Library
Seeing What's Next: Using the Theories of Innovation to Predict Industry Change
Entrepreneurship

Seeing What's Next: Using the Theories of Innovation to Predict Industry Change

Clayton M. Christensen, Scott D. Anthony, Erik A. Roth 2004 15 references

Apply Christensen's disruption theory as a predictive toolkit to analyze industry change, assess competitive battles, and evaluate strategic choices.

disruption innovation competitive-strategy prediction industry-analysis value-chain

Overview

The Core Framework

  • Three theories power prediction: Disruptive Innovation (new-market vs low-end), RPV (Resources/Processes/Values), and Value Chain Evolution (integration ↔ modularity cycles)
  • Three-step diagnostic: (1) Identify signals of change via customer tiers, (2) Evaluate competitive battles via asymmetries, (3) Assess strategic choices that raise or lower odds
  • Disruption is a process, not an event — no industry transforms overnight; watch for fringe developments improving over years
  • Simple beats sophisticated — across every industry studied, simple products targeting nonconsumers outperform ambitious technology pushes
  • Values, not resources, explain incumbent failure — the resource-allocation process systematically deprioritizes disruptive opportunities

Quick Lookup

Situation Do This Avoid This
Evaluating a new entrant Check for nonconsumption targeting + asymmetric motivation Assuming cheaper = disruptive
Assessing incumbent response Run RPV tale-of-the-tape (values filter is key) Resource-only competitive analysis
Choosing strategy for uncertain market Use emergent strategy + discovery-driven planning Deliberate strategy with untested assumptions
Evaluating funding sources Seek patient-for-growth, impatient-for-profit capital Growth-before-profit investor pressure
Predicting industry structure shifts Check for overshooting → modularity → specialist entry Assuming integration disappears
Analyzing regulation impact Apply motivation/ability 2x2 matrix Treating regulation as purely blocking

The Key Insight

"There is an important difference between a signal — an imperfect indicator of the future based on current data viewed through the lens of a theory — and evidence that more conclusively demonstrates that a predicted event has come to pass." — Christensen, Anthony, Roth, Introduction

References