Daily Archives: April 7, 2023

In Source-to-Pay, How relevant is the Analyst Firm?

As a result of the M&A mania in the late teens (during the era of [mega] suite consolidation) and very early twenties (during the pandemic when all of the PE firms suddenly realized that e-Sourcing, e-Procurement and, most importantly, e-Payment solutions were critical [when no one could go into the office]), a lot of known smaller, and even mid-size, players were swallowed up, leaving a vacuum at the lower end of the market.

As a result, two things have happened:

* a slew of new players (run by leaders new to the market) have entered the market; and while most have very limited solution breadth or depth, their use of modern technology is plugging a hole and offering value out of the gate (especially to smaller companies with nothing)

* a lack of talent (which has also been swallowed up into larger companies) at the remaining offerings has resulted in many of the leaders in these companies coming from other areas of enterprise software

… and neither of these sets of players have a deep understanding of our market or the analyst firms in it and too often I’m hearing that part of the strategy is “get on the Gartner Map“, “get on the Forrester Map“, or “get on the Spend Matters Map“. And while the last map*0 is the map you definitely want to be on at some point (as it actually focusses on technology vs. a mix of soft vs. hard factors that make it hard to judge how technically relevant the solution on its own is for you), “getting on the map” isn’t a strategy.

As a corollary, I’m also hearing too often that a big part of the marketing strategy is to “get in front of the big analyst firms as fast as possible and, hopefully get written up“, and if there are analyst relations, all their time is focussed on these big firms. And that worries me. A lot!

Why? Because they think “the firm” is the answer, when, in fact, it’s not the firm but the analyst because “the firm” will only get it right IF the analyst gets it right. And at many of these firms, I’m more worried by the year if the analyst will get it at all. Why?

If we go back to Saturday’s post on AI: Applied Indirection, Artificial Idiocy, & Automated Incompetence, we have the dual problem that most of the solutions out there are claiming capabilities they don’t have and even most people in technology can’t judge whether or not the claims are real or fake, and this goes for analysts too. Especially new, junior, analysts without the right tech background, domain understanding, education*1 and experience in our space.

The reality is that we’ve went from the point where, in the beginning, to be a good analyst you needed to:

* understand the space
* understand the unique processes the technology has to support to serve the space
* understand the current breadth of offerings and capabilities across the vendor landscape

to where, to be a good analyst as technology progressed, you also needed to

* understand the different technology stacks and what they can, and cannot, offer
* understand the different technology options and what they can and cannot do (i.e. algorithms, workflows, etc.)
* understand the nuances of buyer needs across industries and niches (e.g. direct vs indirect, manufacturing vs. distribution, F&B vs CPG, etc.)

to today where, to be a good analyst, you also need to

* understand the different technologies that are used in ML/AI and what actually qualifies as ML/AI and what does not
* understand where advanced technologies, especially those based in ML/AI, are required, and where classic techniques will do just as well, or better
* understand the different levels of analytics, and whether a solution has real analytics, or just pre-packaged reporting
* understand how the different technologies on the market need to link together as we move from the world of suites to platforms

In other words, we’ve gone from the point where to be an analyst, in the beginning, you just needed:

* critical thinking skills
* a basic business understanding
* good writing skills

to where, as technology progressed, you also needed:

* a basic understanding of technology (2 years of computer science or equivalent STEM offering in engineering, physics, etc.) and scientific thinking
* a basic understanding of source-to-pay and related processes across industries and category uniqueness that may or may not dictate different needs
* a basic understanding of integration points to other enterprise systems
* a good domain understanding of the Sourcing/Procurement needs in modern multi-nationals

to where, looking at technology today, you also need:

* a deep understanding of math and analytics (and at least a Bachelor’s in a STEM area)
* a deep understanding of models and metrics and where, and how, all the different data sources integrate for risk, diversity, spend, and opportunity models
* a deep understanding of what’s needed for a modern data interchange, API integration, and procurement management platform
* a deep understanding of how procurement works with and supports supply chain, logistics, and finance and how the pieces support this
* a good bullsh!t detector and the ability to dive into claims that a company may want you to take without question and find out what really is there and what the claim really means
* at least a decade of experience on top of close to a decade of education (because if you’re not a genius, you probably need at least a Master’s or two Bachelor degrees to get all the background you need) to put it all together

But who has that anymore? And where are they?

To be continued … in Part II


*0 as of posting as those maps, V3, were designed as pure-tech [and the last iteration co-designed by the doctor]

*1 most programs, if they teach anything at all, teach classical operations management or logistics, neither of which is modern procurement or supply chain management, and definitely not advanced math or algorithms!