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Most GPOs today are focusing on redefining the value proposition of their shared service centers by readdressing service level agreements, prioritizing talent management, and leveraging digital transformation opportunities.

In this panel discussion Tammy Lindorf, Director of Shared Services at Martin Marietta highlights the evolution of shared services and their A/R automation journey with HighRadius. She also shares her vision for the future of her A/R team and highlights her proven strategies to select a next-gen technology that helps Martin Marietta’s GBS team achieve a best-in-class status in the industry.

On Demand Webinar

How Martin Marietta Achieved 85%+ Cash-Posting Rate By Leveraging Advanced Automation

Session Summary

Most GPOs today are focusing on redefining the value proposition of their shared service centers by readdressing service level agreements, prioritizing talent management, and leveraging digital transformation opportunities.

In this panel discussion Tammy Lindorf, Director of Shared Services at Martin Marietta highlights the evolution of shared services and their A/R automation journey with HighRadius. She also shares her vision for the future of her A/R team and highlights her proven strategies to select a next-gen technology that helps Martin Marietta’s GBS team achieve a best-in-class status in the industry.

Key Takeaways

GBS leaders need to modify their business model to achieve an optimized digital transformation through people, process, and technology
[03:25]
Highlights
  • People Management: Understanding the workforce requirements to improve operational agility.
  • Process Management: Standardizing the best-in-class processes tied to the vision and goals of the organization.
  • Technology Management: Understanding the potential of the next-generation technologies and implementing them in the ongoing operation to stay ahead of the competition in the market.
Shared service leaders’ expectations from technology implementation in A/R
[04:03]
Highlights
  • Enabling better visibility across different business units with ERP-agnostic technology to integrate with data systems for seamless flow.
  • Minimizing human touch and transactional-based activities with automation which allows the team to focus on strategic initiatives involving decision-making.
  • Achieving a positive customer experience by balancing the customer demands while working towards safeguarding the cash flow.
What are the challenges that affect a digital transformation project
[08:15]
Highlights
  • Transitioning from working on low-impact tasks like data aggregation to more value-added tasks like root-cause analysis to identify the validity of the disputes raised by the customers.
  • Having a decentralized system leads to a disconnect in the information between the credit and collection teams resulting in inconsistencies in the core A/R process.
How did Martin Marietta strategically overcome their A/R digital transformation challenges
[09:00]
Highlights
  • Optimizing credit management with an online portal to provide transparency to the customer in the credit approval process.
  • Implementing OCR to replace manual processes enabled the team to better allocate their bandwidth to more strategic tasks like credit reviews.
  • Implementing an automated collection system to allow better visibility across the team resulting in faster follow-up with the customers.
  • Adopting a self-service portal for the customers to enable frictionless billing and payments experience globally through an auto-invoice delivery system.
O2C in 2022: How disruptive can Artificial Intelligence (AI) be in this new era of digitization
[19:48]
Highlights
  • Outperform RPA in terms of data processing with improved experience and functions without regular human intervention
  • Provide a consolidated view of the customer’s credit portfolio to the teams for easy and quick access to the customer-related information across different teams and business units.
  • Deploy AI in credit/AR departments to help the team improve productivity and significantly reduce operation costs.
How Natural Language Processing(NLP)-powered Digital Assistant could help A/R teams create working capital impact for the CFO’s office
[22:40]
Highlights
  • Organize the analyst’s worklist by arranging action items based on their priority levels.
  • Managing the call dashboards by identifying critical customers and providing transactional details resulting in faster data collection.
  • Transcribing live customer calls and capturing the crucial data to quickly track essential details from the call.
  • Suggesting intelligent actions based on the call and enabling the leaders to make 2x faster decisions.

Susie West (0:01)

Hello everybody and a warm welcome to today’s webinar, which is brought to you by shared services sync in association with high radius. Today we’re looking at Martin Marietta’s story where the future-proofing accounts receivable with next-generation technology. My name is Susie West. I’m the founder and CEO at Shared Services link. Pleased to be introducing our two presenters today. Tammy Lindorf who is director of share services at Martin Marietta and Elaine Norwalk is Director of Product Marketing and Management at HighRadius so great to have both these leaders and order to cash experts with us today.

Susie West (0:35)

So Lets have a look at the context for today, shared service organizations. We are on that evolution and we’re sticking with it despite all the challenges for 2020. We are sticking with staying on that evolutionary curve where we’re moving from being mainly transactional to then moving to value-adding and making sure that we’re helping our companies with a competitive edge. So this means more and more global process owners and in order to cash are focusing on redefining the value proposition and making sure that the shared services organization really is handing back immediate value to the business units and making sure that they’re up to date. With what the changing needs of the business units are as far as their demands on order to cash. So Global Process Owners is doing this by redefining the service level agreements, looking at the services that they’re offering and making sure that the talent pool that they have can deliver on all of this, and making sure that the digital suite that supports their service is spot on the service they’re looking to offer out. So this means that GPOs are being faced with a lot of demands, and they’re having to make sure that they’re staying on top of what their operation looks like so that they can deliver that optimum service. Today we’re exploring the next steps for many shared services organizations out there, and looking particularly at how Martin Marietta has evolved their share services and why automation has been instrumental in what they are now doing today, and where they’re going to move to in the future and how they’re going to be future-proofing their accounts receivable with next-generation technology. We’re going to be exploring the operational challenges that they were faced with before they partnered with HighRadius and before they embedded their automation program, and what the results have been how they’ve overcome a number of challenges that they were faced with and some of the results that they now have regarding customer onboarding and automatic cash postings. We’re going to do a bit of a deep dive into technology. We’ll be focusing on cloud technology and artificial intelligence technology, looking at chatbots and digital assistants. So lots of exciting things to cover. Now’s a good time for me to introduce you more formally to Elaine Nowak. Over to you please Elaine.

Elaine Nowak (2:38)

Thank you so much, Susie. So what I want to talk about a little bit today is the shared services maturity and what might be the next model of operations that we can see. So the Shared Services operations have really undergone beyond they’ve gotten beyond that primary objective where initially they were put into place because organizations were looking to reduce costs, and they did that to a cost optimization model. And then the next generation was Okay, now we’re looking at our shared services. How do we find a value creation model that we can put in place and that can drive it and use modern technology to do that? So what I’d like to talk about is where can we go from here? What could be the next level? And what’s that scope of improvement that we might be able to see? So in order to achieve that next level potential of the assurance services center model, what we think accounts receivable leaders need to do is drive change across each one of these three business levers. And this will help you to achieve an optimal digital transformation. You really have to look at people management, so understand the workforce and how it has to evolve as a result and what do those job requirements and skill sets look like? Then secondly, you have to look at process management. So how do you standardize the best in class processes that you are putting in place? And how do you tie those back to the vision and the objectives and goals you have as an organization? And then thirdly, you really have to tie in the technology management piece. So look to the latest that’s available technology is continuously evolving. It is constantly evolving, and there’s always going to be a next-generation & next generation that will come out. So you really need to stay on top of what that looks like what those capabilities are, and use that to help set you apart from others in their markets and from your competition. So first, I’m looking at that cost optimization for the shared services centers in looking at that workforce and you know, if you’re looking at the basic functional skills, but then you support that with first-level things like robotic process automation and those standardized processes that is going to help you achieve that cost optimization objective but if you leverage the more advanced technologies like artificial intelligence now companies can standardize across their shared services, and if you coupled that with economies of scale that’s really going to help organizations to realize their goals.

So when you look at the value creation and the shared services centers, using technologies such as artificial intelligence, that’s when they’ll be able to move past the traditional cost reduction goal. And focus more on customer satisfaction and performance improvement because now you’re really creating the value of the integrated processes. But then how do we get to that next level where you have the competitive edge? So what we think mobile organizations are going to need to do is leverage things like digital assistants and AI-powered tools because that’s going to help you thrive in the competitive market today. So if you combine that with your self-motivated performers, now you’re going to continue to advance forward and remain a leader and the leader within your space. So to achieve that vision of a competitive edge, what we see technologies that need to be enabled and allow organizations to have three things better visibility across their business units, and using that with ERP agnostic technology and then being able to integrate data systems for seamless flow. Secondly, you really want to minimize the human touch and transactional-based types of activities and use automation to allow your analysts to really focus on those strategic initiatives. And then, as a result, we’re going to get to number three, you’re gonna have organizations that are able to achieve better customer experience is now it’s a results-driven and a results-delivery type of approach, and you really can do all this much more quickly. So in a much more time-sensitive frame. So now having said the stage for where we see the future of shared services, let’s have Tammy tell us a little bit more about her work at Martin Marietta and how they use automation to help realize their vision of value creation for the Shared Services Center.

Tammy Lindorf (06:30)

Thanks, Elaine just thought I would give you a little bit of background about Martin Marietta for those of you that are not familiar with us. We’re an American-based company and we’re a leading supplier of building materials including aggregates cement, ready mix concrete, and asphalt remember the S&P 500 and we have a network of 400 operations spanning 27 States Canada in the Bahamas. So first, I want to give you a look at our shared services environment. I was brought on board in 2015 to set up a shared services model for the company and they decided they needed a shared services bottle to better effectively integrate acquisitions and to work towards our mission of becoming a world-class organization that has done a little further into the order to cash landscape. We’re currently structured we have three lockboxes at three different things. And then all of our EDI transactions come into a different bank or division structure and that’s based on regions of the country. The credit collection function is performed out within the divisions and then the cash application and credit references piece of the business is handled within shared services. So as we look at what our challenges were in our order to cash landscape. From the credit and collection side, since we were decentralized, each division had its own process, which caused inconsistencies for shared customers. Our customer setup was manual. So there was a form that was sent in to be set up and then when an internal audit or external audit went to audit the documents that were used to set up credit they were getting inconsistent information where it was difficult to find our cash posting rate before automation was 49% for EDI and 74% for the lockboxes. So one of the first things we looked at is what were the challenges affecting our digital transformation project. And it involves around three things, of course, people process and technology, from a people standpoint, really wanted to transition our team from people just keying in information to a more value-added service of analyzing and optimizing what they were doing. We needed better productivity tracking to understand where the time was being spent. from a process standpoint, we really needed data to understand our pain points, and what process was sucking time from the team. And we also needed to standardize across departments and divisions. We wanted to switch from a technology standpoint from a manual process or offline to letting technology do the work for us. Overcoming the digital transformation challenge so what we did is we evolved from identifying our pain points to defining our expectations from the solution in the vendor to make sure we’re aligned. We of course would like everything to be perfect, but we know that you have to work with the provider to understand what capabilities exist so that your expectations are reasonable. We then worked on getting stakeholder buy-in we created a solution deployment strategy, and then we worked on change management. So when we worked on identifying our pain points from an HR perspective, the first thing we looked at is credit management. The biggest issues we had were inconsistent credit calculations throughout the company, and all of the manual record-keeping and customer setup process. From a cash application. We were experiencing a lot of miskeen by the bank, which was causing misapplications and frustration for our collectors. The manual application that we had to do for a lot of customers that didn’t just pay by invoice. We had customers that paid either by tickets or by statements and that information had to manually be looked up to obtain those invoice numbers to then apply for the payment. So it was very time-consuming. So as we looked at what our expectations were from a credit management standpoint, we wanted an easier customer application form. So we wanted the customer to have a better experience in dealing with us. We wanted more support being maintained. So we wanted a system where all the support could be online and easily reviewed by anyone that needed access. We wanted to standardize our rating procedure on how credit was granted and the credit approval authority to what level different people could approve credit. And then of course on the backend, we wanted to automate the customer setup from a cash application standpoint. We were just looking for increased accuracy. OCR keeps the banking errors to a minimum. So what was happening by humans before we don’t see as many issues with OCR grabbing that information efficiency. So as I mentioned, we had a lot of time spent doing statements and Bill of ladings or tickets that we were able to automate with the system and wanted to automate with the system. From a cost-savings perspective. We wanted to eliminate a lot of those costs that are associated with keying and also help reduce some headcount. Although headcount wasn’t the main driver we felt by improving some of the systems it would just be a natural evolution. So what were we looking for in a vendor it is preferences to limit the number of systems that we interact with. And therefore it was very important for us to find a partner that we could grow with and that had numerous product offerings. So we needed a solution that was scalable and easy to integrate the various product offerings that we found with HighRadius, you know, this credit and cash application, electronic invoice, presentment and payment, and then the collection aspects, so that was very appealing to us. We wanted to find a partner that was committed to system improvements and always looking to grow. One thing that I found very helpful is I actually attended radiance, which is the annual user and innovation conference for HighRadius where their customers attend and get together. Last year it was at the Dallas Cowboys Stadium with more than 1000 industry and finance professionals in attendance. And what I found is it gave me that opportunity to talk to customers and get that unfiltered opinion of what they thought about the system and overwhelmingly the customers just loved it. So that draws through us to the system as well. So once we select that we haven’t done go get stakeholder buyin, luckily, which I know is not the case with a lot of projects. Since I was brought on board to standardize and find efficiency management was already very open to any improvement suggestions. So it was very easy for me to obtain approval plus it didn’t hurt that the solution would provide increased accuracy and efficiency and also cost savings. So from our deployment strategy, it actually evolved, right, because we were committing to multiple areas of HighRadius and we thought we could do them all at once, and then as we learned more about the product and limitation and what other competing projects we had going on, we evolved to how we were going to do that. So I think it’s very important whenever you’re looking at a project like this flexible and ensure that IT is engaged and available. Right there are things that we like to do a lot of acquisitions, so we need to be flexible when an acquisition occurred, and understand how that would affect any timeline that you had developed. From a change management perspective. We made sure to engage the team as early as possible to really understand what they felt the pain points were for them what they were looking for from a new system, we made sure the team was completely involved in the design and testing of the system. We made sure to align staff reductions with retirement, so it wasn’t a matter of the system being implemented to drive account savings. There was just a natural evolution. And then we made sure even after the implementation that we continue to solicit feedback, and whenever possible, implement their suggestion so they can see they have a direct impact on the system. So as we look to where we are now from an EDI standpoint, we’ve been able to move from 49% automation to 70% automation which is great. And then as we analyze those things that are causing a barrier to get that number higher, we have found that 80% of that just is related to the customer not providing what we need to apply for that payment. so no remit or invalid information on the remit. So we’re trying to work with our customers to improve that. But also 9% we found are things that we can work with HighRadius on to further improve the system. From a lockbox perspective, we went from 74% up to 84%. And similarly there 8% of the issues we have are with customers not sending grievances at all, or sending invalid information. And we have 3% that we’ve identified as possible improvements that we can partner with high radius to further drive that 84% Higher. So what else are we looking at for future opportunities? Collection Management is an area that we are looking at. We’re very impressed with the HighRadius tool and would like to evolve into implementing that tool as well. Because we want a system for tracking what the collectors are doing. We want to be able to see their notes ensure they’re focusing on the right customers. We don’t want people making calls just for the sake of making a call. We want them to do value-added tasks. And it also would give us a way to better control our interaction with our shared customers across divisions to avoid confusion. We are also looking at the electronic invoice presentment and payment feature which would allow a solution for us to better track our invoice presentment to that customer.

Tammy Lindorf (16:03)

We want to be able to offer more electronic invoicing options than we currently have with our current platform. We also want to use their cloud solution as a backup processor for payments coming into our customer portal. So we have our own Martin Marietta customer portal that we don’t want to change but we want to be able to leverage HighRadius in the backend to make it more efficient. Next, I’m going to hand this back over to our Elaine so she can explain what HighRadius is offering to meet the challenges that we are all facing.

Elaine Nowak (16:30)

Thanks so much, Tammy. And such tremendous achievements through technology. It’s really pretty incredible what Martin Marietta has been able to do. So we’ll talk a bit more about what it is that actually makes up that technology and then kind of go into the differences between the different types of technology and then show you a glimpse at what we think the future is going to be and how we think you can embrace some additional optimization for your shared services centers. So first, just talk about some definitions when I’m talking about RPA and people are starting to hear this term more and more now. I think it’s less than you’ve never heard it and more like well what exactly is it? So robotic process automation is not a form of artificial intelligence. It actually refers to software that is easily programmed using code and it accomplishes basic human tasks. So RPA doesn’t learn on its own. It’s rules based and it works best on repetitive high volume tasks. So if you think of it, it’s like it executes like a human but it has to be trained for every new task. So it’s only able to process predefined inputs. So you get out what you put it very, very strict, artificial intelligence. On the other hand, it’s programmed to think like a human and it mimics the actions of humans. And it can apply any of that functions that exhibits traits that are associated with the human mind. So learning and problem solving, and then AI technology. What it does is it actually parses data, and then it tracks and evaluates what the users do on any given scenario, whether it’s in the document on a data field, and then it applies what it observes what it’s learned. And it does that to able to make its own better, more informed decisions. So this includes think about functions like autofills or autocorrects, where it makes suggestions and over time, it’ll make suggestions that are much more closely aligned to the way that you are working. So AI mimics that human thought process and it does is based on patterns. So AI process the data that’s fed from structured or it could even be semi structured or even unstructured data forms. It doesn’t have to be in an exact parameter. Like it does for RPA. And then what AI does is its behavior evolves with experience and with exposure to data. So if you think about it, you want to look at AI as probabilistic and variable in nature, so it functions without regular human intervention. And then just to just talk a little bit more about RPA, because I think this is where you really want to look at the difference between RPA and AI is that there’s an expectation that RPA is going to automate complex tasks. Now RPA is going to be able to run 24 hours a day, seven days a week, it’s never going to stop it’s not going to take any breaks. Of course, it doesn’t need to sleep and it certainly is not going to go on vacation. And it’s going to do all of that without forgetting or omitting or misunderstanding or under estimating errors and not encountering any problems. While that would be incredible. It’s really not the reality. And while some of those things are true RPA only automates tasks that don’t require creativity or emotional intelligence are complex decision strategies. So where it fails is when there’s an exception or an unexpected event or a particular case that happens that’s outside the norm of the expectation of the rules that were created to execute for that RPA. Now the other hand, let’s look a little bit more at artificial intelligence and why we think you need to look at technology that uses artificial intelligence in order to get the best and most optimized shared service environment. If you look at how the environment might improve collection, for example, it’ll provide a Consolidated Credit & collection profile for a customer and then it can give you that profile across whatever number of ERP systems you have. So in the case like Martin Marietta, where there was a lot of acquisitions and mergers and more systems coming online, you want to be able to still integrate that information across your systems. And across your geographies, regardless of where your different business units reside. And then secondly, you want to single resource that’s reaching out to your customer, you want to create a shared service where there’s no duplication of efforts where you’re standardizing processes and the way in which you’re working with your customer. You also want to make sure you’re utilizing your resources in the best possible way, so that you can make sure that you are putting them in the best position for them to be successful, and for them to take on potentially different job roles according to where the need is and what their strengths are. And then you also want to look to increase collection productivity and reduce costs. So your credit and HR departments, they’re the service providers for the business, your customers, also your business. So you want to make sure that you’re creating this environment where you’re offering the optimal service. So let’s talk now where we see the future. And that’s in artificially intelligent powered digital assistants. Now, about 1/5th of the A/R manager’s time is lost in accumulated data in order to create some kind of report or to monitor the team performance and 37% of A/R staff productivity is lost by simply looking for customer related data or invoice information. So how can AI enabled digital assistant empower an A/R team to be smarter with more information and data that’s readily available? Well, an assistant can provide quick customer information do you need information on a customer’s open invoice? Maybe you want to know the status of your next payment batch or maybe want to know when the next intraday bank statements coming in? A digital assistant can also provide real time data analysis. You could ask maybe what the average DSO is for a customer or who is the top performing collector this week, or what’s the cash position for a particular business unit. And then we also see an AI digital assistant that’s giving future predictions for better customer service. So you could ask that assistant will an invoice get paid next week? Is it a good time now or what is a good time to call a customer? Or what is the cash forecast 30 days from now? So what I’d like to do now is play a video where we’re going to show you what a future with an AI powered digital assistant can look like in the form of Freeda who is the HighRadius’s digital assistant.

Video Presentation of Freeda (AI powered digital assistant) (22:40)

Freeda(22:53)

Good morning, Samantha. Welcome to work. Let’s see what impact you can make with collections today. Welcome to your work board. You could call accounts I have identified as critical. Send some of you automated email correspondence, review new credit applications or the latest credit risk updates.

Samantha(23:11)

Let’s get started with the calls first.

Freeda(23:14)

Sure! Bringing up your call workboard in a second. Welcome to your call workboard, you have 27 customers to call today. I have already prioritize these accounts based on my AI enabled prediction of their aging 30 days from now. For instance, Permalink has one broken payment commitment for $68,000 and has more than 50% of their AR balance past due by more than 30 days. Would you like to start with them?

Samantha(23:40)

Absolutely.

Freeda(23:41)

Here are the key reasons for this call with Permalink. As you can see, this is their current aging and here’s my prediction of their aging 30 days from now, you can see a surge in their 61 to 90 day aging bucket growing at 43% of their total open invoice value. They also have no upcoming payment commitments which you might want to touch upon on the call. They have already reached 85% of their credit limit and you could use this to negotiate payment. JEREMY JONES, manager of accounts payables as your key contact at this account. Let me know when you’re ready to get started.

Samantha(24:15)

Alright, let’s call Jeremy.

Freeda(24:17)

Sure. I will stand by to take notes.

Jeremy Jones (24:24)

Hi, this is Jeremy and Permalink.

Samantha(24:25)

Hi Jeremy. This is Samantha from Pentacore. I was expecting to receive payment for $68,000 Yesterday, just calling to check whether you’ve already made the payment.

Jeremy Jones(24:35)

Hi Samantha, really sorry about that. My manager has been out sick the last few weeks and he missed approving your payment. You will have to wait till the first week of March for him to get back.

Samantha(24:44)

Well, I just wanted to let you know that you have over $60,000 and invoices which are over 30 days past due and I might have to escalate. Your credit utilization is already at 85% and new incoming orders are likely to get blocked.

Jeremy Jones(25:00)

Yeah, no, no, I understand. See I’m only authorized to process payments up to $30,000. I would have got your payment approved but my manager just fell sick and has been out of the office.

Samantha(25:10)

Well, Jeremy let’s see what we can do here. I’m seeing two invoices which total up to around $28,000. Could you help me with payments for these? since these are well within your authorization limit?

Jeremy Jones(25:23)

Sure I can do this by next Tuesday. Could you please send me the invoices.

Samantha(25:28)

Sure sending them to you right now. You should be receiving an email.

Jeremy Jones(25:32)

Thanks.

Samantha(25:34)

Thanks Jeremy. I will be looking forward to the payment on Tuesday for two invoices for 28k.

Jeremy Jones(25:39)

Thanks, have a nice day.

Freeda(25:42)

That was a great first call to start the day with. I have already captured the key action items from a call. I will create a payment commitment and set a reminder for you to follow up with Jeremy. Are you good with these?

Samantha(25:54)

Thanks please save these.

Freeda(25:55)

Alright, I have drafted a summary email for you to send to Jeremy by using an available template from the library. I have also attached the invoices they need to refer to let me know if you are good with this email and I will send this out?

Samantha(26:10)

This looks good. Please send this.

Freeda(26:12)

Done. Let’s keep the day rolling. Here’s your next customer.

—————————-END of Video presentation——————————

Elaine Nowak (26:20)

Having seen the video I’m just gonna recap some of this really amazing functionality that a digital assistant can provide. So first, it’s an improved work experience. So Freeda helps an analyst by organizing their work list and arranging action items based on priority levels and then makes the recommendations on where to start the day and Freeda also manages the call dashboards and identifies the critical customer and account which ones are past due and what the dates are, and then provides details along with the collection amount. That with this workflow that’s been set by Freeda analysts performs their functions faster and trims down their search time collecting data from all these different sources. So in looking at the screenshots, a collector’s day workboard with Feeda it looks like this. So the live call worklist a summary count of the standardized correspondence insight into new credit application reviews and a summary of the credit risk alerts so freedom makes suggestions based on the work board and the analysts decide to call the accounts that were identified as critical and in doing so Freeda pulls up the account. We look at the broken payment commitment. And then the analyst suggests that let’s start with the customer at the behest of Freeda. The next feature that we see that’s really tremendous for these digital assistants. Is the customer interaction transcription. So Freeda actually transcribes that live customer call and then highlights and captures the most important points. So that really saves a lot of time in logging those calls and then understanding what transpired on that call. So we record the transactions for the analyst and that allows your analysts to quickly track all the essential details from the call and act accordingly. So looking at the screenshot Freeda transcribes live customer calls, you can see that on the right side there along with highlighting and that’s what we see in the orange the most important points such as the date when the payment might be expected. Okay, so next Freeda makes intelligent suggested actions. Freeda captures the next steps suggested actions based on the call with the customer now the analyst is able to make quicker decisions for follow-up. In addition, Freda goes to the very next step actually drafts the email, attaches the relevant documents all of this based on the interaction with the customer. Then the analyst could just come in do a little spot check tweak the email before sending out the correspondence and then be free to notify the analysts of the actions items that he created, such as saving the call notes or updating the correspondence history, and more. And looking at the screenshots when the call is happening. We see the Freeda is capturing all that important information in the suggested actions you can see Freeda captures the metrics and the points that provide clear next steps with these intelligent suggestions and thus enables the collector to make quicker decisions. So all the actions and the notifications, Freeda also captures again for the quick action and decision making. And then looking at the screenshot where Freeda even takes up the action such as drafting the email to be sent to the customer based on the call and attaches those relevant documents such as the invoices is in question. And then lastly, intent analysis. So just to give you a definition that involves the researching of emails, web links, or other phone numbers that are embedded in email messages in order to capture the data. Freeda uses this intent analysis and identifies keywords, phrases, letters, sentences, rows, column headings, all of that from the body of the email. So for example, Highradius’s Deduction Cloud has an email inbox that captures all the deductions-related emails and it collects them in a single place. So the analyst sees all those emails in one place rather than having to investigate all of it or find them all. Freeda can go in and capture the data from a deductions email box and use that information to provide a suggestive action for the analyst and even further down the line. What we see as the future with Freeda is that Freeda is going to be programmed to do sentiment analysis. So that’s understanding the intent of a customer and assigning them to a positive or a negative or neutral bucket by using the voice and tone of that customer captured on the call. So Freda will be able to provide suggestions as to whether or not a customer is even likely to keep a promise to pay. So now the collector can take much more corrective actions proactively. An additional capability that we see on the horizon is the suggestion for real-time questions that you can ask your customers on the call. So the free will suggest as the conversation is evolving. And based on that conversation, what other questions you might want to ask. It could provide those suggestions and then how to answer some of your customer’s questions and then it would be able to predict the probability of what questions your customer might ask and with what percentage of probability they would ask those questions. So we have no doubt that Prieta will become a trusted colleague for your AR and Treasury teams. So just, in conclusion, we really see that in order to create that competitive end and really deliver a best-in-class shirt organization, we’ll need a combination of next-generation technologies such as AI-powered digital assistants and a world-class customer experience. So just a quick about high radius for those who may not be familiar. We are a FinTech enterprise software as a service organization and we leverage artificial intelligence-based autonomous systems. To help companies automate their accounts receivable and Treasury processes. We’re headquartered in Houston. We have offices in Europe and Asia and we are the only true provider of the integrated receivables platform for the entire order to cash cycle that includes credits, electronic invoice presentment, and payment cash application deductions and collections. And the hybrid is treasury management platform helps teams conduct accurate Cash Forecasting using artificial intelligence touchless cash management and bank reconciliation and we as an organization have been vetted by industry leaders, we’ve got strategic partnerships within investments from the likes of Citi, PNC. Bank of America, our AI-enabled autonomous systems to help financial analysts to break free from clunky enterprise software that allows them to really make better decisions and improve the quality of the work-life by automating clerical and really transaction-based work. So today in 2020, we’re really focused on dot one performance so that’s really being a one and 1000 and that we work with our customers to help them become one in 1000 type finance and HR departments. And we recently launched our radius one AR suite, which includes a set of ai powered solutions designed to support AR processes for midsize companies and automates the labor intensive processes it maximizes working capital and enables faster cash conversion. So here’s a partial list of some of our customers, you can see that we’ve got dozens of the largest companies in the world that use some of our AR solutions. And even more importantly, I think is that we’re represented in a wide range of industries and we are ERP agnostic. So we can work with just about any ERP system. And we work with a large number of those midsize businesses to help keep their teams lean and efficient as they grow. We’ve done more than 1000 Plus finance transformation projects across 45 countries and we’ve spent years in research and development to be able to bring a tremendous amount of experience from working closely with other industry leaders that have implemented our solutions. And again, the global footprint with offices around the world. We just opened our newest office in Frankfurt, Germany, and we really work to help organizations just better optimize their processes.

Susie West (33:32)

Thank you so much to Tammy. Thank you.

So much to remain. I thank you for your time and your attendance today. We look forward to welcome you next time. Thank you and goodbye

Tammy Lindorf

Director Shared Services,
Martin Marietta

One of the first things we looked at is what were the challenges affecting our digital transformation project. And it involves around three things, of course, people process and technology.

Susie West

Founder & CEO,
sharedserviceslink

More and more global process owners and in order to cash are focusing on redefining the value proposition and making sure that the shared services organization really is handing back immediate value to the business units and making sure that they're up to date.

Elaine Nowak

Director of Product Management and Marketing,
HighRadius

When you look at the value creation of the shared services centers, using technologies such as artificial intelligence, that's when they'll be able to move past the traditional cost reduction goal and focus more on customer satisfaction and performance improvement.

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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.