That is the question our managing partner, Eric A. Hiller is asking, as a new father. Maybe it’s just the sleep deprivation, 
but Eric has analyzed the processes of caring for a newborn and thinks he has found a ways he (and you) can use Lean and Agile to make the chaotic process of fatherhood and motherhood a little more predictable and easy.
IndustryWeek apparently agrees, because they just published his article. Click here to read and see if you agree!
IndustryWeek.com has just published a new article authored by Hiller Associates title:
The process of product selection that people do in their personal lives (e.g. shopping on Amazon) is strikingly similar to the process of product development that people encounter in their professional lives. Interestingly, people are often better at making the complex decisions associated with product selection than they are at similar decisions in product development.
There are three things we can learn professionally from our product selection experience on Amazon:
To read the whole article, simply click on the link above to go to www.IndustryWeek.com, or simply continue reading the full text below.
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We just finished the biggest shopping season of the year from Thanksgiving to Christmas. A lot of people were making a lot of decisions about where to spend their hard earned money – mostly for the benefit of others with gifts. During that same period design engineers around the world were rushing to finish up pressing projects – and, probably as fast as possible, because they had a lot of vacation left to use, before the end of the year.
We make decisions every day in our personal and professional lives. But, do we make decisions the same way in both worlds? I don’t believe so. People might argue that decisions made at work involve much more complexity. After all, how much product development is really going on in most homes? However, a lot of product selection is going on in people’s personal lives. When considering complex product purchases, product selection starts to resemble product development in many ways. Let’s take a look at how people (including design engineers) make decisions when shopping (product selection) vs. how they make decisions in the corporate world (product development).
Consider the ubiquitous Amazon.com. Customers’ product selection experience on Amazon is overwhelmingly positive: Amazon scores 89 out of 100 in customer satisfaction, the top online retailer score in 2012. But product selection is *easy* right? Wrong. Look at Figure 1. Product Selectors on Amazon must consider multiple product attributes and, moreover, these attributes mirror the considerations of a product developer very closely. Product Selectors must consider performance, cost, delivery time, quality, capital investment, etc., without any salesman or other expert to guide them. But the really amazing thing is that the Product Selectors using Amazon are able to both prioritize these product attributes and consider them simultaneously.
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So, how do the same people who are Amazon customers typically consider product attributes in the corporate world? Very differently is the short answer, as we see in Figure 2. First of all, people at work do not tend to trade-off product attributes simultaneously, but in series. Moreover, often each functional group in a product company (marketing, engineering, manufacturing, etc.), tends to be concerned with one dominating attribute, almost to the exclusion of other product attributes. How does the typical series-based consideration of product attributes that is common in the corporate world compare to the simultaneous trade-off approach that the customers of Amazon use? Exact numbers are difficult to find, but some sources say only 60% of products are successful. While not a precise comparison, the difference seems meaningful: Amazon scores 89 of 100 on the customer satisfaction index, whereas product companies have 60% successful products.
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Why is this? Don’t people get college degrees to be great product engineers, buyers, etc.? Don’t they get paid well to do these jobs? In contrast, most people have limited knowledge of the products they select on Amazon and spend hundreds or thousands of their own dollars to buy them.
There are at least three reasons why the product selection and product development processes differ, and the corporation can learn from all three.
Which product attribute is more important: time-to-market, product cost, or performance? There’s no right or wrong answer, in general, but there is a right answer for any given situation. The question is: does the product developer KNOW the priorities of different attributes. As an individual shopper, you may not explicitly write down the prioritization, but you know it. Your preferences and value system are welded into your DNA, so it is clear. However, companies are not individuals, but collectives of them. It is the responsibility of the product line executive to make these priorities clear to everyone.
This is similar to requirements engineering, but at a strategic level. Requirements are typically specific and only apply to a narrow aspect of the product. I am talking about the high level product attribute priority. Ask your product line executive: “In general, as we go through our development, what should typically ‘win’ in a trade-off decision.” If the executive cannot give you a concise and simple answer, he has some work to do to earn his big salary. For example, he should be able to say something, such as “We must meet all minimum requirements of the product, but we need to get to market as fast as possible, so we meet or beat our delivery date. Oh, and we need to keep an eye on product cost.”
The product executive needs to write the priorities down and share them with all. In this case, he might write:
This doesn’t mean the product executive will not change the priority later as the conditions change, but for now, the whole organization is clear on the priorities. This sounds very simple, but most people in product development are unsure of what the clear priorities are. Therefore, they make up their own.
The second thing that we learn from Amazon shopping is to consider all the constraints and targets for product attributes simultaneously. As we see looking at Figure 1 versus Figure 2, people naturally do this on Amazon, but organizations typically let a different priority dominate by functional silo. There are often arbitrage points (optimums in the design space) that will allow excellent results in one attribute, by only sacrificing minimally on another attribute. For example, the product executive may have said time-to-market is first priority, but he is likely to be happy to sacrifice one unit of time-to-market for an increase of 10 units of performance. This doesn’t mean that the organization is changing their priorities, but that the strategic priorities discussed above simply function as a guiding light that the product development team pivots around to find the point of maximum value for the customer.
Recent research is revealing the dangerous downsides of our always-on, always-new, always-more information society. To be sure, social media, like all technologies has the potential for adding a lot value. The question is: do you control the information or does it control you. The research featured in Newsweek shows three problems that have grown in importance over the last decades:
To answer this, let’s first ask how Amazon is able to overcome these challenge. To overcome the Recency vs. Relevancy challenge, Amazon ensures that recency is not the default option for the display of Amazon customer reviews. Instead, helpfulness of the review (relevance), as judged by other customers, is the default order. Amazon does not push immediacy. There are no annoying pop-ups offering a deal, if you buy in ten minutes. Certainly, Amazon does make buying easy and fast, but shopping at Amazon from the comfort of one’s home is a relaxing experience that promotes thoughtfulness. Finally, Amazon does not overload the customer with information. This is no small task, given that Amazon may offer literally hundreds of items to the customer among which he must decide. Amazon does this by presenting the information on a huge variety of products in a standard way, and by providing simple and powerful filters that discard large amounts of extraneous information.
In order to overcome these new information challenges in your own product development work, ask yourself these three questions:
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The world of online journals, social media, corporate social networks, and interconnected supply-chain applications is here to stay. It brings a world of new opportunity for better and more up to date information for product development. It also brings a deluge of extraneous information, and we need to accept this and learn to manage this. Amazon.com manages these challenges well. Your product development team can manage these challenges too using the principles outlined above.
One of my fellows in the world of product cost and design, Mike Shipulski, just posted the following:
The general synopsis of it is:
Mike is right. The short term thinking kills companies and actually wastes a lot of time and money – paradoxically.
I would offer the following addition: Short, Medium, and Long term all have their places, but there has to a be a thoughtful and maintained plan for each. You just can’t make a plan today and then look at it in a year. Every 2-3 months, you should be re-assessing and moving the plan accordingly. However, you should not see whipsawing, but just gentle, organic fine tuning as you gain more information.
I also would like for Mike to define the Short, Medium, and Long term. I realize that this changes product to product, but a general guideline would be helpful.
I just read an article on the site “Strategy + Business” called Building Cars by Design. It caught my eye for two reasons. First, the fact that a strategy site would deign to talk about engineering concepts was a pleasant surprise. Second, the article discussed Design-to-Cost and Design-to-Value.
If we strip off the automotive context, the main premises of the article from a Product Cost Management point of view are as follows:
I applaud the authors for opening up a discussion on these topics. However, I feel this article is incomplete and does not tell the whole story about these concepts. It also doesn’t really say how to do any of these things or point the reader to somewhere he can further learn how. Here’s my specific suggestions for improvement.
Regarding the last point, I will do my best to illustrate the problem. Take a look at the figure below in which I graph the value the customer gets from the product versus the price the customer pays for the product. Presumably, the authors in the article are saying that customers would be willing to pay up to the point that the slope of the value/price decreases substantially (the curve flattens). But, that assumes the customer has the money to spend – kind of a Field of Dreams Strategy, i.e. “If you build in value, they will pay.”
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But, what if the customer truly does value a set of features, but he just doesn’t have the funds to purchase all of the value? In this case, we have to concede that there is a Minimum Viable Product (MVP) needed for the customer to purchase. This term, MVP, is most often used in software development and start-ups. It is the minimum set of features and functionality that a product must have to have ANY value to the customer. If you can’t master design-to-cost in your product so that it both includes the MVP features the customer needs and allows you make adequate profit under the price ceiling of your customer, the product will not be successful.
If the customer has less funds than the MVP to deliver in your product, they can’t afford it. Similarly, even if the customer has more funds than the MVP requires, but less than when the value/cost curve flattens, you cannot employ a blind strategy of maximizing value to the flattening point of the curve and price near it. You are still going to have to set your price below your customer’s funds to succeed.
So, are the authors of the article talking about design-to-value to the point that the value/price flattens or to the point where the price ceiling of the customer intersects the curve?
Anyone? Anyone? Bueller? Bueller? Bueller?
