Author Archives: Michael Lamoureux



AI in Supplier Management: Today (Part 1)

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.

Tradeshift Innovation Summit in London: A Few Takeaways

Brexit

Last week, I attended Tradeshift's new “Innovation Summit” series in London. It was a short event, lasting only an afternoon, and obviously one intended to test the waters to the receptiveness of both the format and the location, but an interesting one nonetheless.

From a vision perspective, Tradeshift is almost dead-on in terms of what the platform of the future has to look like, and from a marketing perspective, it makes perfect sense. But when there are still a large number of organizations using Excel and email, and a larger number still who remain on first-generation best-of-breed procurement applications, it's hard to sell a true “Procurement 3.0” solution approach when the majority of the world hasn't even caught on to “Procurement 2.0” solutions.

AI in Supplier Discovery: The Day After Tomorrow

In our initial entry of the series, AI in Supplier Discovery: Today, we discussed how the advancements in usability and computing power have made it possible for platforms to implement better and more powerful search algorithms that can actually make searches useful across wide supplier directories and networks. Then, in our last entry, AI in Supplier Discovery: Tomorrow, we discussed how the inclusion of advanced semantic processing, high dimensional (fingerprint) similarity clustering algorithms, range and "like" search algorithms, and machine learning that can improve the algorithms over time as humans identify "good" versus "bad" matches will allow even better, smarter, more useful searches to be performed in the days to come for the identification of the right suppliers for direct categories and services.

But is that the best we can hope for?

While that is all we can hope for tomorrow, we can hope for even more the day after that. More specifically, when we extend our event horizon out just a little bit further, we can predict that at some point in the future, supplier discovery systems are going to support innovative supplier discovery (based on performance, need and soft factors) and predictive smart search (based on upcoming projects, performance profiles and real-time community feedback).

Sustainability, Environmental Stewardship and CSR: The CPO’s Outside-In Agenda (Part 2B)

sustainable supply chain

In our last article in this Spend Matters PRO series, we focused on several pressing issues that are shaping procurement from the outside in, yet chief procurement officers are primarily still concerned with issues set by an inside-out agenda — that is, cost-cutting and supply assurance targets mandated by upper management. However, our PESTLE analysis of factors shaping the modern CPO agenda identified broad outside-in trends that an organization needs to consider if it wants to truly tap and manage the opportunities (and risks) offered by external supply markets. (Read the CPO’s Conundrum: Parts 1A and 1B.)

Nowhere is this more readily apparent than with the topic of sustainability and environmental stewardship, the focus of today’s brief. The environment is an inseparable component of any business. It forms the platform layer off which all goods and services are produced, and cannot be ignored. And the difference between effective and sustainable management and ineffective and unsustainable management, as pointed out in yesterday’s article, is shocking. Not only would investments in environmental sustainability focussed companies over the past two decades doubled an average rate of return, but millennials will pay a (small) premium for sustainably (and ethically) sourced products and you are ensuring that you will have raw material supply for years (and decades to come).

Sustainability, Environmental Stewardship and CSR: The CPO’s Outside-In Agenda (Part 2A)

leading cross-functional teams

In this first installment of this Spend Matters PRO series (see Part 1A and Part 1B), we noted that a number of pressing issues are shaping procurement from the outside in, yet chief procurement officers (CPOs) are primarily still concerned with issues set by an inside-out agenda — that is, cost cutting and supply assurance targets mandated by upper management. Our PESTLE analysis of factors shaping the modern CPO agenda identified broad trends like economic instability, globalization, changing digital business strategies and the need to address corporate social responsibility (CSR) as areas that procurement organizations need to consider if they want to truly tap and manage the opportunities (and risks) offered by external supply markets.

Perhaps nowhere is this more readily apparent than with the topic of sustainability and environmental stewardship, the focus of today’s brief. The environment is an inseparable component of any business. It forms the platform layer off which all goods and services are produced, and, more fundamentally, the resulting ecosystem services from which humans benefit create the foundations for our species’ survival and quality of life. Due to multiple ongoing trends, however, the environment is changing, as are the ways that consumers, investors and governments think about our relationship to the environment.

Accordingly, Part 2 of this series on the CPO’s Conundrum examines the outside-in drivers pushing sustainability and environmental stewardship higher on the procurement agenda. It also explores recent examples of how businesses are integrating these issues into their supply management strategies, while simultaneously addressing them in balance with traditional procurement objectives, such as category management, supply base alignment and demand shaping.

AI in Supplier Discovery: Tomorrow

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

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.