Design Thinking for Innovation – Brazilian Market    Design Thinking tool selected: Learning Launch    Challenge: A traditional repair and maintenance national car  service company with more than 100 stores in Brazil was facing  a large competition of regional car service also multinational  tire producers brands. The multinational tire brands verticalized  their company and launch their own stores also amplified their  portfolio beyond tire services (offering complete solution).   The national car service was reducing gradually your market  share and profitability due to the fierce competition and price  war. In additional their stores layouts were seen as old and the  price perceived by customers was higher than others in the  market. Due to the profitability lost they hadn’t enough budget  to invest in their stores or do some marketing investments. So  the challenge was to recover national car service market with a  sustainable growth and profitability in seven months maximum.       Selection: Learning Launch Design Tool  Learning Launch is a process that address a quickly, cheap and  small tests in the real marketplace allowing companies evaluate  with data and facts a new idea, hypothesis, key customers or  an assumption. The learning launch process consist in test  some hypothesis that can solve or address a customer need or  pains in a complex and uncertainty environment. The learning  process should have a multifunctional team plus a skeptic with  a diversity views for better hypothesis value creation,  execution, dependability analysis and scalability evaluation. The  team shoud prioritize some key assumptions to develop a  design test plan determining who will be impact (personas),  how will be the test, test timeframe and test costs for key  assumptions and finally do the tests in a real marketplace. The  learning launch will evaluate if the idea or assumption are true  or false, disconfirming or confirming facts. If the data gathering  shows a true or confirming facts the team can continue the

development. If the data shows false or disconfirming facts the  team can pivot the idea or throw in the trash can.     Application:   We built a multifunctional team with eight different  departments also two key opinion leaders and five clients. We  applied some design thinking tools before such as ethnographic  research (using our stores and competitors stores to observe  some different client behaviors) mapping 05 personas and their  tangible and intangible needs and pains. Also we applied  design thinking brainstorming with visualization tools clustering  and combining the ideas. We developed more than 30 great  and viable ideas that won’t need big amount of investments!  For the learning launch we prioritized 01 persona: Uber and  others app car drivers, 01 region: Small city in São Paulo  interior and 01 idea: Driver Club (free courses | Driver store  week) and establish the learning launch plan with USD 500  cost. We entered in their community of drivers and  communicated the drive car club and benefits also we  established some partnership with suppliers to address drivers  courses inside stores and developed a story telling for all  contact points inside company (front and back office including  company regional social medias). The small test was very  successful. We grew in one month 135% versus the same  month of previous year and 68% versus previous month. After  03 month test the results continues growing (35% more).       Insight: The Learning launch should be well structured  focused to answer questions that leverage the customer  expectation. We can have some distraction during the learning  launches because some people wants to test other tasks  together in the same test and could generate some noise in our  experiment. So as our Design Thinking course explain – Stay in  the question!

Other important insight was to measure and monitor all the  quantitative test results also customer and people involved  satisfaction and emotional gains with a baseline with the same  profile.     Approach: Some companies wants their results in a short  time, with a minimum cost and don’t wait until we have all data  from the tests. As an alternative, we could run tests of some  ideas that our team generated in parallel at different regions,  testing the ideas for different personas comparing the results  of each other and versus the baseline in the same time but in  different samples. With all tests in a quickly time frame running  in parallel we could speed the scale of the best contributors  and achieve sooner the company goals.

