Disruption Analysis

Origin

The method operationalises Clayton M. Christensen's theory of disruptive innovation (The Innovator's Dilemma, Harvard Business School Press, 1997), refined in Christensen/Raynor, The Innovator's Solution (2003). There the authors distinguish low-end disruption — the attack via price-sensitive, over-served customer segments — from new-market disruption, which reaches previous non-consumers. Both patterns provide the analytical templates.

Typical use

Disruption analysis serves as an early-warning instrument in strategy and technology planning: ahead of portfolio decisions, when assessing new competitors that seem “too bad to be dangerous”, and as the starting point of a Dilemma Assessment. It fits whenever a company is successful in its core business and wants to know from which side that success could be undermined.

Procedure

1. Establish overshoot

   For each relevant performance dimension — speed, capacity, precision, feature scope — check whether the offering's rate of improvement exceeds what customer segments can absorb. Indicators are falling prices despite better performance, unused features, and customers skipping upgrades.

2. Identify candidates

   Look for technologies and business models that are worse on the established performance dimensions but better on others: cheaper, simpler, more accessible. Relevant sources are niche markets, non-consumers and adjacent industries — not the familiar competitors.

3. Compare trajectories

   For each candidate, estimate the rate of improvement and plot it against the corridor of customer use. What matters is not today's performance but the intersection point: when will the rising solution satisfy the demands of the mass market?

4. Test responsiveness and derive consequences

   Finally, test your own organisation: would today's resource-allocation processes fund an answer to the identified attack? From the answer follow monitoring mandates, portfolio decisions, or the build-up of a separate unit.

Limits and typical mistakes

Disruption analysis does not predict single events; it identifies structural vulnerability, not the timing of the attack. The most common mistake is measuring against the wrong yardstick: whoever judges new entrants by the standards of the core business will systematically underestimate them — precisely the mechanism the analysis is meant to expose. Equally widespread: the label “disruptive” is applied inflationarily to every aggressive innovation and loses its analytical edge. Christensen's criteria — initial inferiority, a different value dimension, a faster rate of improvement — must be tested strictly. Finally, the analysis remains inconsequential if it is not tied to decisions about portfolio and structure.

Relation to the Innovator's Dilemma