Sunday, July 05, 2026

In a recent interview, Jeff Bezos — founder and long-time CEO of Amazon — made a point that has stuck with me. Everyone, he said, asks “what is changing in my industry?” But the far more interesting and useful question is “what will stay the same?” You can build a business around the answer to that.

Two things, in my experience, will never change. The first is that companies will always want to reach larger, often enterprise accounts for big-ticket purchases. The second is that success in that pursuit will always depend on finding curious people: the ones forever exploring new ways of doing things, adopting new technology, and adapting to a business world that refuses to sit still.

With that framing in mind, consider Account-Based Marketing. ABM has existed, in substance, since B2B selling began. But it has been through many permutations — and several name changes: from “Major Account Selling” in the 1950s, to “Target Account Marketing” (TAM) in the early 1990s, to the “Strategic Marketing to Named Accounts” that I was practising at Visual IQ and Zscaler through the 2010s. The label “Account-Based Marketing” only took hold around 2015, pioneered by Jon Miller, founder of Marketo and later Demandbase.

Whatever you call it, ABM is here to stay. The newest chapter in this long-running need — to penetrate enterprise businesses at many levels and across many parts of an organisation in order to secure large recurring deals — is the application of AI.

The AI inflection point

Next week I'll be attending a workshop with Demandbase built around exactly this question: how do we turbo-charge and extend an already strong understanding of ABM using AI? In my experience, AI can 10x — sometimes 100x — what you're already achieving in this realm. But the point is not that machines replace the craft; it's that they amplify it.

The AI revolution is about leveraging and accelerating the best of what humans can do — by teaching machines how to perform tasks, and then using AI as an “Iron Man” suit to accomplish our goals, together as one unit.

— Teresa Barreira, CMO at Publicis Sapient (and a fellow Northeastern University MBA alumna)

That is the right mental model. The judgement about which accounts matter, why they matter, and how to reach the humans inside them remains stubbornly human work. AI simply lets you do far more of it, far faster, and with far better signal.

This is not a new interest of mine. About two years ago, content strategist Damien Seaman and I convened a virtual roundtable with leaders across B2B SaaS — CMOs, heads of demand generation, and others — to examine how this account-based approach was proliferating. 

A year later, in August 2025, I worked alongside AI go-to-market experts like Jasper Ruijs (the organizer), including senior leaders from Adobe and Semrush, together with Clay and ABM specialists, to understand how AI was reshaping the way large B2B deals get done: “fishing with spears” — precise, one-to-one marketing — as opposed to the “fishing with nets” typical of smaller, more transactional B2B.

As with everything AI touches, ABM is moving fast. Rather like the Red Queen in Through the Looking-Glass, you have to keep running simply to stay in the same place. Getting ahead of the curve takes even more talent, open-minded thinking, momentum, organisational backing, and investment.

Two stories from the field

I fear I'm getting too technical, so let me set the acronyms aside and tell some stories instead — because the principles are best seen in practice.

Visual IQ: 50 accounts, a pair of binoculars, and a category-defining survey

When I joined Visual IQ in 2013, we had a crack team. On the sales side, most had been poached from Adobe by our Chief Revenue Officer, formerly head of sales at Omniture (which Adobe acquired). These were people with realms of experience closing multi-million-dollar-a-year accounts for digital marketing attribution with global names like TK Maxx, Walmart, Johnson & Johnson, Mastercard and P&G — where, incidentally, many of my fellow marketing MBAs had done their internships.

I learned an enormous amount about ABM from these people. At least once a week I'd sit down with a regional VP of marketing in the US, along with the VPs for Europe and APAC. We would draw up a list of the top 50 accounts they wanted to penetrate and debate the best way in: outbound calling? A physical promotion? An email campaign? LinkedIn InMail or sponsored content? Once the strategy was agreed, the hard, patient work of spear-fishing began.

The physical promotion is worth dwelling on, because it captures the essence of ABM better than any framework. Because we sold attribution — helping marketers see clearly — we had branded binoculars made, embossed with the Visual IQ logo, and sent them to the heads of marketing and digital at our 50 target accounts. In the US it did exceptionally well. The head of marketing at ESPN loved it, and it helped open the door to a roughly $1m deal. That is spear-fishing: a memorable, relevant, one-to-one gesture aimed at a named individual inside a named account.

Visual IQ also taught me the power of owning a category conversation. We published an annual State of Marketing Attribution survey report, built on the views of 500 CMOs. It generated a huge amount of SEO and some of the strongest leads we produced — because it made us the reference point for a question the whole market was asking. 

I've since replicated that playbook more than once, most memorably at a video-game advertising company where a segmented State of Video Game Advertising survey drew around 300 responses in what was essentially virgin territory, with tailored question sets for game companies, advertisers and agencies. The segmentation itself became a form of personalisation, and the response was excellent.

None of this was happening in a vacuum. The reason those spears landed was that the market already regarded Visual IQ as a leader. Forrester placed us in the Leaders quadrant of its Cross-Channel Attribution Wave — the analyst validation that made a cold outreach warm before a single word was exchanged.

The Forrester Wave™: Cross-Channel Attribution Vendors, Q2 2012 — Visual IQ positioned in the Leaders segment (Source: Forrester Research, Inc.).

What made the Visual IQ machine work was that ABM ran on two engines at once. The outbound engine penetrated named strategic accounts in defined regions; the inbound engine qualified the demand our category leadership and content were creating — web downloads, CMO reports, Forrester Wave enquiries, newsletter opens, referrals — and handed genuinely qualified opportunities to field sales. Marketing and sales weren't two departments lobbing work over a wall; they were one motion. I still have the pipeline reviews from that period, and the discipline is striking: strategic accounts analysed for why prior efforts had won or lost, contact reach expanded through ZoomInfo, Salesforce and LinkedIn, and bespoke material built for specific verticals and named targets — never generic blasts.

Zscaler: the free security audit, and the confidence to be expensive

Zscaler taught me the same lesson from a different angle. Our whole proposition was cyber security delivered from the cloud — breaking companies free from the tangle of on-premise security appliances. Once again, we started with the biggest game. We drew up a list of 50 companies we wanted to penetrate and offered each of them something substantial: a free consulting engagement in which we would go in, examine their security posture, find the weaknesses, and hand back a report.

That offer is expensive to fulfil. You cannot make it to 5,000 companies; you can barely make it to 50. Which is precisely why account selection mattered so much. We had to be genuinely confident that the accounts we approached were strong potential customers before we committed real consulting hours to them. Get the targeting wrong and you don't just waste money — you burn your best asset, your experts' time, on accounts that were never going to buy.

Here too, analyst standing did heavy lifting. When you walk into a global enterprise's CISO office offering to audit their defences, the first unspoken question is “why should we let you?” Being named a Leader by both Gartner and Forrester answered it before we did. Gartner's Magic Quadrant for Secure Web Gateways placed Zscaler firmly in the Leaders quadrant, alongside a very short list of credible names — and well ahead of the challengers and niche players.

Gartner Magic Quadrant, Secure Web Gateways, May 2015 — Zscaler positioned in the Leaders quadrant (Source: Gartner).

The through-line from Visual IQ to Zscaler is simple: in enterprise ABM, credibility is the spearhead. The binoculars, the free audit, the survey report — these are the shaft. But analyst recognition, category leadership and social proof are what let the spear actually penetrate. Both companies went on to strong exits — Zscaler to a landmark IPO, Visual IQ to acquisition by Nielsen — and in both cases the account-based motion was central to how the enterprise pipeline was built.

What the practitioners told us

I don't want to leave the impression that ABM is a solved problem, or that my own experience is the last word. It isn't. The roundtable Damien Seaman and I hosted brought together eight senior B2B marketers — from a cyber-security demand-gen lead to a portfolio CMO to a private-equity Chief Development Officer — and what struck me most was how early most organisations still are on this journey, and how mixed the results have been even for experienced hands. A few themes emerged that map almost exactly onto what I learned in the field a decade earlier.

Intent is the modern equivalent of my top-50 list

At Visual IQ and Zscaler we built our target lists from a blend of engagement data and, crucially, sales-team feedback — confirming that accounts which looked engaged were also accounts sales agreed were worth an opportunity. I've always liked the Bezos line that when the stories and the data disagree, trust the stories. 

John Blackmore, who leads demand generation at a cyber-security firm, described the modern, instrumented version of the same instinct: rather than cold-calling phone books, his team listens for intent signals — someone researching endpoint detection, or evaluating a competitor — and inserts itself only into conversations that are already live. In his words, intent now accounts directly for around a quarter of his pipeline and lifts the efficiency of his other tactics by 10–15%. Same philosophy as my top-50 list; far better sensors.

The tool is the assist, not the goal-scorer

The most quotable insight of the day was also the most important, and it validated something I'd seen go wrong more than once. John — a Canadian, so the metaphor is fitting — argued that ABM platforms like 6sense and Demandbase are not the killer app but the assist:

ABM is the assist. It's not necessarily the goal-scorer, but it sets up all your goal-scorers in a great way to put the puck in the net. It can improve the efficiency of every tactic by 10 to 20%. It's worth its weight in gold, even if it never delivers one sale for you.

— John Blackmore, Global Director of Demand Generation

I've lived the counter-example. At Tricentis, the team had the full Demandbase package — and left it on the shelf. Rocio Sasson, VP of Demand Generation at Checkmarx, described the same trap from her seven years using both 6sense and Demandbase: the platform is only as good as the cross-team effort behind it, and personalisation “takes a long time and still doesn't guarantee success.” A tool bought and un-used is worse than no tool at all, because it tells the organisation that ABM doesn't work when in fact ABM was never really tried.

ABM is really a sales-and-marketing alignment strategy in disguise

This, for me, is the deepest point — and it's the one my Visual IQ pipeline reviews prove out in retrospect. Every roundtable participant with real success traced it back to alignment. Blackmore holds two standing weekly meetings with two different sales teams purely to interrogate lead quality — are these good, do you like them, who do you actually want to talk to? 

He put it memorably: you're not buying 6sense; you're buying collegial alignment, and the tool is simply the expression of it. Rocio was blunt about the failure mode: however beautiful the asset, if sales won't work the leads, the whole effort collapses.

This reminds me of Jim Collins, of ‘Good to Great’ fame, made a similar point about using technology. Jim said that in his analysis of top performing companies, technology was not even in the top ten of most important factors driving their success. It was the utilisation of technology to enable other high performing functions (So just like Teresa Barreira, CMO of Publicis Sapient, points out in her ‘AI as Iron Man suit’ analogy).

John Blackmore’s point also matches my lived ABM experience exactly. I've produced thousands of leads that fell to the floor because sales wouldn't pick them up. The reverse — the two-engine Visual IQ motion where marketing qualified and sales closed as a single unit — is what actually produced million-dollar accounts. ABM, done properly, forces that alignment because the model simply cannot function without it.

Personalise the message, not just the list

Damien shared the campaign I still think is the gold standard of spear-fishing: a Canon campaign targeting C-suite executives at listed companies across six European countries. The team printed each target's annual report, found the passages where the company itself flagged document-management pain, and hand-wrote tailored messages on Post-it notes placed at exactly those pages — each package arriving under a cover letter from Canon's country head, peer to peer. 

The result was an 80% response rate across more than 100 accounts. The lesson isn't the Post-it notes; it's that the value proposition to different personas for the same product is genuinely different, and the personalisation has to reach the message, not just the mailing list.

There is far more in the full write-up — including a candid debate on whether LinkedIn produces real pipeline or only brand awareness, the mechanics of preferential paid-search bidding on target-account segments, and geo-fencing as an alternative to trade-show spend. I'd encourage anyone serious about ABM to read it in full: Account-BasedMarketing Roundtable — full write-up.

Where this leaves us

Put the field experience and the roundtable side by side and the pattern is hard to miss. The fundamentals of ABM have not changed in decades — pick the right named accounts, reach the right humans inside them with a message that speaks to their specific pain, and make marketing and sales a single motion rather than two teams. 

What has changed is the instrumentation. Where I once built a top-50 list from engagement data and a weekly conversation with a regional VP, today's intent platforms surface that signal continuously and at scale. And where personalising a hundred accounts once meant hand-writing Post-it notes, AI now makes genuine one-to-one relevance achievable across thousands of them.

That is the opportunity in front of us — and, per Blackmore's hockey metaphor, we are still in the early, high-advantage days of learning to use it well. Now we are also in the early stages of AI, and so those two nascent approaches are combining to produce an effect that is both hard to replicate, and potentially will provide a quantum leap in sales and marketing performance for those rare companies able to harness them both effectively.

So going back to that original Jeff Bezos point – what will stay the same in the next ten years, and what will change? What will stay the same is that there will always be a huge demand for clever, innovative new ways to penetrate large accounts, craft compelling personalised value propositions to those companies, and therefore to drive up B2B deal values.

What will change is that those most able to navigate the massive changes going on in the industry, and to capitalise on them, will increasingly influence the marketing strategy of those successful B2B companies.

Demandbase AI ABM Session next week

Demandbase is hosting an AI in ABM Essentials Certification workshop next week in London.

Details: You will learn practical AI strategies for modern Account-Based Marketing and Go-To-Market teams to prioritize accounts and interpret buying signals.

So I will report back – and either add to this blog post, or create a new one specifically on AI in ABM.

Monday, May 25, 2026

Cracking the UK Productivity Puzzle

My family and I just got back from a week in Greece. It’s a beautiful country with wonderful people. But more importantly, almost all that we have today sprang from that vibrant, innovative, intellectually brilliant culture – Democracy, Mathematics, the Sciences, Philosophy, the arts. 

Sure there are other cultures that have influenced the word a great deal from the Romans (though they stole a lot of their ideas from Greece too!), to ancient India, China, then later the French, German, Spanish, Portugese, Dutch and the British.

But the Greek culture has had a disproportionate impact on the world we live in today. My American wife, Catherine, often has quite a ‘new world' take on issues – On Greece, she also had a very thought-provoking insight; "it’s amazing that this country was the birthplace of so much that is exceptional in the modern world. Yet look at it today, mired in unemployment, poverty, and with a failing political and economic system".

And I got thinking – what caused that decline? I came to the conclusion that one powerful factor was declining productivity growth.

"Making the safe decision is the fastest way to become irrelevant."

Teresa Barreira, Global Chief Marketing and Communications Officer at Publicis Sapient, argues that growth comes from challenging the status quo: 

"Fortune favors the brave who are willing to disrupt, challenge, and change things. It applies to everyone and everything, from individuals to companies and brands." Teresa Barreira on LinkedIn

Countries need to keep innovating, taking risks (as in the quote above), challening the status quo, and improving, to maintain their economic strength. And without economic strength, no other can really persist. 

No country can afford to rest on its laurels, otherwise they risk going from being the Greece of the ancient world to the Greece of today (still beautiful but certainly no one would claim it is a global powerhouse).

Then I started to think about three countries that I am most intimately acquainted with – I have lived and worked extensively in all three countries. The Netherlands, where I was born, and the home of my mother. 

The UK where I was raised for much of my life, and where I went to school, and university. And finally, the USA, the country I moved to by choice – first, to study for an MBA, and then raising a family and working there, for ten years.

But my experiences are one part of the story only. I will rely on data to inform me as to my thesis on falling productivity. But there are other, rather wonderful reasons why comparing the UK to the Netherlands, and the USA can provide such powerful insights.

The USA has the most free market Economy of the three – the lowest taxes, the highest inequality (though the UK is getting closer), and the least protective legislation.

It varies from state to state though – Massachusetts, where I lived, is closer to the UK in workers protection. Whilst States like North Carolina, Florida, or Texas are truly the ‘wild west’ with very little in the way of workers rights, paid vacation, or maternity/paternity leave).

The Netherlands is at the other end of the spectrum politically, and socially. It is very hard to fire someone (as in France, or Germany). Workers are far more protected than in the UK. 

Dutch employees also work some of the shortest hours in the world: 27 hours a week in the Netherlands versus 36 in the USA and 31 in the UK.  https://worldpopulationreview.com/country-rankings/average-work-week-by-country  - as you can see one way thay achieve that is by being super-productive.

It’s hard to talk about large macro economic issues like productivity, or innovation, without veering into politics. When you start to talk about solutions to issues like low productivity growth, it’s almost impossible to do so without talking politics.

However, I am aiming to, as far as possible, avoid taking a political position. That is one of the reasons why I chose two countries with much differing political outlooks, to compare to the UK. I am far more interested in finding out what your views are on how to solve this problem than promoting my political outlook.

 

The Problem – low productivity growth in the UK over the last twenty years, which has been exacerbated by each crisis – from the 2008 financial crash, to Brexit, to the Covid pandemic. 

UK productivity, already struggling, has been hit by each crisis, and not recovered from them (in the way that the USA, has, for example). Why is that?

So I have two theories backed with extensive evidence, why the UK is underperforming both a more free market economy like the USA, as well as a more planned economy like the Netherlands. And one that is more of a conjecture, based on my personal experience and observations. However, I have provided some good data to support that theory as well. 

Lack of investment

My experience of working in the US and the Netherlands bears out the hard evidence, that business investment in the UK is very low and falling, and that this is a major factor in our poor productivity growth. 

I’m not just talking about investment in hardware, software or other work tools. There is very little on the job training in the UK, versus in the US, or the Netherlands.

The numbers behind that observation are stark:

Whole-economy investment in the UK was just 18.9% of GDP in 2025 — the lowest in the G7. The US sits at 21.6%. The Netherlands at 19.7%. 

A three-percentage-point gap against the US doesn’t sound like much. But sustained year after year for two decades, it compounds into a yawning chasm.

The Institute for Public Policy Research went further in their April 2026 analysis. They calculated a “capital gap” — how much less capital British workers have to work with compared to peer countries. 

The answer: British workers have 38% less capital per hour worked than the average of comparable economies. In manufacturing specifically, the gap rises to 47% — versus a peer set of the USA, Germany, France and the Netherlands

British factory workers are working with roughly half the machinery, equipment, robots and IT systems that their American, German, French and Dutch counterparts have. Of course they produce less per hour. They’re working with one hand tied behind their back. (IPPR press release, April 2026)


Somehow this fact made me come back to Greece again - They were using the state of the art equipment, three thousand years ago. But today, they sit significantly lower than any of the countries mentioned, including the UK (Greece is sub 18%, and they're more than half less productive than the Dutch or the Americans).

And it gets worse on intangibles. 

The US invests 6.7% of GDP per year in software, IP, data and organisational know-how. The UK invests just 4.2%. 

That gap is hugely significant because intangibles — software, design, brand value, training, R&D — are increasingly what drives productivity in a modern economy. 

The US has been quietly out-investing us in the very things that compound the fastest, and the gap is widening, not closing.

Then there’s the on-the-job training I mentioned. The hard numbers: British businesses spend roughly half the EU average per worker on training and development. 

Anecdotally, when I attended a US business school, half of the MBA part-time class were funded by their employer, and around a ten percent of the full time. 80% provide financial support to employees pursuing MBA programs specifically (Georgetown CEW / GMAC). In the UK, that would be unthinkable. 

And that, ultimately, is the point: if we invest less in our people, our tools, our skills and our future, we shouldn’t be surprised when productivity flatlines. One way to look at this problem, is that the countries that out-innovate us are simply out-investing us.

The Chartered Management Institute reports that around 82% of UK training spend is funded by employers themselves 

— and naturally, employers prioritise senior and professional roles, not the middle managers and frontline workers who actually run day-to-day operations. 

And that is born out anecdotally by myself. I got a tremendous amount of on-the-job training when I worked in the Netherlands, and in the USA. In the UK, I've had virtually zero.

The result is a workforce that doesn’t get developed beyond what each individual chooses to invest in themselves.

In the States, every employer I worked for had a real training budget — actual money set aside to develop me. In the UK, not so much.

Poor management

If I’m honest, this is the one that surprised me most when I started digging. I’d always vaguely assumed British management was a bit stuffy but basically fine. It turns out, it isn’t.

There’s a serious field of academic work measuring management quality across countries, called the World Management Survey. It’s been running since 2002, led by Nick Bloom (Stanford), John Van Reenen (LSE/MIT), and Raffaella Sadun (Harvard). 

They’ve trained interviewers to score firms across 18 management practices — things like target-setting, monitoring, talent development, and how firms deal with poor performers — using structured interviews with middle managers. They’ve now covered around 13,000 firms in 35 countries.

The results aren’t kind to us.

The US comes in first. Then Japan, Germany, Sweden and Canada. The Netherlands ranks sixth, at 3.04 out of 5. The UK ranks seventh, at 2.95. The gap to the Netherlands is small. 

The gap to the US is roughly half a standard deviation — which sounds technical, but Andy Haldane (then chief economist at the Bank of England) translated it in a memorable 2018 speech, “The UK’s Productivity Problem: Hub No Spokes.” 

UK management practices, he said, are about half a standard deviation lower than comparator countries, and these management skills are statistically significant determinants of productivity.

But here’s what really matters: the headline average understates the problem.

Haldane showed that the UK has TWICE the share of firms with low management scores compared to the US and Germany. 

We have plenty of world-class firms at the frontier — but a long, fat tail of badly-managed companies that other countries simply don’t have to anything like the same extent. 


And that tail has been growing. Between 1997 and 2023, the number of UK firms below the 25th productivity percentile nearly doubled, from around 444,500 to 873,000.

Why? My theory — and this is where it gets uncomfortable — is that we’ve created a class of “accidental managers.” The Chartered Management Institute estimated in 2023 that 82% of UK managers had no formal training before being put in charge of people. In 2019 the figure was 68%. So it’s getting worse, not better. 

The downstream economic effects are brutal. A UK SME generates roughly £147,000 of output per worker per year. A German SME generates £335,000. That’s more than double. 

A UK business with ten employees could theoretically add £1.9 million in annual turnover if it operated at German productivity levels. Now think about how many small British firms are scraping by, when with better management they’d be thriving.

How much of the international productivity gap does management actually explain? 

Bloom and colleagues estimated in 2016 that management practices account for roughly a third of the productivity gap between the US and other countries.

Management isn’t a soft factor. It’s a major component of why the UK is falling behind.

When I worked in the US, most of my managers had been trained — through MBAs, or rotational programmes, or formal leadership development.The Netherlands has also has built-in formalised training for all employee levels.

Lack of cognitive diversity

Scott Page (Michigan, complex systems) published the foundational paper with Lu Hong in PNAS in 2004 showing, with proofs, that a randomly-selected group of diverse problem-solvers outperforms a group composed of the highest-ability individual solvers, on sufficiently complex tasks

Page shows that various types of cognitive diversity — differences in how people perceive, encode, analyze, and organize the same information and experiences — are linked to better outcomes. https://www.pnas.org/doi/10.1073/pnas.0403723101

My experience working in both the USA and the Netherlands is that neither country treats conventional wisdom as sacred.

In America especially, the belief that one person with a better idea can overturn the status quo sits at the heart of the culture. 

From the revolution against King George III to Moneyball, where a young economist transformed baseball by ignoring decades of accepted thinking, Americans have long admired people who challenge established assumptions.

That culture doesn't just produce entrepreneurs and innovators. It creates an environment where different viewpoints are encouraged, disagreement is accepted, and new ideas are more likely to emerge.


Interestingly, the Netherlands, despite its many differences, resembles the USA in one important way: everyone speaks up. In a meeting, every Dutch colleague will offer their view, and no one assumes their opinion matters less because of rank or title.

The Dutch and Americans also share a striking directness, especially compared with the famously oblique British style.

Their meetings can feel blunt, even bruising, but they’re rarely short on ideas. Admittedly of the two, Americans get things done the fastest. The Dutch rely heavily on decision by committee, which can slow decisions down a lot. 
            
By contrast, the UK’s hesitancy sometimes feels cultural, a mix of deep-rooted elitism, and an over-reliance on conventional wisdom. It’s a tendency that thinkers from Napoleon to, more recently, Elon Musk have warned against.

Friday, March 06, 2026

Why CRM Systems Drift Into Disorder

Understanding CRM Data Entropy in Complex Systems

“These systems were working fine a few months ago. Why are they going wrong?”

This question is common in any organisation running large, interconnected data systems. At first glance, it seems reasonable: if a platform functioned well before, why not now?

But CRM and marketing systems are not like cars—you can’t simply “service, refuel, and go.” Their behaviour is closer to that of ecosystems than that of machines.

Why Systems Decay

A key distinction with CRM platforms is that they are not purely technical. They are socio-technical systems: a fusion of software, integrations, workflows, incentives, and—most unpredictably—human behaviour.

The Gremlins Metaphor

Engineers in WWII jokingly blamed mysterious aircraft malfunctions on “gremlins.”
It was a way to acknowledge that complex systems fail for reasons that aren’t immediately obvious and often emerge from subtle interactions. Crucially, it also bolstered morale by avoiding blaming any one individual for the failure.

CRM systems behave similarly. It’s rarely “one big issue.” It’s the quiet accumulation of tiny mismatches, workarounds, and human shortcuts.

Was It Ever Truly “Working Fine”?

A system that appears stable may in fact be held together by ad-hoc patches, legacy logic, or assumptions that only worked under lighter data loads.

Like a bridge that seems sturdy—but once traffic increases, stress fractures emerge.

        

We have this exact same issue around the corner from my house, at Hammersmith Bridge, London - closed to all traffic except pedestrians and cyclists for the last seven years for these very reasons.

Initially, the bridge was strong. But as traffic increased, small structural weaknesses began to show — bolts loosened, joints flexed, stress fractures appeared. This important connecting bridge in the UK has not functioned for seven years now. 

The Role of Entropy

The second law of thermodynamics states that systems tend toward disorder unless energy is continually applied to maintain structure.

CRM ecosystems follow the same principle. Even if perfectly configured on day one (they never are), entropy creeps in through:

  • Human behaviour
  • System complexity
  • Time

These forces push the system toward disorder unless actively countered.

The Beehive Model: When Systems Work

A healthy beehive functions because:

  • Roles are clear
  • Communication is consistent
  • Inputs are reliable
  • Activity flows are coordinated

In CRM terms:

  • Leads flow correctly
  • Fields are completed consistently
  • Deals follow standard paths
  • Dashboards reflect reality

Information moves cleanly through the “colony.”

When the Hive Breaks Down

Entropy emerges through small, seemingly harmless actions:

  • Required fields skipped
  • Inconsistent tracking parameters
  • Manual deal creation
  • Logic edited without documentation
  • Data duplicated
  • Attribution overwritten

Individually trivial.
Collectively destabilising.

This mirrors research across socio-technical systems: micro-errors compound in non-linear ways, producing instability that no single actor intended.

Complexity Magnifies Entropy

Modern revenue stacks include:

  • CRM platforms
  • Marketing automation
  • Intent data systems
  • BI tools
  • Sales engagement platforms

Every integration introduces risk:

  • ID mismatches
  • Sync failures
  • Schema drift
  • Conflicting definitions

The more integrated the ecosystem, the faster entropy accelerates.

Time as a Force of Disorder

Even without major changes:

  • Definitions evolve
  • Teams rotate
  • New fields accumulate
  • Legacy data lingers
  • Integrations layer on top of integrations

The result is gradual “data model drift”—the system you have is no longer the one originally designed.

Below: Dashboard of a Lockheed Martin F-35 Lightning II fighter jet 

Dashboards Are Instruments, Not Reality

A dashboard is to a business what cockpit instruments are to a pilot: essential, but only a representation of reality—not reality itself.

The dashboard provides important signals such as altitude, speed, heading, but it is not the sky, the weather, or the terrain itself. 

Instruments must be monitored, calibrated, questioned, and cross-checked. No pilot assumes the sky looks exactly like the dial.

Dashboards can provide powerful insights, but they should never be treated as the entire picture of what is happening in the business. 

And just as in aviation, the most effective organisations combine instrument readings with context, culture, and human insight to understand what is really happening.

The same principle applies in organisations. Leaders evaluating CRM outputs should adopt a similar mindset.

The Core Insight

CRM systems are not static assets.
They are living organisms that require constant:

  • Maintenance
  • Alignment
  • Definition clarity
  • Human behavioural guidance
  • Technical calibration

Without active energy input, the system naturally drifts toward disorder—data entropy is not a failure of people or platforms, but an expected property of complex socio-technical systems.

The Reality for Leaders

Managing these systems requires constant vigilance, thought, testing, imagination, planning, and long-term strategy, just as the rest of the business does.

Below: Solving Data Disorder, Managing Organisational Culture

Because left unattended, complex systems drift toward disorder. 

How you manage this complex system will depend a lot on your 'problem-solving culture'. If you look at the matrix above, and according to Jim Collins, author of 'Good to Great', only about 5% of organisations sit in the ideal top right-hand quadrant. 

But essentially, CRM/Marketing Automation/Analytics systems are no exception to the second law of thermodynamics - they drift into disorder, naturally. 

Like any complex system built on human inputs, software integrations, and evolving processes, they naturally accumulate entropy over time.

Which means the question is never whether disorder will appear. That is a given.

The real question is who is paying attention when it does. A Strong culture with psychological safety, populated by teams with diverse cognitive styles, will solve these issues faster and more effectively than others. 

Saturday, January 31, 2026

The Real Edge of Private Equity: Active Ownership

I’m a big fan of Scandinavian thrillers, especially the original The Girl with the Dragon Tattoo. So when I walked into the auditorium at the London School of Economics, I had the strange feeling I was looking down at three lead actors from a Nordic noir drama.

The speakers were Ulf Axelson, Professor of Finance and Private Equity at LSE; Per Strömberg, Professor of Finance at Stockholm School of Economics and LSE; and Kurt Björklund, Founder and Executive Chairman of Permira, with roughly $50bn under management.


What followed was one of the clearest, data-driven explanations I’ve heard of why private equity (PE) ownership so often outperforms public equity, and where its limits lie.

Why Private Equity Outperforms: Start with the Data

The first half of the lecture was led by Per Strömberg and focused squarely on the evidence. Rather than starting with anecdotes or ideology, he began with productivity data across countries and firms.

In Germany, for example, fewer than 1% of firms accounted for roughly 65% of positive productivity growth over the period studied. Most firms contribute little. Some actively destroy value.

This matters because private equity does not rely on averages. Its entire model is built around identifying, creating, and scaling outliers.

       

The Mechanism: How PE Actually Creates Value

Strömberg argued that the performance gap between PE-owned and publicly listed companies is not primarily due to regulatory arbitrage or tax advantages, though those exist at the margin.

The core driver is active ownership.

Drawing on both academic literature and operating evidence, PE value creation can be grouped into three broad mechanisms:

1. Governance engineering

PE owners are not distant shareholders. They:

  • Sit on boards
  • Hire and fire management
  • Set incentives tightly linked to value creation
  • Intervene early when performance slips

This sharply reduces classic agency problems between owners and executives.

During my MBA at Northeastern, one of my finance professors specialised in corporate governance, and I conducted research on shareholder activism. One theme emerged repeatedly: public-company executives often optimise for personal incentives that diverge from shareholder value.

Below: PE-owned companies are rigorous in selecting customers that add value

PE ownership compresses that gap. In the same way that active shareholders hold senior leadership to account, Private Equity owners can step in to ensure the company is run as efficiently as possible. 

Per explained that the productivity and efficiency gains of Private Equity ownership (according to him, 2-3% higher than Public Equity, according to Kurt, head of a PE firm, it is closer to 6-7% higher), can be divided into three key categories:

Three types of engineering/tools

1. Governance engineering – being an active owner of the company

2 . Financial engineering – reduce cost of capital 

3. Become sector experts – can leverage networks to assist management

Well, that begs the question – why don’t other companies copy the behaviour of PE companies, to improve their performance?

According to Strömberg, this opens a “can of worms”.

First, PE performance may not be indefinitely sustainable. Funds have finite holding periods, typically six to seven years. Active ownership delivers diminishing returns once the biggest inefficiencies are removed.

However, within that limited time frame, PE seems to be doing better than ever. Exit value experienced a rebound in 2025, increasing 41 per cent to $1.3 trillion, the second-highest year on record. 

Second, PE capital is more expensive. While leverage can be cheaper than equity, the cost of financial distress rises sharply as leverage increases.

PE is not a universal solvent. It is a precision tool, effective under specific conditions.

An Operator’s Perspective: Kurt Björklund of Permira

The second half of the session (unrecorded) shifted from data to practice. Kurt Björklund described himself not as a financier, but as a “financial entrepreneur” and "Sector disrupter".

His framing was revealing.

Public equity investors, he argued, suffer from information asymmetry. Even large shareholders rely on periodic disclosures and carefully curated narratives.

PE ownership, by contrast, is built on information abundance:

  • Proprietary KPIs
  • Weekly operational interaction
  • Direct access to management and systems

Björklund was blunt: unlike asset managers such as BlackRock, he cannot afford to be wrong. Every investment must succeed. That forces extraordinary diligence and relentless focus post-acquisition.

He also warned about classic PE pitfalls:

  • Buyer’s curse in auction processes
  • Cyclicality of capital markets
  • The temptation to “take your eye off the ball” during exit processes

“In my business,” he said, “only the paranoid survive.”

Disruption, People, and the Role of AI

One of the most charged parts of the discussion came during the Q&A, where students (from the LSE, Imperial, Oxford, and Berkeley, USA) repeatedly asked about AI and job security. There were also several questions from analysts at various Private Equity firms.

Björklund acknowledged the anxiety, but did little to soothe it.

He described investments in complex B2B businesses where agentic AI, and improved automation have reduced headcount by orders of magnitude, particularly in areas such as KYC and compliance.

In one example, automation reduced a team from 5,000 people to 500, while increasing profitability. Many in the organisation were conducting relatively complex tasks, which could nevertheless be performed more effectively with AI and Automation.


Above - Top Target Universities (non-US) for Goldman Sachs. Source: Krugman Insights

His view was unsentimental: there will always be jobs for the very best, and the traditional path: An elite education, a top investment bank such as Goldman Sachs, and then a good Private Equity firm, remains viable. But the middle is being hollowed out.

Interestingly, he noted that older employees often adopt AI more effectively than younger ones, attributing this to psychological barriers to AI in younger workers. 

Perhaps it's also because you need deep experience in solving the problems, to ask AI the right questions? It's very easy to generate 'AI workslop' that drives no insight, and diminishes your credibility in the organisation. And that is no doubt from whence that fear emanates.


The recording was switched off halfway through the lecture, at which point the atmosphere in the room changed perceptibly. Kurt (The Chairman of Permira) smiled and said he would assume there were no journalists present, which meant he could now speak a little more freely than usual.

The professors, clearly enjoying the moment, joked that in Sweden, Kurt is known as “Superkurt”: the complete package: handsome, physically fit, wildly successful, and extremely wealthy.
Kurt laughed, didn’t deny it, and carried on.

Which confirmed something I’ve learned from working with private equity firms in the past: there is often remarkably little self-deprecation in the room, even when the person in question is a typically reserved and humble Swede.

Joking aside, this was one of the best lectures I've seen, unique in that it presented top-level insights from both the academic and 'real-world' perspectives.