Deep Data Analytics for New Product Development
eBook - ePub

Deep Data Analytics for New Product Development

Walter R. Paczkowski

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eBook - ePub

Deep Data Analytics for New Product Development

Walter R. Paczkowski

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Über dieses Buch

This book presents and develops the deep data analytics for providing the information needed for successful new product development.

Deep Data Analytics for New Product Development has a simple theme: information about what customers need and want must be extracted from data to effectively guide new product decisions regarding concept development, design, pricing, and marketing. The benefits of reading this book are twofold. The first is an understanding of the stages of a new product development process from ideation through launching and tracking, each supported by information about customers. The second benefit is an understanding of the deep data analytics for extracting that information from data. These analytics, drawn from the statistics, econometrics, market research, and machine learning spaces, are developed in detail and illustrated at each stage of the process with simulated data. The stages of new product development and the supporting deep data analytics at each stage are not presented in isolation of each other, but are presented as a synergistic whole.

This book is recommended reading for analysts involved in new product development. Readers with an analytical bent or who want to develop analytical expertise would also greatly benefit from reading this book, as well as students in business programs.

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Information

Verlag
Routledge
Jahr
2020
ISBN
9780429663314

1

INTRODUCTION

All businesses simultaneously pursue multiple activities in order to survive in highly competitive, dynamic, and global markets. Among these are supply chain management; billing and account management; human resource management and development; quality control; and financial analysis, control, and reporting to mention a few. Equally important, and certainly not to be overlooked, is the continuous introduction of new products. It should be acknowledged, without discussion or argument, that your competition will be doing this especially in 21st century global markets. The surest way to fail is to let your competition gain the upper hand.
It is not enough, however, to merely introduce new products. It also is imperative that they be one’s customers, whether consumers or businesses, will buy. This should be obvious, but knowing and acknowledging this and finding these new products are two different issues. A business’s pipeline, the collection of new products at their various stages of development from inception to introduction to the market, must always be full of innovative products that satisfy customers’ needs and solve their problems and are also one step ahead of the competition. If your pipeline is not full with the right products, new products, or any products, then your business will be forced out of the market.
In today’s world, technology evolves quickly and as a result the competitive landscape constantly changes. Technologies change because they tend to feed on themselves, always evolving from one “species” to a new one. The new species of technology could be a new method of doing something (e.g., communicating through social media) or a new device (e.g., smartphone) or modification of an older device (e.g., snap-on modules for smartphones). At the same time, people’s needs constantly and continuously change in part because they themselves are part of the market but also because they adapt to the new technologies. In the process of adapting, however, their needs, both materialistic and psychological, or external and internal needs, change and evolve. This evolution itself puts pressure on technology to further evolve to meet changing needs. And so there is a circular pattern from technology changes to people’s needs changes and back again. This is depicted in Figure 1.1. How the market changes and how people change are one and the same thing.
FIGURE 1.1There is a constant circular pattern from technology changes to customer needs changes and back again.
This dynamism puts pressure on all businesses to always decide what to produce and introduce as well as what to remove from the market. Old products are therefore an integral part of the cycle in Figure 1.1. So in addition to being full, the content of the pipeline, the nature of the products themselves, must keep pace with the changing technologies and customer wants and needs; basically, their evolving problems. This means technology changes and customer problems must be anticipated and identified. See Arthur [2009] for a good discussion of how technology evolves and the implications of this evolution.
This chapter is divided into four sections. The bases for, not product success, but product failures are described in the first section. The focus is on the failures because this sets the stage for what should be done. It is the failures that motivate people to push ahead and improve, not their successes. The second section draws on these failures and presents a process for generating new products that will have a better chance of success because the process highlights those features that make products fail. In essence, it is a roadmap for what to avoid as much as for what to do. This process is a road map that will be followed and developed throughout the book. The third section describes the main parts of a deep analytical tool set needed for new product development. I refer to this as the heart of the new product development process. The last section is a summary.

1.1 New product failures

All businesses know they must constantly innovate and maintain a full pipeline. The fact that today’s markets are highly competitive, dynamic, and global does not change anything. This just intensifies the problem; makes it more imperative; makes it more complex to deal with and manage. Businesses always innovated; to be the first on the block with the newest and most creative products. Unfortunately, not all new products are successful. Some studies of the status of new products soon after their launch have shown that:1
About 80% fail.
About 66% fail within 2 years of introduction.
About 80% stay on store shelves less than 12 months.
About 96% fail to return the cost of capital.
Consider the 80% failure rate. Whether this is too low or too high is immaterial. The fact that it is not 0% or 5% (and not 100%) is the important point. The 80% failure rate implies that the odds of failure are 4:1.2 Based on this one fact, any new product is 4 times more likely to fail than succeed. The risk of failure is high, so every firm must try hard to “get it right” and get it right the first time; the market very rarely, if ever, gives you a second chance. This risk of failure is important because the cost of developing a new product can be significantly high. These costs include design, retooling of plant and equipment, advertising and promotion, marketing, and personnel hiring and training just to mention a few. If the innovation is just a minor “tweak” to an existing design, the cost may not be substantial, but nonetheless there will be a cost. If the innovation is a major paradigm shift in what the business has traditionally produced or a new-to-the-world innovation, then these cost elements will be substantial. In either case, there is a cost that must be incurred which could lead to financial devastation if the product fails. The higher the risk of a product failure, the greater the risk of financial devastation. So the business has to get it right. But they have only the one chance to get it right! Unfortunately, since there are no guarantees, “getting it right” means reducing the risk of failure, not eliminating it before the product is launched. This reduced risk of failure can only be achieved by having the best information at each stage of a new product’s development so that the right decisions are made about it including whether or not it should even be pursued. The information needed for these decisions includes, but is not limited to, what customers want, what is technologically possible, what is the best product design, and what is the best marketing campaign and pricing.
There are many specific reasons for the failure rates listed above, but I will categorize them into three groups displayed in Figure 1.2. These are aggregations of the reasons for the lack of information. A fundamental Design Failure involves a concept that does not meet customers’ needs or solve their problems. In fact, its use may actually increase the problem rather than ameliorate if there is a fundamental technical fault with the product. The Pricing Failure involves a pricing strategy or a price point that is inappropriate for the market, either placing the product out of reach of most customers or giving the impression that the product is “cheap” so customers will not be willing to pay for it. Finally, the product could have a Messaging Failure so that the wrong claims are made, especially for the target audience. I will discuss each failure group in the following subsections.
FIGURE 1.2There are three reasons for new product failures: design, pricing, and messaging. Each one has its own components, some of which are stated here.

1.1.1 Design failures

Design failures refer to flaws in two design components: concept design and technical design. The concept is an idea, a vision, an intangible statement or description of what should be produced to solve a problem. It consists of a problem statement; a description of the intended target customers who have that problem; an operational statement; and sufficient description so that someone could build it. It is an abstract idea. The technical design, however, is the engineering specification of what can be built given current technology and internal engineering talent. It is a statement of what can be practically done and how. Usually, a prototype or mock-up design reflecting an interpretation of the abstract design concept is constructed from this technical design.
The critical factor for survival is having a new product concept that is brought to market before the competition, but this concept has to be one customers want and need in order to solve a problem, whether real or perceived. It is the customers who count since they buy the product, and this means their wants and needs come first. It is not enough that a business manager “just knows” what should be in the product or what are the customers’ needs.
The problem solution, however, is not singularly focused, meaning that one and only one attribute or feature of the product solves a customer’s problem. Typically, a product has multiple physical attributes such as form, size, weight, number of buttons, display screen, and so forth. Some of these are important to customers while others are not. Each attribute is a technology unto itself so a product is really a container of subordinate technologies. It is the important ones that customers will key on and that will determine whether or not the product will succeed. The design concept must have these critical and important customer-focused attributes. I will discuss methodologies for assessing physical attribute importances in Chapter 3. See Arthur [2009] on the notion of technology as a series of containers.
The design concept may be a good one if it solves the customer’s problem, but it is meaningless if the technical design reflected in a prototype is flawed. Sizes are too small or too large; key buttons (e.g., power button) are difficult to access or operate; the form is awkward; the weight is too high; and so forth. All these interfere with t...

Inhaltsverzeichnis

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. List of Figures
  7. List of Tables
  8. Preface
  9. Acknowledgements
  10. 1 Introduction
  11. 2 Ideation: What do you do?
  12. 3 Develop: How do you do it?
  13. 4 Test: Will it work and sell?
  14. 5 Launch I: What is the marketing mix?
  15. 6 Launch II: How much will sell?
  16. 7 Track: Did you succeed?
  17. 8 Resources: Making it work
  18. Bibliography
  19. Index
Zitierstile für Deep Data Analytics for New Product Development

APA 6 Citation

Paczkowski, W. (2020). Deep Data Analytics for New Product Development (1st ed.). Taylor and Francis. Retrieved from https://www.perlego.com/book/1606430/deep-data-analytics-for-new-product-development-pdf (Original work published 2020)

Chicago Citation

Paczkowski, Walter. (2020) 2020. Deep Data Analytics for New Product Development. 1st ed. Taylor and Francis. https://www.perlego.com/book/1606430/deep-data-analytics-for-new-product-development-pdf.

Harvard Citation

Paczkowski, W. (2020) Deep Data Analytics for New Product Development. 1st edn. Taylor and Francis. Available at: https://www.perlego.com/book/1606430/deep-data-analytics-for-new-product-development-pdf (Accessed: 14 October 2022).

MLA 7 Citation

Paczkowski, Walter. Deep Data Analytics for New Product Development. 1st ed. Taylor and Francis, 2020. Web. 14 Oct. 2022.