Author Archives: Michael Lamoureux



AI in Supplier Discovery: Today

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.

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

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)

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

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?

AI in Sourcing Optimization Today

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.

The CPO’s Conundrum (Part 1B): How Outside-In Issues are Shaping the Course of Procurement

As we noted in yesterday’s Spend Matters PRO article, if you were to ask a roomful of CPOs what was their top concern was, for this year or even the coming decade, chances are the majority would lead with cost management and supply assurance. And while this makes sense, supply assurance and cost reduction are just two of a host of broader issues that are being pushed to the front of mind for today’s CPOs. So we are dedicating a series to the broad scope of issues that the modern CPO must face, starting with an overview of how they break out in the common PESTLE framework. Yesterday we addressed the “PES” — Political, Economic and Social — and today we will address the “TLE” — Technological, Legal and Environmental.

The CPO’s Conundrum (Part 1A): How Outside-In Issues Are Shaping the Course of Procurement

If you were to ask a roomful of CPOs what was their top concern was, for this year or even the coming decade, chances are the majority would lead with cost management and supply assurance.

This makes sense. Within the hierarchy of procurement value, providing the right goods and services at the right time and place, preferably at the right (or better) price, constitute a foundation without which organizations cannot function.

Because of this requirement to secure and manage supply markets, procurement’s value proposition to the business is ultimately defined by its ability to access and derive value from markets. This means procurement value, then, is driven heavily from an outside-in perspective. That value starts with assurance of supply, just as top-line growth and brand development are foundational to sales and marketing.

The problem, however, is that supply assurance and cost reduction are just two of a host of broader issues that are being pushed to the front of mind for today’s CPOs. Because the CPO must manage multiple changing supply markets, and because those supply markets are affected by numerous external forces over which the CPO — let alone the business or even some governments — has no ability to influence, the CPO’s agenda is in reality much broader than assuring supply and reducing costs.

This brings us to what we call the CPO’s conundrum: Procurement organizations are primarily measured by the C-suite on supply assurance and cost control, but the agenda that the outside world is setting for the CPO is far bigger than just that. How, then, can procurement leaders meet the agendas recognized and prioritized by management while also addressing the equally (or perhaps more) important agendas of the changing, external supply world?

This Spend Matters PRO series examines the roots and resulting challenges of the CPO’s conundrum. In this brief, the introduction to this series, we discuss the current items on the CPO agenda, as well as the outside-in forces that are most notably butting their way in.

In subsequent installments, we will analyze overarching issues on the new CPO agenda individually, including corporate social responsibility (CSR) and sustainability, digital business strategy, political and economic instability, and regulatory risk.

Artificial Intelligence in Sourcing: The Day After Tomorrow

In Spend Matters’ last PRO article about AI in Sourcing, we reviewed some of the exciting capabilities that you will be able to expect in tomorrow's e-sourcing systems, where we define AI as “augmented intelligence” because, as we've repeatedly stated in our articles in this ongoing AI series, there is no true artificial intelligence in any enterprise technology today. In fact, there won't be anything close, at least on the open market, even tomorrow. But it will be closer tomorrow, and it will approach the point where it can be labeled augmented intelligence as it will allow you to make better, smarter, decisions — no matter how good and smart the decisions were that you made in the past.

In the last article, we discussed the following augmented intelligence capabilities in particular that will be part of tomorrow's e-sourcing platforms:

  • Event-based category alignment
  • Market-based sourcing strategy identification
  • Automatic strategic sourcing events
  • Suggested award scenarios

However, as great as event-based category alignment and market-based sourcing strategy identification will be, and as fantastic as automatic strategic sourcing events with suggested awards will be, there will be even better augmented intelligence capabilities in the e-sourcing platforms of the future. Specifically, the day after tomorrow, you will be able to expect the following seemingly magical capabilities:

  • SKU replacement
  • End-of-life (EOL) recommendations for products
  • Real-time strategy alignment
  • Auto-pause/extend

And more. But anything beyond these could be quite a ways out, so we will stick to these for now.

Artificial Intelligence in Sourcing Tomorrow (Part 2)

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.

Artificial Intelligence in Sourcing Tomorrow (Part 1)

In Spend Matters' last PRO article, Artificial Intelligence in Sourcing Today (The Situation Now), we overviewed some scenarios where you can find AI in e-sourcing platforms today, where we define AI as “assisted intelligence” because, as we've stated in this series about AI in modern sourcing and procurement technologies, there is no true artificial intelligence in any enterprise technology today. In fact, there is nothing close, at least not on the open market.

But we will be closer to artificial intelligence tomorrow, and in the near future, we may get to the point where the average market leading platform offers you augmented intelligence on a daily basis.

In our last article, we reviewed the common instances of the assisted intelligence technologies on the market today, namely: auto-fill, workflow automation, outlier identification and rule-based auto-award identification.

However, this is just the beginning of what you should have as a sourcing professional, especially considering what's coming in AI Tomorrow. For example, if you go back to our series in AI in Procurement Tomorrow, you know that soon you will have technologies to prevent overspend, buy on your behalf invisibly, buy automatically, identify opportunities while you sleep, identify new categories before you know of their existence and identify procurement methodologies for success.

But these improvements will spill over into the sourcing domain as well. In Tomorrowland, as a buyer, you will also have augmented intelligence technologies that will allow for:

* Event-Based Category Alignment — not just new category detection * Market-based Sourcing Strategy Identification — not just the right methodology for procurement * Automatic Strategic Sourcing Events — not just auto-buy from a catalog or contract * Suggested Award Scenarios — not just canned options

And it will make your buying life much more efficient. But how?

Artificial Intelligence in Sourcing Today (The Situation Now)

Not that long ago we ran a six-part series on AI in Procurement (Today Part I and Part II; Tomorrow Part I, Part II, Part III; and The Day After Tomorrow). By the time we defined the levels of AI today, what will be possible in the future and just how far AI in procurement will take you, you probably thought that was all there was too it and were impatiently awaiting the day when your "best of breed" applications would catch up.

The reality is that this is just the tip of the iceberg.

When your platform provider (or, if necessary, your future platform provider) catches up and starts offering you modern capabilities, those capabilities should extend well beyond procurement and spill over into multiple areas of S2P, including sourcing.

So to whet your appetite about what should be coming next, and to make sure your provider knows that you know what should be coming next (and will be holding them accountable), in this series we're going to dive into the applications of AI in sourcing and discuss what is available today, what is coming tomorrow — and what is in your strategic buying future.

TenderEasy: Vendor Introduction, Analysis and SWOT

trucking

Despite the current tide of populism, the growing globalization of businesses and, thus, corporate supply chains is a trend no procurement organization can ignore.

Alongside this push into new markets for both sales and production comes a need to more effectively procure transportation because moving commodities or finished goods between facilities, like factories or distribution centers, and their final destinations has become more complex. Add to this a litany of procurement-specific obstacles to effective freight sourcing and management — from a dearth of qualified internal resources to sparse, inaccurate data about freight spend — and the challenge becomes even more daunting.

This combination of logistics category complexity and insufficient procurement capability to manage it is what originally gave rise to the sourcing optimization solutions that most North American organizations are familiar with.

Trade Extensions (now Coupa Sourcing Optimization), CombineNet (now Jaggaer Advanced Sourcing Optimization) and Keelvar (one of the few independent sourcing vendors that currently supports bid optimization) all got their starts enabling logistics procurement across thousands of lanes. As they grew, however, each of these vendors evolved their solutions to support additional categories beyond freight, enabling larger and more complex scenarios while leaving other elements of the transportation equation (like execution) to other technology providers.

TenderEasy, a 14-year-old firm that launched its SaaS solution for freight procurement in 2012, has taken the opposite approach. Rather than expand its sourcing optimization capabilities beyond logistics, TenderEasy has doubled down on freight, positioning itself as the entry point to a broader transportation management ecosystem. It committed to this strategy in 2018 when it became part of the Alpega Group, a global logistics software company that offers end-to-end solutions for transport needs, including not only freight sourcing but also access to freight exchanges and transportation management systems.

Leveraging this network of transportation solutions, Stockholm-based TenderEasy is hoping to bring its Europe-centric expertise across the Atlantic — the company already counts Heinz, adidas Group and British American Tobacco (BAT) as clients — taking on incumbent sourcing optimization vendors in the process.

This Spend Matters PRO Vendor Introduction offers a candid take on TenderEasy and its capabilities. It includes an overview of TenderEasy’s offering, a breakdown of what is comparatively good (and not so good) about the solution, a SWOT analysis and a selection requirements checklist for companies that might consider the provider.