In business school you spend a lot of time learning about the idea of value, which is surprisingly slippery — the value of a firm, an idea, a product, a service. Because of this you need a cross-section of disciplines to approximate value — marketing, strategy, statistics, law, operations, innovation, economics, and finance being the most common. And so you start to learn marketing frameworks about customer value, how accounting recognizes value, how the market estimates value, how to use financial valuation models, strategic approaches to creating value, business models to capture value, the ins and outs of Porter’s value chain, the rampant focus in the 80’s on increasing shareholder value (thanks Jack Welch)… you get the drift. Value is a thing. If you can contribute to creating, capturing, or approximating value, business wants it.
In the last decade design, inspired by Stanford’s d.school, has started to infiltrate MBA programs in the form of design thinking while Jon Kolko’s 2015 HBR article, “Design Thinking Comes of Age” heralded its arrival in the corporate world. Combining restraint with a focus on users, artifacts, and prototypes, Kolko positions design thinking as a way for organizations to embrace ambiguity and increase tolerance of failure. In this view, design thinking promises to cut through complexity and boost innovation, which both seem like valuable things for a business to be able to do.
What’s been important about the emergence of design thinking aside from the capacities it creates is that it points to the activities of design as a source of value, instead of focusing solely on the products of design. To me this is an important distinction and increases the relevance of design to business exponentially. It also means that design activities, when made visible as a source of value, have the potential to be learned and used across the entire organization.
Questions about the value of design are usually expressed as some variation on, “what return are we getting on our design investment?” In an attempt to answer this at face value designers try mapping traditional ROI calculations onto revenue streams or cost savings that design might impact. What is the expected revenue of the new product? What are the cost savings of the new design system? We look for metrics that will help us answer the question of ROI but in the process miss the forest for the trees. We contort ourselves into these ROI shapes thinking we are being good business allies but in the process we forget that the value of design is not just in the outcomes, but in the process of designing itself.
I was at a conference for design leaders recently and several hallway conversations came up around the challenges designers face once they have a proverbial seat at the table. I’ve been around the block with these but something new was emerging. Design leaders were lamenting how much design was a blocker to doing business! Seriously. Like, “we have to be good business people now that we are in leadership positions and wow, design sure gets in the way of that!” It’s anecdotal but I suspect the lack of intelligibility between design and business might be part of this story. Engaged in the process of designing the value of design can feel so tangible, but when everyone else in an executive meeting is sharing speedometer dashboards of progress, what do you do?
Dashboards (speedometer or otherwise) are fed with quantitative data. And quantitative data is super useful for modeling the health of a business. And wow do business people love models (and frameworks, let’s be honest). But the thing with models is that they are all wrong. Useful but wrong. I bring this up because for a long time, as a designer, I was intimidated by financial models and business metrics thinking they reflected a hard reality design didn’t have access to. The handshake secret is that there is no hard reality. Income statements and balance sheets are designed just as much as a chair or an app. Generally accepted accounting principles (GAAP) provide guidelines to how financial statements must be prepared, but there is a lot of creativity in how revenue can be recognized depending on your intent (raising venture capital, preparing for an IPO, buying back stock, hiding a Ponzi scheme, etc).
So here is what I’m driving at: we will never be able to talk about the value of design using ROI because we’re not really talking about design, but the output of design. I’m interested in finding models that help us talk about the value of doing design, which is entirely possible given the mutable nature of business artifacts. But before we can talk about models, we need to reframe design as a method of learning.
Designing as Learning
In Design Methods J. Christopher Jones talks about the idea of designing as learning, as “a way of answering one of the questions that must be answered if one is to get from the ignorance-of-the-new, with which one begins, to the knowledge-of-the-new, with which one ends (knowledge of ‘what the problem really is’ as well as of solutions).” People engage in design when they intend to create change in some future state. This usually starts with formal or informal inquiry. As a way of exploring this inquiry a designer might materialize their intention in some capacity to explore the suitability of both the inquiry and the potential solution in order to learn whether it the impact matches the intention. Reflection on the outcomes will reshape the inquiry and likely refine or change it in some way, kicking off the design cycle anew. In this approach to the design loop we move through inquiry, creation, and reflection.
Experience is also learning. Experiential Learning Theory describes a four step cycle through which we learn from experience in order to consciously choose, direct, and control our life. Unlike the pedagogical style most of us were subjected to in American public schools, experiential learning puts our experiences to work as a source of doing, feeling, watching, and thinking. In the design loop we are creating as a means for reflection and in the experiential learning cycle we are acting as a means for reflection.
The diverging and converging that happens in the experiential learning cycle is mirrored in the Double Diamond. Given the cyclical nature of experiential learning the Double Diamond starts to look like a trigonomic visualization of learning cycles mapped over time as if it were a sine wave:
There is a remarkable amount of commonality among these models that involve intentionality, interaction, engagement, and reflection. But most importantly they incorporate a form of doing that requires embodiment. We have to act or create in the world to complete the iterative cycle of learning (and designing).
Design, Real Options, and Risk
So back to this question of value (and models). Why is learning through designing valuable to a business? By embracing ambiguity and exploring divergent futures, design activities can increase flexibility and decrease risk. Let’s go back to the idea of ROI.
ROI is a simple model for estimating whether or not a project should be invested in based on discounted cashflows (DCF) and net present value (NPV). It looks out into the future and says, what type of revenue do we expect this to generate? And how much will it cost? Money in the future isn’t worth the same as it is today so you have to discount those future cashflows back into today’s dollar and subtract the costs to gain an understanding of whether to invest or not. This approach is exceptionally rigid and requires a lot of decision making up front and a commitment to a single direction.
In business school one of my favorite classes was called “Risk and Real Options”, an exploration of financial valuation through a study of options theory and how “real options” — business opportunities evaluated through the lens of options theory — can provide strategic value in a portfolio of products by embracing volatility and deferring decisions. Good-bye fixed futures, hello flexibility. And this is good because these days the world is pretty much 100% VUCA (volatile, uncertain, complex, and ambiguous), 100% of the time.
So if we’re dealing with a VUCA world you can start to see how calculating ROI based off of a 5 year projection and discounting back to today’s dollars using NPV is actually quite risky. A lot can change in 5 years! And yet traditional NPV is fully committed to a particular outcome. Real options, however, are all about flexibility. Instead of committing to a single future, real options give us the ability to “buy” the option to many futures. As time passes the value of certain futures will be “in the money” while others “out the money” at which point we can make a decision to commit to one path over another, learning as we go. An article from the McKinsey Quarterly about the value of real options even makes the statement that “… the option valuation recognizes the value of learning.”
Deferring decisions is only valuable if you are actively learning as you go. And real options allow you to learn. There are a number of different option pricing models, but the one that made the little light bulb go off was the Binomial Options Pricing Model (BOPM). BOPM uses an iterative pricing approach with two possible outcomes at each iteration. This is visualized in a binomial lattice whose output would look something like this:
Each ‘step’ in the lattice is a point of reflection where you can decide whether or not to continue investing in the project. Real options allow you to learn! As my professor Peter Ritchken says, “you should think of the project as an investment in an option. If you learn good things, then you exercise the option and win big. If you learn bad things, you walk away after the information becomes available.”
I started out this whole mess by talking about business and design and value and learning. The dots start to connect when you think about mapping the divergent and abductive sense-making of design activities onto the binomial lattice, both fanning out into a future of unknowns. Rapid iterations through the design loop could feed into decision points at each step in the lattice. Liberated from the need to predict the future, design and real options create value through learning and delayed decision making. By removing the need to make all decisions up front you increase flexibility, decrease risk, and embrace volatility.
Going back to Design Methods, J. Christopher Jones writes that “[t]he purpose of any method of designing, orderly or muddled, is to get one’s mind to become familiar with the unknown possibilities and limitations of ‘the new’ before making irrevocable decisions.” I find myself in this scenario on a weekly basis, using design activities to determine what decisions (both strategic and tactical) can be delayed and what we would need to learn to make them at some point in the future.
The intention in sharing where I’m at conceptually with these reflections on the value of design is to get a read on what resonates, what needs explicating, and what isn’t working. I shared a really rough version a few weeks ago in my newsletter which spawned some good conversations — early indicators this framing is useful. I’d also like to give a super big thanks to Chris Avore, Scott Berkun, Scott Taylor, and Lindie Gerber for their insights and feedback.
What isn’t clear to me yet is how to start mapping design activities more concretely to the concept of real options. Visualizing the relationship between the lattice and the double diamond, understanding how learning loops can inform decision making, and thinking about the practical application of these models the next big area to dig into (I’ll be sharing more via Medium and in a few talks I have coming up). And last but not least, if you are a kindred spirit who is interested in this type of work, let’s chat.