LBL Consulting Inc.
Increasing Product Development Effectiveness and Speed

 

Knowing Customer Priorities Is A Competitive Advantage

 

Customer focused product development obviously requires a deep understanding of customer requirements. Traditional methods to gather customer requirements include customer interviews and surveys. Other potent methods include product clinics, real world product use observations and contextual inquiry. In some markets, interviewing and observing just thirty customers can give you 90% of the requirements.

However, to focus designs on the areas that are critical from a customer standpoint, we must know which requirements are most important to meet. Although, the best people to rate the importance of the customer requirements are the customers themselves, getting this done is sometimes a challenge and a key decision is selecting the method most appropriate for the situation.

Implementing effective concurrent engineering approaches means that Integrated Product Teams (IPT's) are involved first hand in customer needs research. But in the real world, tension exists between project resources, time for customer research and customer availability and patience on one hand, and obtaining the most discriminating assessment of importance ratings on the other hand.

Consequently IPT's must be aware of what techniques are available so they can make intelligent choices in trading off efficiency and effectiveness when determining customer requirement importance ratings.

It's probably no surprise that there are a wide variety of techniques that can be used ranging from fairly quick and simple to sophisticated and more time consuming. Generally, the simpler techniques ask customers to rate the importance of each requirement without regard to other requirements. More involved techniques ask customers to rate each requirement in relation to all the other requirements. The most sophisticated techniques ask the customers to go through numerous pairwise comparisons forcing them to rate the importance of one requirement versus another or rating combinations of requirements at different performance levels against each other.

Here are nine techniques which could be placed in your company's tool box for determining customer requirement priorities.

Rate each requirement in isolation

Rate relative to other requirements

Forced comparisons

 

The following is a brief description of each method along with its pro's and con's. The methods are listed from easiest to do to hardest to do and, consequently, from least expensive to most expensive and from some value to most value and from least customer time and effort needed to most customer time and effort needed.

This article represents many years of constant vigil for ways to determine customer priorities. Much credit for developing, researching or promoting these techniques goes to several professionals, notably Abbie Griffin, University of Chicago and John Hauser, Harvard University (see their outstanding research in The Voice of the Customer, Marketing Science, Winter 1993), Robert Thomas, Georgetown University, Bob Klein, Applied Marketing Science, Inc., the work of Doug Daetz and Bill Barnard at Hewlett Packard (see their excellent book Customer Integration, 1995, John Wiley) and David Saunders, Arbor, Inc.

 

Priority Ranking

Provide customers with a stack of cards with each card having a separate requirement. Have each customer arrange the requirements cards from most important to least important. Convert each requirement's ranking into a ranking number (e.g., the top ranked requirement of 30 requirements would be given the number of "30").

Pro's

Con's

 

Multi-voting

Provide customers with a list of requirements. Have each customer distribute a specified number of votes among the requirements. The allowed number of votes is 1/3 of the total requirements (e.g., 30 requirements, 10 votes). Ask customers to assign one vote to each of requirements they consider most important.

Pro's

Con's

 

Linear Rating Scale

List the requirements and adjacent to each item place an importance scale of "1 to 5" or "1 to 10". Be sure to provide a definition of what each importance rating value means, for example:

5 = won't buy without

4 = might not buy without

3 = not critical, but might spend more for

2 = nice, but would not spend more for

1 = no value to me

 Ask each customer to rate the importance of each requirement using the rating definitions. Compute average rating and perhaps standard deviation for each requirement.

 A "1 to 10" scale can sometimes be better than a "1 to 5" scale since it provides more room for differentiation and, therefore, can reduce bunching of responses (e.g., many requirements get 4's on a 5 point scale). In some cases, customers can not discriminate with high resolution and a 10 point scale may be overkill.

Pro's

Con's

 

Constant Sum Scale

Use an Affinity Diagram to structure customer needs into high level, second level and, if needed, third level requirements. Ask each customer to allocate 100 points among the high level requirements (i.e., "life", "performance", "handles hazards", etc.). Next, have the customer allocate 100 points among the second level customer requirements related to each high level customer requirement. Compute weighted importance of each second level requirement by multiplying its rating times the rating of its related high level requirement. Normalize the ratings to 100.

Pro's

Con's

 

$100/$1000 Distribution

Ask customers to allocate $100 among the requirements to show what value they hold for each requirement (i.e., its importance when buying). Next have customers allocate $1000 to reward suppliers who have done well in meeting any of the customer requirements.

Pro's

Con's

 

Anchored Rating Scale

Again using an Affinity Diagram, organize the customer requirements into high and secondary levels. Present the customer with the high level customer requirements. Have the customer pick the requirement that is most important and assign that a "10" rating. Then ask the customer to assign up to 10 points each to the remaining customer requirements using the item that was given a "10" as a comparison anchor. For example, relative to "Performance" which got the 10, the customer may assign a "7" rating to "Life".

Then have the customer pick the most important second level customer requirement in each category and assign that a "10" rating. For example, under the primary category of "Performance", the secondary level requirement, "Cuts Smooth", may be considered the most important by the customer and he/she assigns that a "10" rating. Then, ask the customer to assign 1 to 10 points to the remaining secondary level customer requirements relative to "Cuts Smooth" which received a "10" rating (e.g., "Cuts Straight" might get a "7" rating, etc.).

The overall rating of each secondary level requirement can be computed by multiplying its importance rating times the rating given its related high level customer requirement. For example, if "Cuts Straight" got a "7" rating and the category "Performance" got a "9" rating, the weighted rating for "Cuts Straight" would be 7 x 9 = 63. Then, to convert the rating to a 1 to 5 rating value, divide each rating by 20 and round off (i.e., 63/20 = 3.15. Round off to a "3" rating).

Pro's

Con's

 

VocalystTM

This is a specific Anchored Rating Scale methodology developed by Applied Marketing Science, Inc. Each requirement is put on a card (each card has a unique number). Ask each customer to place the requirements that are related to each other in separate stacks. Then, the card most representative of each stack is put on top.

Each customer then assigns 100 points to the most important stack and each other stack is scored relative to that stack. Ranking within each stack is then done. Importance ratings of each customer requirement are computed by multiplying the overall stack importance times the importance of the card in the stack.

Additional Pro's

  • People like the physical cards to work with

  • The Vocalyst statistical process is quite rigorous for initially determining the customer requirements and then establishing priorities

 

Kano Survey

Professor Kano, a Japanese professor, developed the concept that, when met, requirements have different impact.

A customer survey designed in a Kano format simply asks each question in two ways. One question says, "If this requirement was met what would your reaction be?". The second question says, "If this requirement was not met, what would your reaction be?"

The same response choices are provided for both questions.

  1. I like it that way

  2. It must be that way

  3. I am neutral

  4. I can live with it that way

  5. I dislike it that way

 By evaluating the survey data, a quantitative indication of importance of each requirement is calculated. In the calculations, "exciters" have much more weight than "expecteds" or "linear satisfiers" and "linear satisfiers" have more weight than "expecteds". Spread sheet software makes this process more straight forward.

Pro's

Con's

 

Analytical Hierarchy Process (AHP)

AHP asks people to make choices between pairs of customer requirements and select whether one requirement is equal, 1/2 or 1/4 as important as the other. The number of judgments a rater must make is n(n-1)/2, so if there were 10 requirements there would be 45 total judgments. With 20 requirements, there would be 190 judgments. Expert Choice, Pittsburgh, PA, provides software that can make the AHP process somewhat more practical to implement.

Pro's

Con's

 

Conjoint Analysis

Conjoint analysis (also called Multi-attribute Utility Analysis) is used to determine what combination of customer requirements (product and service attributes) has the most appeal to targeted customers and when price is included, what combination of attributes and price will provide the company with the best market share and profitability. In essence, it helps compute a utility curve for each customer requirement. A utility curve shows what amount of each customer requirement must be provided to satisfy customers and it also can show when providing more is not better. Therefore, the utility curve provides valuable insight into the return-on-investment for each design improvement effort.

Often in Conjoint Analysis, each requirement is presented to the customers at two, three or four intensity levels. For example, if "Durability" was a high level customer requirement, it could be presented to the customer at two levels - "High Durability" and "Low Durability". Customers are presented requirements cards showing different combinations of customer requirements and levels. For example, three attributes at three levels would require 27 cards. Customers are asked to stack the cards in order of priority, best on top. Alternatively, customers could be asked to write rating values on each card (e.g., from 1 to 100 points). This method would likely avoid ties between cards.

The ranking or rating results can then be used to calculate and plot the utility value of each combination of attributes. For example, the highest ranked card gets a utility value of 1 and the lowest 0. Cards in between have utility values based on where their ranking falls between the 1 an 0 cards.

The first pass of conjoint analysis is usually at the high level requirements. Then, it is done at a more detailed customer requirements level for specific requirements of high interest. Various schemes are used to keep things manageable when working through this process.

To make conjoint analysis more practical from the very beginning, the number of customer requirements should be constrained using various approaches. Focus groups can be used to eliminate requirements that are low importance. Then, the conjoint analysis is done on the remaining customer requirements. Also, requirements could be eliminated that are expected (e.g., won't break, long life or low price) and importance ratings on use-related requirements only are asked for. However, bear in mind that conjoint analysis can be used to determine how much more customers are willing to pay for long life.

Pro's

Con's

 

Summary

As you can see, there are many methods that can be used to determine customer requirement priorities. Each offers a tradeoff in ease of use versus information value. Below is a short hand description of the procedure used in each method and the deliverables the method provides.

 

Method Procedure Deliverable
Priority Ranking Rank from highest to lowest Rank order importance
Multi-voting Distribute votes, = 1/3 # of items Number of votes per item
Linear Rating Scale 1 to 5 or 1 to 10 rating scale 1-5 or 1-10 item rating
Constant Sum Divvy up 100 points Number of points per item
Anchored Scale Biggest need gets 10, rate 1-10 item rating
$100/$1000 other items relative to that
Distribute $100 among		 Indicators of how customers
Distribution requirements and $1000
among suppliers as rewards		 make buying choices and
what suppliers do best
Kano Survey Asks same question twice,
"If had...", "If didn't have..."		 Satisfiers, exciters, expecteds
AHP Forced pair ratings % importance for each item
Conjoint Analysis Forced ratings of combinations,
Different intensity levels		 Best combination of require-
ments, at what levels

Which method is selected is dependent on the customer research time and resources available for the development project and how patient your customers are. Admittedly, project teams are often in a bind where they have highly compressed schedules. Doing more and better customer research often has to be approached incrementally. Each successive project team can do customer research a little better than the last one. With time the "Customer Research" line item in project budgets will increase as the company learns that understanding customer priorities better than the competition is truly in itself a competitive advantage.

The important thing is to let the customers tell or show what their requirements and priorities are. In this way your teams will have a solid foundation for customer focused product definitions and product concepts. Your rewards will be bigger product hits in the marketplace and, consequently, increased profitability and market share.

 

About the Author

Neil Love is a Partner at LBL Consulting, Inc. in San Jose, CA, and has led several best practices studies in integrated product development and quality management for leading firms. He is a Director of the Silicon Valley Chapter of the Society of Concurrent Engineering, a national committee member of the Product Development and Management Association, a State of California Quality Award Examiner and a Certified Management Consultant (CMC). He can be reached at - 408-923-9292 or neil@lblconsulting.com or via web site: http://www.lblconsulting.com




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