Predicting Wearable Adoption

Posted: January 19, 2015

The Delphi Method is a systematic problem solving and decision making technique developed to address complex problem using a group of subject matter experts, and was originally developed as a forecasting method (2007, Cialkowska et al).

The Delphi Method is based on the presumption that decision from an organized and structured group are more accurate than decisions from individuals or non-structured groups. It is an anonymous and iterative process overseen by a facilitator. The facilitator is responsible for gathering responses to surveys or forms from the anonymous participants, and analyses those responses to find common viewpoints and conflicting viewpoints. The process of gathering and analyzing responses is repeated until consensus is achieved.

The modified Delphi Method is similar iterative process. The difference is that the initial round is seeded with pre-selected information from vetted sources (such as literature reviews, interviews with subject matter experts, etc.) The purpose of the modification is to provide a strong foundation for the process using previous recognized work and to improve the first round response rate.

One of the potential downsides of the Delphi Method mentioned by Katherine Waiter in her thesis on wearable computing adoption (2003) is that predictions may be biased by the predictor’s personal interest in the technology or problem. One item of interest in her thesis was the use of the Delphi Method to predict technology adoption. One particular item of interest to me was the prediction that HMDs would start to see widespread adoption in the next 10-15 years. With the Oculus Rift, Samsung Gear VR, and Sony Mobius in or about to hit the marketplace, that particular prediction seemed right on target.


Cialkowska, M., Adamowski, T., Piotrowski, P., & Kiejna, A. (2007). [What is the Delphi method? Strengths and shortcomings]. Psychiatria polska, 42(1), 5-15.

Waiter, K. (2003). Marketing Wearable Computers to Consumers: An examination of Early Adopter Consumers’ Feelings and Attitudes Toward Wearable Computers. (MA), Georgetown University, Washington, DC.

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