It might not be the intent of the consultant or analyst who truly wants to help you, but this is what happens the vast majority of the time (and contributes to the 88% tech failure rate and 94% Gen-AI failure rate). There are a number of reasons for this.

From the consultancy side of the equation:

* Most Consultants are told to please clients and give the clients what they want.

The problem here is that clients don’t know what they want, because they don’t understand what they need. So when the client reps are asked they try to sound informed and recite long feature lists they believe that they are supposed to need based upon the most prevalent vendor marketing. The problem is that each of the client’s reps who are interviewed have different long feature lists that only partially overlap and when the consultants are done gathering requirements from the client, they have 500 feature requirements that result in a 600 question RFP that is totally meaningless as it’s functions, not features, that support processes, not tasks.

* Most Consultants are NOT experts on the tech or what’s available in the market.

When a consultancy is also an implementor and has vendor partnerships, their technology and market viewpoint is biased towards those vendors. There are two reasons for this:

1. that is what their consultancy spends the majority of their time supporting, so they don’t have wide experience (and they aren’t encouraged to get it)
2. they need to sell a certain amount of vendor partner products to maintain their gold/platinum/diamond standing, which means they are heavily incentivized to see one of their partner’s products as a solution to every problem

* Most Consultants usually start with the understanding of the problem you bring them without validating it’s the right one.

The only way to truly understand a client’s need is to start by undertaking a collaborative needs assessment based on a collaborative working session designed to get at the root issues the client is having, what processes they need, and where a technology-based solution should fit in the process. Without the right understanding of the core problem, the core processes required, and what type of solution they should be looking at — and why, the consultant is not going to ask the right questions, understand the reason for the “requirements” the client reps are bringing, and differentiate the requests on the right track (which need focussing) and the requests on the wrong track. This is one of the reasons we see so many RFPs with 500+ feature questions, because the clients don’t really understand the critical functions the client needs that should be focussed on.

From the analyst side of the equation:

* Most Analysts spend the majority of their time on the firm’s paying clients

They get minimal time with any non-clients, thanks to the sales gatekeepers who scare everyone away with the five to six figure sales pitches (that guarantee analyst time, research access, and at least one write-up which may or may not be behind a paywall) and thanks to their super busy schedule jam packed with “advisory” calls which usually boil down to “how good is this pricing or contract” or “which of the vendors on your map is best” and not “how do we go about identifying the right vendor with the right solution for us, which might not be on ANY of your maps”.

* Most Analysts base their recommendations off of where the vendor lands in a map, which is a flawed process

The big analyst firms produce quadrant maps that plot a vendor on two axes where one axis is something like “completeness of vision” or “strategy” and the other is “ability to execute” or “current offering”, where these axis are usually defined based on the mash-up of six to twelve scores where the majority are completely subjective on the part of the analyst scoring them. As a result, with the exception of the one analyst who took the vendor demos and did the review, they don’t really have any solid idea of why one vendor is really better than another, or where the biggest differences are. But most importantly, they have no insight into whether the vendor’s offering is best for you based on your needs because they not only have very limited ability to focus in on the dimensions of relevance to you, but very little depth in those dimensions to match to your specific needs.

Since the majority of consultants and analysts work at mid-size or larger Big X firms that have a lot of existing partnerships and vendor clients, that’s why you rarely get a good recommendation from a consultant or analyst, and why you end up being another casualty in the 88% failure rate (or the 94% failure rate if the recommendation involved Gen-AI).

The only real way to have a good chance of getting a good recommendation is to go with an independent consultant or small firm that has no vendor partnerships, no rigid maps, and no incentive to recommend one vendor over another. Because then there is no bias.

However, since you’re astute, you know this is only a baseline requirement. In addition to being independent (1), you also need a consultant and/or analyst with expertise and experience in the domain and the vendor landscape (2), and the knowledge of what process to follow and what questions to ask (3).

If you do a little bit of research (using your brain, not Gen-AI computed recommendations), you can easily find a lot of good consultants who satisfy the first and second requirements. The third requirement is the hard requirement to meet. Why? Most consultants don’t have a model and process backed methodology to do these types of engagements and rely entirely on past projects, so if your project isn’t similar to one they’ve done before, while they will truly be doing their best, they may not hit all the right points, especially if time (or budget) is tight. Your success is 100% dependent on their past experience, and you really have to vet well.

But if you can find a consultant or analyst who is backed up by a model-backed methodology with the right experience, your chances of success will flip from 12% to 88%, especially if that consultant also does project assurance. Because such a consultant or analyst, not biased to any solution, will use all of the knowledge and best practices learned by the firm in past projects (that were encoded into the model and methodology), greatly increasing the chance of a right recommendation for you. While success can NEVER be guaranteed (unlike failure), the chances can be exponentially increased. And that’s how you succeed in the real world in technology-based solution selection.