Never forget this!

(Click here to learn why DPGLabs.ai is best tool a VENDOR has to judge their perceived place in the ProcureTech market if that’s what you’re looking for.)

This rant is inspired by Dr. Elouise Epstein who, in this LinkedIn post, said the most wrong and dangerous thing she ever said. (And this SI article is an archive of my immediate rebuttal, found in this LinkedIn post.)

Saying that in “in the Age of AI, analysts are superfluous” is akin to saying that, “in the Age of the Internet, the Journalist is unnecessary” … and we all know how false that was, and still is. (Because the claim that the internet allowed everyone to be a journalist was not only far from the truth, but also ignored the fact that many people misuse the internet to spread rumours, conspiracy theories, and false facts that, when combined with FUD (fear, uncertainty, doubt), caused others to spread and amplify those same false facts. And if Gen-AI has proven one thing, it’s that it can spread and amplify falsehoods at the speed of light.)

(Now, this is assuming Dr. Epstein believes that an analyst does more than sticking random logos on a worthless map. But if that’s her definition of analyst, then maybe she’s right.)

There are multiple problems with her statement, and more problems than can fit in the 3K post character limit of LinkedIn, so we focussed on the biggies, as that should be more than enough to point out how Gen-AI has made the Analyst more critical, not less.

1) We are not in an age of true AI. We are in an age of hallucinatory Gen-AI.

This means that, even if all the data available is mostly correct, the AI can still get it wrong.

2) DPG Labs is NOT using evidence, they are using content from various URLs and weighting it (and, if the weighting is high enough, calling it evidence).

This means that if a vendor floods third party sites with unmarked advertorials filled with fake or misleading content, the vendor profile that Gen-AI creates is sure to be wrong.

3) Most vendors and customers blast success stories and hide failures.
(No one wants to admit they blew millions of dollars.)

These only come out in private conversations and the only “evidence” comes a few years when the customer switches to a different platform much sooner than the norm.

etc.

This means that no auto-generated profile can be considered reliable without human review. (And the odds of correctness range from 95%+ for the major vendors where there is lots of correct content to work on to 50%- for new vendors with little content or a lot of misleading/inaccurate content.)

But even if the profile is mostly right, tech cannot do the following:

4) Judge organizational fit.

That goes beyond a score. (That’s why Xavier Olivera and I designed the SpendMatters, now Hackett, Solution Map as a TechMap. We assessed what most organizations couldn’t, gave them average unbiased customer scores against that assessment, and let the organizations focus on what they could assess — their needs, the vendor’s culture, service, relationship approach, etc. — and not what a static map can’t do.)

5) Give you a true timeline and success rate.

Vendors over promise and under deliver, as they all assume perfect scenarios that never materialize. Dumb Gen-AI can just assess statements, not fact, and can’t understand what factors are involved in the 3 month best-case implementation, the typical 6 month implementation, and worst-case 12 month implementation for organizations of similar size, complexity, and geography in the vendor portfolio (where even the best case 3 month is still twice as long as what they promise).

6) Help you decide if you can trust the vendor.

This is probably the most important point. Do they have what they claim, can they deliver it, and are they committed to delivering it to you on time, schedule, and budget. And it’s not just their word, or a third party survey on a select customer sub-set, it’s based on realistic assessments of performance and the individuals assigned to your project.

etc.

That being said, DPGLabs.ai is the best tool a VENDOR has to judge their perceived place in the market.

It’s also the best foundation out there on which to build a true next-generation analyst offering. If this existed a decade ago, the efficiency gains it would have enabled would have allowed us to cover 80%+ of the vendors in depth at Spend Matters (vs 20%-) on Solution Map as it would have slashed our research and writing time^* and allowed us to focus on verification, gaps, and uniqueness.

I described why the offering is the best tool VENDORS have, as well as how it could be the best tool to build a new analyst offering in the comments (of the original post) in detail in this LinkedIn post, where I have included the content below for easy access.

But even though the offering has a lot of value, it’s still nowhere close to a replacement for a true analyst.

The true value of DPG Labs.

After 20 years as an analyst, I’ve learned a lot.

This includes the fact that a lot of vendors don’t know how to position themselves, and know even less about how they are positioned in the market.

To this day, I still see new vendors regularly misusing purchasing, procurement, and sourcing when describing their offerings and wondering why they aren’t showing up in the right lists, maps, or articles.

I see vendors over-focused on the hype-du-jour (AI, Agentic, Intake to / Orchestration, Analytics, etc.) who completely ignore descriptions of rock solid capabilities or unique offerings that would differentiate them from the 40 to 100 other offerings that sound almost the same. (See the SI Mega Map if you don’t believe how many competitors you really have! The 7EB V1 edition has 888 vendor logos.)

I see vendors who have no idea how the market, and more importantly, how the search engines / AI tools used by the market see and position them.

What David Bush and his team have built at DPG labs is the perfect answer to that. By correlating and cross-referencing to a common vocabulary all of the external data and coverage on you against a standard functional map definition (that captures the questions buyers are likely to ask), you can see which categories / verticals / etc. the market is putting you in and which vendors you are being put up against. If those aren’t the vendors you expect to / want to be put up against, this means one or more of the following is true:

• you’re not describing your offering appropriately
• the coverage you’re getting is not focussing on the key / unique / valuable aspects of your offering (and you have to change your analyst relations / marketing / partnership approach)
• you’re (trying to) compete in the wrong market

and you have rock solid proof you can take to the C-Suite that you need to market / sell / partner different if you want to succeed.

Up until now, analysts could only tell you this … and you/the C-Suite could ignore us (by claiming it was our opinion — which it was, but our expertise meant we were right the vast majority of the time). But this tool is essentially doing what pros using AI (enhanced) tools are doing to research you, and showing you where you stand.

It’s the one offering that I would have loved to create when I was at Spend Matters, but never could (because, even 3 years ago, the AI models just weren’t there to support it). And it’s the one tool you need the most. (Plus, market clarity will ensure you score better on the right maps since the analysts will have a better understanding of you before the first interaction, which will help them ask the right questions, focus the demos, and give you the right coverage.)

And even though you can use it to create a shortlist as a potential customer, you can’t use it for final selection. I explained why in this comment, where I also reiterated how great it would be as the foundation for a next-gen analyst firm. The core rationale is the following.

We have to remember:

1. publication is NOT evidence, it could be opinion
2. probabilistic assessment of language is not human assessment of language
3. news coverage is often still marketing, especially when it’s an advertorial or there is paid coverage
4. disgruntled customers can spread lies as well as truth
5. even “verified” sources can be hacked or altered or replaced on the internet
6. … and when (correct) coverage is insufficient, errors (and hallucinations) multiply in Gen-AI (frontier models)

Your (Gen-) AI tools don’t know any of this! Unless every profile you build is reviewed by an expert human AFTER an expert human review of the solution (i.e. a real analyst with real knowledge and experience), which DPGLabs is not doing (as they don’t have a real analyst team), you can’t be sure it’s accurate and not free of hallucinations.

P.S. This means the only profiles I’d trust on DPGLabs are the human reviewed profiles that Dr. Elouise Epstein reviewed, which would be the profiles of the vendors she knows well, and that’s a small minority!

^* Not that Gen-AI produces good content, but, as per above, when enough material exists, it can create great summaries that allow an analyst to get a reasonable expectation of a vendor offering before the demo, produce summaries for the vendor to self-correct, and produce the auto-gen fact sheets, allow the analyst to focus their efforts and writings on the true analysis, opinions, and insights that you really need.