This article is written by Eric Maass, guest writer on the Grow Disrupt website as vetted by Stephanie Scheller, our founder.
About the Author:
DEric Maass retired as Senior Director, Technical Fellow and DFSS Master Black Belt at Medtronic. Eric was an original co-founder of Six Sigma, was the Lead Master Black Belt and Director at Motorola.
He is the author of several books, including Applying DFSS to Software and Hardware Systems, Flawless Launches – Profitable Products and Supply Chain Modeling and Optimization .
Eric has his Bachelor’s degree in Biology, Master’s degree in Biomedical and Chemical Engineering and his doctorate in Industrial Engineering. Dr. Maass is also an Adjunct Professor at Arizona State University
Imagine if you could gain trustworthy insights into what features and functions of your potential new product or service are desired by your customers – and, how much the customers would be willing to pay for those features and functions?
Conjoint Analysis is based on an approach called Design of Experiments, for market research. You show customers possible new products or services as combinations of features and functions at various prices for the product or service, and ask the potential customers how likely they might be to buy or recommend the product or service with those features and functions at that price.
Then, you analyze customers’ responses to determine both the relative importance and customer’s perceived value of each feature and each function.
The time and effort involved is remarkably small, and appropriate for a small business.
Conjoint Analysis can take just a few days to complete, and using either services available on the web or someone with relevant expertise to work with your team, the cost can be very reasonable.
Conjoint analysis has had a wide range of successful applications, successfully used for new products including a medical device and a communication device, for compensation packages for employees, and for Patent and Royalty cases.
The Steps:
- Choose the Outcome or Outcomes you are interested in (such as how likely customers would be to buy your product or how likely they are to recommend your service).
- Choose your approach for leveraging Conjoint Analysis (whether to use your own resources or use a Conjoint Analysis service like https://conjointly.com/ or https://www.surveyking.com/help/conjoint-analysis-explained or https://sawtooth.com/ ; whether to use Choice-Based Conjoint or MaxDiff Conjoint or…)
- Choose which customers or stakeholders to survey
- Choose the features and functions and other aspects to include
- Choose how many and which Levels for each feature and function and aspect.
- Conduct the survey with your customers or stakeholders
- Analyze the responses from the surveys
- Prioritize, Predict, and Optimize towards your desired outcomes
- Summarize for business decision makers
Contrived Case Study – Medical Equipment for Diagnosing a Disease
Imagine we have decided to perform a Conjoint Analysis with customers for a medical diagnostic system – those customers are physicians, Pathologists.
1. The desired outcome is to maximize market share and profitability for the medical equipment.
2. Pathologists are very busy, so the team decides to use Choice-Based Conjoint Analysis – the pathologists will be asked yes or no questions as to whether they would recommend equipment with certain combinations of features and functions at a certain price.
3. A set of pathologists were identified for the study.
4. These features and functions and aspects were selected for the Conjoint Analysis study:
- Price per Assay,
- The probability that the assay results would be wrong – referred to as False Positives.
- Time to Results (how long until the results are obtained)
- Installation Time (how long it takes to install the equipment at the customer’s site)
- % UpTime or Availability (the percent of the time the equipment is up and working)
5. Five levels were chosen for each feature, function or aspect as shown below:
- Price/ Assay $ $5 $10 $30 $50 $55
- Pr(False Positives) .1% 1% 3% 5% 5.9%
- Time to Results (minutes) 10 20 60 100 110
- Installation Time (hours) 2 2 6 10 10
- % UpTime (Availability) 77% 80% 88% 96% 99%
6. The Conjoint Analysis study was conducted with the pathologists:
Assume Profitability = % Pathologists saying Yes * {(Price/Assay) – (Cost/Assay) }
Assume the product development team estimates the Cost/Assay:
Cost/Assay = $5 + .5*{1-Pr(False Positives)} + .025*(100-Time to Results)
+.1*(10-Installation Time) + .5*(100% - %UpTime)
7. The analysis below shows the most important factorsaffecting Pathologists’ saying “Yes”:
The analysis shows what you need to do to maximize theprobability that Pathologists will recommend your equipment:
Further analysis, bringing in the Price and Costinformation, shows what you need to do to maximize Profitability:
9. While these graphs may make sense to some people, these insights should be summarized clearly for the business decision makers that:
A profit of about $29 Million can be achieved if:
The price per assay is $53, which the pathologists will support if the Probability of wrong results (False Positives) is as low as .1%, the installation time is reduced to 2 hours, and
the uptime for the equipment is about 99%.