PDF Summary:101 Design Methods, by Vijay Kumar

Professor Vijay Kumar observes that many businesses claim to value innovation, but few succeed in consistently bringing innovations to market. The reason for this, he says, is that many companies don’t understand how to manage innovation—some don’t even realize that innovation can be planned and managed like other types of projects.

This book is Kumar’s solution to the problem. He lays out a systematic approach to innovation management involving the completion of seven innovation tasks. Kumar also discusses a number of specific tools and techniques you can use in the course of completing an innovation project. We’ll discuss his approach, examine some of the tools he presents, and compare Kumar’s advice to that of other innovation experts, like the creators of Blue Ocean Strategy, Zero to One, and Crossing the Chasm.

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Moore emphasizes that the success of your product hinges on the customer’s ability to complete the solution and make your product work, so you may need to provide other parts of the solution as well (or partner with other companies to provide them). For example, if you produce a hydrogen-powered car, you’ll need to make sure your customers can get hydrogen fuel for it.

Kumar’s discussion of assembling solutions from solution elements alludes to Moore’s concept of assembling the whole product. Kumar’s emphasis on assessing which elements provide the most value to your company and your stakeholders complements Moore’s discussion by giving you a basis for deciding which elements to provide yourself and which to supply by partnering with others: The one who can generate the most value should provide the element.

For example, if your hydrogen car company is a small startup without any existing capacity to produce hydrogen fuel on a large scale, chances are a large commercial producer can supply the hydrogen more profitably than you can.

Task 7: Plan to Implement the Solution

In Task 6, you tentatively identified the best complete solution. Now in Task 7, you’ll prepare detailed budgets, schedules, business plans, and marketing plans to implement the solution. This enables you to validate that your solution is actually practical to implement. It also makes the solution easier to communicate, which is important because you need all your stakeholders on board to move forward with implementation. You may need to build and test prototypes of your solution as part of Task 7 to demonstrate the practical viability and value of your solution.

Preparing Your Organization to Implement the Solution

Other authors caution that even once you’ve developed an innovative solution and a strategy for implementing it, guiding your company through the implementation process often presents its own challenges.

In Blue Ocean Strategy, Chan Kim and Renee Mauborgne recommend having a “consigliere” on your innovation team—someone who knows your corporate politics inside and out. Your consigliere’s role on the team is to advise you on how to present your innovative plans to each of your different stakeholders so you can mobilize the support you need to implement your plans.

In The Innovator’s Dilemma, Clayton Christensen argues that the best way for an established company to bring a disruptive innovation to market is to spin off a new organization that operates almost like an autonomous start-up within the parent company. This is because introducing a new innovation often requires completely retooling and rethinking your supply chain. It also means reaching out to new customers in a new market that typically starts out too small to sustain a large parent company. These factors give small start-ups an edge when it comes to introducing new innovations.

Tools to Use on Innovation Projects

Kumar discusses many specific tools and techniques that can be useful for completing each of the seven tasks of an innovation project. In the remainder of this guide, we’ll present some of the more broadly applicable tools and techniques, how they’re useful, and when you would use them.

We’ll start with some graphical tools in this section and then cover techniques that Kumar recommends using in the next section. Note that Kumar sometimes presents slightly different variations or applications of the same tool as separate “methods,” but we’ve combined them in our discussion.

Two-Factor Cluster Maps

Arguably Kumar’s favorite tool (based on how many variations of it he presents and the scope of what he applies it to) is what we’ll call the two-factor cluster map. To create this map, label the two axes of a scatter plot with properties you want to compare. Then, mark on the plot where different products or services you’re researching fall. This may reveal important relationships or opportunities if you find that the dots cluster together in some areas while other regions of the plot are empty.

For example, you might make a two-factor map comparing the price and user base of a certain type of service, as shown below:

In the example plot, the services you’re comparing are concentrated into two clusters: one at a very low price point and one at a moderately high price point. Between these two clusters is an empty region with no offerings. Maybe that void indicates an opportunity in an uncontested region of the market. Or maybe there’s a good reason that no offerings exist in that region. You’ll need more information to figure out why the voids and clusters exist, but the plot allows you to tell at a glance where they exist.

Applications for Two-Factor Cluster Maps

Kumar suggests several uses for two-factor cluster maps in different tasks. In Tasks 1 and 2, he recommends plotting companies and their offerings on maps with different combinations of factors to explore the dynamics of the industry and identify areas of opportunity. Sometimes you can gain additional insights by plotting competing products as dots and complimentary products as x’s or c’s (or any other marker that distinguishes them from competing products) on the same plot.

In Tasks 3 and 4, he suggests plotting users against different combinations of two factors (for example, age, level of income, frequency of use, how long they’ve been using the product, or their likelihood of renewing their subscription) to identify clusters of similar users. These clusters can serve as a starting point for building user profiles.

In Task 6, Kumar recommends plotting your solutions or solution elements with the value they would provide to the user on one axis and the profits they would provide to the company on the other axis. Seeing graphically how much value each solution provides to whom may make it obvious which solutions are most worth pursuing.

Shortform Commentary: Comparing More Than Two Factors

As we just discussed, Kumar’s cluster maps allow you to easily and visually compare any two quantitative aspects of something across a set of options or offerings. But what if you’ve got more than two factors that you need to compare? You could make a whole series of two-factor cluster maps, comparing every combination of factors, but putting together the results of all those different comparisons would still require additional analysis.

A better option might be to use the “strategy canvas” that Kim and Mauborgne present in Blue Ocean Strategy. This alternative comparison tool lets you visually assess the relationship between any number of options using any number of quantifiable factors: You list the factors at regular intervals on the horizontal axis and record the magnitude of each factor for each option with a dot. Then you connect all the dots that represent the same option, creating a profile curve for that option.

Just as a two-factor plot shows similar options clustering together, options that are similar across several factors will have profile curves that closely follow each other. For example, on the strategy canvas below, Product X and Product Y are clearly very similar offerings.

Kim and Mauborgne present their strategy canvas specifically as a tool for comparing aspects or features of a product so you can come up with a new offering that is clearly differentiated from existing products. But, like Kumar’s two-factor cluster map, the tool could be used to compare almost anything in principle.

In Tasks 1 and 2, you might plot profile curves for all the companies in your industry, comparing things like their volume of sales, warehouse capacity, manufacturing capabilities, environmental footprint, and so forth. Much like clustering on a two-factor plot, if you find that many of them have similar profiles, that could indicate either universal constraints or untapped opportunities.

In Tasks 3 and 4, you might plot profile curves for different users with factors like age, income, frequency of use, and so forth to see if there are similar patterns in how all these factors relate to each other across different users. Or you might collect metrics on users’ proficiency with different applications of a product and plot the numbers for each user against the different applications. If you find that many of the profile curves dip down on certain applications, that would alert you to pain points that are common to many users.

And in Task 6, you could plot a profile curve for each of your stakeholders, showing how much value they would get from each element of the solution. This would show you at a glance which stakeholders will likely have similar interests and which ones may have conflicting interests when it comes to choosing the elements of the final solution.

Comparison Table

Another tool Kumar uses extensively to compare properties of different products, services, or options is the comparison table. To build a comparison table, label the rows and columns of a table with the things you want to compare. Then, in the box where they intersect, describe how that row and column relate to each other. This ensures that you compare every possible combination.

If you want to compare several different products, you might list the products as rows and factors of interest as columns, as shown below. You can color-code boxes with similar results to make the similarities stand out.

After doing your initial comparison, you might rearrange the rows as shown below to make similarities and other patterns stand out more clearly. For example, in the table below, it is more obvious that Product X resembles an improved version of Product C, and that there’s an inverse relationship between cost and portability for most of these products.

Applications for Comparison Tables

In Task 1, Kumar recommends using a table to assess trends in technology, business, people, culture, and politics. Use these as columns and add as many rows as you want for different topics or market sectors. Briefly summarize the trends you’ve identified from media surveys or other research in each box.

Kumar notes that comparison tables are useful in Task 4 for identifying relationships and extracting trends from the data that you gathered in Tasks 2 and 3.

In Task 5, Kumar says you can use a comparison table to aid in brainstorming solutions: List the different phases of the product life cycle as columns and the user profiles or personas that you’ve identified as rows. Then brainstorm ways to improve the user experience for each archetypal user at each stage of the product life cycle.

In Task 7, Kumar recommends building a table that lists your company’s resources or capabilities as columns and the different phases of your solution implementation plan as rows. This helps you assess what resources or capabilities will be needed when so that you can develop your implementation schedule and budget.

Shortform Commentary: Using a Comparison Table to Rank Options

Kumar focuses on how you can use a comparison table to identify patterns and similarities between things or to create new ideas. In addition to these uses, comparison tables are also particularly useful any time you need to objectively rank options in order of preference or importance.

To develop your ranking, label the rows and columns with the factors you want to compare—the list on each will be the same. Then, where each pair of options intersects, compare just those two options. Ask yourself, “Is the option on the row better or more important than the option on the column?” If so, put a 1 in the box; if not, put a 0. Then add up the number of 1’s in each row. The higher the number of 1’s, the higher the option in that row ranks, giving you a more objective way to rank all the options from best to worst. This works because it’s usually much easier to determine which option is better when you only have two options to compare than if you’re trying to compare multiple options simultaneously in your head.

For example, if you’re trying to determine what features of a certain product are most important, you might make the following comparison table:

The above table indicates that speed is your product’s most important feature, followed by ease of use, while weight is its least important feature.

The need to rank options may come up in several of Kumar’s innovation Tasks. In Task 1, you might use the table technique to rank different sectors or applications in terms of how promising they look. Then you do further research on the top two or three.

In Task 3, you could have a user fill out a comparison table listing different features or capabilities of a product so you can get a more concrete understanding of which features are most and least important to users.

And ranking your solutions in Task 6 can help you set priorities for prototyping and planning further development.

Techniques to Use on Innovation Projects

As we’ve discussed, Kumar’s “methods” include both tools and techniques. We’ve covered some of his key tools. Now we’ll examine some of his key techniques.

Monitor Key Media Sources

Kumar advises you to stay informed about new developments—not only in science and technology, but also in culture, politics, and other current events—by monitoring media sources and synthesizing relevant information from them. As you summarize key information from the media, periodically discuss this with your team, and keep your media synopsis files in a database or shared folder where everyone can access them.

This is most useful during Tasks 1 and 2, where you’re identifying trends, choosing a direction for your innovation project, and researching your operating environment, but the repository of information that you create will become a valuable reference throughout the project.

Kumar notes that different media sources are good for collecting different kinds of information. Popular mass media tends to focus on current social and political events. Social media shows you what people are talking about and how they feel about issues or products. Scientific journals and other professional publications describe the latest technical developments in a field.

Beware of Fake News

Kumar mentions in passing that it’s important to identify credible news sources as you monitor the media to stay abreast of new developments. But this may be easier said than done. In Skin in the Game, Nicholas Taleb argues that most mass media sources are chronically unreliable because they face no significant consequences if they fail to report information accurately.

Taleb explains that this is because mass media like TV, radio, newspapers, magazines, and even trade journals involve mostly one-way communication: The media transmits information and the audience receives it, not the other way around. This makes it much more difficult for people to hold them accountable than if information was disseminated via two-way communication networks, like an old-fashioned gossip tree. When information flows both ways, people who spread false or inaccurate information soon lose all credibility, and that gives people an incentive to be careful what they say.

Taleb notes that social media is beginning to reintroduce the two-way communication mechanisms that mass media circumvented, giving people new channels to comment on the news, call out errors or misrepresentations, and present counterpoints. So, as you prepare your synopsis of the media, consider summarizing not only the news that gets reported but also how people are reacting to it on social media.

This won’t guarantee that all the information you collect will be accurate, but at least it will make you aware of errors that other people have already caught. It may also give you a better understanding of how people think and feel about current issues, which may alert you to additional user pain points or other opportunities for innovation.

Watch Users in Action

As Kumar explains, you often gain special insights from watching someone do something. These are discoveries that you would never make by just thinking through the process or talking to users about it. So setting up real or simulated scenarios for users to interact with the product is a powerful tool for deepening your understanding of users’ experiences. This tool comes in handy during several of the tasks of innovation.

During Task 3, when you’re learning about your users, Kumar recommends watching them work with existing products—preferably in the setting where they normally use them, although staging specific scenarios for them to work through at your facility can also be useful if you need to focus on a specific issue.

In Task 5, observing how users interact with a prototype or simulation of one of your solution elements may give you ideas for additional improvements or other solutions. In Task 6, it can help you evaluate solutions, and in Task 7 it lets you validate that your solution will work the way you envisioned it working.

Use Prototypes and Simulations

Kumar discusses different types of prototypes and simulations that you might use, depending on what you want to study. A “behavioral” prototype uses props, actors, and role-playing techniques to simulate how users would interact with a product before any physical prototypes of the product are built. Similarly, he says that just sketching a product or scene showing users interacting with it can help to make the concept more concrete in much the same way that a prototype does.

Meanwhile, a “concept” prototype is a physical prototype that embodies at least one key characteristic of a solution concept so that the concept can be studied. Kumar further divides “concept” prototypes into two categories. “Appearance” prototypes look like the solution concept so you can evaluate the look and feel or user interface of the product. “Performance” prototypes demonstrate how the product would actually work. He notes that some prototypes are a combination of the two.

Experiment on Users with Minimum Viable Products

In The Lean Startup, Eric Ries elaborates on how you should go about observing users and building prototypes. While Kumar’s prototypes are similar to the prototypes Ries recommends building, Ries adds that you should approach testing your product ideas on users scientifically by first forming a hypothesis and then creating a product to test it:

Based on what you know (or think you know) about customers needs, demographics, market data, and so forth, come up with a testable hypothesis, like “20% of women over 50 would be interested in [my new product] at a price of $75,” or “A product with [this feature] would reduce the time it takes a mechanic to repair [this automotive problem] by an average of 3 hours.”

Then test your hypothesis by launching a “Minimum Viable Product” or MVP and observing how users interact with it. Your MVP is a prototype that provides everything you’ll need to test your hypothesis without any additional features that would add time or expense.

One type of MVP Ries describes is a video simulation showing off your product and how it works. If you don’t have a working prototype, use artwork or computer-generated graphics to show how the product will work once you get it working. This correlates to Kumar’s “appearance prototype” because it lets you assess how people would react to the product’s appearance by how they react to the video.

Even if you need a fully functional prototype to test your hypothesis, Ries says your MVP could implement it on a very small scale: Instead of rolling out a service to thousands or millions of users right away, start with just one customer and make sure your service meets her needs before you worry about figuring out how to scale up. This would be an MVP version of Kumar’s “performance prototype” since it lets you test the functionality of the product on a minimal scale.

You can also build MVPs that appear to be fully functional from the user’s perspective even though behind the scenes you’re performing functions manually that the final product would have to perform automatically. Providing this kind of MVP helps you understand what the product actually needs to do to provide value to customers before you invest in developing technology or infrastructure to meet those needs. This could be considered a version of Kumar’s “behavioral prototype” since it lets you test hypotheses about users’ behavior.

Hold Workshops

In addition to product usage simulations, Kumar discusses a number of workshop activities that can be helpful at various stages of the innovation process.

In Task 3, where you’re working to understand how your prospective users think and feel about things, Kumar recommends compiling a folder of photographs showing a variety of people and items in different situations. Then, set up a workshop where you ask users to organize the photos thematically or arrange them into a sequence that tells a story. When they’ve finished, have them explain their choices to you. This may reveal feelings or associations they harbor that you would’ve overlooked otherwise.

For example, maybe you ask them to pick out photos they would associate with good customer service versus bad customer service. You might notice that the “good” photos they pick out are all brightly colored, while the “bad” photos tend to show drab, sterile, office settings. This reveals something about how the setting in which their service needs are addressed impacts how they feel about the service.

(Shortform note: Kumar points out that using photos in workshop activities can give you additional insight into how people think and feel about things or associations that they draw between them. In Brain Rules, John Medina observes that vision is your dominant sense, which may explain why photos or other visual aids can help to bring additional insights to the surface: More of your brain is devoted to processing visual information than to any other sense. As such, images often evoke more vivid impressions and associations than other stimuli, like written statements or survey questions.)

Similarly, in Task 3, Kumar suggests designing workshop exercises to incorporate cultural artifacts—things that have social significance in a particular culture. For example, maybe a certain card game is widely popular within a certain culture. So, at a workshop designed to engage users from that culture, you pass out decks of cards and ask them to select a card that expresses how they feel about the purchasing process, the user interface, and other aspects of the product or how they interact with it. Their responses will give you insight into their culture and how it colors the user experience.

(Shortform note: Be careful how you use cultural artifacts so you don’t offend your workshop participants. In So You Want to Talk About Race, Ijeoma Oluo describes ‘cultural appropriation’ as a form of microaggression that people from marginalized races or cultures often face. Cultural appropriation is when someone from one culture (especially a dominant culture) makes use of something that has symbolic significance in another culture (especially a marginalized culture) without properly understanding its significance or giving due credit to the culture that originated it. As such, making use of cultural artifacts in a workshop without fully understanding their origins and symbolic significance runs the risk of offending workshop participants through cultural appropriation.)

In Task 5, Kumar says sometimes you can make your brainstorming sessions more effective by turning them into a game. For example, you might create several decks of cards: one that lists a user profile on each card, one that lists a certain aspect of the product on each card, one that specifies a certain use case for the product, and one that specifies a certain stage of the product life cycle. Players are dealt a random assortment of cards from all four decks and get points for coming up with unique solutions for the situations represented by their cards.

Optimizing Your Games

With the advent of the video game industry, game design has itself become a field of active research. If you decide to use games as workshop activities and to generally boost productivity, it may be worth your while to study game design theory so that you can make your games effective.

In A Theory of Fun for Game Design, game developer Raph Koster postulates that, fundamentally, games are fun because they give you the opportunity to learn new “patterns” in an environment where the consequences of failure are smaller than in real life. By “patterns” he means skills, behavioral patterns, or principles of nature—especially those that enable you to predict events, increase your social status, increase your power over your environment, or other things that, at least historically, enhanced human survival.

He says humans have evolved to enjoy learning these patterns. But when the stakes are high, we often prefer comfort and security over the fun of experimenting and learning new things. Games exploit this principle by allowing us to learn new patterns that affect the outcome of the game but don’t have significant consequences in real life.

Since all of Kumar’s innovation Tasks involve either learning about patterns or developing new ways to generate value, entire innovation projects could arguably be construed as large, complex games, based on Koster’s theory. In this light, perhaps the key to stimulating performance on these projects is to ensure that the consequences of failure are minimal. Some of the strategies we’ve discussed up to now (like building MVPs) are designed to do just that by keeping costs low until you know you have a winning product.