Karl Dixon, Consulting Director, reflects on 11 years of learnings at CVM People.

This year I’ve been with CVM People for 11 years. The longest I’ve spent with any company by at least x2. During that time, I’ve been lucky enough to learn a huge amount from people far smarter and more capable than I am.

Some of those lessons are around running a business – not very interesting to most readers, I’d imagine (not even really very interesting to me, to be honest). But others are about how people and organisations interact and react, and the common themes, gaps, and challenges which seem to persist over the years, in spite of a changing world, customer expectations, technology, etc.

Since I’m being strong-armed into writing this by Jennifer and our marketing team, let’s go with some from that second category.

One of the big things I’ve learned is the importance of instilling excitement and belief in people when delivering change. Fairly obvious – change won’t work if people aren’t bought into it, no kidding. But more specifically how to engender and maintain these emotions across a reasonably broad stakeholder group.

Some of the very best people at designing and delivering technical solutions – the kind of people who continuously blow my mind with how they think about and understand technical problems, and how they are able to bring these back to the specific needs of business users – are very much not the people I would put in front of those same users in order to make them believe in the outcome.

Building trust, getting to understand people’s personal motivations and concerns, understanding how to communicate change to them in a way that resonates, and creating a sense of credibility in the journey among peers – all of these have been critical in stopping heads from going down and doubt creeping at those inevitable points through change when things get a little bit sticky. This is even more true in situations where the prevailing narrative has been “x is not possible/won’t work for us/something we failed to deliver before”.

 

Talent management – from acquisition to retention – is probably the most important thing a company can get right…and yet so many fail.

For every instance we see of companies getting talent right, there are so many who get it wrong. From failing to understand and compensate for their weaknesses when trying to attract the right calibre of person into the organisation, to failing to develop individual contributor / technical excellence focused development and reward paths to incentivise and retain excellent people who lack the aptitudes or interest in progressing via people management focused roles.

Taking the time to really understand what kind of person performs well in your specific culture and functions is hard. Jenns and I have been trying to figure it out since we took over in 2021… I think we’d just about come to have a clear understanding of it toward the end of 2025.

Related to this, I’ve found that well aligned teams are very much more than the sum of their parts. This holds true even when – as with, say, our Resource Delivery team – each person within the team is responsible for their own outcomes and objectives. That’s not to say I don’t think our people are fantastic – they are – but they really bring out the best in each other and support each other.

 

About half of technology problems are actually process problems

This is something I’ve found that’s very common across organisations of all sizes – in fact, even though it’s easy to spot when looking at client operations from the outside, it’s thinking I still have to guard against slipping into when looking internally at CVM People’s own functions.

Particularly where a function relies on complex processes and systems, it can be common for people to focus on the systems, and their perceived limitations or issues, as a simpler, more tangible, and easier to quantify problem.

Too often I’ve seen this result in people coalescing around the belief that a platform change will solve problem it won’t – and functions walking into an outcome where they go from using 60% of one tool, to using 30% of a new tool, having spent a huge amount of time, money, and political capital to essentially end up finishing exactly where they started just… shinier.

Learning to start at the desired outcomes, and think in a more complete way, analysing both analytically – component by component along a process, and holistically – how everything within a system (people, processes, and platforms) interact and what emergent or unexpected properties or outcomes might arise has been has been enormously beneficial, and something I find I still have to work on to ensure I don’t slip back into older habits and overly simplified mental models.

That’s not to say, of course, that new tech can’t be a fantastic enabler of refined and improved processes, of course. Just the whole needs considering along with the parts.

 

Cool new toys ≠ better results

I feel like this is particularly pertinent right now (for obvious reasons), but it’s something that’s held true pretty consistently, I think. Every few years something comes along that generates a hundred thousand miles of hyperbolic frothing across LinkedIn and enormous quantities of cash and time plunged into adoption projects based on poorly understood solutions and sketchy business cases.

That’s not to say, of course, that we eschew new developments and improved tools – but we should absolutely beware of the relentless over-promising that takes place as standard. I’ve looked at various ‘AI powered’ tools for marketing, recruitment, etc. for the last 7-8 years, and by and large they were, frankly, pretty terrible* for a good while (especially the recruitment ones…). As soon as the core competencies improved, the scope of AI was expanded to include things like generative and now agentic, and again the level of sales bullshit accelerated away from the actual reality of the products** in terms of reliability, quality, accuracy, etc.

A similar case with the whole “big data” craze – many instances of companies binning off well understood and optimised DWHs for Hadoop (remember Hadoop?) lakes, sky rocketing cost and complexity which often never translated into significant operationalised improvements to analytics, targeting, etc.

Of course, in time, as understanding improves, the tech gets refined, and businesses are better able to ascertain the size of the prize in their specific instance, these tools find their places as valuable additions – but only when they are understood and measured as potential solutions to specific, well defined challenges, and not just grabbed at for their own sake.

*For clarity, I’m not talking about the machine learning capabilities of things like e.g. Pega here, well established and refined over decades.

** If you’ve not spent time flicking through the many Reddit threads of disenchanted, despondent developers working for various agentic AI vendors, despairing at the reality of their work, it’s enlightening.

 

Maintaining a work persona just doesn’t work for me

This is much more of a personal learning but – I joined CVM People at 26, I’m now 37, and as I’ve gotten old my patience for trying to project a vanilla / guarded / “business” version of myself has evaporated.

Life is too short and genuine connection between people too valuable a component for delivering impactful work.

I think this is just something that comes with time and confidence. A business persona is a handy defendable position to retreat to when you’re feeling a little out of your depth in your younger years. But I’ve found the ability to drop this and speak more openly and frankly with people to be hugely liberating and beneficial to relationships in general, and I think people also appreciate the fact that there’s no pretence or guardedness coming back at them – that, whether they agree or not, they’ll always get my honest thoughts and advice.

The only downside is the impact it sometimes has on Jennifer’s blood pressure when I’m on the wind up in the office – but that seems a small price to pay.

All of these things are always enshrouded in the particulars of a given organisation, of course – often making them hard to identify, or properly grasp, by the people in the thick of it. But so far they’ve been pretty much a constant throughout my career.

These are the patterns I keep coming back to, whether we’re shaping a team, assessing capability, or unpicking why a transformation is stalling. If you want a sounding board (or someone to call bullshit on the wrong problem), you know where we are.