Numerous statistical techniques are available to assist you in developing new products, but first you have to determine if your new product actually has value.
Factor analysis(def)-a statistical technique used to (1) estimate factors or latent variables, or (2) reduce the dimensionality of a large number of variables to a fewer number of factors.
U.S. automotive manufacturers seem to have been playing a game of catch-up with primarily Japanese auto manufacturers for more than a quarter century. Initially, it was a matter of quality that appeared to make their products better. Then, it was the increased cost due to the high-priced union benefits and aging infrastructures at American manufacturers that was cited as the differentiating factor. And lately, a lack of innovation has been termed the culprit for a not-so slowly eroding market share of the big three. While all of these ‘reasons’ may be true to varying levels, the overall trend of declining market shares is due to more than just these.
B Value Factor Analysis of paint reveals level of difference between competitors. Click here
to enlarge.
Building the right product
All manufacturers have equal access to the knowledge and benefits of statistics-based quality control procedures like Six Sigma, factorial designs, design of experiments, and a plethora of statistical design strategies. Similarly, all manufacturers have equal access to leading-edge manufacturing and automation techniques. And with all the business management programs available, everyone should have equal access to the commonly accepted practices for supporting an innovative culture within the organization.
Or maybe not. In their recent book, “Innovation—The Five Disciplines for Creating
What Customers Want,” Curtis Carlson, president and CEO of SRI International,
Menlo Park, Calif., and William Wilmot, a professor at the Univ. of Montana, Missoula,
discuss five quantitative methodologies for creating and managing innovation projects
through to successful outcomes. These techniques—determining customer and market
needs, creating value, supporting innovation champions, creating innovation teams,
and aligning the organization—create a total value management approach to creating
an innovative organization.
Included in Carlson’s and Wilmot’s approach to innovation is a Value Factor Analysis (VFA) technique—developed by Leonard Polizzotto, VP Business Development and Marketing at SRI. VFA can be used to quantify an organization’s design process to ensure that the products produced are what the customer needs, wants, and values.
Product managers must remember that the main objective for a new product or service
is to provide much greater customer value than that provided by the competition
or alternatives. VFA is a tool that can help achieve this objective. VFA also
helps in uncovering hidden customer needs and in better understanding the more
subtle attributes of the competition.
VFA consists of four variables: quality and convenience and the costs of each. In equation form this is shown as:
Value Factor = [(Quality benefits) x (Convenience benefits)] / [(Quality costs) x (Convenience costs)]
Creating a VFA matrix like the one shown in this article is fast and simple. As a rough guide, a new product or service should have a Value Factor that is 2 to 10 times greater than the competition for the difference to be noticeably significant. That said, calculating a VFA is straightforward:
1) List the product’s attributes (for Quality, Convenience, and Cost)
The number of product attributes will vary from product to product, but users are encouraged to write down as many as they can think of—if you write down less than 10, you’re not trying hard enough.
2) Determine the importance of each attribute to the customer
To get started, these values can be estimated by you and your team. However, you will need to show your VFA to customers to obtain more realistic values.
3) Evaluate each product’s performance attribute
Evaluate how each product’s performance satisfies the identified Quality, Convenience, and Cost attributes.
4) Calculate the total scores for quality,
convenience, and cost as noted in the
attached example.
5) Calculate the VFA according to the
equation noted above
The scores in the attached example are 95 and 104, concluding that there is not a lot of difference between the two paint materials. As a result, the product is probably not worth pursuing as a development project without significant improvement.
Tool chest
Other factors should continue to be used in the development of a new product to understand and improve customer value. Quality Function Deployment (QFD) includes a set of tools for planning and developing high-quality products based on including the customer’s responses. Six Sigma programs as well provide a wealth of information on the costs and production capabilities of new product development programs. Standard statistical tools used in a Six Sigma analysis include:
• Plots and charts–Histograms, Pareto, and control charts
• Time series statistical tools–Analysis of data over time
• Analysis of variance (ANOVA)–Variance analyses and equality of variances
• Tolerance analysis–Margins and tolerances
• Design of experiments (DOE)–Variables that affect quality
• Reliability analyses–Accelerated life testing
A sequential combination of VFA and traditional statistical analyses can go a long way in creating competitive products that should result in increasing market shares rather than those that erode. The simplicity and ease of VFA also allows it to be used throughout a product development program as your new product changes or as your competitor announces new products.
—Tim Studt
More Info: Innovation—The Five Disciplines for Creating What Customers Want
By Curtis Carlson and William Wilmot
Published by Crown Publishing Group, a division of Random House, New York
Published: August 2006
ISBN 13: 978-0-307-33669-9
