Has a Customer Already Developed Your Next Product?

“Find a need and fill it” is the accepted strategy for developing a successful new product — a strategy which research into the innovation process has proven correct. But what is a “need,” and where do you most successfully look for it? During the past three years, a study carried forward at the Sloan School has systematically examined the need information which triggered the manufacture of several hundred innovative and successful new industrial products,1 and has developed some answers which should be of use to managers interested in such products. The key findings discussed in this article include:

• Information about the need for a new product is often found bundled together with valuable product design data. This data may be missed even by experienced market researchers looking for “needs only,” with the result that a manufacturing firm has to invest in redeveloping what it could have gotten for free. Sensitivity to the amount of product design data usually present in “new” product need information can pay off handsomely.
• Information about new product needs in some industries proves to come consistently from the same type of source in case after case. Once this source is identified, management can do a great deal to use it more efficiently.

Managers who use our findings and apply the methods proposed in this article should be able to say as a result, “In our industry, need information leading to successful new products typically also provides us with X amount of free product design data, and comes from Y source — and we can organize to pick up and process this type of information more efficiently.”

Product Design Data Contained in Need Information

The conventional wisdom is that customers provide the needs, while manufacturing firms develop the solution to the needs. But, if one thinks about it, one sees that any information about a need provides information about the nature of a product responsive to the need as well. Consider the following statements of a need. Each succeeding phrase adds more data about what a responsive product should look like:

I need higher profits
— which I can get by raising output
— which I can best do by getting rid of the bottleneck in process step D.
— This can best be done by designing and installing new equipment
— with the following operating characteristics
— and the following design.

Clearly, the amount of work a manufacturer must do to convert the first need statement — “I need higher profits” — into a responsive new product is high. He must employ skilled analysts to study the business of the potential customer and to conceptualize a new product opportunity which will impact the customer’s felt need for higher profits. On the other hand, a manufacturer who receives need information containing the maximum amount of product design data shown need only have his manufacturing people poised by the telephone ready to follow customer instructions (who may be expected to call is covered later).

As the concept is novel, many people find it difficult to get the sense of product design data contained in information about needs. An example from our research data may be helpful. Consider the following case of a product innovation for which a product user did most of the innovation work and provided the manufacturer with a great deal of product design data, along with information about his need.

In the late 1950s, IBM designed and built the first printed circuit card component insertion machine of the X-Y Table type to be used in commercial production. (IBM needed the machine to insert components into printed circuit cards, which were in turn incorporated into computers.) After building and testing the design in-house, IBM, in 1959, sent engineering drawings of its design to a local machine builder along with an order for eight units. The machine builder completed this and subsequent orders satisfactorily and later (1962) applied to IBM for permission to build essentially the same machine for sale on the open market. IBM agreed and the machine builder became the first commercial manufacturer of X-Y Table component insertion machines. The episode marked that firm’s first entry into the component insertion equipment business. Today the firm is a major factor in the business.

For process equipment manufacturers or instrument manufacturers, the pattern in the example should seem familiar. We have found that most of the innovative products2 (see Table 1) commercialized in those industries were invented, prototyped, and used in the field by innovative users before equipment or instrument manufacturing firms offered them commercially. In such instances, the manufacturer who takes advantage of user efforts needs only to contribute product engineering work to obtain a first-to-market product innovation. (Preliminary data indicates that this type of user dominated innovation pattern plays a major role in many other product areas as well, including computer software and medical products.

The Reason That Need Information May Contain a Large Amount of Product Design Data

A user will do some of your innovation work, and provide you with new product need information containing a great deal of product design data, if he needs the new product as much as or more than you do. Consider the two-axis diagram in Figure 1. One axis represents the level of return on innovation investment (ROII) a user of an innovative product might expect if he made the investment to develop a given product. The second axis represents the level of ROII a manufacturer of that same product might expect if he invested in its development. The marker on each axis represents the minimum ROII which would induce a product user or product manufacturer to do the innovation work on a given product. Dotted lines from each of these minimum return markers divide the total innovation return space into four segments, namely:

1. (Upper left) in which only the innovation user will have sufficient incentive to innovate;
2. (Upper right) in which both user and manufacturer will have sufficient incentive to innovate — where one therefore expects to see cases of both user and manufacturer dominated innovation;
3. (Lower left) in which neither party will have the incentive to innovate; and
4. (Lower right) in which only the innovation manufacturer will have sufficient incentive to innovate.

Having completed the diagram, we can theoretically place any new product innovation opportunity on it at a point which reflects the ROII that opportunity offers to user and manufacturer. (In practice it is often difficult to make exact ROII calculations; nevertheless, ROII diagrams are a useful conceptual tool.) As an example, consider the component insertion machine innovation described earlier. As shown on the diagram, the opportunity to develop the basic invention into a new product was attractive to IBM, the innovative user, but not to the product manufacturer. IBM had to invest more than one million dollars to develop the concept, but justified the expenditure in terms of potential savings through the use of the equipment. The machine builder, on the other hand, could never have justified such an innovation investment in anticipation of sales of only a few hundred thousand dollars. The result of this combination of circumstances — high (estimated) ROII to user and low (estimated) ROII to manufacturer — is that the user did most of the innovation work and then triggered the manufacture of the innovative product by transferring a great deal of product design data to the manufacturer along with information about his new product need.

New Product Need Information and Design Data from Nonusers

Up to this point, the discussion and examples have focused on new product need information coupled to design data which comes from innovative product users. In reality, such new product information can come from any person or group with the incentive to generate it. The development of polyethylene film-wrapped bread is an example of an innovation case history in which a materials supplier did much of the innovation work and gave the product manufacturer need information with a large amount of product design data.

Polyethylene film-wrapped bread was developed by Crown Zellerbach, a materials supplier, to replace the cellophane wrap then used by many bread-baking companies. Crown introduced the film commercially in 1957-58 along with an inexpensive machine adaptor, also of its design, which would allow baking companies to use the new film on their existing wrapping machines.

Material suppliers as a group stood to gain far more from this innovation than did machine builders or baking companies. In 1958, the total potential market for polyethylene bread-wrapping film was about $25 million annually, divided among only a few suppliers. Total one-time sales of machine adaptors, on the other hand, amounted to about $20 million, while annual materials savings divided between hundreds of bread manufacturing companies was only $3-6 million.

Do You Get Need Information Containing Product Design Data? From Where?

It is important to recognize whether your firm gets, or can get, need information containing a significant amount of new product design data. If so, it is a valuable resource which offers you free information that would cost a good deal to generate from scratch.

Finding out whether your firm gets need information containing a large amount of product design data — and, if so, from what source — is most conveniently done in two steps. First, draw ROII maps of the product types that interest you to see whether or not it is in someone’s interest to provide you with product design data. Second, if the ROII analysis shows you should be getting such data, look into the firm’s past history for the need information which triggered your past new products, to see how much product design information was provided, from whom, and how.

Mapping ROII

Mapping ROII cannot be precise. Indeed, many aspects of return important to innovators, such as improvements in product “quality,” are not easily measurable. It is enough to use your understanding of your markets to ask, “Who gained what from past product innovations my firm brought to market or would have liked to bring to market?”3 If plastic bread wrap is a product innovation that interests you, for example, you would draw a three-axis ROII chart because three parties — bread wrap user (bakery), wrapping machinery builder, and plastic wrap supplier — would seem to have something to gain from the innovation. Consideration of the figures given in the bread wrap case would lead you to place the innovation at the point in the ROII chart shown in Figure 2.

As we see, the only significant incentive lay with the plastic wrap supplier. We would therefore predict that the supplier would provide need information to the manufacturer which contains a large amount of product design data. As the case history has demonstrated, this is in fact what happened. As a result, while the ROII for the manufacturer was below the minimum acceptable had he undertaken the entire innovation job, the return on manufacturing a plastic bread wrap machine product became quite acceptable when the material supplier had undertaken the risk and expense of developing the product.

Of course, receiving free product design data in instances where one’s ROII would be attractive even if one did have to shoulder the entire innovation investment would be even more desirable. You may be able to find such instances as well by looking in areas where your ROII and that of some other parties are both high. Areas of the ROII map which would be most attractive to a bread machinery manufacturer, therefore (to continue with the example), are shown as shaded Figure 3.

Get the Past History of Your Successful Products

Suppose that your ROII map exercise shows that there may be new product need information containing free product design information potentially available in product categories of interest to you. The next step is to study a sample of past product successes to see what need information containing product design data was available at the time. By discovering a historical pattern, you will learn what to look for in the future.

The process of getting a proper sample is a technical matter beyond the purview of this article. (The references listed at the end of this article can be helpful in such an analysis.) However, it is important to look at a sample of ten to twenty cases in order to make a valid judgement about product design data you might expect in conjunction with new product need information. A judgement made on the basis of just the one or two product histories which come to mind, no matter how successful those products were, will almost inevitably be misleading.

After ascertaining the kind of need and solution information you have — or could have — obtained in the past which led you to your present line of successful products, place this data against a chart of stages of the innovation process such as is shown in Figure 4. Figure 4 illustrates how this is done by placing the innovation case history presented earlier against the stages of the innovation process. Note that in this instance, the user has done everything except product manufacturing and sales.

Typically, the work necessary to bring an innovation from the idea stage to the marketplace is divided between yourself and others. If the pattern is consistent from case to case, and our research shows that often it is, then you will want to organize to do only that portion of the innovation process which history shows you actually do. If, for example, the pattern you find in your firm looks like the one shown in Figure 4, you have learned that you do only product engineering in house and so should only hire product engineers. If instead you hire engineers skilled in the earlier stages of the innovation process, they will want to exercise their skills and will repeat the R&D, at your expense, that the customer has already provided you for free.

The same approach applies to marketing research. For example, consider a recent conversation we had with a major consumer goods company. The company had established that its highest payout products had been innovative rather than product repositionings and repackagings. The conversation focused on how to plumb the consumer’s psyche, until we asked if there was another source of data representing a later stage of the innovation process which might also be tapped. Upon examination, the answer was “Yes.” Each of the more innovative products under discussion had been preceded by a similar product put out by a small company! Analysis of the “experiments” performed by these small companies could provide the major company with much richer need and product design data than consumers could provide via interviews. Note that the company could start the innovation process over from scratch, but what a waste!4 (See Figure 5.)

Getting Your People to Recognize the Facts

While it is easy enough to use the ROII mapping and case sampling approach to prove that a particular firm has sources of need information which also provide free product design data, it is often difficult to convince a firm’s product development group that this is so. Consider the reasons why the casual observer might think that the product manufacturer is the innovator, even when it can be proved that the product user was, in fact, the innovator:

• New product design data from a user which is noted and utilized by your new product group may happen only once per new product. On the other hand, instances in which your people train customers to use the product are as frequent as sales, and continue for the lifetime of the product.
• Everyone is surrounded by advertising that says, “Process Electronics Co. introduces a terrific innovation to the market for the first time.” Process Electronics only means that it was the first to produce and market the product commercially. But in the absence of countervailing advertising by the inventing users and suppliers, it is natural that the impression develops that the manufacturer is the inventor.
• Prototypes developed by users or suppliers are seldom manufactured as received by a manufacturing firm. Firm personnel will typically contribute some product engineering work to the prototype in order to make it more reliable, manufacturable, etc., while preserving the operating principles of the prototype.

Since there is no sense in expensively redoing what you can get for free, it is important that your people understand the situation, at least enough to make effective use of such design data.

Organizing to Match Up With the Source of Your Need and Product Design Information

In addition to learning how much product design data is contained in the need information available to your firm, it is important to learn where the useful need information comes from, how it comes, and at whose initiative. Data on these matters can also be derived from the sample of past innovations. Once the pattern is visible, the organizational changes needed to match up properly will be clear.

To give the flavor of what we mean, let’s walk through an example. Consider a study we did of the nature and source of need information leading to product innovations in two categories of process machinery — machines used to make semiconductors and machines used to make electronic subassemblies. Our first step was, as we have suggested to you, selection of a sample of new products developed in the past which were very successful — the type you might want your firm to come up with in the future.

Our second step was to carefully search for the product design data content and source of the need inputs which lay behind each of these successful new products. In the case of our process machinery sample, we found the need information came overwhelmingly from product users and, in about two-thirds of all cases, contained product design data on field-proven prototypes of the new products. So far so good — but how did the manufacturer get this need information and product design data? We studied our sample of cases further and found two main patterns:

• In 35 percent of the cases, manufacturers got the data from innovative user customers who did not mind sharing process know-how. While selling their existing products to these users, the manufacturers took the initiative to ask user engineers: “What have you done that’s new and useful lately?” Usually the engineers were happy to explain.
• In 26 percent of the cases, manufacturers were sought out by innovative users and given the need and design data because the innovative user needed an outside source of supply for an equipment innovation. Usually in these cases, the user chose to deal with a manufacturer from whom he had bought in the past.

Interestingly, in another 26 percent of the cases, we found that new product needs plus extensive product design data were available from users had the manufacturer looked for them. But he did not. Instead, he incurred the expense of reinventing what he could have had for free.

Given these patterns, the strategy of a manufacturer seeking new industrial products is clear:

1. He should get into the market with a standard product of interest to innovative users — anything which will allow him to establish a sales and service relationship with the right group of user engineers.
2. He should hire people to deal with users who can recognize potential new products as well as sell the standard line. (Not all of a manufacturer’s sales and service people must meet this standard, only those who deal with innovative users. The sample should identify these key users. In our sample, they were the few user companies with the greatest annual sales.)
3. He should organize his new product development group so that it is easy and normal for new product ideas with a large amount of free product design information to come from sales and service, pass to marketing research for assessment of market potential, and then pass to product engineering, manufacturing, and sales.

This example derives from data generated from our research. Your own best strategy may look very different, but it can be developed with the help of an ROII analysis such as the one described in this article.