Fall 2017 — Week 03 Process Journal

Gestwicki and McNely: A case study of a five-step design thinking process

In this paper, Gestwicki and McNely describe the process through which a group of university students developed a game for a museum while following a scrum development process and validating their product with potential users and the museum staff. After having a potential minimum-viable-product developed, the students found during playtesting with potential users that the game mechanics and functionality, while useful, did not align properly with the process and goals that the museum’s education department had. This led to a redesign of the mechanics, and goals, which ultimately proved to be beneficial to the goals that the museum had set for the game.

The fact that the students did not really empathize with the museum’s education department early on, was a big problem — education resources used by museums have very specific goals, and most of the time follow prescribed processes, which would not be considered by students coming from a very different background and potentially biased by other kind of games. I also thought it was interesting how one of the students drew a comparison with her learnings through SCRUM and university — where one is expected to learn, demonstrate knowledge, and move on, rather than learn through experimentation and iteration, which seems to be a pervasive challenge with education.

Questions

- Can education leverage a model where iterative and process learnings are embedded in an iterative model and still fit into timelines and class scope?

- How can the value of iteration can be articulated to school systems in a way that encourages a shift in education?

- What metrics/KPIs are useful to convey the effectiveness of iteration in education models?

Bill Moggridge, Designing Interactions — Designing Something New

Moggridge starts the chapter with an extremely complex and dense statement: “if you’re going to create good designs, you first have to understand people”. He then proceeds to describe some challenges, like the bias to design for oneself, or to know when to stop research and start with first approaches to solving the problems/needs.

Midway through the chapter, Moffridge presents a design process composed of: understanding constraints, synthesis of the context and nuances of the research, framing of the ideas/concepts in a way that is clearly articulated, ideation of multiple approaches to solve a problem or need, envisioning the idea in the context, uncertainty that refines the idea (affordability/dependencies/intuitiveness/etc), selection of the approach to take or solution to develop, visualization of the solution at a deeper level than the envision stage, prototyping so that the idea can be tested, and evaluation of the prototype so that the idea can be further developed or pivoted.

Although the framework proposed by Moggrodge is accurate and useful, in practice (from personal experiences) the envisioning and visualization phases tend to be either internal to designers, or very brief as they are presented during design critique. It is nevertheless useful to be aware that as a process, they exist.

Questions

- How can the value of certain activities that can be perceived as “low value” such as envisioning and visualization be articulated for a business leader?

Ivy Eisenberg, Lead-User research for breakthrough innovation

In this article, Eisenberg raises an interesting point — not only should companies meet with their customers to understand needs, and wants, but there should be a closer partnership with a special type of customer: lead users. These are not the average users of a product or service — they are the most advanced and proficient users that push the product to its limits and can communicate these as well as future needs of their organizations. Lead users are “motivated to innovate in order to solve [their] own problems rather than to sell a product or service”, and therefore should be considered strategic partners when defining product roadmaps or identifying unmet needs from an organization using a product/service.

The framework to do lead-user research that Eisenberg proposes consists of:

1. Focus on needs of leading-edge users, not the average user

2. Seek not only data for needs, but for innovation too — user developed solutions by leading-edge users.

3. Seek needs and solutions in adjacent markets and nonobvious, analogous markets, in addition to target markets.

4. Employ a cross-disciplinary team, bringing in perspectives from various parts of the organization.

The interactions with the lead-users tend to be more exploratory and abstract rather than mechanical description of activities: “they are in the spirit of “What do you know?”, “What do you think?”, and “What is your intuition?” The interviewers aim to understand the perspectives and insights of the interviewees, seeking out stories that are rich in concrete examples”

A few interesting proofs that Eisenberg uses are the 3M case, where a majority of projects that identified lead-user research needs or opportunities ended up becoming funded products, and Lego which incorporated community feedback including that from lead-users, which became new product lines.

Some of the challenges for this approach are:

- Finding the right people: Reaching the real lead users and lead-use experts.

- Getting the right people to answer the e-mail or phone call.

- Remaining open-minded about problems and solutions.

Questions

- How can a startup, without the large presence or foothold with customers, find and work with lead-users in large enterprises?

- How can a startup divide its limited resources to be able to adequately iterate just the right amount to identify, prototype, and validate its solutions for the needs/opportunities?

Non-class reading: A low-flying pet supplies company just sold to PetSmart in the biggest e-commerce sale ever

Chewy.com — a startup that sells dog and cat food was recently acquired by PetSmart for $3.35B. Personalization (handwritten thank-you notes), as well as an extremely attentive and responsive customer support (one sixth of its entire workforce) helped Chewy gain a pre-acquisition market share of 43% of the online pet food sales, compared to a 48% from Amazon.

Chewy successfully identified a market that could be disrupted by leveraging the love people have to their pets, and capitalized on the opportunity to use a high-customer focus on their approach to sell pet food, making the entire process a satisfying, personalized (more adequately, a pet-onalized) experience.

Given the perceived quality of service, as well as their customer base, Chewy was acquired before it went public.