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 posted a blog called “Its so cool to be a Reverse Innovator” which I talk about Reverse Innovation – the process by which a company discovers new growth streams by utilizing its natural strengths to develop new products and services in developing countries and transposing it in developed countries with new competitive advantages.

 

I came across this social health innovation, called Embrace; where students at Stanford worked on a design challenge to create a baby incubator that would cost less than 1% of the price of a traditional, $20,000 incubator.

 

 

According to Jane Chen, CEO and Founder of Embrace; about 4 million low-birth weight babies die within the first 28 days of life because their bodies don’t have enough fat to regulate their body temperature. The problem was that traditional incubators are high in cost and require a constant supply of electricity.  Many people that live in rural villages in India for instance have low incomes and limited access to electricity.


 

Chen and her team developed (after much iteration), a miniature sleeping bag that can stays at a constant temperature for up to 6 hours by using an innovative wax-like material with tubes of hot water running through the sleeping bag.   With the baby’s natural heat and the wax-like tubes, the sleeping bag is able to maintain a constant temperature of 37 degrees Celsius (or 98 Fahrenheit).

 

 

Now, if it costs $20,000 for a traditional incubator, how competitive would this product be if it was sold in developed countries like USA? 

 

 

Embrace essentially created a new business model what will not necessarily impact the traditional incubator market.

 

Here is a video explaining the concept and the challenge by Jane Chen:


 

In this presentation we explore the link between business need and customer need and how to innovate (and remove business problems or discover business opportunities) through persona creation and Design Thinking

The below presentation was prepared for IDEO as part of my application for Intership with the company in USA.  It took me couple of months each to prepare for my idea, prototype and come up with the two concept in the presentation
Persona-lene

Step 1: Finding the Users:
The data can originate from several sources: interviews,  observations, second hand information, questionnaires, reports, cultural probes right through to ethnographic studies.

 

Step 2: Building a Hypothesis:
As you start to talk to people, users, customers, stakeholders, you start builld a proposal in your mind. You concern certain facts or observations and what they mean.  Building a Hypothes is entative comes from syntheisis of pattens and themes.

 

Step 3: Verification:
Here we are focus is on finding data that supports the initial patterns and at the same time supports the personas descriptions and the scenario we are thinking of.  Verification is a reality check. When these data are collected, we ask yourself whether do they then support or go against the initial data or hypothesis.

 

Step 4: Finding Patterns: 
Once you have collected raw data from your sources (eg obversation, interviews etc), we start to categorize them.  I good way is via affinity diagram.  The techinque helps make sense of data.

 

Step 5: Constructing Personas:
Once you complete your affinity analysis and group data together, you start to notice distinct charaterics. For example, of the 16 interviews you
conducted, you start to see a person that has elements is “Ambitious”, likes to “Works the system” , “expects to be rewarded for loyalty” and “Doesnt trust advice”.
Once you formed these elements you build a ‘body’ (ie a photo of how this person would look) demographics information, background (education, upbringing which influence our
abilities), Emotions and attitudes and Personal traits.

 

Persona to work very well need to capture not only what a person ‘Says’, ‘Do’ or ‘Think’  but what they are ‘feeling’.

 

Persona Construction is about discovering, understanding and recording peoples behavour, feelings and philosophies.

 

Step 6: Defining Situations: 
This step is a preparation for the scenarios where it is described in which situations the persona will use the system/site/service or which needs the persona has that will lead to a use situation.

 

Step 7: Validation and Buy-in:
This is very important step especially with large corprate orginsation. By asking everybody their opinion and let them participate in the process ensure better buy-in and use. We dont want to be in a sitution we are asking:

 

  • “ What functionality should the app provide?”
  • “ What if the user needs to …?”
  • “ Someone may want to …”
  • “ The system needs these data elements to complete the function.”

Rather you should be asking:

 

  • “ What functionality should the app provide?” to “ Which user goals should this app support?”
  • ” What if the user needs to …?” to “ What is Alice’s primary goal in this scenario?”
  • “ Someone may want to …” to  “ How important is it for Alice to…?”
  • “ The system needs these data elements to complete the function.”  to “ How can we make it easier for Alice to log this event?

Step 8: Dissemination of Knowledge:
Like Step 7, Persona need buy-in and the better you show your stakeholders how and why these are important design tool, the better usage.  To do this requires you to communicate to them. Many projects forget to inform and teach developers and designers how to use the personas, how to think in scenarios or how to use them in the use-cases.

 

Do you know if Step 7 and 8are done?  Once all stakeholders really empathize with your persona –  that is they can really imagine what it he or she is feeling inside.

 

Step 9: Creating Scenarios: 
Scenario or pathway is used to run or apply your persona through.  It is here where your persona becomes most valuable. A scenario is like a story, it has a main character (the persona) a setting (somewhere the action takes place), it has a goal (what the persona wants to achieve), it has actions that lead to the goal (interactions with the system/site/device), and assoicated obstacles that blocks their way to completing their goal.

 

Step 10: Ongoing Development: 
Life keeps changing and so to Personas.  Persona should be revisited to ensure its in touch with reality.  Ideally, if Persona(s) require change step 7 and 8 need to be repeated.

 

Source: http://www.hceye.org/HCInsight-Nielsen.htm

So, what is a Persona?

 

I came across this description about Persons which I find very useful written by the guys at adaptivepath.com. Personas are fictitious people who represent the archetypal qualities of your audience.  They provide targets for design and are generally very effective for communicating design and research activities throughout an organization.

 

Personas are:

  • Drawn from field research
  • Named as individuals
  • Developed for specific contexts
  • Typical and believable

Personas are not:

  • Based on demographics or market segments
  • Drawn from gut feelings about your audience
  • User profiles or stereotypes e.g. “Soccer mom”
  • A magic bullet

Source: http://www.adaptivepath.com/services/casestudies/paycycle/

How do you create personas?

  • Persona are best created from contextual or Individual Interviews often refer to as ethnographic research. You only need to interview around 16 individuals of your target segment to formulate ”archetypes’ (ie model of a person, ideal example).
  • The results of your interview are analysis via affinity diagram to identify and group common patterns and characteristics or attributes. Once the attributes are discovered, you start to apply more of demographic information to your persona and personality.

What are some of the important elements to a personas?

  • Personas are more then just demographic information, a persona needs to capture behavior, belief and philosophy of person. More importantly their motivation or intentions.
  • For example a persona might decide to ‘Join a gym’, the intention is not getting fit (although a good side effect), the primary intention is to ‘put themselves in a place there are might met interesting people. Another is ‘Hungry Person’, their might decide to go a grab fast food, but there intention is to save time to spend with partner.
  • Therefore a persona’s intentions are just as important as the task at hand