Category Archives: rants

Challenging the Data Foundation ROI Paradigm

Creactives SpA recently published a great article Challenging the ROI Paradigm: Is Calculating ROI on Data Foundation a Valid Measure, which was made even greater by the fact that they are technically a Data Foundation company!

In a nutshell, Creactives is claiming that trying to calculate direct ROI on investments in data quality itself as a standalone business case is absurd. And they are totally right. As they say, the ROI should be calculated based on the total investment in data foundation and the analytics it powers.

The explanation they give cuts straight to the point.

It is as if we demand an ROI from the construction of an industrial shed that ensures the protection of business production but is obviously not directly income-generating. ROI should be calculated based on the total investment, that is, the production machines and the shed.

In other words, there’s no ROI on Clean Data or on Analytics on their own.

And they are entirely correct — and this is true whether you are providing a data foundation for spend analysis, supplier discovery and management, or compliance. If you are not actually doing something with that data that benefits from better data and better foundations, then the ROI of the data foundation is ZERO.

Creactives is helping to bringing to light three fallacies that the doctor sees all the time in this space. (This is very brave of them considering that they are the first data foundation company to admit that their value is zero unless embedded in a process that will require other solutions.)

Fallacy #1. A data cleansing/enrichment solution on its own delivers ROI.

Fallacy #2. You need totally cleansed data before you can deploy a solution.

Fallacy #3. Conversely, you can get ROI from an analytics solution on whatever data you have.

And all of these are, as stated, false!

ROI is generated from analytics on cleansed and enriched data. And that holds true regardless of the type of analytics being performed (spend, process, compliance, risk, discovery, etc.).

And that’s okay, because is a situation where the ROI from both is often exponential, and considerably more than the sum of its parts. Especially since analytics on bad data sometimes delivers a negative return! What the analytics companies don’t tell you is that the quality of the result is fully dependent on the quality, and completeness, of the input. Garbage in, garbage out. (Unless, of course, you are using AI, in which case, especially if Gen-AI is any part of that equation, it’s garbage in, hazardous waste out.)

So compute the return on both. (And it’s easy to partition the ROI by investment. If the data foundation is 60% of the investment, it is responsible for 60% of the return, and the ROI is simply 0.6 Return/Investment.)

Then, find additional analytics-based applications that you can run on the clean data, increase the ROI exponentially (while decreasing the cost of the data foundation in the overall equation), and watch the value of the total solution package soar!

Bring Back the Interns!

Even the offshore interns!

And since, like Meat Loaf,

I know that I will never be politically correct
And I don’t give a damn about my lack of etiquette

I’m going to come out and say I long for the days when AI meant “Another Indian”. (In the 2000s, the politically incorrect joke when a vendor said they had AI, especially in spend classification, was that the AI stood for “Another Indian” in the backroom manually doing all of the classifications the “AI” didn’t do and redoing all the classifications the “AI” got wrong over the weekend when the vendor, who took your spend database on Friday, promised to have it by Monday).

The solution providers of that time may have been selling you a healthy dose of silicon snake oil, but at least the spend cube they provided was mostly right and reasonably consistent (compared to one produced with Gen-AI). (The interns may not have known the first thing about your business and classified brake shoes under apparel, but they did it consistently, and it was a relatively easy fix to remap everything on the next nightly refresh.)

At the end of the day the doctor would rather one competent real intern than an army of bots where you don’t know which will produce a right answer, which will produce a wrong answer, and which will produce an answer so dangerous that, if executed and acted on, could financially bankrupt or effectively destroy the company with the brand damage it would cause.

After all, nothing could stop me from giving that competent, intelligent, intern tested playbooks, similar case studies, and real software tools that use proper methodologies and time-tested algorithms guaranteed to give a good answer (even if not necessarily the absolute best answer) and access to internal experts who can help if the intern gets stuck. Maybe I only get a 60% or 70% solution at best, but that’s significantly better than a 20% solution and infinitely better than a 0% solution, and unmeasurably better than a solution that bankrupts the business. Especially if I limit the tasks the intern is given to those that don’t have more than a moderate impact on the business (and then I use that intern to free up the more senior resources for the tasks that deserve their attention).

As for all the claims that the “insane development pace” of (Gen)-AI will soon give us an army of bots where each bot is better than an intern, given that the most recent instantiation of Gen-AI released to the market, where 200 MILLION was spent on its development and training, is telling us to eat one ROCK a day (digest that! I sure can’t!), I’d say the wall has been hit, been hit hard, and until we have a real advancement in understanding intelligence and in modelling intelligence, you can forget any further GENeric improvements. (Improvements in specific applications, especially based on more traditional machine learning, sure, but this GEN-AI cr@p, nope.)

When it comes to AI, it’s not just a matter of more compute power. That was clear to those of us who really understood AI a couple of decades ago. AI isn’t new. Researchers were discussing it in the (19)50’s, ’56 saw the creation of Logic Theorist, which was arguably the birth of Automated Reasoning, ’59 saw the founding of the MIT AI lab by McCarthy and Minsky, and ’63, in addition to seeing the publication of “Computers and Thoughts“, saw the announcement of “A Pattern Recognition Program That Generates, Evaluates, and Adjusts Its Own Operators“, which was arguably the first AI program (as AI needs to adjust its parameters to “learn”).

That was over SIXTY (60) years ago, and we still haven’t made any significant advances towards “AI”.

Remember that we were told in the ’70s that AI would reshape computing. Then we were told in the 80s that the new fifth generation computer systems they were building would give us massively parallel computing, advances in logic, and lay the foundation for true AI systems. It never happened. Then, when the cloud materialized in the 00’s, we saw a resurgence in distributed neural nets and were told AI would save the day. Guess what? It didn’t. Now we’re being told the same bullshit all over again, but the reality is that we’re no closer now then we were in the 60s. First of all, while computing is 10,000 times more powerful than it was six decades ago (as these large models have 10,000 cores), at the end of the day, a pond snail has more active neurons (than these models have cores), and neuronal connections, in its brain. Secondly, we still don’t really understand how the brain works, so these models still don’t have any intelligence (and the pond snail is infinitely more intelligent). (So even when we reach the point when these systems are one million times bigger than they are today, which could happen this century, we still won’t have intelligence.)

So bring back the interns, especially the ones in India. With five times the population of the US, statistically speaking, India has five times the number of smart people, and your chances of success are looking pretty good compared to using an application that tells you to eat rocks.

Let’s Get One Thing Clear: Like All Financing, Supply Chain Financing Benefits the Lender, Not the Buyer or the Seller

While there might be arguments that some form of Supply Chain Financing (SCF) would benefit all parties in a fair world, it’s not a fair world, as it’s run by greedy capitalists, but that doesn’t mean we have to make it more unfair, or complain about laws being proposed to limit unfairness.

But that’s exactly what a recent article in the Global Trade Review on how the Supply Chain Finance Industry Hopeful EU will Soften Late Payment Rules is pointing out. The EU SCF industry is crying foul when there really is no foul.

The article, which notes that even though an EU Parliament committee is pushing for greater flexibility around the regulation on combating late payments that puts in place a stricter maximum payment term of 30 in both business-to-business (B2B) and government-to-business (G2B) transactions (versus the current 60 days), unless companies negotiate payment terms of up to 60 calendar days and both agree to those extended terms in a contract, there are some parties that are still not happy. (Even when the new regulation even allows for companies trading in “slow moving or seasonal goods” to collectively agree to extend terms up to 120 days in a contract.) (For completeness, we should also note that the forthcoming legislation will enforce accrued interest and compensation fees for all late payments.)

However, some parties believe that payment terms should be twice that as they risk restricting liquidity and interfering with companies’ contractual freedoms. The former statement (restricting liquidity) is complete and utter bullcr@p. The latter statement (restricting contractual freedoms) is a valid point if there are currently no restrictions on payment requirements in local laws, but, guess what, all contracts must adhere to the laws and directives of the countries in which the companies operate, and countries / unions have a right to modify those laws and directives over time to what they believe is in the best interest of the greater (not the lesser) good. And when a recent Taulia research report found that 51% of companies polled are typically paid late, something needs to be done.

The point being whined about … err … made is that shortening mandatory terms without agreement to 30 days and with agreement to 60 days would mean SCF lenders would see their returns slashed, and potentially remove any incentive to offer programmes in the first place. And while it’s true they would see their returns slashed from predatory lending, taking advantage of suppliers who need money now from buyers who want to keep their bank accounts as cash flush as possible (even when not necessary to meet internal operating costs), it doesn’t necessarily mean they have to see their returns slashed from a finance perspective. They could still provide suppliers with loans (at fair interest rates) secured by the equipment the supplier buys or the products produced (which they could seize if they feared lack of payment and then the buyer would have to pay the lender for the goods’ release). Or, if buyers liked unnecessarily fat bank accounts, they could lend the buyer cash with the buyer’s illiquid assets as collateral. And while this is more traditional finance, what’s wrong with that?

Allowing buyers to screw suppliers (when those buyers can afford not to) just hurts everyone in the long run. Suppliers have to borrow, usually at predatory interest rates, to make payroll, which increases their overall operating costs. In return, their costs go up on all future contracts. A buyer might squeeze out a slight gain (in its high interest investments vs. paying the supplier or in its stock price based on correlation that a higher than expected bank account is higher than expected growth), but the buyer will just end up paying more in the long term (and then passing that cost onto us consumers). And the only party winning in every transaction is the SCF vendor who gets 2% to 6% on all the short term cash it provides, which is very safe because someone’s going to take that product. And, FYI, even 2% on a 60 day term, works out to over 13% a year (because by the time the supplier submits, the SCF approves, and the money gets transferred, that’s usually at least 5 days). And the rates are only that good when the supplier has more than one SCF option. When the supplier doesn’t, it’s probably 4%, or 26%+ per year, which is likely 40% higher than the organizational credit card, and nearing predatory lending territory! And while it’s not as bad as the 40%+ some suppliers will be saddled with in hard times when all they can get is the local loan-sharks, it’s still not something we should accept.

So bravo to the EU Parliament and shame on anyone complaining about legislation mandating fair payment terms, especially to SMEs. After all, it’s not banning SCF vendors from helping them in other financing ways, or even negotiating an agreement to auto pay every 60 day invoice in 6 days (for 2% of the transaction value) when you know these suppliers are all going to have 60 days shoved down their throats by big businesses.

While Not a Significant Source, Some New Vendors are Contributing to the Procurement Stink!

There are many reasons that Procurement Stinks!

Some of them are due to the Marketplace Madness.

Some of the marketplace madness (a small amount, but non-zero), is aptly summarized as follows.


“We’re pre-revenue, pre-product, and pre-idea.
So any help would NOT be appreciated!“

(Which, to give credit where credit is due, is
a slight rewording of the tag-line to an Andertoon).

Those companies will likely be among the first companies to fail. When there is at least 50 companies that are offering every S2P module, and over 100 for most modules, there is only so much room for differentiation. This means that most of the new startups by the young 30-somethings that did NOT do their market research (but think they know it all because they are tech wizards who built a solution that did slightly more than the three inappropriate products they were stuck with at their last job) don’t really do anything different from a product perspective (and, in fact, usually do a heck-of-a-lot less — hence, “pre-product”). It might be a newer tech stack, it might look slicker, it might be a bit easier to use, but they all fail to understand that THIS IS PROCUREMENT.

This means that, at a minimum, any “product” they want to sell has to satisfy the following:

  • they have to demonstrate a significant ROI, within a decent return within the first 12 months before the CFO will even consider cutting a cheque
  • but before that, they have to show how they will generate long term value before they will even get budget (if the value is one-time like a spend analysis project, especially at Big X quotes of seven figures, not likely)
  • they have to show that it fits in with the current tech stack or IT will object
  • they have to show that it is compliant with regulations or Compliance will object
  • they have to show how it will also decrease overall procurement or supply chain risks, or risk management will steer the budget elsewhere
  • they have to demonstrate they will be able to do more and protect the brand or the CEO will object

Procurement tech is not about cool. That’s consumer tech. Procurement tech is not about the most modern stack to power the business. That’s IT tech. Procurement tech is about VALUE. Procurement is expected to cut costs, NOT increase them!

Until the new generation of founders learns that, and learns there is no way that Procurement will NOT be able to make a case for their ??? ??????? that literally does nothing different than the ??? ?????? tech that came before, the old Procurement Pros aren’t going to buy it. And these start-ups won’t hit break-even as a company, and if they don’t get acquired, they will go belly up as the investors realize how over-crowded the space is and any further investment would be throwing good many after bad into the bottomless money pit.

You NEVER Have to Go Crazy on 3 Bids and a Buy!

This is a follow-up to last Friday’s article on RFP Everything? Are You Mad? Even The Squirrels Will Think You’re Nuts!,
which was in response to a LinkedIn Post where a consultant noted that a remarkable example of AI was autonomous tail spend RFP’s generating over 15,000 RFP’s annually through a programmed bot. the doctor‘s response to this was that it was absolutely terrifying. Sales professionals who are already over-inundated with ever more demanding RFQs where they know, statistically, they will only get 20% to 33% of the business if they are on par, and less of the business if they are not, are going to be so overwhelmed that they are going to have two options:

  • pick favourites and stop responding, or selling, to clients that over-inundate but under-buy or
  • acquire an auto-responder and counter auto-generated RFQs with auto-generated bids from their catalog, which may be good, bad, or pointless

Neither is good for the buying company. The counter to this was that there is a category of services which is one off and needs the collection of a number of competitive bids. The value of these services in the €10-100k bracket needed a tail spend management program for which we developed the automated ‘3 bids and a buy program’ … and there is no better way to organize it.

Which is totally not true, because the doctor saw a better way successfully implemented 16 years ago. Back in the day, Iasta (acquired by b-pack, renamed Determine, acquired by Corcentric) identified that one of the BEST uses for strategic sourcing decision optimization was services procurement (when most firms were still using it for indirect or fledgeling direct).

What they did was:

  1. identify all of the services their large mid-market clients would contract over the course of a year with typical durations
  2. collect bids from national, regional, & local providers
  3. build a huge optimization model which would identify the lowest cost providers for each service in each area and then make an annual award to a mix of national, regional, and local providers guaranteeing a certain volume / $-value of services across a certain number of service categories / roles across awarded service areas as long as the provider locked in the rates for a year

It was ingenious because, when the service was needed, the company simply sent the requisition to one of the chosen providers (lowest-cost first if available, or second-lowest if not or if they weren’t sending enough business to the second-lowest in other categories to meet the commitment).

ONE single RFQ event. One year of quotes negated. The approach regularly identified up to 40% savings, and realized up to 30% savings. David Bush and team were geniuses!

The morale of the story is this: if you think you need to send 15,000 auto-generated RFQs to get tail spend under control, you haven’t done enough thinking about, or analysis of, the problem!