The double diamond
We believe the best way to make significant improvements to patient health, clinician experience, and care delivery is to experiment quickly at low cost - scaling only once we find high impact solutions. Most successful innovations differ substantially from where they started. Since getting it right the first time is rare, small, quick tests are required before system-wide implementation.
Employing a scientific approach toward creating, evaluating, and implementing new ideas helps us learn faster and at lower cost what works and what doesn’t. The iterative and agile approach we use to apply design thinking to care delivery has four components that alternate between divergent and convergent action. This approach is represented by the double diamond.
A disciplined process for creating new value
Projects at the Acceleration Lab move through four phases of work with the ultimate goal of bringing successful innovations to scale.
Phase one: it might work
In phase one, we work to gain a deep understanding of the problem or opportunity space, rapidly test potential solutions, and generate early evidence that we can move the needle. Learning what not to do in phase one is a success as long as we’ve done so quickly and at low cost. Sometimes this is called "failing fast and cheap." Efficiently invalidating hypotheses helps to create a culture of experimentation that enables organizations to succeed.
Phase two: It does work
In phase two, we move from conducting small experiments to testing at a level of scale that will produce the evidence needed for operational stakeholders to invest in the solution. We also work to articulate a business model that demonstrates a clear return on investment.
Phase three: How we work
In phase three, we leverage the knowledge, metrics, and momentum from previous phases to secure funding and support for the solution at scale. Projects graduate when a sustainable infrastructure for the solution is implemented at Penn Medicine.
Phase four: How others work
In phase four, we seek to energize and catalyze other health systems to adopt successful innovations.
The process of innovation is an iterative and conditional one. Where you start, what tools you use, and when you use them will depend greatly on the context of the problem space, who is on your project team, and your access to users and stakeholders. The double diamond framework and the tools highlighted below are a collection of ingredients rather than a linear or rigid recipe for success.
As you move through the innovation process, you will find yourself balancing convergent and divergent thinking and understanding problems and solutions simultaneously. We hope you find this toolkit to be a helpful resource and that you reference it often to help inspire and guide successful innovation.
Contextual inquiry involves directly observing people in context, asking questions, and developing shared understandings of experience.
Conducting contextual inquiry starts the design process but should be done continuously to help you learn more about the problem, how users and other stakeholders define success, and gather the insight you need to develop and evaluate successful and lasting solutions.
Instead of relying on a verbal recount of experience, ask users to show you how they use a product or service. What people say they do is often quite different than what they do.
Observing users in action will help you understand the spectrum of experiences users can have with the same product or service.
Surveys, interviews, questionnaires, and focus groups don’t tell you what you need to know. Prompting users to show instead of tell often reveals what others have missed.
One of the best ways to learn more about a problem area is to experience it yourself. Immerse yourself in the physical environment of your user.
Do the things they are required to do to gain a firsthand experience of the challenges they face. Completing a day in the life exercise will enable you to uncover actionable insights and build empathy for the people you're hoping to help.
Sensemaking involves organizing all of the data and insights you gather through contextual inquiry and design experimentation to identify patterns and themes to guide the direction of your design process. Sensemaking frameworks will help you visually organize data, manage complexity, and communicate project direction with stakeholders.
A journey map is a visualization of a user's process to accomplish a task. Journey mapping involves plotting user actions onto a timeline.
Details on users' thoughts, emotions, and feedback are then added to the timeline to provide a holistic view of the experience or journey. Journey mapping will help you uncover what's working well in the current state and identify key pain points that need addressing.
You can build a journey map based on several users' observations, creating an archetype user journey, or you can use a template in real time as you conduct individual observations of users.
When working on problem definition, you will uncover many interconnected root causes.
To manage this complexity, gain consensus on the problem space, and ultimately scope the project, you can use the problem octopus to organize the problem space visually.
The basic concept is that you start with the head of the octopus, asking, "What is the high-level problem we are trying to solve?".
From there, you can use the five whys to drill down to the next level root causes of that problem definition, building out different tentacles. Continuing to ask "Why?" and "Why else?" will enable you to get to the most granular root causes of the problem.
An assumption is a statement about something that must be true for your solution to work.
When you have defined a solution you'd like to test, ask yourself, "What must be true for this to work?" Once you have a complete list, plot your assumptions on a 2x2 matrix where one axis is how certain you are that your assumption is accurate and the other is how detrimental it will be if it is not.
Mapping assumptions will help you determine what you need to test to de-risk a potential solution. Assumptions that you are uncertain about and that are crucial for your solution to work are your riskiest assumptions.
When assumptions are identified and design experiments implemented, you must employ a rigorous evaluation of outcomes.
Innovation accounting is a framework for tracking assumptions and experiment outcomes to ensure that you're following an evidence-based approach rather than confirming your own biases.
After you have defined a problem and a needle to move, it’s time to start thinking about solutions. Leverage the tools below to trick your brain into thinking outside the box. Traditional brainstorming, where participants simply try to come up with as many ideas as possible, is helpful but often reflects existing biases or perceived constraints. Tools designed for intentional divergence can help teams overcome such limitations to develop novel solutions.
The use of analogy is all about asking, "How would others solve this problem?" Sometimes, the solution to a problem already exists in another industry or setting.
Ask yourself, "How would Amazon, Airbnb, or Warby Parker solve this problem?" If you need to make something go faster, does EZ Pass or Disney Parks offer a useful model? Other times, you might identify elements of multiple solutions that combined could solve your issue.
Shameless plug: Our Accelerators in Health Care Game makes it easy for innovators to leverage the power of analogy and other tools for thinking divergently about solutions.
Human decisions and behaviors are heavily influenced by the environment in which they occur.
A nudge is an intervention that gently steers individuals towards a desired action. Nudges change the way choices are presented, or information is framed without restricting choice - although some nudges do change available offerings to drive behavior change.
To learn more about types of nudges like defaults, active choice, financial and social incentives, and more, visit the Nudge Unit website.
It's time to put your ideas to the test! Rapid validation allows you to de-risk your assumptions by testing them in the real world. Designing simulations and piloting prototypes - even if they are not sustainable - will help you gather evidence quickly and at low cost in context. This will help support your project's direction and uncover things that don't work before any significant investment is made. It can also help you generate the evidence needed to secure resources to keep moving forward.