Category Archives: Procurement Innovation

“The Suite Was Supposed to Settle Everything.”

This is a requested response to Paul Marty’s inquiry: Is Source-to-Pay Dying.

We’ve heard the “one app to rule them all myth” since the late 60s when IBM said the MRP would control the operations and no other app would be needed. This was rekindled in the mid 80s when Oracle said the ERP would control the organization and no other app would be needed. Then in the late 90s when the web would provide a common interface to everything. Then the late noughts / early tens when the Suite would solve everything. It’s the myth that keeps on giving.

The reality is that any new monolith application model only solves all the problems that came before, not the problems you have now, and not the problems that are coming.

That doesn’t mean suites don’t have value, or that suites won’t provide more value than any other alternative, just that it’s not a panacea. Determining whether it provides more or less value requires understanding the true total value realized (taking all costs and benefits into account) compared to the true total value of the alternatives, many of which are unproven.

“Is The Economic Value Moving Somewhere Else?”

First off, let us note that, fundamentally, the new AI orchestration craze is no different, as it ultimately depends on a protocol that can bind everything together. This isn’t new either. Remember CORBA? Probably not, as most of you probably don’t even know what it is. Look it up. At the dawn of the dot com era, it was going to solve everything. It made all the same promises MCP is making now.

The reality is that the fundamental truths of technology have not changed.

> If it sounds too good to be true, it is.

> Technology can’t advance any faster than discovery (either mathematical computing theory or practical scientific discoveries that allow for new engineering that can build better machines to support better models), and that has, and will, always be slow. How many hundreds of thousands (or millions of years) has it taken us to compute a theoretical warp bubble, and how many decades/centuries more before we can achieve it? (We’ve went from conjecture with the introduction of Star Trek 60 years ago to theoretical possibility 5 years ago … but now we need to create the energy source, the materials that could withstand it, etc. etc. etc.)

> … businesses not only need to make money every year, but are punished by the capitalistic economy if they don’t; so even if all they have is the same old sh!t, they still need to sell it, and the best way to do that is to slap a new coat of paint on the old Mustang and tell you it’s a brand new model (even though the engine hasn’t changed in almost a decade)

This doesn’t mean that AI orchestration doesn’t provide value, just that it’s not the ultimate answer and that you have to truly understand it’s true cost vs its true benefits and, where autonomy is granted, true risks before you can make a decision.

“What if the employee does not need to enter the procurement system at all?”

That doesn’t change the fact you still need a procurement system.

Just because an intake layer can work across applications, and just because an AI agent can complete a routine workflow without ever displaying the myriad of screens suite vendors spent years (if not decades) refining, that doesn’t mean that the core functions go away. Either those have to be part of the intake/orchestration system (in which case it’s really a suite with a new kind of interface) or you still need the underlying best-of-breed / suite systems, which are only accessed through their APIs.

In the latter case, the true economic value remains in the best-of-breed/core systems … and the only value of the intake/orchestration/AI agent is the cost of user time reduction (i.e. 5 FT AP agents to manually process all the invoices vs 1 FT AP agent to manually deal with the exceptions). So if the cost of the software is greater than the manpower saved, it’s negative value.

This assumes that the agent is deterministic and will do all processing according to user defined rules and in user defined bounds. If you are using LLM-powered agents and giving them autonomy, there is no guarantee they will follow all rules and stay without bounds — autonomy means that they can decide only 10K over their approval limit is ok because it appears to be a known supplier, onboard an uncertified supplier, issue a new PO to a supplier who is late on other critical deliveries, etc. which can result in significant losses.

Which brings us to the most important question:

“ONE INTERFACE > MANY SYSTEMS > WHO DECIDES?”

This is a key question for multiple reasons:

1) You can’t cost / benefit a system without knowing.

As above, if the decision is ultimately human, you can accurately cost the system and determine it’s fixed (workforce reduction) benefit as well as it’s expected benefits from (weighted) average results and track true benefits over time.

But if the decision is ultimately the system, you can’t truly estimate the benefits as you don’t know what it will do, how many mistakes it will make, and what the cost to clean them up will be — and if it uses LLM technology, you can’t even cost the system as you don’t know how the token/compute cost is going to increase over time as you don’t know the token growth that will be required or how soon you’re going to have to pay true compute costs (the big AI companies can’t keep losing $4 for every $1 of revenue, and with today’s energy and water costs, the true compute cost is about 5X what most of the players are charging … and this will only increase over time.)

2) You can’t quality control without absolutely knowing who decides what, what the range of options are, where, and how to encode the checks.

Which means that:

“THE CENTRAL QUESTION … IS WHO OWNS THE REASONING THAT DETERMINES WHAT PROCUREMENT SHOULD DO”

Especially when the answer to:

“Are Twenty Agents Really Twenty Opinions?”

is NO!

I know Jon W. Hansen might disagree with me here, since he uses multiple systems to arrive at his (starting) algorithmic analysis of the marketplace regularly, but agents reason off of the data they are given.

When you interconnect them, they share “data” and “reasoning” continuously. Also, even though they are ultimately sophisticated probabilistic models no human can fully understand, the core is similar to deep multi-level feedback neural networks. This means that common “data” and “reasoning” increases the weighting on that “data” and “reasoning”, increases similar output, which increases similar input to the minority models, which causes that “data” and “reasoning” to become more heavily weighted in them. Or, in simple terms, a majority of agents will bully the minority of agents into their viewpoint until there is one opinion, not twenty.

Even if all 20 agents start out different, as they share “data” and “reasoning”, there will be some commonality, and as the “data” and “reasoning” flows back and forth, the weighting of the commonality will increase until it snowballs into a majority, given enough exchanges (over time).

While some “experts” will try to tell you this all but certainly guarantees you will get the best results once the agents agree, that is ONLY true if the common “data” and “reasoning” is accurate. Some agents will have bad / fake / hallucinated (wrong) data and others will share faulty “reasoning” because they don’t actually reason. (They predict arguments … think of them as a super powerful fancy version of next word suggestion on your iPhone, except they are predicting answers to questions and sometimes even the steps involved to get there!)

While individual agents sometimes work well if they have enough raw question/answer input/output previous step/next step data top work from (and that’s how they create mathematical “proofs” — they can scan millions of research papers and proofs, build up all the associations as input/output pairs, and then see if there is a way to chain them all together from a question to an answer where the output of one step in one paper is the required input of a step in a paper in another paper, possibly published in an unrelated journal in an unrelated discipline), they sometimes don’t work very well at all!

They’ll tell you to eat one rock a day. Or that strawberry only has 2 rs. Or, because they don’t understand reality, when asked, they will tell you that “the woodchuck could carry 57,600 pounds of wood in a day” when asked “How much wood could a woodchuck chuck if the woodchuck was 10 lbs?” (I didn’t make this up, DeepSeek did!) (And, even worse, it gave some extremely ridiculous “reasoning” to back it up which might fool someone who didn’t think twice because the logic was pretty good, while the data it worked on was ridiculous [and obviously hallucinated]. I should also point out that this was a result “I” totally expected because there shouldn’t be much “data” on “how much wood a wouldchuck could chuck if a woodchuck could chuck wood” on the internet [which is it’s training data], because we all know a woodchuck can’t chuck wood but the AI doesn’t know that.)

Thus, whether you use one agent or twenty, you will get one opinion, and one result, which could be a total hallucination if none of the systems had enough correct “data” and examples to “reason” on.

Given that, as Paul Martyn points out, the best decisions are made when there is

  1. A diversity of experiences and information to draw on
  2. Independent thought by the participants (that can provide truly different views to the ultimate decision owner)
  3. Decentralization of knowledge for risk mitigation

and that today’s AI, which is NOT intelligent, cannot be trusted to always make the best decision as

  1. all agent systems have access to the same data on your network and the web
  2. agents cannot think, only produce “outputs” based on different weightings of “inputs”
  3. agents with minority data/reasoning can, and will, have at least their reasoning, if not their data, overwritten by the majority

This brings us to the following conclusions:

1. Traditional Suite and BoB solutions ARE still needed, even with orchestration and agents (especially since the later should be restricted to either fully deterministic processes or processes where the cost to fix/clean up after an occasional bad decision by software is less than the cost of having a team of people do that process manually)

2. The New Hotness Hype will always take sales away from established players, as the lazy and greedy look for that panacea solution that does not, and cannot exist … but when those solutions fail to achieve the result, some of those sales will return (as the only other option will be to build the missing parts into the acquired system, and why waste money trying to extend a system that’s fundamentally broken?)

3. “The Market is Not Dying”, as Paul Martyn states, but it is shifting. Suites will become the transaction engines and systems of record in organizations that experiment with new interfaces, orchestration, and AI agents. Hybrid suites, which embed orchestration and intake, will take over in organizations that want modern connectivity and interface but want to limit the number of vendors they need to deal with. And traditional suites will gain traction in highly regulated industries and governments where everything has to be 100% predictable and in-line with thousands (if not millions) of pages of policy regulations!

As Jason Busch likes to say, “many things can be true at once” and as long as those things are not mutually exclusive, they will be in the market.

(P.S. Thanks for taking up my day with no warning, Paul!)

Center-Orchestrated Procurement Requires Unique Platforms

In our last few articles, we’ve been writing a lot about the need for center-orchestrated Procurement due to the current global trade environment. As a result of this, a number of policies, processes, and platforms will need to change for a modern global Procurement organization in order for it to be efficient, effective, and even endorsed.

While the core platform requirements don’t change, the unique requirements for the platform are different. When you only have to serve yourself, whatever works for you is good enough. But when you have to serve a diverse base of global users, who have to adhere to a diverse spectrum of global requirement, what works for you is sometimes completely irrelevant.

Then there’s also the fact that center-orchestrated procurement, by definition, requires:

  • orchestration — if the platform can’t orchestrate data streams, workflows, and users, it’s not sufficient
  • common data model — every platform must support the common data model in the central data store to allow for easy data integration and cross organization analytics
  • centralized supplier onboarding — there needs to be a central supplier master and management platform
  • “excellence” — if the platform can’t encode and distribute best practices across the global organization, it’s not the right platform
  • standards — efficiency comes from standardization to the extent possible, if the platform doesn’t support that, it’s no good
  • supply chain awareness — it needs to integrate with the logistics, supply chain, and PLM systems in order to allow for organizational aware sourcing and procurement
  • knowledge management — it should capture all of the knowledge needed to run the orchestrated workflows effectively
  • global risk management — all of the risks must be identified, tracked, mitigated and managed centrally

Breaking this down, you can see that before any sourcing or procurement platform, it needs to support:

  • real orchestration support — it needs a fully defined API that allows all data to be pushed in or pulled out, functions to be executed, and workflows to be configured; it can be a standard REST API or MCP, but it has to be orcehstratable
  • centralized common data model and data federation platform — that can support all sourcing and procurement data collected and generated by all systems with the ability to define the external system mappings as appropriate; this doesn’t mean the organization dumps everything into a lake / warehouse / lakehouse, but builds the foundation for federated data analysis as the best analytics platforms can pull in the data needed on demand when they have a common data model to work off of (pre-defined mappings from the global organizational systems, and a designation as to which system is “master” for any specific piece of data — which means the data model specifies, for each datum, the master system)
  • centralized supplier onboarding — the central supplier master should support global supplier onboarding; if it can’t be localized as needed (language, accessibility, etc.), then it needs to support fine-grained orchestration that will allow a local platform to mimic the global requirements and feed all of the data into the central system
  • excellence — any platform used for centralized operations need to support the creation of specialized workflows for each region, location, and project; moreover, the specialized workflows need to inherit the global requirements while supporting the regional and local overrides with minimal effort; nothing should have to be defined twice and no unnecessary work duplicated
  • standards — the platform needs to support multiple authentication, security, and privacy standards and implementations to meet global requirements; remember, different countries will require different security protocols, login protocols, privacy requirements, government platform integrations, etc. — the global platforms you select must support switching them in and out as needed by the locale
  • supply chain awareness — the platform needs to understand your supply chain data model and be capable of integrating with your supply chain platforms to integrate the required data to make supply chain aware decisions
  • knowledge management — the platforms must capture more than process, they must capture the decision making frameworks used to select and execute the processes and do the required analytics; for the categories, they must cover the strategy; for the suppliers, the soft evaluation criteria based on the objective and subjective rankings; for Procurement process selection — catalog vs. RFQ vs. tail-spend provider — the logic used; etc.
  • global risk management — a solution for identifying, tracking, and monitoring changes in global risk criteria and alerts and pushing out relevant information to the appropriate regions and locations through the tools the end users actually use (using the built-in orchestration capabilities)

In other words, the platform has to be a lot more adaptive, layered, and customizable than most platforms in use today.

Setting Up Center-Orchestrated Procurement Part 2

In our last post, we reminded you that since the dangers of centralization in a de-centralized world not only eliminated centralization as a valid Procurement Operation Model, but also limited the effectiveness of center-led and center-of-excellence models in today’s global trade environment, the Procurement Operating Model for a global organization needs to evolve in order for a global organization to be efficient and effective in today’s global trade environment.

We started to discuss the required changes by referring back to the list of center-led procurement best practices we gave you twenty years ago, and describing how the center led model needs to evolve along those dimensions. However, those aren’t the only dimensions that need to be considered, so today we discuss the rest, some of which probably aren’t part of your current model.

In addition to the 7 points we discussed in Part 1, a centrally orchestrated procurement center of excellence organization (Orchestric CoE) also differs in the following ways:

8. Centralized Risk Modelling, Mitigation, and Management

The only constant in global supply chains today is disruption — a lot of which can be (partially) predicted by well defined risk management. An organization that tracks global geopolitical, economic, and trade (tariff/isolationism) risks as well as more localized geopolitical and civil risks, port closures and strike risks, natural disaster and climate risks, and so on. That takes all of these into account in the formulation of, and constant adjustment of, sourcing strategies that focus on friend-, near-, and home-shoring (and hence regionally focussed Procurement) as well as “safe” supply lanes.

9. Standardization, Localization, and Rationalization – Products and Services

We’ve argued against over-standardization to the point that only a few suppliers can meet your needs, but without standardization to a reasonable extent across your global supply chain, you’re not going to ever see any economies of scale, risk reduction, or overall improvement.

Standardization allows products to be sourced and sold across regions, economies of scale to be monopolized across the supply base, and easy product development in established categories.

However, there will be different requirements with respect to product (raw material) content, industry standards, safety factors, warranty, and repair that will need to be met. Sometimes it will be possible to create products that meet all the needs, sometimes now, so the Orchestral COE will be responsible for defining the base standard and regional variations where required, as well as any additional specific localizations required to increase utilization or sales.

10. Standardization, Localization, and Rationalization – Policies, Terms & Conditions

You also want to standardize organizational policies and terms and conditions for contracts and service agreements to the extent possible. It makes it a lot easier to define processes, starting contract clauses, and conditions for success. It also makes it easier to identify what needs to be localized or altered in different parts of the world, track those differences, and understand when changes need to occur how much of the supply base and operating base is affected.

11. Global Logistics Coordination

In an article on how there is no cost savings if it doesn’t hit the P&L, we noted that most consulting process changes and (sourcing and) procurement platforms don’t actually save anything, not even a single cent, because the cost reductions usually came at the expense of cost increases elsewhere, which often exceeded the cost savings in Procurement.

The first place this usually hits is logistics — because, classically, Procurement always sought the lowest cost and that always came from the furthest supplier, which lengthened the supply chain and greatly increased logistics costs, as well as stockout-related costs as stockouts became more likely and frequent on every disruption. Also, when multiple supplier tiers sourced from far away, you ended up with a product where some of the raw materials circumvented the globe multiple times — and that’s just not efficient or cost effective.

And even when similar regions were sourced from, it was often the case a supplier as far outside of the network in the region as possible would be selected, leading to the need for new routes that wouldn’t run full truckload on a regular basis, more cross-docking, and greater inventory costs. The Orchestric COE needs to work with Logistics and ensure that the global logistics network is taken into account during centrally orchestrated events, or, when the supply base needs to change, updated appropriately to keep overall costs and risks low.

12. Operational Impact Tracking and Management

Any time a major change is proposed in the product base, supply base, shipping network, or standard operational policy, it’s up to the COE to determine what organization wide impacts will result and what the costs will be. Since there’s no savings if it doesn’t hit the P&L, there’s no savings if the change will shoot up costs in another part of the organization more than the change saves. So its up to the Orchestric COE to work with the other units as part of its cross functional teams to determine potential impacts, potential up front and ongoing costs, and take that into its total cost of ownership models when sourcing and managing day-to-day procurement.

In other words, you can’t lead from the center with one playbook and expect results. You have to orchestrate from the center, ensure the knowledge flows across the supply chain graph, and adapt to the market for each category when it needs to be sourced and procured. And that requires a different operating philosophy than a classic center led / center of excellence model.

Setting Up Center-Orchestrated Procurement Part 1

In our last post, we noted that, since the dangers of centralization in a de-centralized world not only eliminated centralization as a valid Procurement Operation Model, but also limited the effectiveness of center-led and center-of-excellence models in today’s global trade environment, the Procurement Operationg Model for a global organization needs to evolve in order for a global organization to be efficient and effective in today’s global trade environment.

We said that model was a Center-Orchestrated Procurement model where we modified a hybrid center-led procurement model based on a center of excellence to one that orchestrated global Procurement versus one that did the global sourcing events and handed off the daily Procurement pulls to a local organization with junior buyers only. Orchestration of regional and local Procurements against a global need or category strategy as well as localized day-to-day Procurement, systems selection and implementation, analysis, and best practice development.

But what does that look like? And how does it differ from center-led?

Not much from the outside looking in, but quite a bit from the inside looking out. To try and explain the subtle differences, we’re going to go back and compare it to the list of center-led procurement best practices we gave you twenty years ago, with a few additional notes to help you transition into a next generation, adaptive, Procurement Operation Model that will allow you to survive the tumultuous world of global trade we currently have to deal with.

1. A Chief Purchasing Officer (CPO) on the Executive Team leads the COE

This stays the same. A strong CPO has to lead the Central Procurement Office. She’s the one who ensures that the right plans, processes, and platforms are selected to meet Procurement’s goals and align with the business objectives, divert resistance, and bring various business divisions and units onboard when needed.

2. Cross Functional Teams

Cross functional teams also stay in place, except you need them at both the global level — where Procurement aligns with global product focus, marketing, and supply chain efforts — and also at the regional/local level where they exist to support the relevant categories that are sourced regionally and locally.

3. Multi-Year Supply Plans

This is where center-orchestrated differs from center-led. It’s not multi-year supply plans, it’s appropriately windowed supply strategies with regular review according to the category under consideration. Categories with stable global dynamics and long-term predictable demand or where scarce supply needs to be locked up should be multi-year, but categories where demand is unpredictable and supply is typically not a problem should be shorter, especially when market dynamics don’t favour locking in long term contracts.

Moreover, if the category is one that needs to be sourced regionally, or locally, the windows should be adjusted to the regional economics of the time, because if costs in one region happen to be spiking or at a floor, the plan and contract length (for a contracted category) should be adjusted accordingly.

Moreover, to be more precise, it’s appropriately windowed supply strategies with regular review based on Busch-Lamoureux Exact Purchasing where the organization adopts a next-generation supply management methodology that overcomes the weaknesses of the Kraljic Matrix and every other 2*2 methodology based on it which all refuse to acknowledge that risk, complexity, and impact are completely independent directions. Using this methodology, each category can be appropriately classified into the right octant of the pocket-cube, where the organization can identify the right default strategy for categories in that octant as well as conditions under which the correct strategy would vary and how it would vary.

4. Coordinated Metrics and Incentives

In order to properly analyze regional Procurement, every division has to be analyzed off of the same set of metrics. However, for that to be fair, they need to understand what those metrics are up front and the metrics need to make sense. This means they need to be designed and coordinated by an expert center of excellence that knows how to design metrics for execution and orchestration, not just reporting.

In addition, there must be well defined and aligned incentives that will convince each unit to work towards common objectives and goals and follow the best practice advice departed by the central office.

5. Web-Based Automation and Decision Support Tools

This is still required, but it’s not the core. The core is standardized data model and [analytics] platform and foundational global sourcing, procurement, and supplier management platform. And, today, a well-defined automation and AI strategy that indicates what can be used by who, where, when, why, and how. No generics, detailed specifics!

Centralized and center-guided Procurements need to be on the same platform for multiple reasons. This allows the COE to define a standard strategy and process that can be rolled out and setup for each region, and in the case where some regions can share suppliers (where the supplier would be primary in one region and secondary in another), a model can be setup where each region could define their own requirements and preferences and a bi-regional or global optimization model could be developed to define a global allocation where local suppliers to a region are given the preference defined by the region and regional needs are all met.

Moreover, where a platform doesn’t support, or can’t easily be rolled into a region, the region knows what processes its local platform need to support, what data it needs to collect, and how it needs to integrate to the global organization.

6. Ongoing Education

Education is still critical, but it’s not top-down inside-out education, it’s bi-directional knowledge transfer, capture, and education. The reality is that best-practices tend to be time-based and regional. What works for one region might not work for another, and what works for one set of market conditions might not work for another. Only by enabling, capturing, and applying bi-directional knowledge transfer can the organization come up with good standard processes and platforms as well as modifications and exceptions with respect to different regional requirements and market conditions.

7. Speak to the Supplier Community with a Central Voice

More precisely, speak to each supplier with a common central voice, where that voice might be central, regional, or local. Also, define standards for supplier onboarding, communication, management, development, correction, measurement, and performance management.

The supplier master and management solution needs to be centralized, as does the general supplier management philosophy.

But these are not the only requirements, and differences, that need to be addressed in a modern center-orchestrated procurement model.