Most executives can feel it: the ground keeps shifting under their feet. Customers have less patience. Talent has more choices. Regulators have more teeth. And your competitors, some of them barely existed a few years ago-move like they’ve got nothing to lose.
Here’s the thing. “Digital transformation” often gets treated like a fancy refurb: new cloud, new data platform, maybe a slick app, and a few dashboards that impress the board for a quarter. Then reality bites. Adoption stalls. Costs creep. People quietly rebuild old workarounds in Excel. And the organisation ends up with newer tech… plus the old mess.
Christensen’s Theory of Disruptive Innovation gives you a sharper way to see what’s happening, and what to do next. Not as a buzzword. As a lens for decisions: where to invest, what to protect, what to let go of, and how to avoid funding a beautiful failure.
First, a friendly reset: disruption isn’t “new and cool”
Disruptive innovation has a specific shape. It starts in simple, lower-performance use cases, often cheaper, more accessible, “good enough” – then improves and moves upmarket until it threatens incumbents.
That’s why a lot of “big new tech” isn’t disruptive at all. Plenty of innovation is sustaining: it helps leaders serve their best customers even better. Useful, profitable, necessary, just not disruptive in Christensen’s sense.
If you’re leading digital transformation and you call everything “disruptive”, you lose the plot. You start backing the wrong horses, with the wrong expectations, using the wrong scorecard.
So let me ask a slightly uncomfortable question: are you trying to modernise the core… or outmanoeuvre a disruptor? Those are different games.
The awkward truth: your biggest strengths can become your trap
Large enterprises are brilliant at a few things:delivering predictable results,
– managing risk through governance,
– optimising for scale,
– satisfying the needs of high-value customers.
Those same strengths can make you slow to respond when a simpler offer starts nibbling at the edges.
Why? Disruptors rarely begin by stealing your best customers. They start by serving:
– people you’ve priced out,
– use cases you’ve ignored,
– jobs-to-be-done that look “too small” to bother with.
That’s the bit incumbents wave away. “Low margin.” “Not strategic.” “Not enterprise-grade.” You know what? That dismissal is often the whole opening.
Two doorways into disruption: low-end and new-market
Christensen frames disruption as a process, but it tends to enter through two common doors:
1) Low-end disruption: “Good enough, and cheaper”
A challenger targets over-served customers, people paying for features they don’t use. The product is simpler, the service model is leaner, and the price makes procurement teams grin.
In digital terms, this can look like:
– a SaaS tool replacing a heavy on-prem suite for a narrow workflow,
– a low-code platform letting business teams ship small automations without waiting for a 12-month queue,
– a niche vendor taking a slice of a bigger platform’s footprint.
2) New-market disruption: “Non-consumption becomes a market”
This is the sneaky one. It creates a market where there wasn’t one, by making something accessible to people who previously couldn’t use it (too complex, too expensive, too specialist).
In the enterprise, new-market disruption shows up when:
– front-line teams build their own workflows with lightweight tools,
– customers self-serve instead of calling,
– small businesses buy software that used to require consultants and a programme team.
And yes, this is why consumer-grade experiences keep reshaping B2B expectations. People don’t “turn off” their standards when they open a work laptop.
So what does this mean for your transformation portfolio?
Most transformation portfolios are a mixed bag:
– some work is mandatory (security, resilience, compliance),
– some work is modernisation (reducing technical debt, refreshing platforms),
– some work is growth (new products, new channels, new data monetisation).
Christensen helps you stop treating all of that as one amorphous “transformation”.
A simple portfolio question that pays for itself is:
Which initiatives defend the core (sustaining), and which create a credible response to disruption (disruptive)?
The governance, funding, and KPIs should differ.
If you force a disruptive bet through core governance, it gets suffocated by:
– quarterly ROI demands,
– exhaustive requirements packs,
– vendor selection cycles that last longer than the product’s first two releases.
And if you run core modernisation like a start-up experiment, you get fragility and audit findings. Not fun.
The numbers that should sober you up (without killing the mood)
Cloud and AI have poured petrol on expectations. Spending is real money now, not pocket change.
– Gartner forecast public cloud end-user spending at $723.4bn in 2025, up from $595.7bn in 2024.
– Security spend keeps climbing too: Gartner projected $213bn in information security spending in 2025, rising again in 2026.
– Flexera’s 2025 State of the Cloud press release reported 84% of respondents said managing cloud spend is their top cloud challenge.
Then there’s delivery risk. Large IT programmes still carry “black swan” potential:
– McKinsey’s Oxford-linked research on large IT projects (>$15m) reported 45% average budget overrun, 7% schedule overrun, and 56% less value than predicted, with 17% of projects so bad they threaten the organisation’s existence.
– A Budzier/Flyvbjerg paper (public sector sample) highlights fat-tail risk too, reporting 18% of projects as “black swans” and a “typical” black swan with 130% cost overrun and 41% schedule slippage.
These figures aren’t here to scare you. They’re here to make one point: your delivery model has to match the type of change you’re making. Otherwise, the maths catches up.
A practical “disruption lens” you can use today
Try sorting initiatives into three buckets:
Bucket A: Keep the lights on (and stay out of court)
Cyber controls, resilience, regulatory commitments, key vendor renewals. Boring. Necessary. Fund it like oxygen.
Bucket B: Make the core cheaper to run
Application rationalisation, data centre exits, ERP upgrades, platform consolidation, toolchain simplification. These are sustaining moves. They pay off through reliability, cost control, and speed-over time.
Bucket C: Place disruption bets (small, sharp, protected)
These are the moves that create new capability:
– a digital product that changes the customer relationship,
– a new operating model for how you release software,
– a data product that becomes a revenue line,
– an AI-enabled service that cuts cycle time in half.
Bucket C needs protection from core gravity. That doesn’t mean a “free pass”. It means a different deal: tighter learning loops, clearer kill criteria, and a budget that supports iteration rather than theatre.
“Wait… are you saying big transformations are bad?”
No. And yes. (Told you there’d be a mild contradiction.)
Big transformations can work. They just fail when leaders confuse size with certainty.
What helps is staged commitment:
– start with a narrow slice that proves the operating model,
– expand when you’ve proven adoption, controls, and economics,
– keep the option to stop without political meltdown.
People hate hearing this, but it’s true: a lot of programmes don’t fail on technology. They fail on social adoption. The system “goes live”, yet the organisation doesn’t.
The IT myths that didn’t age well (dustbin material)
You’ve heard these. Some of us have even said them out loud in steering committees. No judgement.
1. “The paperless office is just around the corner.”
Printers are still thriving. The real win is simpler workflows, fewer handoffs, cleaner data capture.
2. “If we buy the suite, we’ll fix the process.”
ERP and CRM rollouts don’t magically resolve messy incentives. They can hard-code the mess.
3. “Cloud is cheaper by default.”
Cloud can cut cost; it can just as easily inflate it. Spend follows behaviour, not architecture.
4. “Agile means no planning.”
Agile done well is disciplined: clear outcomes, tight feedback, strong product ownership. Chaos isn’t agility; it’s just chaos with stand-ups.
5. “One tool will become the single source of truth.”
Truth is negotiated across systems, definitions, and ownership. The fix is governance people actually follow.
Why bring these up? Disruptors love myths. Myths keep incumbents busy “improving” yesterday.
AI is the current stress test (and it’s not only technical)
Generative AI has moved from curiosity to working reality in many organisations. McKinsey reported 65% of respondents saying their organisations were regularly using gen AI in early 2024. Later, McKinsey reported 78% using AI in at least one business function (March 2025 survey).
Yet adoption at scale is uneven, and risk is real: McKinsey’s 2025 write-up notes 51% of respondents at organisations using AI reported at least one negative consequence.
And regulation is tightening. The EU AI Act entered into force 1 August 2024, with staged applicability: prohibited practices and AI literacy obligations from 2 February 2025, obligations for general-purpose AI models from 2 August 2025, and broader full applicability 2 August 2026 (with some high-risk areas later).
So where does Christensen fit? AI tools often start as “good enough” helpers, drafting, summarising, triaging – then creep into higher-stakes work as quality improves. That’s disruption logic in motion. The winners won’t be the firms with the flashiest demo. They’ll be the firms that redesign work, controls, and accountability at the pace the tools improve.
Three plays that tend to work for incumbents
Play 1: Separate the disruptive bet from core delivery
Not a dramatic spin-out. More like: a small product team with a clear mandate, a ring-fenced budget, and permission to ship.
Keep it connected to the enterprise where it matters (data, security, legal). Keep it independent where it gets crushed (release cadence, scope control, customer discovery).
Play 2: Treat procurement as a strategy lever, not a back-office step
Disruptors win with speed. If your vendor cycle takes nine months, you’re funding your own delay.
Modern procurement patterns, smaller initial commitments, measurable outcomes, clear exit routes-let you learn without getting stuck.
Play 3: Measure adoption like you mean it
If your KPI is “go-live”, you’re basically celebrating the start of the hard bit.
Use metrics like:
– active usage by role,
– cycle time reduction,
– error-rate drop,
– customer effort score,
– percentage of work handled through the new path.
Not hundreds of metrics. A few that tell the truth.
A closing checklist (the one you can read between meetings)
Name the threat clearly: low-end, new-market, or sustaining competition?
Split your portfolio: mandatory, core efficiency, disruption bets
Change the scorecard per bucket: learning speed for bets, reliability for core
Assume delivery risk is fat-tailed: plan for outliers, not averages
Get serious on cloud economics: cost follows behaviour
Treat AI as operating model change: tools are the easy part
If you take one idea away, make it this: disruption isn’t a tech event; it’s a business pattern. Christensen gives you a way to spot the pattern early, then respond with intent rather than panic.
And honestly, that calm, real calm, not slide-deck calm, might be the rarest executive advantage going.
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