Artisanal vs. Mass-Produced: The Real Economics of a Boutique Data Consultancy

Not all consultancies are created equal. Think of it as artisanal versus mass-produced. While large firms churn out projects like a factory, boutique data consultancies craft solutions with care, expertise, and collaboration. In this article, we explore the real economics of a boutique consultancy.
Contents
Author
Svet is a seasoned technology leader with deep expertise in data strategy advisory and technical delivery management. With the background in investment banking and over a decade of experience on the professional services side, she has led complex data transformation programmes across a number of industries.
I’ve received quite a few comments and questions about the economics of running a boutique specialist consultancy after my very enjoyable chat with the one and only Joe Reis.
Answering those questions helped me find the perfect metaphor for how we operate versus how large and super-large consultancies typically do.
Think of it as artisanal versus mass-produced. Both exist and have a place in a modern economy, but they deliver value in very different ways.
As the CEO of a boutique data consultancy, I want to shed some light on why the economics of our model so often result in better value for clients, not just in terms of cost but also in impact, speed, and partnership quality.
The Artisanal Model
On the one hand, you are buying something created with lots of passion and expertise, tailored specifically to you and YOUR needs, built by people who take time to think things through properly and don’t cut corners. They take pride in their craft and are at the top of the league in their respective areas.
An important distinction is that you are buying directly from the craftsmen themselves. The operational and managerial layer in this type of company is typically very lean. In our case, about 70% of the price you pay represents the running costs of the team and can be traced directly to people’s salaries. That allows them to earn a decent living for themselves and their families, which in turn sustains the level of care and quality you receive as a client.
This is what a boutique data consultancy is built on: craftsmanship, care, and the kind of pride you only find when people truly love what they do.
The Mass-Produced Model
On the other hand, the large firm model is more like a factory or in the worst cases a sweat shop, where bottom line optimisation often takes priority over quality. Everyone is a cog in the machine, and every human relationship is a transaction.
In that setup, you buy from a corporation that owns many factories and relies on a heavy managerial and operational structure to keep it all together. It’s almost impossible to trace what proportion of your payment goes to the actual team doing the work. In organisations that are considered financially strong, it is rarely more than 20% once you remove the cost of partners, senior managers, and all the overhead that the team must carry.
This is the mass-produced model in consulting: efficient at scale, designed for output, not insight; profitable, but lacking soul.

Why the Economics Work This Way
A boutique data consultancy is built around focus and efficiency. It invests in humans with expertise, not bureaucracy. Every project team is assembled with intent, not assigned through an internal staffing algorithm.
This structure keeps overheads low and impact high. The money you invest flows directly to the people doing the thinking, analysing, designing, and delivering outcomes.
It’s a model that keeps people at the centre, where great work starts with genuine collaboration and care.
Closing Thoughts
You can draw your own conclusions about what type of arrangement is likely to deliver you a better value and experience.
I personally believe in the world where heart combined with skill is at the core of the business, as opposed being either an afterthought or non-existent, who is with me?
Author
Svet is a seasoned technology leader with deep expertise in data strategy advisory and technical delivery management. With the background in investment banking and over a decade of experience on the professional services side, she has led complex data transformation programmes across a number of industries.


