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At a conference in November 2020, the chief executive officers (CEOs) of two exceptional healthcare start-ups-AliveCor Inc. (AliveCor) and Neurobit Inc. (Neurobit)-discussed their paths to innovation: AliveCor, a trailblazing health tech company, had emerged in 2011 with electrocardiogram (ECG) hardware and software that had since garnered global recognition. Neurobit, a digital health start-up, entered the scene in 2018 with sleep biomarker-based health analytics that could predict adverse cardiopulmonary or neurological outcomes. As the CEOs shared their stories, common challenges emerged regarding data acquisition, privacy concerns, and regulatory compliance. Amid their successes, the two companies experienced the necessity of addressing data challenges to achieve AI's full potential in healthcare. They made trade-offs between time and resources amid a rapidly evolving industry and employed various strategies and solutions, from academic collaborations to extensive data collection, in their quest to determine the best strategy to use to overcome the challenges of efficiently and cost-effectively acquiring and utilizing data to drive innovation and gain a competitive edge.

An employee's health crisis affects the whole team, deepening the complexities of management. The authors suggest six research-based recommendations for responding with sensitivity and professionalism when a team member is diagnosed with a terminal illness: opening a dialogue, adjusting work arrangements, educating and preparing the team, planning for business continuity, supporting the team emotionally, and responding to the death of the employee.

When looking to fill a position above entry level, companies have two choices: transfer/promote an internal candidate, or hire from the outside. Anecdote and research alike show that external hires are usually offered a higher starting salary than internal candidates.

When companies consider the entire life cycle of their products, they can get more value from materials and resources and do better on sustainability measures. The authors describe four types of circular business models: extending product lifetimes; tapping idle or wasted capacity; reclaiming material resources; and using resources more frugally. The article discusses the capabilities required to execute each type of model.

OSUM, headquartered in Canada, is a privately held company in the oil and gas sector and enjoys being a significant producer in Western Canada. It is headquartered in Calgary, Alberta. In 2023, Canada was the single largest supplier of imported oil to the United States, responsible for over 35% of US imports, much more than Saudi Arabia, Venezuela, and all the OPEC countries combined. OSUM uses steam-assisted gravity drainage (SAGD) technology to extract heavy crude oil using an advanced form of steam stimulation. Water plays an important role in this extraction process. In an oil extraction plant, there are several interconnected systems that communicate with each other with established controls and interlocks. The plant operator's role is to ensure the plant runs smoothly without malfunctions, breakdowns, and other disruptions. To facilitate this, alarms and sensors are attached to different systems to signal any potential disruption and mandate a call for timely intervention. However, there are times when multiple alarms are set off, creating a conundrum for the operator, who is challenged with prioritizing which alarm to tackle first. Nuisance alarms, such as chattering, can be a source of distraction for the operator. Such distractions can negatively impact plant operations and result in plant downtime, costing the company significant dollar loss. Being concerned about the increasing cases of spikes in alarms, the company tied up with Drishya AI Labs to help solve this problem by leveraging machine learning algorithms so that such distractions could be reduced.

Spreadsheet Supplement for case IM007B

Sequoia Capital, a venture capital firm founded in 1972, quickly grew to become one of the most storied venture capital firms in the world. Fueled by a strong culture, Sequoia's investment track record included the names of some of the largest global successes. However, times were changing. The venture capital industry at large was facing several challenges. Additionally, Sequoia had made some major decisions to restructure the firm. In a market environment in which investors in venture capital were increasingly cautious, Sequoia seemed to be making several changes to their core identity as a firm. What would all of this mean for the future of Sequoia, and would the firm still be able to maintain their historical dominance in spite of several headwinds?

This case study explores how the VINCI Group, a French multinational operating in concessions, energy, and construction, bolstered awareness and adoption rates of new technologies within the organization. Through its separate innovation hub, Leonard, VINCI aimed to foster learning, creation, and experimentation to improve the group's day-to-day activities. However, while the company's highly decentralized structure encouraged entrepreneurial innovation, some argued it hindered collaboration by fostering internal competition instead. Were there opportunities being overlooked because of this structure? And how could Leonard continue to promote innovation in such a large group?

Early on the morning of April 27, 2020, Justin Oppenheimer stood outside the entrance to the lobby of the Hospital for Special Surgery (HSS) Pavilion Building with mixed emotions. On one hand, Oppenheimer, HSS' Enterprise Chief Operating Officer and Chief Strategy Officer, was excited that HSS was only two weeks away from resuming in-person outpatient office visits (i.e. physician visits not requiring admission to the hospital). Since the middle of March 2020, the global COVID-19 pandemic had forced HSS and other hospitals in New York to suspend nearly all outpatient office visits in an effort to slow the spread of respiratory illness. The Outpatient Care Task Force (OCTF) chaired by Oppenheimer had anticipated the difficulty of reopening while the future of the pandemic was still uncertain and made various accommodations, including dramatically limiting physicians' schedules. Simulations run by the OCTF, however, suggested that even with these accommodations, several patients would be forced to wait outside of the Pavilion building. Given HSS' reputation for patient experience and that many patients seen at HSS suffered from ailments that made it painful to stand, Oppenheimer knew that asking people to wait outside of the building would not (and should not) be tolerated for long, particularly during inclement weather. Oppenheimer opened his phone and sent an urgent meeting request to OCTF to see what further adjustments could be made to alleviate this problem.

Firms and investors alike are beginning to recognize the importance of tracking how revenues from existing customers are evolving over time and to appreciate the value in understanding what might explain changes in these revenues. Consequently, in addition to looking at measures such as the retention rate to assess customer base health, they have begun examining a quantity called Net Revenue Retention, or NRR, which measures the fraction (or percent) of revenues expected from a cohort of customers that were actually generated during the period. In this note, we formally define the NRR metric, show how it can be broken down to pinpoint the type of revenue changes taking place, i.e., in what way(s) existing customers are spending differently, and explain NRR's potential role in guiding customer management decisions. The framework presented further highlights how knowledge of NRR can help avoid issues that arise when revenues from newly acquired customers are blended with those of from existing customers, as well as how NRR relates to other customer management metrics, such as retention rate, CAC (customer acquisition cost) and CLV (customer lifetime value). The note provides several concrete examples to illustrate the main ideas presented and the relevance of NRR in practice.

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The present case examines new challenges, associated risks, and the bold decisions that start-up leaders may need to make to navigate through an environment filled with volatility, uncertainty, complexity, and ambiguity (VUCA). Sanjib Jha, a seasoned entrepreneur with experience in several start-up firms, is confronted with this predicament in May 2020. Varun Dua and Devendra Rane started Coverfox Insurance Broking Private Limited (Coverfox) in 2013 as an insurtech start-up with the aim to radically change the Indian insurance market. The company's founders quit in November 2016, leaving a leadership void. The new management continued focusing on the top line by running the business model, but they lost sight of the runway and cash burn, which put the organization's future at risk. Coverfox wanted to be the Razorpay in the insurance ecosystem aggregator. Coverfox had already been dealing with issues such as investor exit, cash burn, and operating costs far exceeding the budgeted levels, and the COVID-19 pandemic further compounded these issues. When the existing management's ability to turn the business around was called into question, the investors appointed Jha, an investor of Coverfox, as its chief executive officer (CEO). In May 2020, a few months after becoming CEO, Jha was faced with a decision dilemma. He had to make a firm choice- to suspend the business operations, sell it off or lower the monthly cash burn of US$1.1 million significantly thus increasing runway and continue toward break even and profitability. How can Jha, the new CEO, manage the confidence of investors, optimize cash burn, increase the runway, and envision Coverfox's future?

At 25 years old, Terence Hon found himself spending most of his time thinking about how to retain the young staff in his company. As a second-year student at the University of Hong Kong, Terence had cofounded GreenPrice, Hong Kong's first sustainable supermarket, with teammates Allison Chan, Ben So, and Cherissa Hung. The venture had found its target customer base among middle-class consumers who were attracted to the concept of purchasing short-dated products at heavily discounted prices. Each GreenPrice store had 1,000 to 1,200 stock-keeping units (SKUs) at any given time, and the supermarket chain saved over 2.55 million items that were set to expire annually. While the eight stores in GreenPrice's retail network were profitable, the high turnover rate among the nearly 100 employees at GreenPrice was keeping Terence awake at night. Terence and his cofounders pondered whether they should have emphasized GreenPrice's social mission more in the recruitment and retainment of its staff, since the commitment to sustainability could be a means to attract young people. They needed to determine whether GreenPrice should favor those who were most capable but were not interested in sustainability or those who were less capable but cared deeply about the environment.

At the height of the COVID-19 crisis, Terence Hon, cofounder of Hong Kong's first sustainable supermarket, GreenPrice, had the option of selling pandemic necessities that were in high demand in addition to his core business of selling short-dated products. Having founded the venture several years ago with teammates Allison Chan, Ben So, and Cherissa Hung when they were still university students, Terence and his cofounders pondered whether they should accept an offer that was tempting for its high margins, even as they needed to determine whether it contributed to their business objectives and their social mission as the first supermarket chain in Hong Kong that sold short-dated products that otherwise ended up in landfills. In addition, while GreenPrice had faced the challenge of high rents in the expensive, real estate-driven city, the ongoing health crisis caused vacancies in shopping malls to go up, resulting in a significant decrease in shop rental fees. Terence and his cofounders needed to make strategic choices on whether to enter the market for pandemic products while determining the optimal locations for expanding their retail network and the customer segments that they should target.

Having a human in the loop is critical to mitigating the risks of generative AI errors and biases. But humans are also vulnerable to errors and biases and may trust artificial intelligence either too much or not enough. Findings from a field experiment by MIT and Accenture suggest that targeted friction in the form of labels that flag potential errors and omissions can direct users' attention to content that should be given closer inspection without sacrificing efficiency.

Soha Hayat, CHRO at GST Retail, a fashion retail brand based in the United Arab Emirates (UAE) that had stores across the Middle East region, had just returned from a monthly leadership review meeting. Although the reviews so far in 2022 had been difficult, the October 2022 review was perhaps the most shocking for Hayat. The Human Resources department had been under severe scrutiny for some months, and in this meeting, the leadership team had categorically stated that HR was slowing the entire firm down. Hayat believed that the problem had much deeper roots than what was being projected. GST was recuperating from a massive slowdown induced by the COVID-19 pandemic, which had begun early in 2020 and persisted throughout much of 2021. In the past few months, as customers returned to shop, sales had grown, signaling recovery. The leadership team, which wanted the company to bounce back quickly and instill confidence in their investors, had set ambitious new targets. This came with its own downside for GST, whose workforce count was at an all-time low. Hayat and her team wanted to initiate a revamp of the HR department through a dynamic technological transformation. The existing software deployed at GST was familiar to everyone but incapable of the transformation that was needed. Recently, Hayat had heard a lot about the capabilities of Artificial Intelligence (AI)-based solutions into HR. However, this was a relative new technology which would require substantial planning and as she leaned back in her chair, the question looming over her was, how should she proceed?