Successful innovation demands more than a good strategic plan; it requires creative improvisation. Much of the "serious play" that leads to breakthrough innovations is increasingly linked to experiments with models, prototypes, and simulations. As digital technology makes prototyping more cost-effective, serious play will soon lie at the heart of all innovation strategies, influencing how businesses define themselves and their markets. Author Michael Schrage is one of today's most widely recognized experts on the relationship between technology and work. In Serious Play, Schrage argues that the real value in building models comes less from the help they offer with troubleshooting and problem solving than from the insights they reveal about the organization itself. Technological models can actually change us--improving the way we communicate, collaborate, learn, and innovate. With real-world examples and engaging anecdotes, Schrage shows how companies such as Disney, Microsoft, Boeing, IDEO, and DaimlerChrysler use serious play with modeling technologies to facilitate the collaborative interactions that lead to innovation. A user's guide included with the book helps readers apply many of the innovation practices profiled throughout. A landmark book by one of the most perceptive voices in the field of innovation.
Michael Schrage is a Research Fellow at the MIT Sloan School of Management's Initiative on the Digital Economy. A sought-after expert on innovation, metrics, and network effects, he is the author of Who Do You Want Your Customers to Become?, The Innovator's Hypothesis: How Cheap Experiments Are Worth More than Good Ideas (MIT Press), and other books.
This book is supposed to be interesting but ended up as a fairly poor read, because it is littered with snippets of case-studies rather than full-blown detailed case studies. And these snippets does not total up to a statistical case to convince me.
A lot of the ideas were taken from software engineering and computer science, e.g., genetic algorithms, and thus (being in the line myself) must be taken with a heavy dose of skeptism. Some of the example cited like Boeing weight-budget economy is interesting but requires a more in-depth treatment and that's why it's 2-stars and not 1.
Another problem I have with this book is that I don't agree to some of the points like having customers involved in your new products. In a lot of innovations, the customers are not in the best position to know what they want because they cannot predict the future.
Continues to Offer Rationale/Implications Regarding the “Serious Play” of Modeling and Simulation - Schrage’s book is about the ways companies are increasingly using computer-aided models, simulations and prototypes to develop new products and services. However, as he conveys in the preface, the book is as much about the behaviors and social effects surrounding the people involved as they use new approaches and tools for such innovation. In fact, with a diagram on page xv, he shows the importance of the development of a “shared space” in the communication/ collaboration process for innovating versus typical transactional communication.
Within the book, there are three main parts with 4, 3, and 2 chapters respectively. Part I (Getting Real) deals with the economics of innovation and the importance that models and simulation have in testing ideas and reducing cost/risk in bringing new offerings to market. Schrage looks at “spreadsheet software” and its different incarnations, e.g. VisiCalc, Lotus 1-2-3, MS Excel, and its rapid adoption for “deal” design/negotiation/closing as a simple example of such modeling and its ramifications. Part II (Model Behavior) goes into the significance of “who” builds and manages models or prototypes and the critical need for involving different stakeholders in gaining input and acceptance. The author points out important questions such as how will a simulation or model be used to solve a problem and what are the ways it might help envision possible futures that can be effectively managed. Part III (Capturing the Value of Innovation) addresses the worth of modeling and “play” in achieving breakthroughs and the critical aspects of managing power and influence surrounding these activities. Schrage elaborates that resolving “who wins” and “who looses” as a model is developed and managed requires more adaptation than solving related technical issues. He concludes the book with a helpful “Users Guide” with 10 “rules of thumb” for assisting those who aspire to honestly utilize modeling and gain from “serious play” including (1) Ask who benefits? (2) Decide and measure intended paybacks, (3) Fail early and often, and so on.
Among my favorite aspects are Schrage’s mention of business/process models and their use related to organizations and change (due to my consulting background in that arena). For instance, on pages 26 and 88, he relates companies that got considerable value from business and process models vs. solely those for products and services. Also of note for me was his description of prototyping and simulations, on page 171, as not just “bundles of analytic software,” but more like animated films creating narratives with protagonists, conflicts and climaxes that illuminate their subjects and situations.
While Schrage has a more recent book, “The Innovators Hypothesis” that offers a good practical course companies can adopt to innovate, “Serious Play” continues to be helpful in clarifying the rationale and implications of modeling and simulation for business and perhaps other disciplines as well (e.g. see my review of Remodelling Communication: From WWII to the WWW (Toronto Studies in Semiotics and Communication)).
I came across this book by Schrage and really enjoyed it. Simulations playing a big role in NASA or ISRO was known case. But every great company uses it was eye opening and this kind of connects to digital and model based systems engineering.
This book is about innovating in **established organization**. The book, however, does bring some values to startups by pointing out that "it is the kind of 'shared space' that enhances collaboration, which is a core of innovation"
The other interesting aspect of this work highlights the idea that if the models do not cause controversy, the models are not looking at the right set of assumptions. In other words, models that are not challenged are not exploring the right part of the space, and as such are useless before they provide any kinds of results. This reminds me of other research that suggests that good experimental design yields experiments that “fail” about half the time. Experiments after experiment that prove something we already know are not terribly useful and suggest that the limits of the system in question have not been tested.
The main points of the book are summarized in the User's Guide chapter: 1. Who benefits? The corollary to this question is, who stands to lose? Identifying the people/organizations who stand to benefit from a given prototype creates a context for the prototype. 2. Decide what the main benefits should be and measure them. Rigorously. Models and prototypes that are not built for a purpose can become beasts that exist simply because someone created them. A model or prototype is built for a reason. Anything beyond that should be a new development project. 3. Fail early and often. As always, mistakes made early in any development are cheaper to fix than those made later. Failures are also useful to help find the limits of the system being modeled, as mentioned above. 4. Manage a diversified prototype portfolio. It's best to have several types of prototypes, which are managed and used to explicit ends. 5. Commit to a migration path. Honor that commitment. 6. A prototype should be an invitation to play. The sign of a good model is that people play with it. The sign of a great model is that it plays people. 7. Create markets around the prototypes. To manage the work, there needs to be a system to encourage people to play with the models and make changes. Restrictive market rules will discourage play, but unrestricted access may encourage noodling for no reason. 8. Encourage role-playing. The central theme of the book: models are meant for playing, testing ideas, creating conversations, and simply working out problems that can't be solved without some representation (physical or electronic). 9. Determine the points of diminishing returns. How many models is enough? Is the limit on models only specified by time, or is it also the number of models run? The perceived benefit to the customers? 10. Record and review, relentlessly and rigorously. The models and prototypes create conversations. Improvements happen from model to model. This information needs to be recorded to do the best job of managing the work around the models.
The book also warns that modelers need to be aware of who else gets to play with the model, and who else gets input to the model. Schrage's view is certainly slanted toward getting input from as many stakeholders as possible, as early as possible.
Some useful insights but goes all over the place and mixes prototyping and simulation. The chapter on metrics seems to undermine the whole concept of serious play. Rather outdated now, of course, and the examples didn't all stand the test of time.