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The case highlights the challenges encountered by Laura Williams, founder and owner of Williams HR Law, a firm based in Toronto, Ontario, providing a full range of legal services on labour, employment law, and human resources (HR) matters. Demand for the firm’s services grew exponentially in 2020 following the tragic death of George Floyd and due to the ongoing workplace challenges encountered during the global pandemic. Williams faced decisions regarding the best and most sustainable ways to address increasing demand. She had solidified her reputation in the marketplace as an “advocate-of-choice” and was mindful of ensuring that her growth decisions did not negatively affect her brand or impact the organizational culture she had proudly developed. She was committed to ensuring that her growth aligned with her purpose—to provide best-in-class legal support that enabled clients to make informed decision-making and diffuse workplace issues before they escalated.

This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of confounding variables. Then it walks through the steps to designing an experiment, including a discussion of how to calculate the power of a test.

In 2021, Amazon announced its market entry into Portugal with a dedicated offer. The dominant local electronics retailer, Worten, had been expecting and preparing for this move for years. The company had driven a digital transformation program and extended its e-commerce offer, which culminated in the building of an online marketplace that sold Worten products and third-party products. Over time, the marketplace extended to new categories, allowing customers to purchase a broad range of products. E-commerce had not been very popular in Portugal compared to other countries, but that changed with the Covid-19 pandemic in 2020, during which Worten knew how to serve customers in a safe and quick way, and which boosted e-commerce adoption. Worten also continued to lever its dense network of physical stores across the country to provide fast delivery and service options to customers. They hoped that this high level of service would be a great differentiator against Amazon and protect Worten's leading market position.

The case captures the experience of a customer in a service failure incident when ordering a Porsche Taycan, and the recovery process managed by the local dealer. It outlines in detail the customer's journey from first contact in a test-drive to placing the order, and finally, taking ownership of the new car. Descriptions include the negotiations and interactions between the customer and the salesperson in addressing the service failure and its recovery. The case unfolds with the head of Customer Relations at Porsche learning about the incident from a routine customer satisfaction report. Key decisions faced by the manager involve conducting a root cause analysis of the incident as well as finding recommendations to improve internal processes in handling customer complaint and in recovery. The case covers concepts of root cause analysis, double deviation in service failure, theories of justice in service recovery, customer satisfaction management, and on a secondary level, dealership management.

On July 1, 2020, the co-head of the logistics and planning department at Marico Ltd., based in India, was reviewing reports on various issues related to stock inventory and warehousing. After studying the reports, he found that both lost opportunity and warehousing costs for the company were high. Compounding the problem was the ongoing COVID-19 pandemic, which had added pressure to the company’s impending cost pressures. Initially, Marico Ltd. had thirty-three warehouses. However, after the Government of India introduced the Goods and Service Tax in 2017, various state taxes across the country were eliminated. The new law revolutionized the logistics industry and allowed Marico Ltd. to reduce the number of its warehouses to twenty-five. Could the company further reduce the number of warehouses without adversely impacting service levels?

On July 1, 2020, the co-head of the logistics and planning department at Marico Ltd., based in India, was reviewing reports on various issues related to stock inventory and warehousing. After studying the reports, he found that both lost opportunity and warehousing costs for the company were high. Compounding the problem was the ongoing COVID-19 pandemic, which had added pressure to the company's impending cost pressures. Initially, Marico Ltd. had thirty-three warehouses. However, after the Government of India introduced the Goods and Service Tax in 2017, various state taxes across the country were eliminated. The new law revolutionized the logistics industry and allowed Marico Ltd. to reduce the number of its warehouses to twenty-five. Could the company further reduce the number of warehouses without adversely impacting service levels?

Bail funds, organizations that collect money to post bail for community members who are eligible for cash bail to stay out of jail until the time of their trial, have grown throughout US history, buoyed by major civil rights events such as the Red Scares, Civil Rights movements, Vietnam War Protests, among others. Given the volume of potential community members who would benefit from bail fund assistance and the plethora of defendant information required to process the bail payments, such funds like the Springfield Bail Fund face a logistical and management challenge.

Bail funds, organizations that collect money to post bail for community members who are eligible for cash bail to stay out of jail until the time of their trial, have grown throughout US history, buoyed by major civil rights events such as the Red Scares, Civil Rights movements, Vietnam War Protests, among others. Given the volume of potential community members who would benefit from bail fund assistance and the plethora of defendant information required to process the bail payments, such funds like the Springfield Bail Fund face a logistical and management challenge.

Dr. Jay Jayson, an orthodontist, had recently completed renovating the waiting area of his office and now needed to decide whether he should also renovate the treatment areas. He considered the advantages and disadvantages of his current clinic setup: he thought that the reception environment was comfortable, and that the patients felt confident in the treatment and process, but he was concerned about the impact on patients of any delays in care. He also realized that he had one new patient consultation room that could be pulled into service as a treatment chair. Would hiring more registered dental assistants help him treat more patients? Was there another way to see more patients without renovating the office?

Presentation for product W26091.

Dr. Jay Jayson, an orthodontist, had recently completed renovating the waiting area of his office and now needed to decide whether he should also renovate the treatment areas. He considered the advantages and disadvantages of his current clinic setup: he thought that the reception environment was comfortable, and that the patients felt confident in the treatment and process, but he was concerned about the impact on patients of any delays in care. He also realized that he had one new patient consultation room that could be pulled into service as a treatment chair. Would hiring more registered dental assistants help him treat more patients? Was there another way to see more patients without renovating the office?

The Serum Institute of India (SII), the world’s largest vaccine manufacturer by volume, faced a unique challenge in the manufacture and distribution of COVID-19 vaccines to its major stakeholders. SII had COVID-19 vaccine manufacture and supply commitments to COVAX, a joint initiative ensuring equitable access to COVID-19 vaccines for all countries and a transfer technology (licensing) agreement with AstraZeneca PLC to supply its COVID-19 vaccine. However, a sudden surge of COVID-19 cases in India during the second wave of the pandemic sharply increased demand for COVID-19 vaccines in the country, forcing the government of India to temporarily ban the export of vaccines from India. At the same time, a ban imposed by the United States on the export of critical raw materials and components used for vaccine manufacturing threatened to bring the vaccine production process at SII to a halt. SII’s chief executive officer had to now juggle meeting domestic demand within India and fulfilling SII’s international supply commitments. Failing to deliver on the commitments would not only spell legal trouble but also pose long-term reputational and business risks for his company. He had few options to navigate the situation.

In 2014, ProGlove emerged the third-place winner in Intel's "Make It Wearable Challenge". The ProGlove team of four who had met at the Technical University of Munich in Bavaria, Germany, had submitted the idea of a "smart glove," which was a barcode scanner, motion detector, and RFID reader connected to the back of an industrial-grade work glove for use in high volume manufacturing. The idea was based on observations of BMW's assembly lines, where each item had to be scanned before being assembled. The process involved finding a scanner, picking it up, scanning the component, and then putting away the scanner again. A smart glove could achieve this more quickly and ergonomically, optimising worker productivity and allowing extra steps in quality control to be included in the production. The team eventually walked away with US$250,000 prize money from the competition. A visit to the Consumer Electronics Show in the US in early 2015 made them realised there was interest in their product not only from manufacturing companies but also from the logistics and service industries. The company grew, developing a sturdy and easy-to-use smart glove with bar code scanning capabilities. Customers eagerly adopted the new glove, benefitting from the combined improvements in speed, quality and ergonomics for a relatively low up-front cost for just the scanner and glove. In 2018, the new CEO, Andreas Königs, brought the company's focus back to the software side, and launched the new "ProGlove Insight" in March 2021. ProGlove Insight combined hardware with software that was capable of analysing the glove's data and making it available to the management for advanced analytics and decision-making.

Arnie Katz, chief product and technology officer at StubHub (SH), was helping to lead a contest intended to result in innovative and valuable new ideas. Product managers presented more than 100 new business initiative proposals to create new value for customers and provide additional revenue streams and differentiation opportunities. The secondary-ticket (resale) market in the United States was becoming increasingly fragmented, and SH was losing market share. It was imperative to move SH from being a trusted platform for conducting ticket-resale transactions to becoming an integral part of fans' experience of live events. This case is intended to be used in conjunction with a technical note on product-market alignment (PMA): ""Product-Market Alignment"" (UVA-OM-1706). Katz and his teams conduct successive rounds of investigation and data gathering across the three dimensions of PMA: defining the customer need, identifying business value, and evaluating operational capabilities. This case also presents a bridge between high-level operations strategy and a more granular discussion of process capabilities. Agile software development is discussed. This case is suitable for operations-management classes focusing on Agile, scale-up, product and project management, emerging technology, and new product development. It can be used with a graduate, undergraduate, or executive education audience.

The ability to achieve product-market alignment (PMA) differentiates businesses that will thrive from those that will fail. Yet many find it difficult to create-and sustain-products that continuously generate value, even as their markets change. Traditionally, managers seeking to develop new products or reexamine current offerings have relied on frameworks that compare customer views on the desirability of various product features to the financial potential of those features. This note expands this common approach to explicitly include the consideration of operational resources and capabilities. This includes the resources needed to develop the product or service and to deliver it. An organization's operational capabilities can dictate whether, how, and which potential new products can be built, so it is important to understand the interplay among marketing, finance, and operations when developing new products or refreshing existing ones. The framework in this note is useful both when developing new products and reexamining existing offerings. This note can stand alone, but works well when used with a case, ""Product Development at StubHub: Don't Stop Believin'"" (UVA-OM-1705), that explores a company's efforts to innovate and create new value for its customers.

Swedish technology start-up Primateria AB (Primateria) was founded in November of 2004 with the main idea to provide science-backed consulting services for cutting-tool producers and end-users. What had started as a consulting service without the need for assets turned quickly into a production-driven service to support the cutting tool supply chain. The company had managed to consistently grow without external capital, had automated processes, opened a second physical location, and added physical vapour deposition coating capabilities. For the road ahead, the owners had to now decide how to protect Primateria’s intellectual property and how to meet the need for localized services for their large international clients quickly.

Data preparation is a necessary pre-processing step in analytics. It aims to clean the data from various resources and improve its quality for better productivity. This process includes many tasks such as fusion, cleaning, and augmentation of data. This teaching note will focus on illustrating data cleaning using the programming language Python, with all codes completed in Google Laboratory. Different solutions using the programming languages R and Microsoft Excel are also provided. To effectively illustrate the data preparation process, the relatively simple dataset Bengaluru House Prices is used. This is a relatively messy dataset with a few variables and many records, making it ideal for explaining data preparation steps.

In March 2020, Evolko Systems Private Limited encountered several strategic and operational effects resulting from the outbreak of the COVID-19 pandemic. The private health care technology company, which was based in California, United States, used artificial intelligence and machine learning to provide products and services to India’s health care market. The company’s chief executive officer had to mitigate risk from the pandemic using his company’s business model and value offerings. The outbreak of the COVID-19 pandemic, which resulted in a lockdown order effective across all of India to slow the progress of the virus, affected some of the company’s key business elements and had a macroeconomic impact on its operations. The chief executive officer’s challenge was to explore all options to continue the business operations and to determine how to transform its physically interactive business model to one with little or no physical contact with clients.

In 2019, the Brazos Valley Food Bank (BVFB) in Texas increased its distribution and food-storage capacity and was delivering food to food-insecure people in six nearby counties through its partner agencies. While the number of food-insecure people in each of these counties was relatively stable, the food distribution capacities of BVFB’s partner agencies and the food supply fluctuated. As a non-profit organization, BVFB needed to equitably distribute food across all the counties it served, but it first needed to decide how to define “equitable food distribution.” Which parameters, food needs, or costs should it use to calculate this? How could it ensure that its food distribution did not favour one county over another? Was equitable food distribution achievable for BVFB at all?