Center-Orchestrated Procurement

In a recent piece on the dangers of centralization in a de-centralized world we noted that not only was it time to bury anything that remained of centralized Procurement, but also classical centre-led Procurement. While centre-led Procurement worked great for about two decades, we saw it crash and burn during the COVID pandemic and any signs of recovery cease once global trade was again interrupted on a regular basis thanks to geopolitical conflicts, sanctions, seaway closings, tariffs, natural disasters, and economic instability, among other things.

As a result, the model needs to evolve for global multi-nationals looking for a way to standardize their Procurement without creating as many problems or costs as they solve or remove. The answer is centralized orchestration through a centre of excellence designed to support, but not lead, since, with the exception of any materials, components, parts, or products that can only come from a handful of suppliers in a few locations and, thus, truly need to be sourced globally, Procurement should be a mix of regional and local activities.

The need for friend-shoring, near-shoring, and home-shoring has hit an all time high, which means that Procurement has to be a lot more localized than it has been in leading multi-nationals for the past two decades. That means it needs to be done locally, with local expertise, to ensure the right suppliers and right products are selected for the local (market) needs.

But you can’t revert to decentralized Procurement because that will essentially bring back all of the original problems it came with. Some may present different, but you will have a lack of standardization where it is needed, a loss of economies of scale, duplicate effort in Procurement process and best-practice creation, multiple platforms where you should have a single platform, and so on.

Even though Procurement needs to be more localized than it has been in decades, it still needs some standardization, economies of scale, single platforms, and efforts that generate value versus duplicate, wasted, efforts. So a Center of Excellence is needed now more than ever, but we’ve repeatedly seen that a pull-based center of excellence never gets used. Procurement pros are so overworked and constantly bombarded that they don’t have time to even think about consulting a center of excellence, especially one in a totally different time zone.

That means, for it to work, there has to be a push element as well … but no one likes processes, platforms, prognostications, or prescriptions being forced upon them.

That’s why we need to step up from center-led procurement to centralized orchestration, not led, orchestration — because good orchestration understands the process, defines the workflows, and, most importantly, knows where the source and lead systems, processes, and people are. It knows when a sourcing event should be fully centralized, fully decentralized, and, more importantly, split … broken into a number of regional buys with appropriate splits, selections that could serve other regions in a pinch, and standardized processes. It knows how to coordinate, when it needs to push events, and when it needs to pull information and awards to better coordinate globally. It doesn’t lead, it orchestrates. It’s a subtle difference, but an important one.

The Dangers of Centralization in a De-Centralized World!

For years, centralization (and then center-led) was promoted as the best Procurement organization methodology because it would deliver many benefits including, but not limited to:

  • economies of scale
  • purchasing expertise
  • administrative efficiencies
  • specialization
  • volume discounts
  • optimal resource allocation

However, while it often delivered economies of scale, volume discounts, and specialization, it never increased purchasing expertise, just shifted administrative efficiencies and only optimized the resource allocation in the center … the rest of the business (and affected personnel) didn’t benefit at all.

Furthermore, these benefits were only delivered in times of free global trade, low/no inflation, and stable economies. Take any of these requirements away, and the discounts and/or economies of scale might disappear overnight and the specialization that was so highly sought might also disappear as well.

The reality is that the right model is really a center-of-excellence which helps to orchestrate best practice procurement across the multi-national/global organization, but, except in a few rare cases, doesn’t really carry out the day-to-day Procurement function. The reason for this is that centralized (and even center-led) suffers from all of the following drawbacks, which are only heightened in today’s global economic landscape.

Missed Local Opportunities

Most manufacturers and distributors aren’t truly global, and when you try to centralize on just a few suppliers, while it will keep costs down for some of your markets, it will increase them greatly in others because the manufacturer and/or distributor just doesn’t have the economy of scale or knowledge in those regions.

The reality is that the best sourcing outcome is one that takes advantage of opportunities at the global, regional, and local level — especially when local opportunities far exceed the national or global ones. The best example here often comes from services. I remember the first time early sourcing optimization providers tackled services projects where an organization regularly outsourced a number of services roles. Due to the perceived complexity of dealing with multiple contractor, manpower, and service management firms, most organizations would try to find 2 or 3 national firms to handle their needs. As a result, even though they would save 10% or so using optimization-backed strategic sourcing, they’d still regularly overpay by 30% to 40%, especially when fully loaded costs were considered. Most IT support firms had their key talent localized in a few offices in big IT hubs (San Francisco, Chicago, New York, Atlanta, Houston, etc.) and for firms that had local offices across the mid-west, so when you want them at remote locations, not only are you paying big-city rates, but you are paying high fully burdened costs. Most states have at least one big city with a few consulting or manpower shops that have the same breadth of resources. They may not be the very best, or the top talent you’ll need if you have a highly specialized problem, but that’s not 90% of your needs. The local DBA trained and experienced in your database, the local fleet/aircraft mechanic with 20 years, and the local HR manager will generally be good enough and almost half the cost. That’s why most organizations who focussed just on national/global providers would, despite their attempt to optimize spend, would overpay by 30%.

Plus, when you are trying to ensure a product or service sells well in local markets, it’s the local expertise that makes the right selection, not a buyer from half a world away.

Loss of Key Market Knowledge

A buyer in the US has no clue what a customer in China wants (unless she just came from China, in which case she probably doesn’t really understand the market she is now based in), and a buyer in the UK won’t get the slight differences in the US market and have no clue about Latin America.

Also, a remote buyer doesn’t typically know who the regional and local manufacturers are or what they are capable of. This is key, even if you decide to go with a remote supplier as the primary supplier as the regional and local suppliers will be your backup when the remote supplier becomes temporarily, or permanently, unavailable.

Supply Base Degradation

Having fewer suppliers doesn’t strengthen your supply base. It just shrinks it to a size that you believe is more manageable. But a strong supply base isn’t a small supply base, it’s a supply base where you have strong supplier relationships, are in a position to help develop the suppliers, and can actively manage performance in near real-time.

They key to performance is detecting issues quickly — as soon as shipments are late, defect/damage rates rise in the warehouse, warranty claims rise, or service levels fall — and then quickly meeting with the supplier to deal with them. This requires being close to the supplier both to detect the issues quickly and resolve the issues quickly. Neither happens when all your suppliers are half a world away.

Ever Lengthening Supply Chains

When over-centralization occurs, most of your suppliers will be half-a-world away for at least half of your markets. When this propagates through the supply chain, you have suppliers at each level commonly sourcing from half a world away. By the time you get to the source, raw materials in your product could have circled the globe three times. How is that efficient? It’s not. And it’s part of the reason that supply chain fragility, and delays, keeps increasing.

Loss of Opportunities Due to Over-Standardization

Standardization is good as it decreases the total number of SKUs you need to track, products you need to buy, and suppliers you need to deal with. But if you standardized down to only a few options, and those suddenly became unavailable, then what do you do. You’ll be set back months to quarters, depending on how long it takes you to locate alternate options in the best case, and come up with new designs in the worst case.

Economies of Risk

The promise was economies of scale (which you hit as soon as you maximize a production line for as little a day, depending on how long retooling costs), but the realities are that what you got was economies of risk. Over centralization resulted in a single supplier failure, single border shut down, or single supply lane closure cutting off your entire supply chain. The more locations that depended on that supplier, border, or supply lane being available, the greater the impact will be.

Loss of Key Process Inefficiency

The promise was resource optimization and process efficiency, and while that was true for the centralized sourcing and procurement organization, the reality is that the efficiency didn’t extend beyond there. Moreover, it made remote operations, which are now fully dependent on a center office half a world away in a timezone where no part of the work day overlapped, less efficient. All requests have to go into a central message queue and, even in an emergency situation, it would be at least a day before a response, and possibly multiple.

This means that local procurement and inventory management teams can’t function efficiently. But the worst case scenario is when a disruption occurs and the local factories or warehouses can’t react and have to wait for days, or weeks, for guidance and possibly months for a new supply source to be identified. Without localized Procurement, process efficiency, especially during a disruption or disaster event, goes out the window.

Operations Research Lessons are Timeless … Especially in the Age of AI

Twenty years ago we published a piece focussed on Mark Daskin’s Everyday Lessons from Operations Research that he delivered at INFORMS 2006. They are just as relevant today, if not more so, in the age of AI (Hype).

  1. Service and Performance Gets Worse as Utilization and Variability Increase
    This is true in so many ways. Dumb users asking stupid questions with poorly formed prompts that don’t match the training prompts flooding the internet with poor and hallucinatory answers that are fed into the next AI model in the collective race to the bottom. Response times decreasing as the models need to get bigger to process ever more mediocre data and, hopefully, create better responses (even though that won’t happen). Costs going through the roof as a result of the constant need for more computing power.
  2. … But Variability is necessary.
    Because every request is fundamentally different, even if phrased the same as the lack of standardization, and training on that standardization, ensures every user has a different intent with their request.
  3. Expect the unexpected in today’s world.
    Most responses will be okay, some will be bad, a good number will be completely hallucinatory, and every now and again the hallucination will provide a revolution insight — which will go unnoticed because most users now lack the cognitive power, and possibly the intelligence, to even detect a hallucination in the first place due to the mass cognitive atrophy Gen-AI is, provably, inducing.
  4. If it is too good to be true, it probably is not.
    But yet we continue to believe the lies, damn lies, and hallucinatory hype spewed by the purveyors and pushers of Gen-AI and the garbage it spits out.
  5. Life is full of errors.
    And Gen-AI multiplies those errors tenfold to ten-thousandfold!
  6. A good decision can result in a bad outcome.
    Even when the AI gets it right on the data, the data is always backward looking, not forward looking, and the right decision based on a past trend can still be wrong if a key variable or assumption just changed and the data does not yet reflect that. So even when the AI actually gets it right, it can still be wrong!
  7. If you are not using all you have, don’t pay for additional quantity.
    If you only have a small amount of data to train the model on, don’t pay for the largest model available — not only will it not help your case, it will hurt as there won’t be enough data to “train” the model even to reasonable levels of accuracy (relative to what the model is theoretically capable of). Always go with the smallest model that will theoretically meet your needs — and, moreover, if you have multiple distinct needs, multiple distinct models will perform much better than trying to create one big mega model.
  8. You can never do better by adding a constraint.
    Never, ever, ever. Whatever you are trying to minimize will increase. Constraints restrict options and that will always result in increased cost, increased risk, etc.
  9. Keep it Simple
    The best AI, especially in the age of Gen-AI, is no AI. More specifically, don’t use AI where AI is not needed. Deterministic automation, when properly applied, has worked well for decades and now, in an age where we can encode adaptive workflows, suggest exception resolutions, have the rules automatically update when a resolution is accepted or created, and improve over time.
  10. Think about problem formulation.
    The formulation dictates the potential solutions … and the better you define a problem, and a stepwise algorithm to resolve that problem, the less need you will actually have for (Gen-) AI.
  11. Look for compromise solutions.
    If a problem ends up being defined particularly constrained or complicated when multiple parties get involved, work together to simplify the constraints or complexity where it truly isn’t needed. There’s a big difference between preference and requirement, and understanding that allows for the creation of good comprise models and solutions.
  12. Data is not information.
    It never has been, and never will be. Moreover, data pulled out of an LLM might not even be accurate, so the chance of it producing usable information is even less. Always remember that.

Procurement Hasn’t Learned Any Lessons in the Last Two Decades! Part 4

William Hefley’s 15 lessons learned from dealing with client organizations talk on “Identifying Issues in Sourcing: Informing Development of Best Practices” that was delivered at the 2006 Informs Annual meeting aren’t the only lessons that should have been learned 20 years ago that still haven’t been learned by the majority of Procurement organizations today. So we continue the series!

16. Process Change Requires Mapping, Desired State Definition, Gap Analysis, and Change Management

Any time the C-Suite decides a process needs to be updated, a department outsourced, or a solution replaced, they jump right to bringing in a Big X consultancy to tell them what to do without understanding exactly what they are doing now, what they need to do in order to improve, and what the gap is. They give the consultancy a big picture objective, desired outcomes, and tell them to go, go, go. The consultancy feeds the company profile, the company requests, and their standard advice and decks into an LLM and has it produce a 200 slide strategy deck. Then they hand it to the new interns, fresh faced graduates with no real world experience, to review and touch up and draft a “killer executive summary”. The interns shunt it up to the project lead, who spends an hour customizing it to his story telling style, books the delivery meeting, presents it, makes exaggerated promises, and everyone cheers.

A project with little thought goes ahead, gets delivered, and then crashes and burns. And the cycle repeats.

17. Major Technology Implementations/Replacement and Supply Chain Network Redesign are Mega-Projects

Every organization treats these as simple sourcing and simple one-and-done projects when nothing could be further from the truth. Technology project (partial) failure rates are past 88% and AI project failure rates are 94%. The odds of you succeeding are insanely bad! The reason is that every one pretends they are simple projects, unrealistic timelines can be easily met, and adoption will automatically happen when the implementation is complete. We all know nothing could be further from the truth. But even worse, buyers continually reward vendors who underpay the effort, present the shortest project schedules no matter how unrealistic they are, and give many assurances that their incredible ease of use will make users want to use the solution.

18. If An Engagement Doesn’t End At Least As Much As it Starts, It’s A Lost Cause!

Companies love to add new processes, new SaaS solutions, new technologies, new product lines, new service lines, new support partners, and new GPOs to “keep costs down”. But very few ever completely end processes, decommission SaaS (especially if the licenses can be put on P-Cards / personal credit cards), retire old product lines, block user preferred services, etc. It’s uncountable how many times organizations have brought in vertical experts to optimize telco costs, streamline SaaS costs, consolidate janitorial and suppliers and MRO, etc. only to see half the promised savings never materialize as some offices refuse to change carriers, give up their preferred SaaS app (which is why some enterprises have over 1,000), still buy what they need as-needed from the local distributor, etc. Without the resolve to end things, new engagements don’t deliver because anything they “save” or “improve” gets “lost” or “degraded” because the organization just diverts focus even further.

19. A Needs Assessment Must Precede Any Services Selection and Engagement

Right now, most consultancy based projects start as a result of a balance sheet exercise, a consultancy push, or a technology hype cycle. In the latter case, right now the vast majority of organizations are engaging Big X consultancies to help them with their “Gen-AI” initiative — even though they have no idea how it works, what it does, or where it should be applied. The same thing happens every time a new consultancy craze (outsourcing, rightsizing, DEI, etc.) comes along. And any time the CFO decides a cost is too high and the CEO mentions it to a consultancy CEO, suddenly there’s a new demand for a transformation project to cut costs. All without any analysis of what the organization actually needs, what opportunities there are for real process improvements and cost reductions, and what the organization actually needs to achieve success.

20. There’s No Success Without Project Assurance

And, of course, every organization believes that once the project is done, the new process will be adopted, the new system will be used, and results will magically materialize. The reality is that without a proper change management and training plan, stage based implementation, work alongside training and monitoring, and general project assurance, the new process will be ignored, the new system bypassed, and nothing will change. And in two and a half decades in this space, I’ve never seen a system implementation or process transformation plan with proper project assurance.