• Supply Chain Analytics to Manage Blood at VHS Blood Bank, Spreadsheet Supplement

    Spreadsheet supplement for case IMB819.
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  • Supply Chain Analytics to Manage Blood at VHS Blood Bank

    Rotary Central TTK-VHS Blood Bank, situated in the premises of a multi-specialty hospital named, Voluntary Health Services (VHS) in Chennai, is a supplier of safe blood and blood components to various hospitals across Chennai. VHS is a non-profit organization serving the needy sections of the society. It procures blood from voluntary donors by organizing blood donation camps at various places in Tamil Nadu and separates blood into its components after appropriate testing of the collected blood. It also makes arrangement for regular blood transfusion for Thalassemia patients in its hemophilia center. Since blood and blood components are perishable and have a short shelf life, accurate forecasting of demand for various components of blood is essential. Due to gap in supply and demand and perishability of blood components, Athmanathan, CAO (Chief Administrator) of VHS Blood Bank felt that the data could be used to predict the future demand on a daily basis and to help in planning blood donation camps accordingly.
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  • Using Markov Chain to Forecast Sales Booking - Spreadsheet

    Spreadsheet supplement to case IMB757
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  • Using Markov Chain to Forecast Sales Booking

    We Sell Everything in Software' WSES Inc. is a products company and specializes in software solutions for different industries such as defense, clinical research, consumer goods, capital markets, security, banks, and insurance among others. One of the divisions of WSES focuses on enterprise software product. Every quarter, Jack Williams, CEO had to give forecast of sales to the stakeholders for the enterprise software product division. The forecast which he had given for the last quarter was USD 2.4 billion whereas the actual sales booking was only USD 1.48 Billion. Jack wanted more accurate forecasting of sales and he had a discussion with Michael Summers, the CFO. Michael explained to Jack that this was something which was not in his hand since he was taking the numbers from Ben Osborne, Vice President of Marketing. Ben explained to Jack that the process they were following was taking the last quarter's sales and adding their estimate of 1.5% to it. Jack did not approve of this method. He felt that since WSES has such rich sales data over the years, they should be having a way to hear what the data is saying. They engaged Mark, with Ph.D. in Statistics, to understand if they could find a structured way to forecast the sales number based on historical data available with WSES.
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  • Testing Marketing Hypotheses at WSES, Spreadsheet Supplement

    Spreadsheet supplement to case IMB693.
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  • Predicting Net Promoter Score (NPS) to Improve Patient Experience at Manipal Hospitals, Spreadsheet Supplement

    Spreadsheet supplement for case IMB649.
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  • Predicting Net Promoter Score (NPS) to Improve Patient Experience at Manipal Hospitals

    Manipal Hospitals, which was started in 1953, had the advantage of being the "oldest" healthcare group in India. In six decades, the group could establish the reputation for being ethical and patient friendly. In 2017, Manipal Hospitals catered to around 2 million customers from India and overseas every year through their tertiary and secondary care facilities. In 2017, MHE managed an aggregate of 5,200 plus beds among 16 hospitals, over 13 locations across 6 states in India and one hospital in Klang, Malaysia. The Group's acute care flagship quaternary care facility located in the heart of Bangalore, India's IT capital was set up in 1991. The 680-bed Manipal Hospital at HAL Airport Road provided care in over 60 specialties under one roof. Ajay Bakshi, MD and CEO of Manipal Hospitals strongly believed that the word-of-mouth (WOM) is much stronger than any other type of promotion and thus it is important for MHE to keep customers informed about the improvements. With the improved system for feedback collection, he was confident of moving towards a more tangible outcome from feedback collection. Collecting Net Promoters Score (NPS) and tracking the trend of NPS was an integral part of patient care at MHE. He also believed that closing the loop is a central theme of the Net Promoter Score and thus NPS should be pivotal to understanding the deficiencies in the system and improving it. Ajay believed that NPS score itself is just the tip of the iceberg. The real value was provided by understanding what leads to the NPS score, especially the causes of detractors and promoters and asking follow-up questions on the reason for the score. It provided a gold mine of information which can be used to improve patient care.
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  • Branding and Bollywood: The Behavioral Route to Branding Films

    Ami Shah who works with social media promotions associated with Bollywood movies was interested in obtaining behavioral insights with a comparison between '`Gulaab Gang" and '`Queen'' (both these movies are based on themes associated with women). '`Gulaab Gang'' was a box office failure while '`Queen'' was a major hit. An attitudinal survey among the viewers of each of these films forms the behavioral input to the case study. Amidst the high visibility campaigns of films in Bollywood, Shah believed that behavioral aspects of movies is something that has not been explored much with respect to branding of films. How can these behavioral inputs on movies enable lessons to be learnt on branding? Can a framework for branding be suggested from the analysis based on the behavioral analysis?
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  • Forecasting Demand for Food at Apollo Hospitals, Spreadsheet Supplement

    Spreadsheet supplement to case IMB463.
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  • Breaking Barriers: Micro-Mortgage Analytics Spreadsheet Supplement

    Spreadsheet Supplement for IMB445
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  • Central Parking Services Private Limited Spreadsheet Supplement

    Spreadsheet Supplement for IMB451
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  • Central Parking Services Private Limited

    Central Parking Services (CPS) with headquarters located in Bangalore, India provided parking solutions at various malls, office buildings, airports, residential apartments, hospitals and so on throughout India. In 2013, Poornima, Director of new initiatives at CPS, wanted the company to take a strategic direction toward using analytics to strengthen its operational decisions. The company was growing exponentially and with that came the challenge of managing the high pressure of growing demand, clients' expectations as well as driving end-customer satisfaction. The company was struggling with operational issues such as demand supply gap and waiting time at the entry and exit gates of parking lot. Pricing and manpower planning are two important decisions CPS has to make to ensure profitability of the company.
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  • Breaking Barriers: Micro-Mortgage Analytics

    Providing affordable housing to a rapidly increasing low income group population in Urban-Semi Rural India remains one of the biggest challenges as well as opportunities faced by the Housing Finance Sector. Several new housing finance companies such as Shubham Housing Finance have pioneered a "small ticket" loan product to address the market gap. They recognize that these customers are not "high-risk" as perceived by conventional financiers, but "unknown risk". To assess this "unknown risk", they rely on detailed, field-based verification rather than on formal financial documentation. The primary objective of this case is to analyze the past data from these field level interactions and the eventual credit evaluation decision to determine the factors which result in a favorable decision. The application scoring model is expected to deliver a competitive edge to Shubham's operations by enabling faster decisions earlier in the assessment phase, targeting applicants more likely to pass through to the credit worthy status, standardize applicant evaluation across the nation and enable Shubham to offer competitive products. The objective of the case is to predict the probability of loan sanction using the socio-economic attributes of prospective loan applicants by employing techniques such as chi-squared automatic interaction detection (CHAID) and binomial logistic regression.
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  • DOSA KING: A STANDARDIZED MASALA DOSA FOR EVERY INDIAN

    Indian Foods Fermentation Limited (IFFL) was established in 1992 by Narayanan to develop an expert dosa maker that will be used in fast food restaurants, "Dosa King". According to market research carried out by IFFL in 1992, on any given day, 20 million dosas were consumed in India. Narayanan and his colleagues at IFFL decided to develop an automatic dosa delivery system that would deliver standardized dosa at an interval of 30 seconds. The system requirement was that the dosa should have the same size, color, crispiness, and taste. The project was funded by venture capitalists and Narayanan had to take several decisions during the design and development of automatic dosa delivery system. The Dosa King was intended to be a mass-distributed item, and the number of retail points across the country was meant to be in excess of 10,000 within 5 years from its launch in 1992. The IFFL realized that their largest stakeholder would therefore inevitably be the retailer or franchisee who invested in dosa machines, batter, and masala, and also interfaced with the customer. The IFFL conducted a market survey to capture the "voice of the customers" for the dosa delivery system and identified various system requirements. At various stages of product development, Narayan had to take several key decisions related to the design and development of machine, decision on inputs for preparation of dosa batter and other accompaniments, etc. In 1992, India did not have any western fast food chains. India went through a period of major economic reform in 1991 and the economy started growing much faster after the nineties. Narayanan expected the demand for fast food to grow in all major cities of India. Equipped with his experience at Coca-Cola and Nestlé, Narayanan was confident that he could change the restaurant industry in India.
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  • 1920 Evil Returns - Bollywood and Social Media Marketing

    Ami Shah, founder of IntelliAssist, helped clients to create social media marketing strategies for their products or services and assisted them in the execution of these campaigns. In 2012, Shah had designed the social media marketing campaign for the Bollywood movie ''1920 Evil Returns'', which was a sequel to the movie 1920 that was released in 2008. The next movie in the 1920 franchise was expected to be released in 2014. She was analyzing the impact of the campaign and wondered whether the right social media mix had been used. The social media campaign for 1920 evil returns was very successful and she had the numbers to show for it. Active fan engagement and positive word-of-mouth also validated the success of the social media campaign. However, Shah wondered whether she could have done it differently. Was the spending-mix effective? What strategy should she adopt for the next movie in the franchisee tentatively titled, ''1920 London''? Ami had used a mix of social media for running the 1920 Evil Returns campaign which ran for 45 days. Facebook and YouTube were primarily used for the social media campaign. Google Ads were used on popular Bollywood websites such as Bollywood Hungama, SantaBanta along with news websites such as India times, Hindustan Times and Rediff.com. Total social media spend was INR 0.95 million. Ami had to decide on the next movie's 1920 London digital marketing strategy based on the analysis of 1920 Evil Returns.
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  • Apollo Hospitals: Differentiation through Hospitality

    Dr. Ananth Rao, who heads the Quality Department at Apollo Hospitals, Bangalore, had undertaken initiatives to measure and benchmark the hospitality services at the hospital. In-patients spend around 80% of their time under the care of the staff from different departments such as nursing, housekeeping, food & beverages, operations, and so on. The Quality team at Apollo Bangalore received 1,434 complaints from the 1,38,600 in-patients treated between March 2011 and December 2012. The feedback was generally open-ended, in the form of patients' comments, opinions, or suggestions. Of the 1,434 complaints received, the housekeeping department received the maximum number of complaints, while the dietary service had the least number. Some of the complaints were genuine concerns, while some were related to minor discomfort. Some of the complaints were very specific, while some were generic. All of these were analyzed, which would enable the hospital to work towards reducing the overall number of complaints. Text analytics was used to analyze the open-ended complaints. In order to gain deeper insights, "Defect-Defective" techniques were used to identify the processes that caused the defects. The processes were re-engineered to eliminate all the defects and a pilot study was done using the "Define Measure Analyse Improve and Control" (DMAIC) cycle. Dr. Rao and his team have developed benchmarks for several common complaints with three levels of service by adopting the Kano model. Critical to Quality (CTQ) metrics have been defined and Sigma levels were calculated for each CTQ. Dr Rao is pondering on what is a good Sigma score target to set given the importance of hospitality in Apollo Hospitals.
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  • Consumer Choice between House Brands and National Brands in Detergent Purchases at Reliance Retail

    The case analyzes the consumer choice behavior in the case of detergents sold in an Indian retail store, Reliance Retail. The protagonist, Parul Khanna, the house brand (private label) manager at Reliance Retail wanted to know whether promotions have any short-term or long-term impact on brand switching and customer retention. Sudz, the house-brand detergent sold by Reliance Retail, was envisioned as a cost-effective detergent, giving comparable wash results as some of the established national brands such as Surf, Rin, Ariel, and so on. The questions nagging Parul were: Could customers who had been habitually purchasing a certain brand for many years really consider a house brand and make that switch? Is there a need to interfere in the market and create a "catalyst" effect? Students are expected to evaluate the impact of promotion on brand switching and brand loyalty among detergent purchasers. The case may be used in advanced statistics, stochastic process, and business analytics courses of MBA or Executive MBA programs as well as in a Ph.D. program in Statistics and Business Analytics.
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  • A Game of Two Halves: In-play Betting in Football, Spreadsheet Supplement

    Spreadsheet Supplement to Product #IMB401
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  • A Game of Two Halves: In-play Betting in Football

    According to the Federation Internationale de Football Association (FIFA), while the sports industry itself generated revenue totalling USD 300 billion in 2011, sports betting was worth USD 350-400 billion. The primary objective of this case is to analyze the past data from the English Premier League (EPL) to develop winning strategies for in-play betting. In-play betting allows bettors to place their bets while the match is in progress. In most instances, the bettors can place bets any time during the match and can bet on the final score, match result, next goal scorer, and so on. Unlike the other bets, in-play betting odds are updated in real-time by the betting companies based on the events in the match. In-play betting provides an opportunity to the bettors to mitigate the risk on their other bets. For example, consider a bettor who has placed a bet on a particular team to win before the start of the play. During the match, if the other team leads, he/she can mitigate the risk of losing money by placing another in-play bet. The objective of the case is to predict the outcome of football matches using classification techniques such as multinomial logistic regression and chi-squared automatic interaction detection (CHAID). The accompanying data in the Excel spread-sheet (IMB403EPL.XLS) may be used by the instructor to demonstrate application of several classification tools.
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  • Pricing of Players in the Indian Premier League, Spreadsheet Supplement

    Spreadsheet Supplement for Product #IMB379
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