On March 11, 2011, at 2:46pm, a 9.1-on-the-Richter-scale, six-minute long earthquake unleashed a tsunami that ravaged the Tohoku region of Japan, damaging the Fukushima Daiichi Nuclear Power facility and releasing sufficient radioactive material into the air and ocean to make it one of only two "level 7" nuclear disasters in history (second only to Chernobyl). But just how much radioactive material had escaped was not clear. A tense time was made worse by sporadic disclosures of fragmented information. Those who had power or cell service, mostly friends and family outside the region, were glued to their television and smartphone screens, but, by definition, no one could see the radiation they feared. Frustrated by their own desires to know what should have been knowable, three technologists-Sean Bonner, Pieter Franken and Joi Ito-founded non-profit Safecast around a volunteer-centered, open, citizen-science, "crowdmapping" model to monitor radiation levels. With the help of thousands of volunteers, by 2018, Safecast had become not just the "go to" source of information on radiation issues in Japan and elsewhere, but also the vanguard example of citizen science. Yet as Safecast's dataset strengthened exponentially, the sustainability of its financial model weakened. The same open, crowd-based model that made the founder's data collection sustainable was still financially unsustainable. Was there a business model that could sustain the organization financially without undermining their volunteer-based operations, and if so, what would it look like?

Inspired by research linking happiness and productivity, Hitachi had invested in developing new "people analytics" technologies to help companies increase employee happiness. Hitachi had begun manufacturing high-tech badges that quantify a wearer's activity patterns. Data from these devices revealed an unusually high correlation between certain patterns of activity and a person's subjective sense of happiness at work. Unlike mood rings or even facial expressions, both of which were highly unreliable, Dr. Kazuo Yano--the mastermind responsible for bringing ""happiness sensors"" to market--believed he now had the ability to accurately sense happiness. When combined with other sources of data like Outlook calendars or email, Dr. Yano's team could pinpoint with scientific precision which activities, events, or even people generated the most happiness in employees at work. With a firm proof of concept in hand, Dr. Yano was ready to push the business model further. He was rolling out an app to provide personalized "happiness" recommendations to employees, and he was considering other ways to automate the model to bring it to scale. He was confident that the new technology had the power to transform employee happiness and the productivity of workforces, in Japan and beyond, if he could only find the right business model to launch such a happiness movement.

It was October 2013, and global law firm Clifford Chance was coming under fire for the second time in less than a year for reputedly failing to provide a supportive work environment for its female associates. A memo entitled "Speaking Effectively" was just issued to the U.S. offices of the firm and immediately sparked controversy, as some female associates claimed that the gender-specific advice in the memo was condescending and sexist. This controversy came close on the heels of a memo released in November 2012, in which a third-year associate gave her resignation and explained why she was leaving the firm by detailing her unsustainable schedule as both a corporate lawyer and a mother to young children. Both memos were leaked on the internet, prompting bloggers, media outlets, and the public to chime in with their own opinions as to whether the firm was sexist. How should Clifford Chance have responded to these allegations? Was the firm sexist, or were things being taken out of context and blown out of proportion? If the firm determined that it needed to take heed and create a more inclusive culture that better met the needs of its female associates, where should it begin? Finally, how were the lessons learned in this case applicable to corporate America in 2014, where only 5.2% of Fortune 500 CEOs and 16.9% of board members in the United States were women?