Melodies in Marketing

I came across this interesting qualitative assessment model for predicting whether change is possible, and to what degree it will arise, from my reading of Pip Coburn’s “The Change Function“. Pip’s context was finding how out people’s inclination to adopt new technologies, based on a user-centered model that functions like a cost/benefit analysis. While the large reliance on qualitative data can make this change propensity difficult to assess, it serves as an excellent guide for developing and testing new product concepts in design research, and evaluating their implementation value and market potential.

Degree of Actual Crisis or Need
How bad is the dilemma we’re facing? Is it causing difficulties for us to function in our work or personal lives? Is it costing us time, money, health, growth rate? This analysis asks us to be critical, because marketing and bright, shiny, objects/processes can fascinate us into believing our current situation may be lacking somehow; that if it could be improved, we’d be that much better off. Remember, desires can be turned into needs (rational or not), by changes in perspectives (through influence and/or analysis). This goes for things small like new running shoes to massive ERP software packages. The incentive to change (purchase, sell, adapt behavior) is a result of performing this preliminary assessment.

Total Perceived Pain of Adoption
If I/we decide to change or act upon an opportunity, what is it going to cost us? Common factors include:

• Relative Affordability
• Learning Curve (difficulty, time)
• Time to Benefits Realization
• Readiness/Will for Change (based on Myers-Briggs)
• Risk of Failure

Change
While solving this formula may seem difficult or confusing because of the division involved, a simpler way to look at the problem is as follows: To what degree is the actual crisis or need, larger than the total perceived pain of adoption.

• If Positive, change will be increasingly beneficial.
• If Equal, the decision to change is practically indifferent since neither benefits nor pain will be incurred.
• If Negative, change will be increasingly detrimental.

Time is the all pervasive dynamic factor that affects prices, product & technology life cycles, and other socio-economic and political forces. Benefits may slowly accrue, hit a peak, then gradually decline. The initial pain of adoption may be high or low, then gradually adjust along its own path over time. A simple positive net result in a proposal for change may be quite obvious; what isn’t known is the best time to take the first step to maximize future benefits (or minimize losses). Hence, the need for building and comparing different scenarios using forecasts and multivariate data.

While using qualitative data in a mathematical context may be quite difficult through the summation of assigned numeric values and their weighted coefficients, this model can be very helpful in performing critical opportunity assessments.

Special thanks to my pal Luis Carlos Pelaez, for contributing his thoughts and insight into this subject.

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Have you seen or applied unique models for evaluating the potential for positive change? How about alternate ways of doing cost/benefit analyses? Your feedback would be greatly appreciated.

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