consulting is broken by its own incentives. here’s the model i’m betting on
— Written by Sonia Nash, Founder, NashMind Consulting Ltd. Put together into a podcast by NotebookLM.
For fifteen years I watched good companies buy transformation from people who had never delivered it. A finance team would sign a seven-figure engagement, and within a month the senior partner who sold the work had rotated off, replaced by a team of bright twenty-somethings learning the client's business on the client's budget. The deck was always polished. The outcome less so.
I don't say this to be cynical. I say it because I sat on both sides of that table: as the enterprise buying transformation, and later as the person accountable for delivering it. Most recently as Head of AI at SAP, and before that across finance and procurement transformation programs where the gap between what was promised and what actually shipped was impossible to ignore. That gap is why I started NashMind Consulting Ltd.
What I kept seeing
The traditional consultancy is a beautiful machine operated by many talented people, but it's optimised for the wrong thing. Its economics depend on leverage: a few senior names win the work, and a pyramid of junior staff delivers it by the hour. The more hours, the more revenue. The incentive to solve your problem quickly and cleanly runs directly against the incentive to keep the meter running. Once you've seen the pattern, you can't unsee it. A few examples of how it plays out:
The bait-and-switch on seniority. The senior who ran the pitch (incidentally the one whose track record convinced you to sign) is gone by week two. Their real job was to win the work, not do it. What you actually get is a team of sharp but green analysts, and you slowly realise you're paying premium rates to teach them your business. By the time they understand finance/procurement well enough to be useful, the engagement is ending, and that hard-won context walks out the door with them.
The recommendation that was decided before the analysis. I've watched "independent assessments" arrive at a conclusion that happened to match the platform the firm had a partnership with. Of course you need to look within existing products and partnerships during an assessment and solutions are often found there, but this is potentially reductive if the questions were framed to lead there. The client pay six figures to validate a decision the consulting firm had an incentive to reach anyway.
Scope that grows to fit the pyramid. A problem that one experienced person could scope in a week gets sized into a three-phase program, because a three-phase program is what keeps a team of eight billable. The finance team ends up with a transformation roadmap far larger than the problem it was meant to solve and the parts that mattered most get diluted across quarters of status meetings.
Slide decks that never survives contact with reality. The final deliverable is genuinely impressive: elegant, benchmarked, board-ready. And then it sits on a shelf, because no one on the team had ever actually run the migration, renegotiated the supplier contracts, or lived through the change management. They knew what good looked like. They'd just never had to build it.
Mix platform partnerships and billable-hour incentives to a delivery model designed around leverage, and biased advice becomes the default. Add to it advisors/consultants who have never spent a minute working in X department and who don’t know the realities and intricacies of the job they’re meant to assess and you have a recipe for solutions that optimise technology rather than the business. True impartiality is expensive, so most consulting firms quietly choose not to pay for it.
Don’t get me wrong, this is a structure that has worked in the past for many customers, particularly large enterprises who could afford it.
NashMind is my attempt to build the opposite structure; one that also works for mid-size companies.
What's actually different
Impartiality and honesty by design. I have no platform to sell and no upsell buried in the recommendation. I have worked with multiple platforms/products/vendors over 15 years and they all have their merits, strengths and weaknesses depending on what you’re trying to achieve. If the honest answer is "you don't need this," or "the tool you already own does 80% of this," that's the answer you'll get even when it costs me revenue. Why? because integrity matters to me.
Experience over slideware. Every recommendation comes from someone who has actually done the transformation, not just diagrammed it. Fifteen years in finance, procurement and IT, with the last stretch leading AI at enterprise scale means I've done the job and made the mistakes already. I know the pain of accruals and intercompany reconciliation. I’ve implemented AND ran full purchase to pay systems and teams at several companies. I’ve build AI tools and workflows that both worked and failed; I’ve been there. You're paying for judgment earned the hard way, not for a team learning your domain in real time.
Tailored, never templated. There's no copy and paste playbook I stamp onto every client. The whole point of deep experience is knowing which parts of the standard approach to throw away for your situation. That's slower to sell and harder to scale; but the outcome will be a lot more tangible for customers.
We don’t shy away from getting hands-on. Many consultancies prefer to stay “high-level”. Many don’t support the activities required as part of a transformation: user training, change management support including comms, the creation of assets to be used by the user population during and after any transformation project such as feedback loops, change requests and KPI monitoring, policies, training videos etc. These are very often the difference between a well received and well adopted tool and one that sits on the shelf.
Why now — consultancy in the age of AI
NashMind has been in the back of my mind for quite some time but timing is everything. AI is not just a new tool, it is a true disruptor in some industries. And tech consultancy is first in line to benefit (or suffer, depending on how you choose to look at it!).
The reality is that AI is collapsing the cost of delivering expertise. The work that used to justify a pyramid of analysts gathering data, drafting first-pass analysis, building the models, assembling the deck etc is becoming work that one experienced consultant plus the right tools can do faster and better. Historically, one senior expert, no matter how brilliant they were, simply could not process three million rows of fragmented vendor data, map out 200 separate procurement processes across 30 countries, and then synthesise it all into a coherent strategy. AI tools can reduce weeks of data processing and analysis into a few days, and therefore remove the need for an army of junior analysts.
I’d argue that time-based pricing is quietly becoming a penalty for efficiency. So now that AI can dismantle the traditional consultancy pyramid, how does the industry approach the selling of expertise?
McKinsey's internal AI tool now runs over half a million prompts a month, with consultants reporting up to 30% time savings on knowledge work. And when the work takes less time, there are fewer hours to bill which is why the industry is scrambling toward outcome-based pricing: roughly a quarter of McKinsey's fees are now outcome-based, BCG expects AI-tied revenue to reach 40% by 2026, and Accenture is exiting some 11,000 roles to sell guaranteed results instead of tracked time.
Which means the economic advantage of the big firm is eroding; a large junior headcount at the bottom versus a very small headcount of experts at the top. Experts who will not get their hands dirty. For decades, the answer to "why can't a single expert do this?" was capacity: one person couldn't process the volume. AI changes that math. A lean, senior, AI-augmented practice can now take on work that used to require a floor of junior consultants. So you’ll probably wonder… why having a consultancy at all if one of my resident expert can use a handful of AI tools?
I want to be careful not to oversell this. AI won't replace judgment, context, or accountability and those are the parts clients are actually paying for. A model can draft the analysis and crunch some numbers faster; but it can't sit across from your CFO and take responsibility for the recommendation. It can't tell you which battle inside your organisation is worth fighting this quarter. A finance professional could indeed come up with a great solution to a process bottleneck themselves; however, who is overseeing the risk, governance and compliance of tools used? The expertise still has to be real. What AI does is strip away the busywork that used to hide behind big teams and big fees, leaving only the part that was ever worth paying for.
That's the bet NashMind is built on: that in the age of AI, the winning consulting model is smaller, more senior, more honest, and more hands-on where it matters. Not larger.
Who this is for
NashMind is built for leaders navigating finance, procurement, and AI transformation who want a direct line to someone who has done the work: not a proposal, a pyramid, and a hope. It's for the CFO tired of being sold to by every vendor, the founder who needs a straight answer, the transformation lead who wants a partner rather than a vendor.
It's also not for everyone. If you want a hundred consultants on-site and a brand name on the invoice to defend the decision internally, I understand and I’ll happily tell you that it isn’t what we offer here at NashMind. And if you already know the answer you want and need someone to validate it, we may not be the right fit; impartial advice only helps the people who actually want it and we want the kind of open, bi-directional communication that will ultimately help you reach the best outcome for your organisation.
Where this goes
This is the first of what I intend to make a regular conversation about AI, transformation, and how the business of getting expert help is quietly being rewritten. Here on the blog, on Linkedin or in 3D via a good old in-person chat.
If any of this resonates, I'd welcome a conversation. Not a pitch; a conversation. That's usually the best way to find out whether there's something worth working on together.
— Sonia Nash, Founder, NashMind Consulting