Category Archives: Sourcing Innovation

Operationalizing the Pocket Cube for Exact Purchasing Part II

A few weeks ago, we not only told you that Exact Purchasing is a Pocket Cube, but we broke it down and defined each octant for you, as well as indicating which categories of goods and services were most likely to fall in each octant (with the disclaimer that there is variation between industry and sometimes even companies in the same industry based on size and focus).

This was a great start, but once you understand the breakdown, the next step is understanding how you go about sourcing and procuring the categories in each octant. Today we continue our deep dive into the core technologies you will use with the Architecture focussed-octants.

High Complexity, High Risk, High Impact: Supply Chain Architecture

This is the most critical of all the octants — the far upper, upper right no matter which way you look at the pocket cube. These are your most critical, most complex, and most risky purchases where any interruption can be devastating, and a long term interruption could even bring the risk of bankruptcy (as you lose your key product line and/or ability to serve your customers).

While a lot of automation (and hardened AI) is used for constant monitoring, this is the category where the least automation is employed in the sourcing, contracting, supplier management, procurement, and analysis. Every decision needs to be human made and human reviewed as these are the categories where a single slip-up (or automation mistake because someone miskeyed data somewhere along the chain) can cost millions.

This isn’t to say that advanced technology isn’t extensively deployed — as it most certainly is at every single step of the process, just that the focus is on Augmented Intelligence (and making your employees super-human in their productivity and decision making prowess).

For example, best-of-breed multi-objective strategic sourcing decision optimization that can handle not only multiple providers and product options but also multiple carriers using multiple modes while balancing overall landed cost, supplier and supply chain risk, and compliance is a key requirement of RFP analysis and multi-regional dual-source award definition (as two suppliers in the same province of China that use the same port that could both be taken out by a single natural disaster, port shutdown, or local energy plant failure is NOT dual-sourcing and NOT risk mitigation).

AI might be used to pull together the first pass of the RFP, but the specs will have to be human reviewed and validated, key aspects of the response will have to be human reviewed and validated, and the award analyzed by multiple stakeholders before approval. AI can assemble a contract off of templates, but due to the complexity and risk, legal and risk management will have to carefully review that all risks that can be covered are (and mitigated to the extent possible from a legal perspective) and engineering that product/project management that the specs are complete and the obligation timeline appropriate.

Constant risk monitoring on every signal available will need to be employed, and alerts propagated on the detection of an event that could lead to an issue, not days, weeks, or months later when the issue finally materializes. (And if a human doesn’t review and respond in the system — not an issue, keep monitoring, escalate, etc., escalate the alert up the human command chain.)

  • (Strategic) Sourcing: Strategic Sourcing with Multi-Objective Optimization that balances cost, risk, compliance, and organizational objectives
  • Supplier Management: Compliance, Risk, and Performance
  • Catalog Management: Detailed product (sample) review and verification
  • Contract Management: Manually constructed off of templates, LLM and Human Reviewed to ensure all required obligations captured and risks addressed
  • Procurement (Channel)*: Goods PO (Catalog), Contract Invoice (Payment Schedule), Framework PO (Fixed Delivery Schedule), Consignment PO (VMI)
  • Monitoring: ACK, ASN, Receipt in the Procurement System; Lead Time, Delivery, Quality Trends in the Inventory Management and Production Systems; Financial Status, Litigation Monitoring, Sanction Monitoring, News, Event, and Sentiment Monitoring; Commodity markets, marketplaces, and currency exchanges;

High Complexity, High Risk, Low Impact: Cost-First Architecture

The only difference between this category and the last category is that the impact, while likely relatively significant if any disruption or issue is not resolved promptly, is not as severe (and not organizational life-threatening). It’s still a complicated category to manage due to the high complexity of the products and services, and the high risk they carry due to the supply chain or (current) market conditions, but one that you don’t need to spend nearly as much time.

You’re still doing everything at least semi-manual every step of the way, but you’re not going nearly as deep — you’re covering all the angles, but you’re not triple measuring and verifying them. You’re still using decision optimization, but it’s merely a two-factor cost vs compliance optimization. You’re reviewing the award recommendation, but you don’t need to get the stakeholders involved once you have collected their requirements. You’re verifying specs, but unless it’s a component to be integrated, you don’t have to review samples. And so on.

Also, by continually monitoring for new products and suppliers, and verifying these as they are selected, it’s pretty quick on a disruption to spin up a new event using automation that will essentially recreate the last event but send the RFP to new suppliers as well as suppliers that didn’t win last time (pre-populating with their last responses and bids to make it super easy for them to participate).

And once the key risks that have be captured in a contract are defined, and acceptable clauses created, Legal doesn’t have to review every contract (and you can handle it), and Engineering only has to get involved if a supplier is proposing a change to the spec, material composition, or obligation timeline.

  • (Strategic) Sourcing: Strategic Sourcing with Decision Optimization that balances cost and compliance
  • Supplier Management: Compliance
  • Catalog Management: Product Spec Verification
  • Contract Management: Automatically constructed off of templates, LLM and Human Reviewed to ensure all required obligations captured and risks addressed
  • Procurement (Channel)*: Goods PO (Catalog), Contract Invoice (Payment Schedule), Framework PO (Fixed Delivery Schedule), Non-PO Invoice (Emergency Replacement)
  • Monitoring: ACK, ASN, Receipt in the Procurement System; Lead Time, Delivery, Quality Trends in the Inventory Management and Production Systems; Sanction Monitoring, News and Event Monitoring; Commodity markets, marketplaces, and currency exchanges;

* Unless the Channel-Master Joël Collin-Demers says otherwise.

Operationalizing the Pocket Cube for Exact Purchasing Part I

A few weeks ago, we not only told you that Exact Purchasing is a Pocket Cube, but we broke it down and defined each octant for you, as well as indicating which categories of goods and services were most likely to fall in each octant (with the disclaimer that there is variation between industry and sometimes even companies in the same industry based on size and focus).

This was a great start, but once you understand the breakdown, the next step is understanding how you go about sourcing and procuring the categories in each octant. In this follow-up series we dive in and define the core technologies you will use for each octant as well as their focus.

Today we start with the Transaction focussed-octants.

Low Complexity, Low Risk, Low Impact: Transaction Capture

This is the most “non-critical” of all of the categories in the pocket cube … the true lower left. The impact is minimal if a purchase is delivered late, or has to be replaced with another order. It’s so unimportant compared to literally every other category that, with the right technology, you can literally automate all of it without any worry whatsoever — because the worst case is an ASN/delivery doesn’t materialize and you re-order from someone else, a shipment doesn’t meet spec and you return it and reorder (from someone else), or a service isn’t up to snuff and you don’t (fully) pay for it.

The core technologies are the following:

  • (Strategic) Sourcing: (Deterministic) Autonomous Sourcing
  • Supplier Management: AVLs (Approved Vendor Lists)
  • Catalog Management: APLs (Available Product Lists)
  • Contract Management: Auto Creation and Auto-Sign
  • Procurement (Channel)*: Goods PO (Item Master), Service PO (Fixed Cost Service), PCard Purchase (One Time)
  • Monitoring: ACK, ASN, and Receipt in the Procurement System

Basically, once you define what the categories are, what the product requirements are in each category, and which vendors you have vetted as being real and “safe” enough to source with, you automate the entire sourcing process end-to-end. (You can even use experimental AI here if you want — the vast majority of the time worst case is that a wrong order is made, and you will have to inform the system of its error, return it, and order again. Unless, of course you ask for 100 10g pot for your nursery, and it interprets that as you needing 100 bags of 10gs of pot and orders 1,000 grams of marijuana for you off the dark web in a state where that’s still illegal … but that is rather statistically unlikely so you’re probably safe.) Once you have your AVLs and starting APLs that capture the specs, as well as your standard RFP/RFQ templates, classic robotic process automation can do the entire event from trigger (stock falls before a certain level, an approved buyer request comes in) to final payment on final delivery on final receipt. You step in if a human detects an issue, and otherwise, you just let (for what is typically tail spend) the process flow.

Low Complexity, Low Risk, High Impact: Continual Transaction Monitoring

The difference between this category and the last is that while the products are simple, commodity, and very low risk, you need them to keep operating day to day and you can’t be without them for too long. However, the lack of complexity and risk means that this is another category you heavily (heavily) automate and only step in to review the award recommendation to make sure the specs are met. You set up additional monitoring, and the system kicks off another event or PO (to a backup supplier) the minute an ACK or shipment from the primary is too late (and even sends a cancellation to the primary for breach of terms), again involving you only to verify an award (if the award is not one that has been previously verified, since a re-sourcing/re-order should be automatic).

This can again be handled mostly by classic RPA, but some AI will be used to monitor for new products from the existing supply base that can be used (even if the supplier hasn’t supplied the category/product before), because the human award review will ensure that new products get human approved before they are purchased.

  • (Strategic) Sourcing: (Deterministic) Autonomous Sourcing with Award Review
  • Supplier Management: AVLs and Performance Monitoring
  • Catalog Management: APLs and regular review and approval of new product options
  • Contract Management: Auto-Creation and Auto-Sign
  • Procurement (Channel)*: Goods PO (Catalog), Service PO (Fixed Cost), Contract Invoice (Fixed Payment Schedule), Blanket PO (Fixed Delivery Schedule)
  • Monitoring: ACK, ASN, Receipt in the Procurement System; Lead Time, Delivery, Quality Trends in the Inventory Management System;

* Unless the Channel-Master Joël Collin-Demers says otherwise.

Why Do You Need Frameworks and Systems for Sourcing Excellence?

I’m going to call out a comment made by the Sourcing (Optimization) Grand Master himself, Paul Martyn, to a recent post I made echoing Matthew Buckingham‘s statement that today’s procurement leaders aren’t enough for tomorrow:

“If tomorrow’s environment demands creativity and crusading, how do you see procurement leaders operationalizing that without it devolving into noise?

More specifically:

What does “creative” procurement look like in a measurable, repeatable way

And how does a “crusader” avoid becoming a blocker instead of an enabler when pushing the C-suite to abandon comfortable models?

Feels like the gap isn’t mindset, it is translation into decision systems that actually move outcomes.”

You need

3) outcomes

2) created by decision systems

1) that support your sourcing and procurement needs

This requires

1) Sourcing Excellence in execution

2) BIC multi-objective optimization and analytics that fit into

3) a proper category framework for your organization, like the Busch-Lamoureux Exact Purchasing Framework, that helps you understand the systems and processes you need to employ in each category

Links

You Need Automation. But You Don’t Always Need Agentic and You Almost Never Need Gen-AI!

In a previous post we dove into how analytics must drive source to pay, because most of source to pay should be automated and touch free as most of the source to pay process is straight forward (and capable of being automated for the last decade), non-strategic, and low to medium value.

Strategic Sourcing is an activity that should be focussed on high risk, high complexity, and/or high value categories and occasionally focussed on medium risk, medium complexity, and/or medium value categories where there is incomplete information or insufficient product/category history, atypical turbulence in the market, or highly particular requirements that just came into effect as a result of new regulations. That’s a minority of products/categories, not a majority.

Procurement should only be focussed on significant exceptions. And, with proper, modern, systems with proper e-document integration and exchange, most of the documents should be arriving in standardized digital formats, and most of the processing should, thus, be fully automated. And most of what is non-standard will be PDF in relatively standard formats that LLMs will be able to process to 95% accuracy and only require a few human verifications and field completions. The days of 20 people invoice processing team should be long gone, as the tech, even for standardized PDFs, has been in production by the leading players for over 8 years. Invoice discrepancies can be auto-identified, suppliers auto-notified, suggested corrections auto-included, one-click acceptance emails/screens for the suppliers included, and most contingencies accounted for. Only in the rare situations where suppliers refuse to accept a correction, invoices are in very non-standard or handwritten format, payments don’t go through, etc. should a human need to get involved. However, 95% to 99% of all documents and transactions that flow through Procurement should be 100% automated.

But most of this doesn’t need experimental Agentic AI or Gen-AI. Classic RPA will do just fine. For most of the rest, Adaptive RPA, with a bit of Machine Learning / Auto-Suggestion based on human-based exception processing, will do the trick nicely. If you look closely at current generation (A)RPA, Machine Learning, Optimization, and Predictive Analytics and walk through the full source-to-pay process, there is very little that can’t be automated without Gen-AI LLMs or experimental Agentic Systems. Sourcing — there are many standard (seven step) processes that can be completely automated based on data analysis, data-based risk assessments, goal definitions, and optimization. RFX (including e-Auctions) can be fully automated and, from the time you specify a product/category to source, everything can be automated to the award (including the demand pull/calculation from other systems).

When it comes time to contract, if you have standard templates or a large clause library, the system can automatically create the contract from the template and RFP responses, integrate DocuSign, and auto-execute it. If you don’t, or if you have to use the supplier’s paper, then you might use an LLM to create a draft for human review and/or analyze the supplier’s paper for terms, pricing (to make sure it matches the bid) and potential risks, as well as suggested revisions, before you sign. Gen-AI/LLMs unnecessary, but useful on a point-basis if you don’t have a good historical equivalent of a solution like Coupa Exari or iCertis.

Supplier onboarding can be fully automated with RPA powered dynamic workflows and third party data ingestion, as can risk and compliance analysis — no modern Agentic solutions needed.

Then we get to automatic invoice monitoring and point-based re-orders, receipt creation from inventory integration, and invoice processing in e-Procurement which has all been around for at least a decade. Automated approvals subject to tolerances, rules and pre-approvals — as well as predictive analytics on payments for new or one-time suppliers/orders or (slightly) out-of-tolerance invoices can automate the entire invoice-to-pay process.

We can get through the entire process on best-of-breed, classically oriented, RPA tech with some machine learning that processes human decisions in exception management, alters or augments the rules (and guardrails), and auto-processes the same type of situation next time. We quickly get to 95%+ throughput for any task that should be mostly automated, and a top human employee with BoB (A)RPA solutions and some augmented intelligence packages for analytics and research becomes 10 to 20 times as productive as they would have been in the past.

That’s the real future of Procurement. Small, top-talent teams (mentoring small emerging top-talent teams) doing the work of teams five to ten times their size, doing it better, and delivering more value than anyone would have believed possible with best-of-breed tools. Not error-prone, hallucinatory, agentic systems that work well in demos and a few select categories, and go all over the place in reality (and then try to hide their mistakes like Nick Leeson [who single-handedly collapsed Barings Bank] until they do a modern equivalent of the 2005 J-Com trade and cost you hundreds of millions of dollars on your key billion dollar product line).

So while you need to modernize at all costs, you don’t need to go full Agentic on unproven solutions. Get 90% of the way on tech that has been proven where you can control the automation level until you get comfortable with automation and learn where you can safely hand tightly boxed “decisions” to the machine (where well-defined calculations would determine your decision the majority of the time) and where you can’t. Otherwise, you’ll just end up being another member of the 94% AI failure camp. That’s not a statistic you want to be part of, especially given the cost of this tech today (and the increased cost tomorrow as energy grids start to break and the compute costs for modern AI tech goes through the proverbial roof).