Customer-to-Cash Receivables Software – Digital World Class® Matrix Research – Transcript

By Bryan DeGraw and Rick Gardner
May 3, 2024
Season 5, Episode 25

Bryan DeGraw:

For organizations that are leveraging these types of software, we were seeing a 40% increase in the levels of automation within the transactions for credit, order management and billing. Cycle times were reduced on average by three days, but we also saw an improvement in the accuracy levels of the transactions.

When you think about a business case, it was an improvement in the number of staffing required for these areas. We saw savings in terms of the process cost. We saw an increase for a $5 to $10 billion annual revenue organization – a $7 million improvement in their accounts receivables collected on time and accurate.

Announcer:

Welcome to The Hackett Group’s “Business Excelleration Podcast.” Week after week, you’ll hear from top experts on how to achieve Digital World Class® performance.

Gary Baker:

What factors enable some customer-to-cash receivable software providers to deliver far greater value and breadth of capabilities than others? How are CDC software providers integrating AI and Gen AI into their offerings? On today’s “Business Excelleration Podcast,” we talk about The Hackett Group’s new Digital World Class® Matrix research covering C2C receivables creation with The Hackett Group Associate Principal Bryan DeGraw and Senior Director Rick Gardner. Gentlemen, welcome to the podcast.

Rick Gardner:

Thank you, Gary.

Bryan DeGraw:

Hey, thanks Gary. Glad to be here.

Gary Baker:

Bryan, why don’t you start us off. Tell us a little bit about the scope of the study.

Bryan DeGraw:

Yeah, absolutely. Yeah, so this is a second part in a two-part series covering customer-to-cash. In 2023, we released a report that focused on cash application collections and dispute management, so specifically looking at software vendors in that space. In this latest version that we released, we looked at the front end of the process, so software vendors that provided solutions for credit management, order management and customer billing, and specifically the electronic invoice presentment and payment technologies.

We analyzed 18 vendors in this space, and among those, some focused on multiple areas and processes such as credits, order management and EIPP, and some specialized. So, across those 18, we had three companies that were Digital World Class within credit management. In order management, we had two companies that were Digital World Class, and in the EIPP space – customer billing – we had another three companies that were Digital World Class. So it’s a great depth and breadth of software across these three areas and something we’re excited to release because now we have two reports that cover software vendors across the entire customer-to-cash process area.

Gary Baker:

Rick, why don’t you tell us a little bit about the types of companies that participated in this?

Rick Gardner:

Yeah, sure, Gary. As Bryan mentioned, we have roughly 18 companies that participated in the study with about 10 of those focused in the areas that we would consider either credit-to-cash or order-to-cash type ecosystems. By that, just as Bryan described, they cover things from the order capture all through credit scoring, billing, payments to customers, cash applications, collections and disputes. The other eight companies had some different models and kind of different go-to-market ecosystems. Some of those were CFO-focused. By that, we would mean the solution is not just covered order-to-cash type functionality, but also incorporated things like account-to-report or treasury and risk management or enterprise performance management type capabilities.

We had several that actually were focused more on the supply chain and logistics-type processes. So everything from inventory management to fulfillment, shipping and logistics with their order managed solution, marrying together those aspects of the functionality. And we also had some companies that we would certainly consider more enterprisewide, ERP-type solutions that covered obviously not just the financial components, but human resources and CRM tip functionality. It was interesting and exciting to kind of see how these different companies – different solutions – were applied throughout the clients that we interviewed.

Gary Baker:

Bryan, what kind of impact are these solutions having on the customers?

Bryan DeGraw:

Hey, Gary, that’s a great question, and it’s also what makes The Hackett Group’s Digital World Class® Matrix unique in the marketplace. There’s volumes of content if you’re looking for features and functionality of software, but what The Hackett Group has brought to bear in our matrix is looking at measuring and capturing value realization. What’s unique about the question you ask is what we quantified and included in the report is insights around automation levels, cycle time levels, accuracy, customer as well as employee experience.

And so just some of the highlights that were part of the report, we identified that for organizations that are leveraging these types of software technologies, we were seeing a 40% increase in the levels of automation within the transactions for credit, order management, and billing. Cycle times were reduced on average by three days in terms of completion of transactions. And speed – there was definitely a completion of transactions quicker by leveraging these tools. The accuracy as well, so speed is great, but we also saw an improvement in the accuracy levels of the transactions.

Now, that translates when you think about a business case – how does that translate into key elements of cost, cash and service? And so we also were able to correlate and see it was an improvement in the number of staffing required for these areas so they can be reallocated to more value-added activities. We saw savings in terms of the process cost, and then from a cash perspective, because all of these areas touch on receivables, the timeliness and accuracy of receivables and cashflow, we saw an increase by an average estimate for a $5 to $10 billion annual revenue organization – a $7 million improvement in their accounts receivables collected on time and accurate.

Gary Baker:

Interesting. What are some of the kind of innovative features that these solutions are delivering?

Bryan DeGraw:

Yeah, so innovation. We certainly dug and wanted to understand what’s driving those outcomes. And some of the key things that we saw is these software providers have really evolved beyond transactional automation. Certainly that’s a cornerstone or foundation of what they bring to the table, but what we saw in terms of the unique features, certainly bringing in elements of AI and machine learning. So we’ve seen machine learning in this space for a while now in terms of being intelligent about matching on cash application. Well, we’re seeing that same capability being leveraged in the speed to analyze and make decisioning around credit management. In order management, the accuracy of the ingestion of orders from customers being able to process them accurately.

And then on customer billing, and what we really focused on is solutions that are presenting invoices and giving customers a lot more options now to view it real time. If necessary, communicate and dispute issues at a line-item level, and then also to pay. So it’s taken it well beyond just automating a transaction and, of course, moving from paper to being digital, but providing a lot of insight into how to get the work done and that the interface is really something that’s unique now is the experience from someone who manages those processes and interacts with their customers with those processes.

A couple of other things is, of course, that all happens with technology and tools. So the software solutions that we saw that were really excelling are creating a lot of ease of integration. There’s lots of moving parts when it comes to doing credit analysis, accepting orders, sending invoices. There’s a myriad of platforms that is occurring on. The ability to easily integrate and accept data coming from multiple systems and be able to send it to multiple systems is something we also saw where again, the Digital World Class organizations are really excelling at that capability. And staying on the cutting edge of new regulations – new requirements – that are coming out.

Again, the software solutions that did very well in the electronic invoice, presentment and payment, they’re right on the edge of what’s happening in terms of new regulations around with taxes. So those are some of the interesting features that we saw and very innovative as well.

Gary Baker:

Rick, from a buyer’s perspective, what are some of the key criteria that buyers should consider when they look at these solutions?

Rick Gardner:

As we did the report, one of the things we tried to do is for each of the solution providers, rank them in roughly 12 or so overall capabilities and categories. Now if we think from a buyer’s perspective – if we roll those up and think about some of the key criteria – there’s about eight or so broad areas that we looked at. A few examples, and they, I think tie in a little bit to what Bryan was just talking about, but geographic scope. To Bryan’s previous comment, some of the regions have more tax complexity – compliance complexity. Do the solutions have experience and capabilities in those areas?

What is the ecosystem that you’re looking to either build or fit into? So are you looking for a solution that’s going to give you the ability to expand across the O2C channels or across the supply chain and logistics channels? Or are you looking for a point solution to fill in any ecosystem that you’ve already built out? What are the key value drivers you’re looking to solve? Some of the solutions may be a little bit more easy to use and pick up and navigate, but may not have as much robust functionalities.

And then what are some of the key channels that you’re looking to support? Is it a business-to-business model you’re looking to support? A business-to-consumer, a business-to-government type channel? So, really aligning what the right tool, channels requirement, your business objectives and your investing appetite. Of these solutions we looked at, certainly, we’ll call it cost for your output is a consideration point, and we’ve got certainly a number of emerging solutions that may not have all the full capabilities of the others but come in a much more reasonable price point for users to consider.

Gary Baker:

Bryan, AI seems to be all anybody is talking about these days. Where are these customer-to-cash software vendors in terms of leveraging AI and Gen AI, and what are their overall plans for continuing to develop their technology?

Bryan DeGraw:

Yeah, Gary, you’re exactly right. There’s not a day that goes by that we’re not talking about what AI is going to do or potentially do. That was certainly the case when Rick and I met with all of the vendors that were part of this exercise. Now, whether they responded via a written RFI or we actually had live demonstrations with them, they all have plans and road maps in their future to look at AI. Now, what we did see, there’s certainly different levels of AI maturity – levels of AI. What everyone is looking to the future now is that generative component where AI is really going to be a game-changer.

What we did see in the software today is there’s elements of machine learning, and in AI that can be taken advantage right away. I’ll just list a couple of them, of what we observed in the different solutions that we evaluated and where we saw them being very applicable. And again, I’m going to say some things that people have heard already. The robotic process automation – so RPA – these software vendors, they’ve packaged that in where it makes sense. So we see in the credit management area, the ingestion of credit data and the ability to pull it from different source systems and integrate it into your modeling tools. We see that component of that technology being applied today from a perspective of case management and dispute resolution.

And again, I’m going to describe where we’re seeing these technologies across the end-to-end, customer-to-cash process – what Hackett calls agile orchestration of data. So the ability to create cases, do workflow management, set hierarchies and make sure you have escalation. We’re seeing that today in these solutions in what they describe as dispute or deduction management and case management. We’re seeing that component of a broad spectrum or a toolbox that’s called intelligent automation, of which generative AI is going to be the future of intelligent data capture. That’s a key element in a technology being leveraged today in credit management, order management and cash application.

Again, data that’s being fed into – whether it’s being pushed or pulled into these processes and customer-to-cash – the technology around the intelligent capture of that is being leveraged today. And so if you think about if anyone’s familiar with OCR technology, when that first came out, it was very template-based. As you wanted to pull data from any type of source document, you had to know exactly where that piece of information existed on the document. So the technology has evolved to, it doesn’t matter where it is, this is the format – the expected format, the number of characters. We’re going to find this key piece of data so that intelligent data capture is leveraged today in these solutions.

Conversational assistants, right? I think we’re all familiar with virtual assistants in the different tools we use on a daily basis so that technology is being leveraged in these tools as well. We see that most often in collections, so the ability to use chatbots and virtual assistants to help manage the workflow in terms of controlling and managing a portfolio, as well as doing autodialing and going outbound, as well as inbound. And the other one we saw is cognitive automation. So, both in credit and collections, we’re seeing the ability for processes that are a bit unstructured at times to be able to handle insights and judgments and predictions.

You’re gathering a lot of information about a customer, and you’re doing a credit analysis, and you’re modeling for their credit decisioning. You’re getting data from external sources for new customers. For existing customers, you’re getting data from external plus internal, and you’re ingesting that all in and making a cognitive decision. The tools are able to give that and present a recommendation today for credit decisioning, as well as collections. So which customers should I call? Which ones are potentially creating the biggest risk? And if I look at an aging report today, on that list, the customer in the account that’s at the bottom of the list today may potentially be on the top of the list in two days.

The technology in the software that’s doing that analysis is being more predictive and saying, “You need to call a customer that’s No. 30 on the list, not No. 1.” And again, as humans, we would tend to work from the top of the list down, but the technology is being more predictive and not looking at it as a top-down list, but really doing the analytics and saying, “Based on our risk calculations that we understand,” and sometimes the tool can understand it faster than a human. It’s saying, “Call the customer that’s at the bottom of the list.” So those are the exciting things that are happening, and there’s more to come when it comes to AI that we’re excited to learn and see.

Gary Baker:

Rick, I know you guys have been really busy producing these Digital World Class® Matrix studies. What’s next?

Rick Gardner:

You’re right, Gary. We’ve got a number of different studies both in process and upcoming. Just as an example, the enterprise performance management study’s just been released and is available for our clients to view. We’ve got two others that are near completion, and it’ll be generating reports here shortly – one on human capital management software, another on human resources outsourcing providers.

And then we also have two that are just getting ready to launch – one on contract life cycle management intelligence – I’ll actually be leading up that initiative, and another on master data management, which my partner on the call here, Bryan, will be leading up as well. That’s just a number of the matrix studies that are coming up. There’ll be a few additional ones at the latter half of the year, but those are next up in our agenda.

Gary Baker:

Thank you both so much for joining me today.

Rick Gardner:

Thank you, Gary.

Bryan DeGraw:

Yeah, appreciate the time, Gary.

Gary Baker:

Listeners, you can download a complimentary summary version of this research from the finance insights page of our website. I’ll also put a link in the show notes.

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