The Grumpiest Cat Who Ever Lived

There’s something really powerful about a company’s name. Above everything, a name is the first thing you learn about them, but for most founders building new consultancies, creating an appropriate name (and brand) is almost an afterthought.

In my case, naming my company Superposition (and everything that has come after it) was no mistake, and it’s all thanks to my cat Molly.

About 18 months ago, I was still working for a boutique healthcare consultancy, trying to build an analytics practice from the ground up. One funny thing that happens when you’re a data & AI consultant in a shop that does many other things, though, is that your identity can somehow simultaneously be many things at once:

You’re not a data governance, architecture, engineering, or visualization, automation, or AI expert anymore. You’re the data or AI person.

To all non-data people, what you’re capable of doing is really in the eye of the beholder.

So any project that has the word “data” or anything near it becomes your territory (whether you like it or not), and in that company, that dynamic became so commonplace that a colleague and I used to joke that we were “Schroedinger’s Data Consultants”.

That is, until we got fired.

As a very classic type-A career Big 4 consultant, getting fired induces a weird sort of identity crisis that’s hard to describe. You’ve been a tryhard in advancing your career for so long that you feel discombobulated purely because you’ve been stopped in your tracks for (probably) the first time in your career. For me, though, it was sorely needed, because I was very burned out - even if I didn’t realize it.

This fact became very apparent, though, when at the same time this was all happening, Molly died.

Molly was my first pet - an extremely grumpy Birman cat my wife and I rescued a few years back (despite a lot of complaining about it on my end), who, beyond her many funny qualities, had a very distinctive feature: her quirky, deformed left ear.

Despite the fact that she wasn’t around us for very long, my wife and I became very attached to Molly, and her death was obviously a very introspective moment for both of us.

It was the first time in years that I had a chance to sit and reflect on everything going on in my life, and in that process, I came to the conclusion (slightly motivated by getting fired) that I needed to finally seek the dream I’d had for years and try to start my own business.

Because that business would become a Data & AI consultancy that serves other consultancies, I decided the most appropriate way to honor that was to name it Superposition (to honor the inside joke)

But most importantly, because in his famous experiment, Mr. Schrödinger illustrated the concept of Superposition with a cat in a box.

So, Molly suddenly became an internet star and forever a legend through our name and logo, as the proverbial cat in the box:

And the rest is history.

The point of explaining all this is to illustrate to you that a consultancy, at the end of the day, is the reflection of the people behind it.

Your experiences, your background, everything that makes you you. All of which is doubly true in the current state of our industry.

In recent years, it feels like consulting is going through an identity crisis. As AI tools become more prevalent, we often hear people say ridiculous things like “consulting is dead” on a daily basis.

And while that is certainly an exaggeration beyond compare, especially coming from people who don’t understand why others buy advisory services in the first place, what is true is that how we do our work is changing really fast.

Consultants are expected to be faster, cheaper, and more knowledgeable than ever.

Which means any consultancy (especially one that builds AI tools the data foundations behind them) needs to focus on what makes them different.

To compete, you can’t just “make data actionable” or “enable AI for the enterprise” - you need to be specific about who your service is for, why you’re the most qualified person to provide it, and what you have that literally no other consultant has.

You need to be the superhero of your own story, and you need to own it.

If you’re scaling your Data & AI consultancy and feeling stuck (especially from a go-to-market perspective), it’s likely because you can’t get out of your own way.

Building an effective consultancy requires understanding three things:

My work centers on creating a framework to arrive at this answer through a series of structured conversations that focus on defining your strengths as a consultant, the realities of the market you want to compete in, and what it means for you as your consultancy grows.

So that’s why I’m so passionate about discussing this topic in particular!

Check out this video where I talk to one of my recent clients, Jason Hart (the founder of Domain Methods), about the work we did together on that same topic, and stay tuned for a deep dive on this project in the coming weeks!

Scope creep is the natural predator of any consultancy.

A large part of the success of any consultant is their ability to deliver a project for a client, but also to do so in a way that remains consistent with the time and effort we estimate that it will take.

This is a recurring problem for consultancies big and small, but for boutique shops in particular, it can be almost existential.

It is definitely always important to keep our clients happy and to do our best to deliver what we were contracted to, but given that our time is our most precious resource as entrepreneurs, we founders of small consultancies need to be extra protective of what our clients ask for and, above all else, need to be extremely comfortable saying no to:

Or else you’ll end up like my friend Gritty here whenever your client asks for “just one more real quick thing”:

Most consultants know the classic Design Thinking technique, where we ask our stakeholders to think in terms of “How Might We” statements. In normal settings, this is a very effective way of generating ideas for new projects - especially where teams are stuck in defining a future roadmap.

In the AI world, though, this framework often creates more anxiety than clarity, unless you add one very key ingredient: The term.

The original formula for the framework is simple:
How Might We (action verb) + for (target audience) + so that (improved outcome).

Like, for example:

A strong idea on its own, that in an AI context takes a real pain point and generates a flood of really cool (and usually unfocused) solutions with no sense of what’s actually real.

That’s where defining the term for the idea will make a huge difference:
- Short (weeks-months): your quickest wins with existing data and minimal change
- Medium (months-years): which require process and infrastructure change
- Long (multiple years): interdependent transformational change across people, process AND technology.

That extra step matters because the AI implementation world isn’t held back by a lack of ideas, but rather by FOMO. If every AI idea matters the same, then no idea matters at all, and to combat that, we have to be honest with our clients about what it’s going to take to make it real.

When we do this right, we Data & AI consultants can turn a room of skeptics into stakeholders who actually understand what pain we’re solving, how AI will enable that, and what their next tactical step actually is.

So save this for your next AI ideation conversation with a client, and if you want to see it in action, I offer free demos of it in action here!

Next week we’ll be celebrating 🎉🥳 Superposition’s 1-Year Anniversary! 🎉🥳

It’ll be a very special edition of the newsletter where you can expect:

If you’ve brute-forced your boutique Data & AI consultancy and feel like you need an external perspective to get unstuck, I’m here to help!

Get in touch to learn more about how I enable Data & AI consultancies to sell, deliver and scale more effectively through my workshops. If you haven’t already, visit my:

and let’s chat more about where you’re struggling with your consultancy!

Otherwise, thank you so much for reading, and see you next week!

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