Procurement Technology - Premium Content

AI in Supplier Management: Today (Part 1) [PRO]

suppliers

With this brief we begin the next installment of our series on the application of artificial intelligence (AI) to various source-to-pay technologies. Previous entries focused on AI in procurement (Today, Part 1 and Part 2; Tomorrow, Part 1, Part 2 and Part 3; and The Day After Tomorrow), AI in sourcing (Today; Tomorrow, Part 1 and Part 2; and The Day After Tomorrow), AI in sourcing optimization (Today; Tomorrow; and The Day After Tomorrow, Part 1 and Part 2) and AI in supplier discovery (Today, Tomorrow and The Day After Tomorrow).

Following the path from supplier discovery and selection is the topic of our current series, supplier management. As with each preceding entry, the aim is to define what is available with AI(-like) technology and what will be possible tomorrow. And just as the best platforms for supplier discovery are starting to use machine learning and RPA, so too are the best supplier management platforms — but we're getting ahead of ourselves.

Artificial Intelligence Meets Payables and Dynamic Discounting: Oracle Cloud Vendor Snapshot Update (Part 3) [PRO]

In recent years, Oracle has transformed itself from the inside out, from a procurement solutions perspective, putting its full force behind building a suite of applications designed for the cloud — rather than behind the firewall.

It has reinforced this product development and go-to-market effort with strong incentives to existing customers to migrate from E-Business Suite, PeopleSoft and JD Edwards to its Cloud solutions line. And it has successfully been targeting new procurement customers — some of which do not have an Oracle back-end.

This Spend Matters PRO research brief provides a recap and summary of Oracle’s Cloud procurement applications, shares insight into roadmap direction for the suite and explores recent investments in artificial intelligence and other enabling technologies. Organizations wanting a primer on Oracle Procurement Cloud can read our Vendor Snapshot series: Background/Solution Overview, Strengths/Weaknesses and Summary, and Competitive Overview/Recommendations.

Microsoft 365 Freelance Toolkit: Retooling How Enterprises Work (Part 3) [PRO]

In Part 1 and Part 2 of this four-part Spend Matters PRO series, we wrote about how the Microsoft 365 freelance toolkit emerged and continues to evolve at Microsoft (based on our interviews with Microsoft managers who are central to the initiative). We now shift our perspective to the contingent workforce industry innovator Upwork Enterprise, Microsoft’s launch partner for the freelance toolkit.

In Part 3, based on discussions with Eric Gilpin, SVP of Upwork Enterprise, we look at the Microsoft 365 freelance toolkit from Upwork’s perspective and examine Upwork’s role as a partner and key participant in the process as well as what the partnership means for Upwork itself. Part 4 will include an analyst perspective on the freelance toolkit, the Microsoft-Upwork partnership and what it may indicate for services procurement practitioners.

Artificial Intelligence Meets Payables and Dynamic Discounting: Oracle Cloud Vendor Snapshot Update (Part 2) [PRO]

digital business transformation

With its new Intelligent Payment Discounts solution, Oracle is bridging the worlds of procurement and finance together in a unique way that unifies procurement, accounts payable and core financials.

In Part 1 of this research brief, we offered a detailed overview of this new, AI-based solution, providing an introduction to its different components for organizations that might consider it.

In today’s installment, we will conclude our analysis, exploring Oracle Intelligent Payment Discounts’ strengths and weaknesses related to other early payment solutions, either as an extension of invoice-to-pay or on a standalone trade-financing basis — and provide a user requirements checklist to help companies prioritize if the solution is the right fit for them.

Our analysis includes a perspective on the advantage that Oracle has in selling this solution compared to other early payment and financing solutions (e.g., C2FO, Prime Revenue, Taulia, etc.) and procure-to-pay/invoice-to-pay (e.g., Basware, Coupa, Ivalua, SAP Ariba, etc.) outside of feature/function capability alone based on its unified architecture with Oracle Cloud Financials. That is, for companies migrating, upgrading or switching to Oracle Cloud — not those on legacy E-Business Suite, PeopleSoft or JD Edwards solutions.

AI in Supplier Discovery: Tomorrow [PRO]

interest rates

In Spend Matters’ last PRO article for the AI in Supplier Discovery series, we overviewed some situations where you can find it today, or at least functionality that looked like it was enabled by artificial intelligence (even if it was not), and set ourselves up for a discussion of true AI that is going to creep into supplier discovery platforms tomorrow.

However, when we say true AI, we mean the definition of AI as “assisted intelligence,” because there is no true artificial intelligence out there and probably won't be for a very long time (with some futurists conjecturing it will be 2060 before machines are as smart as the dumbest of us). Note that we don't even mean “augmented intelligence,” as even though the platforms will augment your knowledge, it will still be up to you to make the right, intelligent, decisions tomorrow. (And maybe the day after that, but that is a subject for our next article.)

In our last article, we reviewed the capabilities of the leading discovery platforms today, which mainly revolved around:

  • Smart search
  • Community intelligence

...and the intersection of both.

We discussed how the improvements in computing power and web-usability made it possible for platforms to implement better and more powerful search algorithms that actually made searches useful across wide supplier directories and networks; how community intelligence allowed an organization to quickly narrow potential supplier pools down to reasonable sizes; and how the intersection allowed for the definition of "like" searches that could not be done before now.

But as of today, those "like" searches are still pretty high level. And they are best at finding suppliers that provide finished products and services that can be well-defined and compared to other suppliers that provide similar finished products and services. In fact, most systems with "like" searches are for the identification of suppliers for indirect. Not direct. (And not services either.)

But that is going to change tomorrow. Tomorrow, supplier discovery systems are going to support:

  • deep capability match that uses bill of materials, production requirements and other deep factors to support supplier search for direct suppliers
  • resource capability match that can identify needed skill sets, knowledge and related attributes for services suppliers

And we'll finally have smart supplier search for all. But how will it happen? And what will it look like? Let's explore.

AI in Supplier Discovery: Today [PRO]

With this briefing on supplier discovery, we continue our series on AI in various source-to-pay technologies, which we started with AI in Procurement (Today Part 1 and Part 2, Tomorrow Part 1, Part 2 and Part 3, and The Day After Tomorrow) and continued with our recent series on AI in Sourcing (Today, Tomorrow Part 1 and Part 2, and The Day After Tomorrow) and AI in Sourcing Optimization (Today, Tomorrow and The Day After Tomorrow Part 1 and Part 2). The goal of this series is to define what is available with AI today, what will be possible tomorrow, and where the future may take us.

But first we must remind you of the status quo: Artificial intelligence does not yet exist, in the strictest definition of the term.

However, if you define AI as "assisted intelligence" (systems that can automate repetitive and standardized tasks performed by humans) or "augmented intelligence" (systems that can learn from humans and their data to provide insights that lead to, or recommend, better decisions), then there are technologies out there today that meet that need.

Today, the mainstream applications of AI in supplier discovery (which are, sadly, few and far between) generally fall into two categories, which themselves have limited functionality, but, there is still some functionality and it is a beginning.

E-Catalogs: The ‘Fifth Element’ of Procurement [Plus +]

elements

E-catalogs are still a key part of any e-procurement solution and e-marketplace. However, they are no longer simply a tool to load the prices and features of products and services for approval and then integrate into an e-marketplace to purchase against it. Today, e-catalogs are becoming an intelligent and integrated source of information that enable nearly all purchasing scenarios, with the support of a robust e-marketplace where requesters can search between e-catalogs (including punchouts or any other e-commerce site) — all while in compliance with the organization's business rules and standards.

AI in Sourcing Optimization: The Day After Tomorrow (Part 2) [PRO]

In the first article of this Spend Matters PRO series, we recounted the state of artificial intelligence in optimization so far — or, more accurately, the lack of AI in optimization. While AI in its most base form of "assisted intelligence" is readily available in many modern procurement and sourcing platforms, as evidenced in our previous series on AI in Sourcing and Procurement, it has not yet creeped into optimization.

But that doesn't mean that AI will not creep into sourcing optimization tomorrow. While we may not see AI creep into any of the current platforms on the market (for different reasons for each vendor), that certainly doesn't mean that the next vendor to bring an optimization solution to the market won't learn from the oversights of their predecessors. In fact, in looking to get an edge over the existing, established platforms, it will assuredly be the case that tomorrow's optimization platforms will not only have a greater focus on UX and automation, but on AI.

And while AI won't be embedded in the optimization engine tomorrow, it will surround it and make AI more usable. And while the story may not change much the day after tomorrow, the surrounding capabilities and usefulness of the platform as a whole will continue to increase.

In Part 1 of this briefing, we indicated — taking a queue from our pieces on AI in Procurement the Day After Tomorrow and AI in Sourcing the Day After Tomorrow — that we will see tail spend elimination, automatic opportunity identification, real-time strategy alignment, end-of-life (EoL) recommendations and performance improvement — which we will detail in this article.

But that won't be all. What else? Read on.

AI in Sourcing Optimization: The Day After Tomorrow (Part 1) [PRO]

In the first article of this Spend Matters PRO series, we recounted the story of AI in optimization today, or, more accurately, the lack of artificial intelligence in optimization today. While AI in its most base form of "assisted intelligence" is readily available in many modern procurement and sourcing platforms, as evidenced in our previous two series on AI in Sourcing and Procurement, it has not yet creeped into optimization.

But that doesn't mean that AI will not creep into sourcing optimization tomorrow. While we may not see AI creep into any of the current platforms on the market (for different reasons for each vendor), that certainly doesn't mean that the next vendor to bring an optimization solution to the market won't learn from the oversights of their predecessors. In fact, in looking to get an edge over the existing, established platforms, it will assuredly be the case that tomorrow's optimization platforms will not only have a greater focus on UX and automation, but on AI.

Now, as per our last article, AI won't be embedded in the optimization engine — because that has to be powered by mathematically algorithms that have been rigorously proven to be sound (no errors, ever) and complete (will examine every solution and find the best one guaranteed) and given that most "AI" today (in the assisted and augmented intelligence category, because there is no true AI) runs on statistical or probabilistic machine learning algorithms, they just don't make the cut. (Although they can be paired with sound and complete MILP algorithms based on simplex or interior point to find faster starting solutions to difficult problems.)

But what about the day after tomorrow? What will we see then?

AI in Sourcing Optimization Tomorrow [PRO]

Our last article recounted the story of artificial intelligence in optimization today, or, more accurately the lack of AI in optimization today.

While AI in its most basic form of "assisted intelligence" is readily available in many modern procurement and sourcing platforms, as evidenced in our previous briefings (AI in Procurement and AI in Sourcing), it has not yet creeped into optimization. The most advanced platforms have limited themselves to easy constraint creation, data verification and detection of hard constraints that prevent solutions — as in the case of Coupa — or easy data population, wizard-based scenario creation (using standard model templates), and automation — as in the case of Keelvar. In the former case, the underlying statistical algorithms can be found at the heart of some modern machine learning technologies (but aren't quite there), and in the latter case, the robotic process automation (RPA) is nothing more than an automated, manually defined, workflow.

But that doesn't mean that AI won't creep into optimization tomorrow. While it may not with the current vendors on the market (for different reasons with each vendor), that doesn't mean that the next vendor to bring an optimization solution to the market won't learn from the oversights of its predecessors and bring some obvious advancements to the table — especially when certain vendors are releasing their platforms with an open API to support an Intel-inside-like model where sourcing or AI vendors can build on leading optimization foundations to offer something truly differentiated.

And what could those differentiators be? We'll get to that, but first let's review the premise.

Simply put, in the traditional sense of the abbreviation, there is no AI, or artificial intelligence, in any source-to-pay application today, as there is no AI in any enterprise software today. Algorithms are getting more advanced by the day, the data sets they can train on are getting bigger by the day, and the predictions and computations are getting more accurate by the day — but it's just computations. Like your old HP calculators, computers are still dumb as door knobs even though they can compute a million times faster.

However, with weaker definitions of the term, we have elements of AI in our platforms today. Assisted intelligence capabilities are beginning to become common in best-of-breed applications and platforms, and “augmented intelligence” capabilities are starting to hit the market for point-based problems. For example, tomorrow's procurement technologies will buy on your behalf automatically and invisibly, automatically detect opportunities, and even identify emerging categories.

But if AI is going to take root, it has to take root everywhere, and that includes sourcing optimization. So what could we see tomorrow?

Let's step back and review what optimization does. It takes a set of costs, constraints and goals, and then it determines an award scenario that maximizes the goals subject to the constraints and the costs provided. So where could AI help?

Turbocharging E-invoicing Through the Supplier Network Value Proposition [Plus +]

e-invoicing

As we discussed in the first part of this e-invoicing research brief, there are many more goals of automating the invoicing (and invoice receiving) process than simply driving process efficiency. Indeed, advanced e-invoicing deployments now go far beyond the plumbing required to automate the issuance, workflow and approval of an invoice in a streamlined manner with as few accounts payable touch points as necessary (not to mention providing suppliers with greater visibility throughout the process). Today, supplier networks have emerged to extend the value proposition of basic e-invoicing to a number of new areas, including the better management of working capital (and much more). In the second part of this series, we discuss how supplier networks are extending the e-invoicing value proposition, advanced scenarios that e-invoicing and network providers are starting to enable today and who some of the key vendors in the space are, including specialists, suite providers and regional solutions.

AI in Sourcing Optimization Today [PRO]

SciQuest

As we continue our investigation into AI in source-to-pay technology, which started with our AI in Procurement series and continued with our AI in Sourcing series, we take a deeper dive into optimization. Primarily the focus is on strategic sourcing decision optimization, but we'll discuss related areas as well.

First, let’s recap the status quo to remind us of the reason for the existence of these AI briefings.

AI, or artificial intelligence, does not yet exist, especially in the strictest definition of the term. Computers are not intelligent, not even artificially. They can do more calculations than ever before. They can take advantage of more data than ever before. They can find significantly more correlations than ever before and compute, with better and better statistical reliability, which are just correlations and which are true cause and effect relationships. But they are still, when you get right down to it, as dumb as door knobs. Probability is not intelligence. But it is damn good guidance.

In sourcing, logistics and supply chain, we are primarily concerned with decision optimization. Read on to find out the latest developments and expectations.