Category Archives: Services

Phil’s new HfS Services-as-Software FlyWheel Is Right On the Mark From a Customer-Centric Viewpoint

… but hides the full support required on the back-end!

This is important to point out for two reasons:

  • Gen-AI Hype-mongers will use this as another excuse to claim most white-collar functions will be entirely eliminated when, in fact, it strengthens the need for true back-office white-collar workers and real software engineers
  • Expert human support becomes more critical at each stage of the process (while bit pushers became less and less useful)

But let’s backup. In his most recent piece where he (re-)introduced the SaS Flywheel, Phil made one critical statement which is constantly overlooked by the industry: Stop treating FDE as optional: Your AI Flywheel will not spin without it.

As Phil astutely points out: the hard question nobody is answering is this: who actually wires AI into your live systems, governs it in production, and makes it keep working when the AI software vendors leave the room. The answer is, of course, your Forward Deployed Engineer (FDE) — and if your transformation strategy does not have it, you are building an AI theatre, not an AI operating model. (Which, FYI, is what most companies are building — and, as Stephen Klein astutely points out, putting on puppet shows. Great for entertainment, but not so great for getting anything done. Especially since they all overlook what AI can actually do.)

Now, a forward deployed engineer alone will not get you out of pilot purgatory, but it is an essential condition — just like you can’t climb out of a deep wide hole with smooth 90° vertical surfaces on all sides without a rope or a ladder, you can’t fly your way out of a pilot without a working plane, which you don’t have without an engineer to keep it running.

As Phil continues, FDE is not implementation – it is the engineering layer that makes AI governable this is because FDE teams build ontologies that reflect how the enterprise actually operates, wire models into real data with real permissions, and design the governance architecture that keeps autonomous systems accountable, which will, and for quite some time into the future, wire in non-overridable human oversight, approval, and review.

Phil goes on to list a few key things that LLMs cannot do on their own. (It’s in no way a complete list, but hopefully enough to get executives questioning all the AI-BS form the AI-Hype-mongers presenting grandiose claims that likely won’t be a reality within most of our professional life-times. Even better, Phil points out that Agentic AI without FDE governance is not transformation. It is risk accumulation!, and points out five key requirements of workable AI that can’t be achieved without an FDE. (There are more, but again, these should be enough key points to help executives realize that not only are LLMs sorely insufficient for almost every task they are being promoted for, but they aren’t even usable at all without the help of a FDE team.)

Phil also does us a great service by pointing out that while vibe coding creates velocity, FDE prevents it from becoming chaos — which is what happens every single time you employe vibe coding without FDEs (and a real engineering team — but we’ll get to that).

Vibe coding is simultaneously one of the biggest boons to software development and the greatest destructors, especially since it is almost universally misunderstood and misapplied. For example, while Phil’s statement that business analysts can express intent and receive working agent code in return is technically correct, it’s not practically correct. That’s because vibe coding produces code that is insecure, inefficient, and not appropriate for enterprise software. In fact, just about every startup that tried to launch an enterprise app on vibe-coding alone have lost hundreds of thousands (or more) attempting to do so — see this great post from Alex Turnbull.

Vibe Coding is super useful because, with the help of an FDE team with a good business analyst, the end user organization can quickly create functional prototypes that demonstrate precisely what they are looking for, which are much more powerful functional specifications than traditional functional specification documents with text descriptions of required functionality and powerpoint mockups. Plus, these prototype specifications can be created in a fraction of the time. But that’s all they are, prototypes. Real applications still need to be built by real software engineering teams who can build optimized, bug-free, secure code — vs. unoptimized, buggy (especially at the boundaries), and insecure code regularly generated by AI-based vibe coding tools (where, depending on what source you access, 53% to 78% of code generated has serious security issues).

In other words, it’s a great article, from a customer-centric viewpoint and written for customer executives. From a back-end, provider perspective, it’s missing one key step — the development step that takes vibe coding prototypes and produces real (AI-backed) enterprise applications.

Moreover, it centralizes the FDE activities when, in reality, they are ongoing throughout the entire cycle.

  1. they activate, and put the foundation in place
  2. they train the users on how to properly use the LLMs for accelerated research and are always on call for help
  3. they maintain the orchestration layer, and improve (and correct) it as necessary
  4. they work with the end users to vibe code prototypes
  5. they work with the development team to build the next generation (or iteration) of the enterprise apps in the SaS model

In other words, AI can enhance SaS, but it cannot replace the need for skilled humans on the provider side (for development, implementation, maintenance, and improvement) or the buyer side (for process definition, improvement, decision criteria, etc.).

At the end of the day, AI can only replace bit-pushers who do tactical data processing tasks which should have been automated by machines 30 years ago (when it was promised), but it can’t replace anyone who needs to make a (strategic) decision. This is true regardless of the model, and the right model, like Phil’s SaS flywheel, actually exemplify the need for the right, skilled, talent.

STOP PAYING PROCURETECH/FINTECH ADVISORIES A DOLLAR JUST TO LOSE THREE DOLLARS!

Last week, in our post where we asked if ProcureTech Generated Billions While Practitioners Lost Trillions, we noted three things:

  1. Approximately 1.8 Trillion Dollars (more than the annual GDP of 92% of the countries on Earth) will be wasted this year on Tech-Related Spending
  2. Approximately 600 Billion Dollars will be spent with the big consultancies and analyst firms who do Financial (Technology) and Procurement (Technology) consulting and advisory
  3. That’s three dollars lost for every dollar spent on big consultancy and advisory firms

So how do you stem the bleeding? Especially if you can’t STOP spending mooney on tech advisory because you can’t stop spending money on technology because you can’t survive in today’s digital world without it?

You STOP forking over (high) six and seven figures without a guaranteed return! In other words, unless they save you some coin, then your money they will not purloin!

More specifically, if they are promising outcomes, then (the majority of) their compensation should be 100% dependent on outcomes. If you don’t make bank, then their compensation will tank.

To be even more precise, don’t buy:

  1. any technology platforms where the majority of compensation is tied to successful sourcing events, transactions, etc.
  2. any GPO services unless it’s 100% outcome oriented
  3. any functional outsourcing unless the majority of compensation is tied to ROI

Now, the technology providers and consultancies will push back, steadfastly claiming that their technology and services are worth way more than they are charging, but here’s how you counter:

  1. you will pay a base annual fee for the platform that will cover 150% of their base hosting costs, so they won’t lose, and then a percentage of transactions, identified savings through sourcing events, contract value, etc. where the percentage is calculated such that if you save 100% of their promised savings, they will make 50% more than what you would pay on a fixed cost after negotiation — if they are so confident in their claims, this should be a no-brainer
  2. you will pay a fixed amount on each transaction, calculated based upon the expected savings before you sign the contract, and if they can deliver the savings, you will definitely be using them regularly — and, as with the Tech Provider, you will calculate this so that they win bigger than if you pay them a fixed cost IF they generate a return for you
  3. you will pay a fixed rate per hour that is enough to cover the assigned personnel cost (their salary plus 30% overhead), and any compensation beyond that will be dependent on the department delivering an ROI beyond a certain amount (which is the amount required to cover the basic fee you are paying them); and again, you’ll fix the compensation such that if they deliver 100% or more of what they promise, they will win big too

Now, you’re probably saying the doctor is daft by telling you to offer them 50% more than what you’d have to pay on a fixed cost basis if they deliver, but here’s the reality, without incentive, THEY WILL NOT DELIVER!

There is an 88% technology failure rate across the board, and 94% failure rate if it’s a (Gen-) AI project. The reality is, as we pointed out in our series on how, even if they have good intentions in the beginning, your (technology) vendor will screw you, the vast majority of systems fail to deliver, because, once the contract is signed and you have access to the system, they have zero incentive to do anything else for you.

Similarly, once they have you on a multi-year contract, why should the GPO or consultancy have any incentive to go beyond the minimum? If you want them to continually serve you and look for ways to generate a return for you, make it worth their while. And then you won’t be paying them one dollar just to lose three dollars in return!

This is where you start. Then, you question any consulting contract over 100K to 200K as a mid-market and 1 Million as a large global enterprise. At that point you have to define the value you expect and what gain-share agreement you are going to craft to ensure it.

Does ProcureTech Generate Billions While Practitioners Lose Trillions?

A couple of weeks ago, THE REVELATOR, in his AI Whispering asked Why does the ProcureTech solution side of the table make billions, while the practitioner side loses trillions (and more)? And it’s a fair question. Because even though the practitioners don’t lose trillions on ProcureTech and ProcureTech consulting (as that’s only in the Billions), they DO lose Trillions on Tech and Tech Consulting that the ProcureTech Consulting and ProcureTech providers SHOULD be helping them save money on.

To be precise, at least 1.8 Trillion is going to be lost by Practitioners this year on Technology and Technology Consulting. Earlier this year, in our post on SaaS Spending, we predicted that at least 1.5 Trillion would be wasted based on total industry spend and an average waste of AT LEAST 30% (due to overspend, unused applications and project failure), but we are now revising that up to 1.8 Trillion based upon a minimum projected spend of 5.4 Trillion based on recent Gartner estimates.

To put this in perspective, only 15 countries have a GDP in excess of 1.8 Trillion! In other words, the total technology spend wasted is greater than the individual GDP of 92% of the countries on earth.

But it gets worse.

If you add up the global revenue of the 23 Big Consultancies, which you will be using for ProcureTech, FinTech, and related consulting, it comes to 551 Billion.

Accenture 65
Bain 7
BCG (Boston Consulting Group) 13
Capgemini 25
Cognizant 20
Deloitte 67
E&Y 51
Fujitsu 26
Genpact 5
HCL Technologies 14
Infosys 25
Kearney 2
KPMG 38
McKinsey 19
Mercer 2
NTT Data 30
Oliver Wyman 3
Publicis Sapient 18
PWC 55
Recruit 23
BAH (Booz Allen Hamilton) 1
Tata 31
Wipro 11

And if you add up the global revenues of the 9 big analyst firms, which you will be using for ProcureTech and Fintech advisory, it comes to 51.5 Billion.

Clarivate 0.5
Forrester 0.5
Gartner 6.5
Hackett 0.5
IDC 4.0
IQVIA 15.0
Kantar 3.5
Moodys 7.0
S&P 14.0

That’s a total of 602.5 Billion you’re spending for ProcureTech and FinTech consulting and advisory in return for a loss of roughly 1.8 Trillion!

In other words, for every dollar you spend, you lose three. That’s the reverse of the ROI you should be expecting. You should NOT be investing in Technology or Technology Consulting unless you will get a 3 to 1 return. But what you ARE doing is investing in Technology Consulting and Advisory for a 3 to 1 LOSS! That is the EXACT OPPOSITE of what you should be doing.

So what should you do? STOP!

Or, if you can’t stop, change the game. More to come …

What is a Strategic Supplier Relationship?

Simple question. Sophisticated answer.

This was posed by THE REVELATOR in a recent LinkedIn article referencing his recent post on Procurement Insights’ Influence on Walmart’s Supplier Management Transformation.

First of all, the supplier has to be strategic.

For it to be strategic, it should be a supplier that is strategically selected, strategically engaged, strategically developed, and strategically managed. The goal of all of this should be to identify, build, and maintain a stellar supplier, as per a series we did here on how do you identify a truly stellar supplier.

But it’s more than that. Because strategic is more than just identifying long-term aims and interests and the means of achieving them, it’s execution. And when two parties are involved, its execution on both sides.

This means that it’s also critical that you are a strategic customer for the supplier. And while it’s hard to completely define what that is, as every supplier could have their own definition, at a minimum, just like a supplier should be stellar for you, you should be a customer of choice for the supplier, a topic we’ve also covered in the past.

But that’s not enough, because you can classify a supplier who supplies high-volume components as strategic with stellar service based on a set of KPIs, and the supplier can classify you as strategic based upon spend threshold and the fact that you always pay your invoices on time, and there can be nothing strategic about the relationship.

Unless there is active collaboration, a mutual commitment to mutual development, a shared goal along strategic objectives, and trust, there is nothing strategic about it and the relationship will fall apart the minute a major disruption or event occurs such as a supply shortage two or more tiers down in the supply chain that forces a supplier to choose which customers get their orders and which don’t (because it cannot fulfill all its contracts due to a force majeure event), or a sudden bankruptcy from your customer that forces you to cancel a big order (which will result in them not bidding/accepting further business from you).

For a relationship to truly be strategic, there has to be regular communication and collaboration on the shared goal of supporting the upstream supply chain of your current and potential customers utilizing the same values (sustainability, quality, performance, etc.) and a commitment to work together to solve problems when the going gets unexpectedly (and almost catastrophically) tough. When there is a shortage of a critical material, you will get your supply first, or if that’s not possible, the supplier will work with you to design an alternative (that uses a different raw material) or find alternate sources. When your biggest customer goes belly-up bankrupt, you will work with them to find additional, substitute, business you can give them to maintain the relationship and the business until you find a replacement customer.

Strategic means dependable, and that the dependability is both ways.

Why Big Analyst and Big X Consultancies SUCK …

In a post on LinkedIn a while back, THE REVELATOR indicated that the real reason Gartner sucks (and that their stock dove 30%) is because, at the end of the day, they aren’t very good at tying advice to outcomes (and likely don’t even attempt to do it at all most of the time in ProcureTech). But in all fairness, that holds true of all the Big Analyst firms and Big X Consultancies. Also look at Forrester and IDC reports — it’s always the same old vendors or the hype of the day, whether or not that hype is delivering any value whatsoever. (And the answer is “very little” for intake and orchestration — because you can’t orchestrate an empty pit and if you attempt to orchestrate an elementary music class, be prepared for the migraine of your life — and essentially none for Gen-AI, with MIT pointing out that only 5% of deployments are delivering any value whatsoever.)

But it’s not just the Big X analyst firms. It’s the Big X consultancies as well! Now, I know you are saying “but surely they do better, they are consultants, they do projects, they have best practices, and they’re paid for results” and while that is all true,

  1. they’re not all experienced consultants (and the number of juniors on many projects is scary — I’ve heard too many stories about a PE firm trotting in a McKinsey or Accenture* after a big acquisition (because it’s their standard acquisition playbook) to optimize and rightsize operations who come in with a team of 20, of which only two actually provide value beyond what the company already knew. One of the biggest companies in our space literally marched them all out at the end of the day and told them NEVER to come back because when it came to ProcureTech expertise, they identified one individual (the project lead, who they’d likely never see again) who was sharp and got it and would definitely be able to add value if entrenched in their operation, one (his right hand man) who was smart, hardworking, and capable of learning fast and who might be able to add value, and 18 juniors who didn’t know anything that wasn’t in the 7 year old playbook on Procurement handed to them when they started, a playbook this company had rewrote multiple times over the years)
  2. they don’t all have deep relevant project experience in Procurement (or whatever business function you’re bringing them in for) in your Industry
  3. their “best practices” are super generic so they can be applied across the board, which means they are not tailored for your industry and definitely NOT tailored for you (so they are not best)
  4. and they are paid on promises of results, which sometimes don’t materialize

Just like I keep saying it’s not the analyst firm, it’s the analyst, it’s not the consulting firm, it’s the consultant, and the sad reality is that the bigger the firm, the smaller the percentage of senior experienced talent in that talent pool, as the best talent who don’t make partner (and then have to focus more on managing and selling than project delivery) are constantly recruited by clients, consultancies, and even tech companies or the ones able to go out and join/build niche consultancies. There ends up not being enough senior, experienced, talent to go around and you’re essentially playing the lottery that one of these resources will end up full time on your project.

Since these consultancies want to be outcome focussed, in an effort to do that with more junior people, what ends up happening is they end up writing the advisory playbooks as metric focussed — what percentage of spend is on personnel in a best in class, what percentage of spend is on tech in a best in class, and what is the typical breakdown of headcount and tech spend by module or platform. Then, they tell you:

  • your headcount spend is too low, so you need to go out and hire X people in Y roles because, well, metrics and statistics and that will help because of scripted reasons (more sourcing pros mean more events mean more savings, more supplier managers mean better quality, etc.)
  • your headcount spend is too high, so you need to fire X people in Y groups because they must be tripping over each other and/or bringing your profit margin down
  • you aren’t spending enough on tech, so go spend 10 Million on Gen-AI and that will automagically fix everything
  • you are spending too much on tech, so go out to bid for a new ERP, S2P suite, orchestration platform, etc. because you obviously didn’t go to market right when you bought your current tech

Not realizing that

  • the headcount needs differ in every industry AND every company
  • the tech needs differ by industry, company, and process
  • it’s not spend, it’s ROI per spend

and this means

  • you might only need one supplier data manager in commodity indirect because there’s always three more suppliers waiting to supply you the same thing
  • but you might need ten supplier relationship managers in direct, each managing a different supplier (pool) producing a different, custom, component for your advanced engineering or biomedical device
  • you might not need best in class optimization backed sourcing for indirect because automated auctions will get you market price every time
  • but you might need best in class optimization, analytics, and market should-cost modelling platforms to get a grip on your direct sourced custom designs
  • and sometimes spending more on headcount and tech than across-the-board “average” yields a significantly better return because your quality stays high, stockouts only occur during global disruptions, your data processing is 95% automated freeing your staff to focus on strategic issues, etc.

But what can we expect from fresh grads with little mentorship (who are rushed into Gen-AI “training”) who get all of their insights from these Big Analyst firms that

  • publish quadrants and waves that are completely unrelated to reality for the majority of companies with the same 10 to 20 large vendors every year that only work for select large enterprises (and the other 40 to 80 vendors continue to be completely ignored),
  • constantly push and promote context-free (Gen-)AI, despite one of these firms publishing a now buried/deleted study a few years ago that stated 85% of AI projects fail and the recent MIT study that tells us, no, in fact, 95% of these projects fail to deliver any value, and
  • unless you get one of the few analysts who actually gets it, employ playbook-based responses to inquiries that don’t have any context (because the analysts don’t have any time to create tailored recommendations to context because they spend too much time doing basic data collection where 80% of it could be captured in a survey monkey tool [or 95% by a well trained SLM {or, better yet, classical semantic tech with provable accuracy rates} that could map free text to standard process needs and vendor solution categories for easy verification and correction by a true human expert]).

The reality is that until

  • big analyst firms and big consultancies admit their flaws,
  • start tying actual outcomes to the standard projects/recommendations they made, and
  • start analyzing and using these results to tailor recommendations to their clients that have a good chance at actually delivering value

these firms, and their standard recommendations, are going to continue to suck and your chances of success are going to remain at 12% for standard projects and 5% for Gen-AI projects.

Sad, but true.

* not realizing that the reason the company was such an attractive acquisition target in FinTech/ProcureTech was because they already knew all the best practices that the big firms have in their playbooks and were employing them effectively; these Big X tend to do well on average companies that are not best in class or deep in modern process or technology