Procurement Technology - Premium Content

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.

How E-Invoicing Extended Procurement’s Influence with Accounts Payable [Plus +]

e-invoicing

Editor's note: This is a refresh of our 2016 series on e-invoicing's influence on procurement-accounts payable relationships, which originally ran on Spend Matters PRO.

In this Spend Matters Plus research brief, we examine how procurement, through the use of technology, has extended its range of influence from its own processes to accounts payables and made electronic invoicing and supplier connectivity instrumental in the outcome of what we now call procure to pay (P2P). We also discuss the evolution of the purchasing function up to the integration of e-invoicing, the value proposition of e-invoicing, its challenges, what we see coming in the e-invoicing market and, finally, who some of the solution players are within the space.

Exploring ‘Total Cost’ as a Productivity KPI for the P2P Process [Plus +]

Total cost of ownership of the procure-to-pay process is not simply about measuring the costs associated with acquiring a P2P platform, it’s about tracking all P2P processes and managing them as a business key performance indicator. Managed well, the TCO P2P KPI can positively impact the bottom line of any business. Many organizations think that when acquiring a P2P platform, a firm business case needs to be constructed based on the total cost of the platform and high-level benefits that are reasonably achievable. But there’s actually a more effective way to think about the cost and returns of P2P technology. In this Spend Matters Plus brief, we explore this new way of measuring P2P returns and cost through a modified TCO approach.

Artificial Intelligence in Sourcing Tomorrow (Part 2) [PRO]

digital

In this Spend Matters PRO series on AI in Sourcing, we began our discussion of some situations where you will find AI in e-sourcing platforms, where AI is defined as “augmented intelligence” (because, as we have discussed in prior articles, there is no true artificial intelligence in enterprise platforms today and there won't be tomorrow either). AI is a buzzword, not a reality. But we don't need true AI to achieve software that can radically increase our productivity. Reaching augmented intelligence will add multiples to our productivity and savings.

In our last post, AI in Sourcing Tomorrow (Part 1), we discussed how the sourcing platforms of tomorrow will offer event-based category alignment functionality as well as market-based sourcing strategy identification. Together, these augmented intelligence features will not only save you a lot of time and effort in the identification and conducting of a proper sourcing event, but will also maximize your chances of success with the strategies that you follow.

It will be a magnificent start to the sourcing process. But it won't stop there. Because it can't stop there.

As per our article on AI in Sourcing Today, there's a lot of manual effort involved in a sourcing event. And the platforms of tomorrow will integrate workflow automation and auto-fill to handle a lot of the drudgery that will be required in any sourcing project.

However, just including workflow automation and auto-fill isn't getting you to sourcing utopia, where you’re getting maximum return for minimum effort. Something more is needed. How much more? Let's read on to find out.

Best Practices for Your P2P Implementation Project And How to Keep it From Becoming a Nightmare [Plus +]

complex sourcing

Editor's note: This is a refresh of our 2015 series on running a successful P2P implementation, which originally ran on Spend Matters PRO. Read Part 1 here.

In the Spend Matters webinar “Nightmare on Procurement Street,” we discuss how to successfully implement a procure-to-pay solution (P2P) and avoid the process from turning into a terrible experience. This 2-part Spend Matters Plus series lays out what tips we suggested for procurement organizations embarking on a P2P project. This is not meant to be an all-inclusive, step-by-step implementation guide, however. We simply want to share our best practice ideas based on our experience and our discussion in the webinar. Today, we will focus specifically on project management as a procurement responsibility, as well as ensuring finance and accounts payable (A/P) are included in the P2P implementation project. Other areas we will cover are remembering the importance of supplier integration, system testing and user training in the P2P process.

How to Succeed with Systems Integrators and Procurement Technology Implementation: Lessons From Spend Matters UK/Europe and Determine [PRO]

e-procurement

In too many cases, system integration (SI) and consultancy partnering decisions take a back seat to technology selection and related business process considerations when in fact all three areas are important to consider in equal measures as parts of source-to-pay and procure-to-pay deployments. This misstep is often one of the root causes of procurement organization dissatisfaction with technology decisions and adoption.

In this PRO brief, Jenny Draper, Spend Matters’ managing director for UK/Europe, shares her experience and best practices on the topic from serving as a procurement consultant over two decades before recently joining Spend Matters.

This best practice essay includes Jenny’s lessons learned on the importance of systems integration partners and how to set them up for success (and get the most out of a relationship). It covers such topics as when (and why) superior technologies fail, change management missteps, the role of the modern SI and finding the right fit partner. She then explores specific lessons learned from Determine’s boutique partner ecosystem in Europe.

Throughout, the brief also includes key takeaways and summary recommendations for procurement organizations going through procurement technology selections and deployments.