Handcraft your Product or Service using a Lean Design Approach
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What is Lean Design Approach and Handcrafting?

If you want your company to truly scale, you first have to do things that don’t scale. Handcraft the core experience to shit! This means you need to get your hands dirty and serve your customers one-by-one. In this podcast, Reid Hoffman talks to Brian Chesky, CEO of Airbnb, and goes through his early work on handcrafting solution. We called it an MVP or applying a “Lead Design Approach“. A way to discover, learn and validate ideas and design a possible product roadmap. It’s actually what we do at HIVERY. But more on HIVERY later.

 

In the podcast, Brian shares the imaginative route to crafting what he calls an “11-star experience.” I often call this “Thought Experiments” and it is an important design concept in applying Design Thinking/Human Centred Design (HCD) thinking to your product/service innovation.

 

Here are my key points of the podcast is this:

 

  •  Find passionate users – they can map your product roadmap. I often call them your “Extreme users.” These are those who are passionate enough to give you honest straight up feedback. The idea is to turn these feedback facts into real insights, these, in turn, are your Design Principles for your future product. It is the minimum you need to design into your solution to address their core pain points.

 

Remember I said “design principles” you are not implementing all their feedback as is. You should not see them as a list of features.

 

  • These are the users who feel the pain the most. These are the users who your product really matters so use to them co-design what is desirable, feasible and viable. The aim is to build your product roadmap for the future but with a focus on what you need to do/build today.

 

Powerful design question to use: “What could we do to surprise you? What can we do, not to make this better, but to make you tell everyone about it?”

 

  • By getting your hands dirty and “handcrafting” your MVP you gain insight never possible. By handcrafting, I mean you are basically going to “concierge-ing” the shit out of your MVP and later on automate (ie add technology, processes etc) what is important and what you need to do to scale and drive efficiencies.

 

  • This means you need to serve your initial users/customers one by one to gain this insight. Sit with them side by side, shadow them, observe them and build empathy and understanding. How else can you gain this insight to the problem?

 

  • With Airbnb, their first 10 customers were based all in NYC, yet they had their office in San Francisco, so they moved and visited them. Not to feel too creepy about entering their customer home, they say they are wanting to learn more about their users and in exchange, they provided them free professional photos to gain access to their users and insight to their service. They go a lot of feedback and ideas.

 

In fact, one of the extreme passionate customers had a booklet of notes for the Airbnb guys. This is what I call serious co-designing with your customers. 

 

  • Use “Thought Experiment” ( Thought Experiment is a process of the imagination used to investigate what may happen). Einstein is most famous for using this mental technique and help them came up with this his theory of Relativity.

 

  • The Airbnb guys used the concept of “11-star experience“. The “Nirvana product/service“.

 

  • The Airbnb guys went door-to-door, meeting Airbnb hosts in person – and shares the imaginative route to crafting what he calls a “1-star experience” to “11-star experience“. Need to think “extreme product/service” as your Nirvana, but build for today and think to scale up in the future. Example: Elon Musk wants to go to Mars (11-star product). How I get there? Need spacecraft, how do I fund spacecraft? Make it and funded by launching satellites for telco in the short term and build components for Mars.

 

  • In the podcast, they (Airbnb) talk about what “a 7-star experience” Through Experiment looks like…You knock on the door. Reid Hoffman opens. Get in. “Welcome. Here’s my full kitchen. I know you like surfing. There’s a surfboard waiting for you. I’ve booked lessons for you. It’s going to be an amazing experience. By the way here’s my car. You can use my car. And I also want to surprise you. There’s this best restaurant in the city of San Francisco. I got you a table there.”

 

As mentioned about, this is the framework is actually used at HIVERY. When we start any Artificial Intelligence (AI) initiative with our customers, we go through a Discovery-Experiment-Deployment approach. We essentially, we combine Science with Design and Design with Science.

 

DISCOVERY

Unpack business needs, data availability and success metrics conducted Thought Experiments a build data and user empathy.

EXPERIMENT

Co-design small experiments to validate system value

DEPLOYMENT

Map out the operational plan for full deployment and support

 

It’s in HIVERY’s DNA.

Enjoy the audio

 

According to IBM, 90% of worlds data was created just in the last 6 years – 90%! Fuelled by the internet generation, each and every one of us is constantly producing and releasing data. Be it ourselves to companies to capturing customer information and sales transaction. The volumes of data make up what has been designated ‘Big Data’. This massive data sets are piling up year on year.   The problem is how to leverage this data to make better decision?

There are three (3) simple stages one needs to unpack to:  Define the Problem, Solve the Problem, Communicate Actionable Results Clearly.

 

 

 

1. DEFINE THE PROBLEM

 

 

The first, DEFINE THE PROBLEM. Speak with any startup or design thinker and they would say fall in love with the problem not the solution. In fact, Albert Einstein was said If I had only one hour to save the world, I would spend fifty-five minutes defining the problem, and only five minutes finding the solution. Coming up with solutions is easier. Solving the right problem and defining can be challenging. This is no different with big data projects and trying to leverage it to make better insightful decisions.

Framing the problem is about defining the business question you want analytics to answer and identifying the decision you make as a result. Its an pretty important step. If not don’t frame the right problem, no amount data or analysis in the world is going to get you the answers you are looking for.

Defining the problem is split into two parts, framing the problem (what your solving to frame) and reviewing previous findings (what worked or didn’t work) to help you refine the problem.

Framing the problem involves asking yourself “Why is that a problem?” . Toyota famously created the “five why’s” technique. Its about understanding the root cause of the problem. Designs companies like IDEO use phases with the words “How Might We…” to help frame the problem.

reviewing previous findings, involves finding out what worked in the past and why things didn’t work before. This also helps refine the problem.

 

 

 

2. SOLVE THE PROBLEM

 

 

The second stage is SOLVE THE PROBLEM. This often thought to be the primary one. This stage where you starting collecting the right variables (i.e. data fields), collecting sample data to test/play with, and doing some basic analysis to test assumptions quickly. This is also similar process as Cross Industry Standard Process for Data Mining, commonly known by its acronym CRISP-DM.

CRIP-DM is a data mining process model that describes commonly used approaches that data mining experts use to tackle problems.

 

 

800px-CRISP-DM_Process_Diagram

 

 

We at HIVERY we use similar simplified version called DEP – Discovery, Experiment/Pilot and Deployment.

 

 

Screen Shot 2016-03-27 at 3.12.50 PM

 

 

3.COMMUNICATE ACTIONABLE RESULTS CLEARLY

 

 

 

The third and final stage is COMMUNICATE ACTIONABLE RESULTS CLEARLY.  If you want anything to happen as results of stage 1 & 2, you got to communicate your results effectively. If a decision maker do not understand the analysis done or what the results means, he or she won’t be comfortable making a decision based on them. With our “communication-challenged” world, communicating sophisticated analytical results effectively and simply makes the world of different.

 

 

A good data visualisation books on this topic is called Storytelling with Data: The Effective Visual Communication of Information by Cole Nussbaumer Knaflic.

 

 

Data needs to be to engaging, informative, compelling. Human often use stories to communicate effectively and help create memorable knowledge transfer.

Lists companies similar to IDEO, Frogdesign, Adaptive Path,  Continuum, Jump, Cooper etc

Credit to this Quora.com post, here is the list…

Product Development & Design

Web & Software Based Product Design

Mobile & Connected Device Design & Development

Service Design Consultancies 

Humanitarian Design & Social Innovation 

Ethnography for Innovation

Design for the Network

I have been recently seeing more and more reviews and stories on the topic of Reverse Innovation.   Could it be maybe Vijay Govindarajan’s recently released his new book entitled Reverse Innovation or maybe Im getting more aware of examples that fit this type of innovation, nevertheless I thought I write something brief.

 

When I think of Reverse Innovation two concepts come to mind.  The use of applied Design Thinking and Lean Start Up methodologies. More I read about Reverse Innovation the more I think about these two methodologies being used to develop products and services under new constraints.

 

Reverse innovation is the process where a product (or/and service) is essentially created, sold and used within a developing market but (and this is where the magic happens)  it is ultimately transposed into a developed market but with significant competitive advantage or changed business model.

 

Why I say it’s a combination of applied Design Thinking and Lean Start Up is because it combines the empathy aspect of Design thinking by looking at a countries environmental characteristics and constraints (i.e. low income, low standards of living, high rates of population growth & dependency burdens, general poor infrastructure and market distribution) and applies an iterative product development approach by wokring on minimal viable product (MVP) to test assumptions, validate learnings and either pivot or progress.

 

There are a lot of examples but the one I came across that I liked was the GE Healthcare and how they went out and asked the question:

 

How might we provide affordable and simple to use high tech-technology health in developing regions?”

 

According a GE report  in India; about 75 percent of medical professionals work in urban centers, leaving 3/4 of the India’s 1.2 population to be served by just 25% and these are most in very rural areas.

 

Backed by GE Healthcare’s strengths including: global infrastructure, strong brand reputation, partner relationships and scientific knowledge; the team successfully developed a low-cost electrocardiogram machine for the India market.  The machine came to a cost $800 compared to hospital-class units that range from $2,000 to $10,000. Either way; that is a cost-savings of 60% to 92%.

 

Now let me ask you this; if you had a product that was 92% cheaper and just as superior on the market do you think you have a competitive advantage?

 

GE Healthcare’s low-cost electrocardiogram has subsequently been marketed and sold in China and in the US with great success – and without losing substantial revenue on their existing products in this category.

 

Key thing for me is that constraints breeds creativity and innovation, and Reverse Innovation is really a way by which a company can leverage its own existing strengths by applying it in a new context that  leadings to new growth streams.

 

Check out the video below:


 

 Further reading