If there’s nothing else again, let’s get to the really important questions like where is the bar?
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.