Evaluating the Continuous Discovery and Delivery Model

The Continuous Discovery and Delivery (CDD) is one model to capture the design process. It is similar to a Lean UX approach in its etic perspective and to a Double Diamond process in its structure. The product manager leads a team continuously through these 5 stages:

  1. Product Discovery 
  2. Prototype Discovery
  3. Product Delivery
  4. Products and Product/Market Fit
  5. Product Vision

Product Discovery

Product Discovery is the first stage in CDD. Its purpose is an idea winnowing function. Throughout this phase, ideas are dreamed up and evaluated against a set of criteria designed to eliminate 4 risks:

  1. Assess Value. Will users buy it (or use it)?
  2. Assess Usability. Can they figure out how to use it?
  3. Assess Feasibility. Can the engineers build it?
  4. Assess Viability. Can stakeholders support it?

Speed is the number one priority in the CCD model. Discovery must be quick and the model expects that the product team spins through many ideas. While Cagan does place some importance on understanding the domain itself, the volume of ideas is primary. The output of this phase is a validated product backlog.

Prototype Discovery

Prototypes are the hinge around which the Cagan model of product design turns. The model equates prototypes with experiments and are to be both quick and inexpensive. This way, a team can learn fast without spending too many resources. In this model, a mature product team will test 10-20 product ideas per week.

The Product Designer handles constructing the prototypes throughout this phase. The prototype is the designer’s “primary canvas” according to Cagan. 

Cagan attempts to draw a comparison of an old and new way of product design. In this old way, he says, prototyping came at the end of a product design.

The main difference today is that we do usability testing in discovery—using prototypes, before we build the product—and not at the end, where it’s really too late to correct the issues without significant waste or worse.

(Cagan, 2017)

He is correct that usability testing is far more valuable prior to launch, but this is hardly a new concept. Don’t Make Me Think, by Steve Krug and published in 2000, outlined the same idea. The fact that Cagan feels the need to address it 17 years later shows that there is still a long way to go for corporations and design teams to fully embrace prototype testing as a design tool.

Product Delivery

Once an idea has been selected and prototyped, the product team delivers a robust, reliable product that can fund a company. The project team concentrates on maturing the product so that it is:

  • Scalable
  • Performant
  • Reliable
  • Fault tolerant
  • Secure
  • Private
  • Internationalized
  • Localized
  • Works as advertised

Products and Product/Market Fit

At this stage, the product is officially released as the smallest possible product that still meets the needs of a particular market. The product manager evaluates the market fit at this stage. This identifies what market size exists and how well the product meets the needs of that market.

Product Vision

The product vision stage is the connection point to making this a continuous process. The vision is a leap of faith and accomplishing it may not be possible and if it is, not for a few years. 

A Critique of the Continuous Discovery and Delivery Model

The Continuous Discovery and Delivery model is adequate for many product teams. Yet there are several cautions to adopting it wholesale.

CDD pre-supposes a domain knowledge no different from the waterfall method Cagan seeks to critique. Unfortunately, these conditions are only present where the team has a long history with the product. Getting this level of knowledge requires many strong, stable teams. If that’s not available, the team will need a robust practice in documenting and sharing work—often frowned upon by Lean/Agile organizations. To get an adequate level of depth of domain knowledge breaks a major concern of discovery in CDD—speed. CDD cannot afford the time to comprehend either the domain, the users, or the products they need.

In the absence of good domain knowledge, where do the ideas that feed a product discovery come from? It’s users telling you what they want, stakeholders requesting pet projects, and/or the product manager’s self reflection. These are dry wells of ideas. While the Continuous Discovery and Delivery model helps weed out the worst of these ideas, it is still vulnerable to the myth of the local maxima. Since the discovery phase focuses on winnowing ideas over exploring the problem, it is easy to find the best of many low-quality ideas. 

The CDD’s standpoint is etic, that is having a company-centric view of the world. A practitioner of this model does not have time to see the context—missing what a successful product means to customers. 

In contrast, models like Goal-Directed Design (GDD) take an emic stance. This perspective uncovers the behaviors, needs, frustrations, and goals that point to the kind of products people will use.

Ethnographer Dr. Sam Ladner describes this difference well. She writes, 

“The emic position puts the research participant in the center. When ethnography is used in the private sector, this means a product based on ethnographic research will solve real consumer problems. Other innovation methods are usually etic; they take the company’s standpoint. Innovation strategies like Six Sigma, Kaizen, and lean production start with the company’s needs. These methods have the company’s standpoint, not the consumer’s.”

(Ladner, 2014, p. 18)

The cultural context gained during an ethnographic study is invaluable to helping avoid many issues that will never be found by assessing value, usability, feasibility, and viability. It belongs to a Designer’s domain of desirability. John Payne outlined some ways of understanding that the emic perspective provides.

  • Cultural affordances – Misalignment with a culture could cause unintentional consequences. 
  • Native Understanding – What an artifact means in one culture may not be the same in all cultures. This applies to products, too. 
  • Perceived Meaning – Understanding one set of mental models and how it may apply to another set.
  • Social Role of Products – What is the role a product plays in society?
  • Ripple Effect – Products often have an effect far greater than what they intended.

While no system can prevent all failed products, taking the time to understand the domain and the user helps the team make smarter decisions.

Despite several strengths and the ability to produce decent products, CDD has its shortcomings. The key is to incorporate more user research and cultural investigation. Absent that, this model relies too heavily on cleaning up low-quality ideas.


Cagan, M. (2017). INSPIRED: How to create tech products customers love (Second edition). Wiley.

Krug, S. (2006). Don’t make me think! A common sense approach to Web usability (2nd ed). New Riders Pub.

Ladner, S. (2014). Practical ethnography: A guide to doing ethnography in the private sector. Left Coast Press.

Payne, J. (2018, October 9). Post–Human-Centered Design: Evolving to a Societal Scale. https://live-epic-people.pantheonsite.io/tutorial-post-human-centered-design/

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