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ScaleneWorks People Solutions LLP (ScaleneWorks), is a Bangalore-based talent management company, which commenced its operations in the summer of 2010 with a vision to build an organization of great value and be among the most respected talent acquisition solution providers globally. Sanjay Shelvankar, CEO of ScaleneWorks was considering the use of an analytical approach to predict renege. Past data from Indian IT companies revealed that 30% of the candidates did not join the company after offer acceptance, which significantly increased the overall cost of recruitment. Sanjay wondered if Analytics could possibly help in identifying the key drivers that influence a candidate in either joining/not-joining a company after accepting the offer, as it would largely help clients save both cost and time. However, there was a risk involved: any error in this prediction could turn out to be a costly affair, as the client could ''wrongly'' reject a potential candidate even without interviewing him/her.

ScaleneWorks People Solutions LLP (ScaleneWorks), is a Bangalore-based talent management company, which commenced its operations in the summer of 2010 with a vision to build an organization of great value and be among the most respected talent acquisition solution providers globally. Sanjay Shelvankar, CEO of ScaleneWorks was considering the use of an analytical approach to predict renege. Past data from Indian IT companies revealed that 30% of the candidates did not join the company after offer acceptance, which significantly increased the overall cost of recruitment. Sanjay wondered if Analytics could possibly help in identifying the key drivers that influence a candidate in either joining/not-joining a company after accepting the offer, as it would largely help clients save both cost and time. However, there was a risk involved: any error in this prediction could turn out to be a costly affair, as the client could ''wrongly'' reject a potential candidate even without interviewing him/her.

Flipkart, the poster child of Indian e-commerce, was an early entrant in the nascent Indian e-commerce market and quickly established itself as the leading company in this space. Flipkart has grown into an online retail giant, valued at over USD 15.2 billion as of 2015. Flipkart has been selling over 30 million products from more than 50,000 sellers in 70+ categories as well as has 30 exclusive brand associations with in-a-day guarantee in 50 cities and same-day guarantee in 13 cities. Flipkart was 33,000 people strong and had over 50 million registered users with over 10 million daily visits and 8 million shipments per month. Flipkart has been putting in much effort and emphasis on the use of Analytics in every aspect of decision making. Headed by Ravi Vijayaraghavan, the analytics team had over 100 data scientists in 2015. Customer churn is a major concern for Flipkart since it has direct impact on Customer Lifetime Value (CLV). CLV is an important measure to differentiate customers, which can further help the organization to manage them effectively. The main challenge in calculating the lifetime value of customers of e-commerce companies such as Flipkart is that the exact life of the customer is unknown owing to data truncation, that is, the actual point in time of customer churn, which may not be identified in e-commerce, since there would be no prior communication from the customer about the churn. Hence, traditional models of CLV calculation may not be appropriate for e-commerce companies such as Flipkart.

We Sell Everything in Software (WSES) Inc. dealt with innovative off-the-shelf products and had a high growth trajectory. They had a healthy pipeline and their annual marketing spend of $500 million was allocated on the basis of conversion probabilities at flat 6% of the expected sales value. WSES did not have a structured approach for calculating sales conversion probabilities - it followed the gut feelings of its marketing and sales team. Therefore, it incurred high marketing cost including travel costs, client visits, time spent by the sales team/technical experts/support staff, and logistics costs. Jack, the CEO of WSES, was worried that despite having such a huge expenditure list, the sales conversion possibilities based on the pipeline was at best an ancillary information, as there was no substance in justifying the ''gut feeling''. Thus, Jack was not too convinced of this method and was exploring multiple options with Ben, Vice President, Marketing. Considering that WSES pursued around 1,000 opportunities every year, which they either won or lost, Jack felt the need to have these data that they had collated over the years validated and thereby interpreted. Thus, WSES engaged Mark with a Ph.D. in statistics to understand if they could determine a structured approach to compute conversion probabilities and devise an optimal way to allocate marketing spend such that even with significant reduction in marketing spend, the objectives on expected values on sales and profits were met.

Spreadsheet supplement for case IMB541.

Mission Hospital started its operations on April 02, 2008 with the aim of providing highest quality patient care facilities to all individuals at affordable rates. This super specialty hospital located in Durgapur, West Bengal, India, specializes in cardiac surgeries. Many of its patients are from nearby states and neighboring countries, and are covered under different health schemes. Among hospitals in India, flat rate for different treatments is becoming popular, mainly owing to healthcare tourism and government schemes. Dr. Satyajit Bose, chairman of Mission Hospital, was considering adoption of a package pricing (flat fee) strategy under which patients would be provided a fixed price for their treatment at the time of admission. This would imply that the package price should be calculated by the hospital on the basis of patient's clinical and non-clinical information available at the time of admission. Flat fee (or package pricing) can result in a loss to the hospitals if they do not accurately estimate the treatment cost for a patient. The hospital faces the challenge of identifying the key factors that drive the total cost of treatment so that it can quote an appropriate price to the patient.

Mission Hospital started its operations on April 02, 2008 with the aim of providing highest quality patient care facilities to all individuals at affordable rates. This super specialty hospital located in Durgapur, West Bengal, India, specializes in cardiac surgeries. Many of its patients are from nearby states and neighboring countries, and are covered under different health schemes. Among hospitals in India, flat rate for different treatments is becoming popular, mainly owing to healthcare tourism and government schemes. Dr. Satyajit Bose, chairman of Mission Hospital, was considering adoption of a package pricing (flat fee) strategy under which patients would be provided a fixed price for their treatment at the time of admission. This would imply that the package price should be calculated by the hospital on the basis of patient's clinical and non-clinical information available at the time of admission. Flat fee (or package pricing) can result in a loss to the hospitals if they do not accurately estimate the treatment cost for a patient. The hospital faces the challenge of identifying the key factors that drive the total cost of treatment so that it can quote an appropriate price to the patient.

Hewlett-Packard (HP) has been a 75-year-old technology leader with operations across 170 countries and an employee strength of over 3,20,000 employees. In 2013, HP launched Actionable Analytics Services (HAVEn) a Big Data analytics platform, leveraging the capabilities of Hadoop, Autonomy, Vertica, Enterprise Security, and n applications. HP enterprise wanted to mobilize the prospective and existing customer base to embrace the HAVEn offering. Historically, large organizations had a fair coverage and influence on the entire sales cycle with them driving need identification all the way through to influencing the purchase decision and purchase. However, recent studies started showing that this was changing, and nearly 70% of the purchase decision was made before engaging a sales representative independent of the offering. The HAVEn team was aware of this shift in trend, and for an enterprise class product, with high initial investment needs and relatively new outlook to how businesses could extract value; the need to influence sales cycle right from stage-one to drive adoption was an important task. Pramod Singh, Director of HP digital analytics and Ayush Jain, manager of HP social media analytics were approached by the HAVEn team to help them identify the most relevant influencers in the Big Data space and help device a strategy of engagement with the same. Topic relevant influencer identification was tough considering the volume, velocity, and complexity of social media content. Quantifying the influence of the brands, thereby enabling comparison and competitive benchmarking was even more difficult. The problem of firstly defining influence, and then identifying influencers relevant to a topic of interest, in real time, using a data source that was high volume, high velocity with little or no structure, was a challenge that enticed Pramod and Ayush to group their best talent pool together.

Spreadsheet supplement for IMB499.

Larsen and Toubro (L&T) was India's largest technology, engineering, construction and manufacturing company. Construction and Mining Business (CMB) sold equipment such as Dozer Shovels, Dozers, Dumpers, Hydraulic Excavators, Motor Graders, Pipe Layers, Surface Miners, Tipper Trucks, Wheel Dozers and Wheel Loaders. CMB also provided the services of equipment installation and commissioning and other maintenance services. Supply of spare parts was critical, since the customer faced severe losses in case of equipment unavailability. Forecasting was done on an ad hoc basis based on the experience of the planning personnel. The value of each spare part ranged from INR 10 to INR 8 Million. It was critical to maintain a correct balance for the spare-parts inventories, since unavailability led to loss of revenues, decreased profitability, customer dissatisfaction and also gave rise to the fake products industry. Excess inventory led to high inventory carrying costs, working capital lock-in and also a possibility of spare parts becoming obsolete. Vijaya Kumar, Deputy General Manager of CMB, had to arrive at a forecasting methodology with an error of less than 10% for the 20,000 odd spare-parts. This warranted for 20,000 forecasting models, however this was not only very time consuming but also very expensive to develop and manage. Kumar wanted to build the forecasting model quickly so that he could roll out the forecasting strategy on a pan-India basis within a few weeks.

Spreadsheet Supplement for IMB495.

The case describes the use of linen at the Apollo hospitals. Apollo Hospital in Bannerghatta Road Bangalore is a tertiary care hospital with a capacity of 250 beds. In 2013, Apollo Hospital spent INR 5.1 million on managing bed lines (consisting of bed sheets and pillow cover). Dr Ananth N Rao, head of quality at the Apollo hospitals thought that the cost of linen management can be optimized using mathematical programming techniques which can have a significant impact on the bottom-line of the hospital. Each bed in the hospital is given two bed sheets and a pillow cover; however, there was 2% additional usage of linen owing to various reasons such as linen becoming dirty, wet, etc. Apollo hospital keeps a safety stock of linen for two days and any linen sent for washing is returned on day d + 2. The objective is to develop a mathematical programming model to minimize the total cost of linen management.

The Akshaya Patra Foundation (TAPF) was founded in 2000 in Bangalore to provide free mid-day meals to the students of government schools. TAPF's kitchen in Vasanthapura provided meals to 650 schools in and around Bangalore benefitting 87,045 children. In 2014, TAPF provided meals to 1.4 million students and by 2020 they wanted to reach out to 5 million students. This massive expansion needs to be achieved without compromising the quality of food provided and simultaneously ensuring that all the key performance indicators such as time of delivery and temperature of food at the time of delivery are maintained as per the specifications. Muralidhar, the head of quality at TAPF along with his team have implemented several quality improvement projects. However, massive expansion plan by TAPF posed a greater challenge to Muralidhar. One of the critical to quality metric in TAPF is the "cooking-to-consumption time'', which should ideally be less than 6 hours. As the number of children to be fed increases, the cooking-to-consumption time is likely to increase. Muralidhar is contemplating use of lean and Six Sigma concepts to ensure that the cooking-to-consumption time is kept within the allowable time limit.

Spreadsheet supplement for IMB483.

Easwaran Iyer, Dean of the Jain University's Business School, wanted to ensure that they admitted the right set of students to their Master of Business Administration (MBA) program, but he was not sure about the parameters that could be used to identify students who were ideal for the MBA program. Jain University received applications for the MBA program from across India and admitted approximately 400 students every year. There had been a steady increase in the number of applications received by Jain University over the years. Placement performance played a major role in attracting good quality students to the MBA program in India. In 2012, over 180 Business Schools in major cities such as Delhi, Mumbai, Bangalore, Ahmedabad, Kolkata, Lucknow, and Dehradun closed down. Although, there could be many reasons for their closure, their inability to place their students played a key role. At the beginning of every admissions season, which began in April and stretched until July, Iyer thoroughly screened the admission seeking candidates and decided along with his admission committee which of candidates were admitted or rejected. Although there was no penalty if a non-placeable student was selected, it would weigh heavily on the institute's reputation. A wrong pick could eventually contribute towards an increase in the number of unplaced students as well as a reduction in the average salary. Moreover, there was the possibility of rejecting a placeable candidate. What made Iyer's job tougher was that he was expected to increase the batch size while also increasing the quality of the admitted set of students. He acknowledged that MBA admissions needed much more analytical reasoning, taking multiple criteria into consideration.

Established in 1983, Apollo Hospitals is one of India's largest hospital chains. In 2014, Apollo had 32 hospitals spread across the country. The focus of this case is of the Apollo Hospital at Bangalore. The quality head, Dr. Ananth Rao was worried about the food bill that accounted for 4% of the total cost and wanted to develop a forecasting model to estimate the demand for food and beverages being served to its patients for breakfast, lunch, and dinner. Accurate forecasting will help them to minimize the wastage of food resulting in reduction of food bill. Apollo served approximately 120 food items from its kitchen. Dr Rao believed that the demand for food was dependent on the occupancy level (number of in-patients) of the hospital. Moreover, he also expected a short-term trend in the food requirement because patients are likely to order similar food during their course of stay in the hospital - this is because of dietary restrictions as also the fact that people would generally not wish to experiment with food in a hospital environment. The profile of the patients in the hospital is unlikely to vary significantly over a period of time and so it is expected that the food trend will not change much with time.