Convergence Prediction Framework
A diagnostic framework for predicting whether convergence is likely in an industry and identifying which dimensions will converge versus which permit differentiation.
A diagnostic framework for predicting whether convergence is likely in an industry and identifying which dimensions will converge versus which permit differentiation. Helps decide when to adopt 'best practices' versus when to resist the herd.
When to Use Convergence Prediction Framework
Use when evaluating industry trends, considering adoption of competitor practices, or assessing whether differentiation is sustainable. Particularly valuable when facing pressure to adopt new technologies, pricing models, or operational practices.
How to Apply
Assess Competitive Intensity
Evaluate how intense competitive pressure is in your industry
Questions to Ask
- How many competitors exist?
- What are typical profit margins?
- Is the market commoditized or differentiated?
Outputs
- Rating: Very high / Moderate / Low
Identify Constraints
Determine whether technological, physical, or regulatory constraints limit solutions
Questions to Ask
- Are there regulatory mandates that require specific approaches?
- Do physical laws constrain viable solutions?
- Are there technological bottlenecks?
Outputs
- List of strong vs. weak constraints
Evaluate Customer Preferences
Assess whether customer preferences are homogeneous or heterogeneous
Questions to Ask
- Do most customers want the same thing?
- Are there distinct segments with different needs?
- How much do customers vary in willingness to pay?
Outputs
- Homogeneous / Heterogeneous assessment
Check Network Effects
Determine if network effects or switching costs favor standardization
Questions to Ask
- Does value increase with scale/adoption?
- Are switching costs high for customers?
- Is interoperability important?
Outputs
- Network effects strength rating
Assess Environmental Stability
Evaluate how stable the competitive environment is
Questions to Ask
- How rapidly are customer needs changing?
- Is technology disrupting the industry?
- Are regulations stable or evolving?
Outputs
- Stable / Rapidly changing assessment
Determine Convergence Likelihood
Synthesize findings to predict convergence
Questions to Ask
- High intensity + Strong constraints + Homogeneous preferences + Stable = Very High convergence
- Low intensity + Weak constraints + Heterogeneous preferences + Changing = Low convergence
Outputs
- Convergence likelihood rating
- Convergent vs. divergent dimensions