Procurement Technology - Premium Content

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

In our last pair of Spend Matters PRO articles about AI in supplier management today, Part 1 and Part 2, we overviewed some situations where you can find AI in e-sourcing platforms today, where we define AI as “assisted intelligence” because, as we've stated in our series about AI, there is no true artificial intelligence in any enterprise technology today. In fact, there is nothing close, at least not on the open marketplace.

But when we get to the point where we have an augmented intelligence solution that can help us not only monitor supplier performance (across a community), automatically identify issues and risks, and even help us with automated resource — and asset — assignment but can also help us identify automated corrective action resolution plans, risk mitigation strategies, and real-time relationship monitoring and resource re-alignment, they start to approach augmented intelligence and become quite useful to us indeed.

In this article, we are going to discuss the AI-enabled functionality that we expect to see in the leading supply management platforms tomorrow. We will continue our pattern and start by defining what we expect to see, how it will likely work, and then give some hints of the technology platform that will underlie it.

Tomorrow, we expect that the leading supplier management platform will also have the following capabilities:

— Smart information selection and auto profile updates
— Market-based supplier intelligence
— Real-time relationship monitoring
— Automated resolution plan creation, monitoring and adjustment
— Automated risk mitigation strategy identification
— Optimized real-time resource re-alignment

SAP Ariba Sourcing: How Does it Compare Today and What is Coming Tomorrow (Part 2: Playing the Scout Card) [PRO]

Procurement organizations previously embraced complexity in tools to enable both event sourcing and category management processes. Now, the tide has turned. Solutions that are best-in-class from a user-experience perspective, but may lack advanced features (e.g., sourcing optimization, the most capability/depth for RFP/RFI/auction support, full opportunity analysis like should-cost modeling, full project management, comprehensive integrated supplier and risk management, etc.) are increasingly winning the day — sometimes even replacing solutions that offer deeper functional capability.

Simply put, this is what I term the Scout phenomena (but in all fairness to Scout, the provider, is aggressively building out capabilities in areas that it has lagged in for our SolutionMap benchmarking tool).

In the forthcoming new releases of its sourcing product, SAP Ariba has not just co-opted Scout’s playbook. It has built on it. By masking complexity and prioritizing usability not just as a primary, but the top objective, forthcoming “SAP Ariba Sourcing” releases represent a fundamental replatforming that will put casual, business and procurement users at the center of a vastly improved and consumerized UX.

In Part 2 of the Spend Matters PRO research series providing analysis of the SAP Ariba Sourcing solution, we offer insight into the new user experience as well as analysis, commentary and customer recommendations based on SAP Ariba’s planned release schedule featuring the new UI/UX. Part 1 provided insight into SAP’s relative strengths and weaknesses today (based on the Q1 2019 SolutionMap release) and shared what we learned last month at the SAP Ariba Live event on an overall roadmap basis for the sourcing product line.

Defining AP Automation Functional Requirements (Part 1): Core Invoicing (Set-Up, Creation, Submission and Receiving) [PRO]

AP Automation is getting a lot of attention recently from multiple angles. This includes both finance/procurement organizations considering these solutions independently or as a component of broader invoice-to-pay or procure-to-pay investments. And it also counts the investment community, which continues to throw support behind a broad range of providers (just recently MineralTree raising $50 million).

As we’ve noted before, from a breadth perspective, AP automation technology can encompass the following functional areas on the highest level, which include electronic invoice capture, paper/PDF invoice capture (scan/capture), core invoice processing, invoice validations/matching (e.g., match to a PO or goods receipt), invoice approvals, supplier portal, supplier enablement services, systems integration, pre-onboarded suppliers payment integration and payment.

As part of our continuing coverage of AP automation, this Spend Matters PRO series will explore the functional requirements that finance and procurement organizations should look for in a solution with “foundational” and “advanced” capabilities.

Part 1 takes our first look at the core invoicing requirements for AP automation and some of the criteria that Global 2000 and middle market organizations should consider when selecting solutions (i.e., invoicing set-up, paper scan/capture support and e-invoicing). Subsequent briefs in this series will analyze other AP automation requirements that customers should look for in a solution.

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?