Category Archives: SaaS

Yes Mid-Markets, 120K is More Than Enough for Source-to-Pay!

the doctor is sure that by now you have certain (mega-)suite vendors whispering in your ear that you really need their full 1 Million+ (annual subscription) S2P solution to maximize efficiency and savings (and that the doctor was crazy*0 when he told you that you should be able to get a sufficient Source-to-Pay solution for 120K a year), which, while possibly true stated that way, you don’t need to spend nearly that much to maximize your ROI.

But how do you maximize ROI without necessarily maximizing savings and/or efficiency? Simple! The same way you optimize profit by optimizing COGS vs. increasing volume. Just like every $1 of savings goes straight to the bottom line vs only $0.10 of revenue, every dollar you don’t spend on a technology solution goes straight to the bottom line vs. only squeezing out an extra 1% on savings.*1

But the best way to see this is to, gasp, do some math! Let’s take three mid-markets at 250M, 500M, and 750M. We’ll use industry averages for COGS (with 33% salaries & contractors; 2% utilities; 5% rental; and 20% amortization/depreciation) and assume 40% external spend. Depending on the industry, external costs can go to 50% or more, but not much in the Mid-Market (MM). We’ll assume an average 5% savings potential and 80% spend addressability over 3 years (as some existing contracts will be long term and not addressable in the short term, and some tail spend will just be too small / one time to ever bother with). We’ll assume that a base solution can achieve 80% of that savings potential, or 4% over three years (if there is sufficient manpower to address all the relevant categories [semi]-strategically).

 

Size 250M 500M 750M
Addressability (80% of 40%) 80M 160M 240M
Savings Potential @ 4% 3.2M 6.4M 9.6M
3 Year Cost 360K 360K 360K
ROI 8.8 17.6 26.4
Savings Potential @ 5% 4M 8M 12M
3 Year Cost 3M 3M 3M
ROI 1.4 2.7 4.0

 

Now, what type of ROI would you like to see if you are a 250M MM? A 1.4X ROI or a 8.8X ROI? the doctor knows what type of ROI he’d like to see! Also, if the mega-suite provider cuts the price in half, it only doubles the ROI to 3.2X. Barely acceptable, and you need the manpower to identify the full savings potential and everything to go perfectly to realize it. (What’s the probability that this will hold true continuously for three [3] years? Zero Percent. 0%)

Unless you have a (very) large category over 10M (where the savings potential on that category is 500K), the reality is that the 80% solution you will get by an average across-the-board solution / self-assembled platform-powered BoB suite will provide you an ROI that far outshines what the oversized, overpriced solutions will do for you as a mid-sized business. (Those suites are only needed for 1B+ enterprises where there are 50M to 100M+ categories where an extra 1% makes a huge difference.)

the doctor loves sourcing optimization, but it typically won’t find that much savings beyond what you can find with good spend analysis on RFP data in a category < 5M. (It might take a few hours of spend analysis, but you will get 80% of the savings with intelligence. If the vendor includes an affordable optimization module (2K/month; likely with model size caps), then you should use it on every category, if just to get a baseline, as you will get a good ROI from the module with continuous use, but if they want 10K/month and you are a 250M business, you likely won’t get enough of a return, especially since most of your categories aren’t that large or complex. Note that if you are a 1B+ multi-national enterprise, the story is the exact opposite. You absolutely need it and in your well managed categories, you won’t identify enough savings without it.)

For most categories, all you need to do in sourcing is 3-5 bids, side by side unit cost and total landed cost (TLC) comparisons, supplier award selection with RFP (spend) analysis, contract cutting to capture the price, configured POs in the eProcurement system to capture the contracted price, and line-item match on the invoice to the PO to make sure you’re paying what you should be. This is two-decade old tech now, but more than sufficient, when properly implemented and enforced, to capture 80% of the “savings” (or cost avoidance) in a category. Procurement savings come more from the proper implementation of a process than from technology that enables that process. What technology does is make it easy to do the process efficiently and effectively because it can guide you through the process, prevent you from missing steps or making mistakes, provide you the insight you need to make the best decisions, and even train you on best practices you aren’t familiar with. And allow you to repeat the process many more times on many more categories in a much shorter timeframe than if you were trying to do it all by hand.

Plus, the technology will allow you to do more with less, so you can minimize the need to expand the Procurement team as the company grows. Remember, good people cost $$$. In fact, a fully burdened high-end resource will cost as much as you pay for the tech, if you are paying the right price. This means that the tech will not only provide you an ROI on measurable cost reductions, but a measurable cost avoidance as you grow as you will not need to add as many people to a Procurement department that will become more efficient over time (as more and more tactical tasks get automated, freeing up the team to focus on value-add tasks). (Remember, tech never replaces the people you need, it just makes them many times more efficient so that you only need one or two high performing individuals for a function vs ten for one that is poorly managed; allowing you to add those ten resources elsewhere to produce more product or grow the business further. However, remember that Procurement does more than one function, so you may still need those 10 people for contract management, supplier development, additional strategic sourcing events, etc. but you won’t need them processing paperwork.)

So don’t overpay for S2P tech. You absolutely need S2P tech, but overpriced tech won’t get you the ROI!

*0 they may be right, I may be crazy … but it just may be a lunatic you’re looking for …

*1 An extra savings of 10% on a maximum savings of 10% leads to a maximum additional savings of 1% overall on a single category. In inflationary times, which we are now back to, you’ll never find more than 10% slack in the TCO of any category. In fact, you’ll do good to find 5%, which means going from average capability to advanced capability will only shave an extra 0.5% off of the total category spend on average.

Don’t think that these inflationary times are going away anytime soon. Supply chains are at their shakiest thanks to both the pandemic and the repercussions thereof, the rapid increase in climate change which has led to a rapid increase in natural disasters, the increased geopolitical destabilization around the globe, and the rebelling workforce, many of whom have gone from living barely above the actual poverty line (relative to where they live) to below it. Now add that to the flat and recessionary economic conditions in most major GDP players, and we won’t be seeing good times ahead for quite a while.

Ignite Wants to Spark Your Sourcing Success with Actionable Analytics!

the doctor has written about many Spend Analysis vendors over the last decade*, including Ignite Procurement, which is one of the few newer vendors that he expected would soon breakout of their (Nordic) niche and start expanding, something which they are now starting to do having tripled their customer count in the last 6 months to over 200 customers.

The reason for this expectation? They earned their top right status in the Spend Matters Spend Analysis Solution Map when the (quadrant) maps still existed and the doctor was responsible for grading them as a Top 5 Best-of-Breed Mid-Market focussed Spend Analysis player located in Western Europe / the UK.

Founded by ex-BCG (Boston Consulting Group) consultants in 2017, with the first version of the platform launching in 2018, the key players not only have a firm understanding of spend analysis, but what analysis capabilities a customer needs to find their spend waste and their opportunities. Plus, they understood since day one that spend analysis in a vacuum is not that meaningful and is most meaningful in the context of negotiations, supplier management and development, contract obligation management, labour compliance and ESG reporting, for example. Negotiations work best when they are fact based, supplier development efforts are best focussed on those suppliers where improvements would result in considerable cost reductions or value generation, contracts are meaningless if not adhered to (and the resulting overspend completely unnecessary), labour violations in the supply chain can result in huge fines to your organization, and exceeding your carbon caps can be even more expensive (not to mention the fines if you don’t properly report). (And yes, this is a bit of foreshadowing.)

The core of the Ignite “Spend Management” solution is the analytics offering which, like most spend analysis solutions, has two core components:

1. Data Management

It’s very easy to get data into the Ignite Platform. In fact, it can be as easy as dragging-and-dropping a file onto the browser pane as Ignite allows you to define all of your taxonomies as well as your standard file format mappings to those taxonomies. It can then detect if the data is new, incremental, or updated and allow you to add, add only new records, update existing records, or even load the file into an entirely new cube.

When it comes to taxonomies, you can start with your own or built-in and then, during analysis, you can define and redefine taxonomies on the fly, with reclassification as simple as dragging-and-dropping. You can also define and update mapping rules quickly and easily as well, fixing errors or updating classifications as the need arises.

Data enrichment is easy-peasy compared to generic analytic platforms or suites as they support a number of financial metric, industry classification, currency exchanges, commodity intelligence, CO2 emission sources, and risk metric sources out of the box and provide a full integration platform with APIs, pre-built connectors, and timed data pulls (via SFTP, for example) for those who need custom integrations.

The platform also supports multiple tables and spend cubes and allows you to work on global tables and cubes or local tables and cubes for what-if analysis.

But most importantly, it’s one of the few best-of-breed platforms with a fully integrated visual data flow manager where you can define the entire loading, mapping, enrichment, classification, and automated analytics, reporting, and notification process, including automated supplier normalization.

2. Analytics

The Ignite Platform has just about everything you would expect from a modern analytics platform including arbitrary dimension selection, formula-based dimension derivation, easy (powerful metric based) filters, multiple chart and widget types, easy drill down, easy view/report modification, and ad-hoc analytics.

It also comes with a full suite of out-of-the-box analytics to help you identify potential savings opportunities through contracting (off-contract spend), renegotiation, supplier (re) negotiation, supplier benchmark improvements, spend consolidation, invoice management, payment term rationalization, price improvement, etc. Contract coverage, PO Coverage, key supplier coverage, and a suite of KPI reports are also available out-of-the-box (including a spend development dashboard that can go beyond just spend to impacting metrics such as OTD, quality incidents, etc. if you track the data in the supplier management module).

It’s ability to identify supplier-based (re)negotiation and development opportunities is extremely good and based on its proprietary Ignite Matrix that maps “share of wallet” vs EBIT Margin (which it calculates using mandatory government disclosures and integration with appropriate feeds, such as Enin in the Nordics, and appropriate adjustments) and scatter plots the results to help you quickly identify where your business is contributing to a supplier’s high profit margiin (and where the supplier has room to negotiate without jeopardizing its stability).

On top of this they have also built:

3. Supplier Management (Information / Performance / Risk / Compliance)

With its strong data management underpinnings, the Ignite Spend Management platform can store any all supplier related you wish to track and analyze, which not only allows deep spend-related insights by supplier, but performance and risk (metric) insight by supplier, with the ability to track and compare over time.

In addition to providing a full Supplier 360 view across all data captured in the platform, the Supplier Management capability includes standard campaign management where a buyer or supplier management can create questionnaires for supplier data augmentation and collection of relevant data and documents for supplier performance / risk / compliance management.

4. Contract Management (Governance)

Due to its strong data management underpinnings, the platform can also store all relevant contract meta-data in addition to the contract documents and allow users to manage, report on, and automatically annotate spend that is covered by a contract (as well as determine if it was billed, and paid, at the contracted rate using the appropriate payment terms). Also, as with most contract management plays, it can support tasks and alerts and the linking of contracts to tasks and alerts.

5. Scope 3 Management / Carbon Accounting

The best foundation for a carbon calculator / carbon reporting application is a true analytics platform that can support the definition of all of the appropriate Scope 1, 2, and 3 Categories of relevance to the organization and/or required by the appropriate authority to which reports must be made; the integration of data feeds to allow for the appropriate carbon emission calculations; the collection of actual data from suppliers that can supply it; the generation of the appropriate reports with the appropriate calculations for mandated reporting; and the tracking of changes over time. This is precisely what the Ignite Procurement platform supports.

The entire platform is easy to use and the UX is quite modern, but you don’t have to take our word for it — you can see a three minute demo on their webpage … just scroll down to the Meet Ignite Procurement section. So if you’re looking for an analytics platform that can provide you actionable spend insights on your contracts, suppliers, and ESG that you act on to reduce waste and increase value, you should make sure that Ignite Procurement is on your shortlist, especially if you are in its current target marketplace in the EU/UK.

* Not all on SI, many write-ups are on Spend Matters, behind the revised paywall.

Five Best Practices for Buyers (when searching for software solutions)

Building on our piece on five easy mistakes source to pay tech buyers can avoid, here’s a piece on five (5) best practices to get the buy right. We’re even throwing in a bonus practice since we dove deep into the critical sixth mistake most tech buyers make in source to pay (who need to realize that No Tech Should Be Forever).

#1 Understand your core pain points

Don’t buy based on hype, buy based on need. Any good salesperson can spin you a good yarn on how much that sourcing solution will save, how that SRM will get your suppliers in line, and how that tail-spend solution will prevent your spend from going into a tail-spin. But there’s no guarantees that any of those solutions will solve your current problems, which might require e-Procurement or Spend Analysis.

Review your source-to-pay processes and determine where your pain points are. Is it in quote collection or analysis? Adequate supplier discovery, identification, or certification? Contract negotiation, implementation, or obligation management? Purchase orders and approvals? Invoice verification and matching? Opportunity identification? Supplier proliferation? If you don’t know where the majority of time is being spent and how much of that time is fighting fires, doing unnecessary tactical work, or taking too long to do something that should be quick, then you’re letting someone else identify your problems, which might turnout to be problems relatively small in the grand scheme of things.

#2 Understand which pain points can be best alleviated with technology vs. those that can be best alleviated with process improvements.

Technology can’t solve all of your ills. (And it especially can’t solve all of your ills if it is based on Automated Idiocy. Remember, that’s what the “AI” they are selling you is.) It’s important that you understand what technology can and can’t do before you look for a solution. This will help you identify honest providers offering honest wares and vapourware vendors selling silicon snake oil.

Consider the above pain points. If it’s quote collection, a good RFP system will help. If it’s quote analysis, maybe, maybe not. It may be the complexity of the ask, and not the complexity of the process, that’s the problem. If it’s supplier discovery, you will likely need a discovery platform or a large supplier network; if it’s supplier identification, possibly just a better process of identifying which suppliers you’re already using who can solve a new problem for you. Supplier certification, that requires manual review and sometimes tech can’t help at all. When it comes to contract negotiation, while platforms can shuttle contract drafts back and forth, negotiation is between people. Implementation and obligation management, that’s the kicker, and more than what you can accomplish with just an electronic filing cabinet, which is what many “contract management” systems are. Purchase orders are as much a process problem as a technology problem, most AP systems can generate them. Approvals, process problem to identify it, but often a technology problem to ensure that the process is followed. Invoice verification — manual approval is required but m-way invoice matching can help with the process by identifying the corresponding purchase order, any payments made to date, any credits accrued to date, any approvals required, and so on. Opportunity identification? Well, all of the pain points you identified represent opportunities, but beyond that, you’ll likely need spend analysis. Supplier proliferation — that’s a process and management issue. All the SRM does is track the suppliers.

If you don’t understand what the pain points are that tech can actually solve, you’ll never select the right tech.

#3 Identify your top 3 pain points that can be addressed with technology and the corresponding source-to-pay module(s) you need to address those pain points.

Once you’ve identified the pain points, whittled down to the subset of pain points that can be best addressed by technology, and then identified the three (3) that will have the biggest impact if addressed, you can continue with your quest for tech.

#4 Compile an appropriate shortlist of vendors.

Once you know what you want to address with tech, and why, you can start the process of identifying an appropriate short-list of vendors. This is not just three to five vendor names given to you, or three to five vendor names that come up first in a Google search — it’s three to five vendors that are confirmed to offer a module that will address the same (sub)set of problems you are looking to address.

This is not three to five vendors that claim to offer the same technology, as many vendors will purposely use, and sometimes abuse, the same terminology in an effort to sell completely different products. For example, sourcing, procurement, and purchasing are sometimes used to mean the same thing by three vendors, and sometimes mean completely different things by three vendors. There are vendors that call their sourcing systems procurement, purchasing vendors which just offer catalogs, and so on. You have to research their offerings carefully to determine whether or not they truly offer a solution to what you are looking for.

#5 Determine what you need in a partner before you start evaluating vendors and the RFPs they submit.

You don’t just need a vendor that can provide technology, you need a vendor that can provide a solution and work with you, offering as little or as much as you need in the way of training, implementation, integration, and services. You need a venture that will match your culture, get along with your team and make sure you are successful with their product. You need to identify everything that makes a good vendor before you start the evaluation, otherwise you will grade just on the tech, and the tech is not enough. (It’s a necessary part of the solution, but not a sufficient part on its own.) All supply chain problems have a human element. Never forget that.

#6: Bonus Get help with the shortlist and the RFP.

If you’re not familiar with the technology, the vendors, or the terminology, it can be difficult to determine which vendors might actually be able to solve your problems and what vendors will just bamboozle you into thinking they can* when you send them the RFP. Get help from someone who is an expert in the technology, the vendors, and the true capabilities the vendors offer.

* Not necessarily on purpose; a misunderstanding caused by different usages of terminology (see point #4) can cause a vendor to believe they have the perfect solution for you.

Don’t Trust an Analyst Firm to Score UX and Implementation Time!

A post late last month on LinkedIn started off as follows:

“If you’ve ever read any research papers or solution maps on procurement tech, you’ve probably figured out a couple of things.

1. It’s confusing and overly complex
2. It doesn’t cover the basic, most obvious-of-the-obvious fundamentals that everyone needs to consider.

These are:

– User interface and user experience (UI/UX)
– Ease and speed of implementation

Why don’t they do this?

Honestly, I don’t know the answer.

The cynic in me says it’s because their biggest paymasters have a horrible UI/UX and require a very complex and lengthy implementation.”

This really bothered me, not because UX and implementation time aren’t super important, they are, and they are among the biggest determinants of adoption (which is critical to success), but because anyone would think an analyst firm should address this.

The reality is that no proper analyst will attempt to score these because they are completely subjective! As a result:

  1. There is no objective, function-based/capability-based scale that could be scored consistently by any knowledgeable analyst on the subject and
  2. What is a great experience to one person, with a certain expectation of tech based upon prior experience and knowledge of their function, can be complete CR@P to another person.

Now, some firms do bury such subjective evaluations on UX and implementation time in their 2*2s where they squish an average of 6 subjective ratings into a dimension, but that is why those maps are complete garbage! (See: Dear Analyst Firms: Please stop mangling maps, inventing award categories, and evaluating what you don’t understand!) So no self-respecting analyst should do it. As an example, one analyst might like solutions with absolute minimalist design, with everything hidden and everything automated against pre-built rules (that may, or may not, be right for your organization and may result in an automated sourcing solution placing a Million dollar order with payment up front for a significant early payment discount to a supplier that subsequently files for bankruptcy and doesn’t deliver your goods) while a second might like full user control through a multi-screen multi-step interface for what could be a one-screen and one-step function and a third might like to see as much capability and information as possible squished into every screen and long for the days of text-based green-screens where you weren’t distracted by graphics and animations and design. Each of these analyst would score the same UX completely different! On a 10 point scale, for a given UX design, three analysts in the same firm could give scores of 1, 5, and 10, averaged to 5 … and how is that useful? It’s not!

(And while analysts can define scales of maturity for the technology the UX is based on, just because a vendor is using the latest technology, that doesn’t mean their UX is any good. New technology can be just as horrendously misused as old technology.)

The same goes for implementation time. An analyst that mainly focuses on simple sourcing/procurement where you should just be able to flick a SaaS switch and go would think that an implementation time of more than a week is abysmal, but an analyst that primarily analyzes CLM and SMDM would call BS on anything less than six weeks and expect three months for an implementation time. This is because, for CLM, you have to find all the contracts, feed them in, run them through AI for automated meta-data extraction, do manual review, and set up new processes while for SMDM you have to integrate half a dozen systems, do data integrations, cleansing, and enrichment through cross-referencing with third party sources, create golden records, do manual spot-check reviews, and push the data back . Implementation time is dependent on the solution, the architecture, what it does, what data it needs, what systems it needs to be integrated with, what support there is for data extraction and loading in those legacy systems, etc. Implementation time needs to be judged against the minimum amount of time to do it effectively, which is also customer dependent. Expecting an analyst to understand all the potential client situations is ridiculous. Expecting them to craft an “average customer situation”, base an implementation time on this, and score a set of random vendors accordingly is even more ridiculous.

The factors ARE absolutely vital, but they need to be judged by the buying organization as part of the review cycle, AFTER they’ve verified that the vendor can offer a solution that will meet

  • their current, most pressing, needs as an organization,
  • their evolving needs as they will need to get other problems under control, and
  • do so with a solution that is technically sound and complete with respect to the two requirements above while also being capable of scaling up and evolving over time (as well as capable of being plugged into an appropriate platform-based ecosystem through a fully Open API).

A good analyst an guide you on ways to judge this and what you might want to consider, but that’s it … you have to be the final judge, not them.

That’s why, when the doctor co-designed Solution Map when he was a Consulting Analyst for Spend Matters, the Solution Map focussed on scoring the technological foundations, which could be judged on an objective scale based on the evolution of underlying technology over the past two-plus decades and/or the evolution of functionality to address a specific problem over the past two-plus decades. It’s up to you whether you like it or not, think the implementation time frames are good or not, believe the vendor is innovative or not, and are satisfied with the vendor size and maturity, not the analyst. Those are business viewpoints that are business dependent. Analysts should score capabilities and foundations, particularly where buyers are ill-equipped to do so (and this also means that analysts scoring technology MUST be trained technologists with a formal, educational, background in technology — computer science, engineering, etc. — and experience in Software Development or Implementation –and yes, the doctor realizes this is not always the case, and that’s probably why most of the analyst maps are squished dimensions across half-a-dozen subjective factors [as they are not capable of properly evaluating what they are claiming to be subject matter experts in; as a comparison, when you have a journalist or historian or accountant rating modern SaaS platforms that’s the equivalent of having a plumber certify your electrical wiring or a landscaper judging the strength of the framing in your new house — sure, they’re trade pros, but do you really want to judge their opinion that the wiring is NOT going to start an electrical fire and burn your house down or the frame is strong enough for the 3,000 pounds of appliances you intend to put on the 2nd floor? the doctor would hope not!).

The cynic might say they don’t want to embarrass their sponsors, but the realist will realize the analysts can’t effectively judge vendors on this and the smart analysts won’t even try (but will instead guide you on the factors you should consider and look for when evaluating potential solutions on the shortlist they can help you build by giving you a list of vendors that provide the right type of solution and are technically sound, vs. three random vendors from a Google search that don’t even offer the same type of solution).

Have the Analyst Firms Finally Admitted They Don’t Know What They’re Doing?

the doctor recently went on a big rant about the analyst firms and the utter lack of usefulness in the maps they release, the focus they put on what they don’t understand, and the award categories they invent because, even though they have/had some great talent (and should be doing incredible work), what they’ve publicly released has been mostly valueless to the market they’ve been trying to serve (when it wouldn’t be too hard to provide a lot of value based on all the research and work they do). In the doctor‘s view, this is very sad because if they could demonstrate the value they provide, they would be more relevant across the market (and likely get a lot more business from smaller and/or more innovative providers who think that, because of the budgets the big players like Oracle, SAP, and Coupa have, the analysts are always going to recommend those companies anyway).

However, now he’s gone from sad to mad about something he has just heard from a couple of vendors regarding one of the biggest firms, because, if true, it means not only do they not have a clue about what is and is not valuable in tech, but they are unnecessarily creating confusing and obfuscating technology that still may be best in class.

So what have they done now? Well, apparently they are now basing 30% of the score on whether or not the vendor has “AI” in their platform, something which they’ve repeatedly proven they have ZERO ability to score whatsoever! So, either a vendor makes false, grandiose claims (and tries to use Applied Indirection to fool the Analyst Idiot that they have more than Artificial Idiocy in their Application Implementation), or they get scored low even if they have the best technology built on best practices, proven algorithms, and consistent results that give their customers a 5X to 10X ROI.

True AI adds value, but, in the doctor‘s experience,

  • up to 80% of AI claims are Applied Indirection (at best) or Artificial Idiocy (at worst); in fact, some of the “AI” in spend analysis is still the “AI” they used in the early 2000s, and the doctor would rather not spell out that sad, but still true for some vendors, racial slur
  • up to 80% of the rest, or up to 16% of tech that claims AI, is level one Assistive Intelligence; and this is typically just classic RPA (Robotic Process Automation) using human-defined parameter-based rules, and the “AI” is the automatic parameter adjustment based on user overrides … not very intelligent, eh?
  • up to 80% of the rest, or up to 4% of the tech that claims AI, is level 2 Augmented Intelligence, which is the first level of AI where the tech can learn from human feedback and provide better insights and recommendations over time on one or more specific tasks, and the first level of AI that you should even consider as AI
  • up to 80% of the rest, up to 1% of the tech that claims AI, and the highest level modern technology has generally achieved, is level 3, Apperceptive Intelligence, or Cognitive Intelligence, where the systems can not only learn from specific human feedback to recommendations but from general knowledge and intelligence available to it from integrated data sources to mimic the performance of the best human experts over time, even evolving processes, behaviours, and actions within well-defined bounds
  • and then the rest, 0.1% or less, is nearing level 4, Autonomous Intelligence, where the system can learn, evolve, adapt, and maintain itself over time without human intervention … and hopefully execute meaningful, appropriate decisions grounded in best process and fact that considers all of the relevant information available (and not go off of the rails and advise you to commit suicide because you feel bad, Hail Hitler, or sacrifice a trolley full of people and a cross-walk full of pedestrians because there might be a cat in the road — all things AI has already done)

And even where a platform has semblances of real AI, chances are that the AI (the vendor is now forced to include or arbitrarily be relegated to the dustbin because, apparently, it’s not solutions but buzz-acronymns that matter now) is producing worst results than the best traditional algorithm or methodology on expert curated data sets and dimensions. For example, the vast majority of the market believes AI improves forecasting. It doesn’t. The best AI is still inferior to the best techniques developed in the 70s when applied to the right data dimensions. All the “AI”, which is just fancy, souped-up versions of classical machine learning (using algorithms developed in the 80s and 90s for which we didn’t have enough computing power until recently), does is run all of the data through a model that integrates classification with prediction to filter out the most relevant dimensions and the best curve fitting technique as all these algorithms, at the core, are based on 50+ year old statistics! This means that, at the end of the day, their best case performance is something a human genius figured out 50+ years ago.

But to achieve that best case, the developers have to implement the right AI algorithms, tune them properly, allow them to run long enough to correctly fit (but not over-fit) the training data sets, and monitor those algorithms over time … and to do that they need to be an expert in those algorithms, which they probably aren’t. So, in order to “check a box”, and sell you a product, they are ultimately integrating algorithms that will give you an inferior result (while requiring considerably more computing power that runs up your cloud utilization bill), versus sticking to tried-and-true algorithms and processes that their experts tweaked over years and that their experts can explain and verify at any time.

And this is an almost reasonable example of what a technology vendor might do (as the best predictive algorithms are not untested “AI” but based on classical, tried-and-true, statistical or optimization functions). Most of what the doctor has seen is MUCH worse than this. And the fact that some big analyst firms are now forcing vendors with good tech to integrate underdeveloped, unproven, and often untested AI just to get a rating, make a map, or be recommended is downright stupid.

SHAME ON ANY ANALYST FIRM THAT DOES THIS! Buzzwords are not products, and unproven tech is not value. Analysts should be recommending the best solutions, regarding of the tech they are based on. the doctor is simply appalled!