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Research shows that mobile banner ads can be effective for some products--those that are both utilitarian and "high involvement" (bought only after much deliberation on the consumer's part). Marketers who understand this can spend their mobile dollars more wisely and tailor and time their ads for maximum impact.

"No" doesn't necessarily mean "never." In fact, new research from Stanford shows that people who've refused your first request are much likelier to agree to your second one than anyone would expect.

Since the global financial crisis, speculation has been rampant about the dollar's looming if not imminent displacement as the world's leading currency. The author makes the case that the crisis has actually strengthened the dollar's position.

The numerous gains in health and wealth over the past few centuries have had the unintended effect of widening inequality gaps: Every breakthrough makes some people better off than others. Although some amount of inequality may be necessary for growth, inequality becomes intolerable when the successful use their advantage to pull even further ahead of the rest.

Data about hours worked per employee, productivity per employee, and per capita GDP in several countries around the world. The bad news: Even "hot" emerging markets like Brazil have seen little growth in productivity in recent years, so even if labor markets recover, those gains might not result in much added GDP.

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.

In the early years of the new millennium, citizens of the growing industrial and commercial city of Pune, India, often faced power cuts as the state-run electricity utility struggled to meet growing demand. Government projections suggested that this situation would continue for several years. Rather than take this situation for granted, a group of concerned industrialists met under the umbrella of the Confederation of Indian Industry and the leadership of Pradeep Bhargava to find solutions to this problem. They soon realized that each of the large companies resident in the city had huge back-up diesel generation sets that were often idle since the power supplied from the grid was cheaper, even after they paid a commitment charge to the utility for ensuring continuous power supply. Could this back-up resource be used to meet the shortfall of power faced by the city? A quick back-of-the-envelope calculation revealed that the city's shortfall and the captive generating capacity of the largest companies matched each other. Feeding this power into the grid was complex technically as well as from a regulatory perspective. Instead, the group realized, why not persuade the companies to use their diesel gensets for their own consumption during peak periods, thus freeing up grid power for use by the citizens and other businesses of the city? This proposal came to be known as the Pune Power Model. Different stakeholders such as the industry regulator, citizen groups, the government, political parties and the industry had different views on the feasibility as well as the desirability of pursuing this model. This case describes the challenges faced, and the change strategies used, by the proponents of the Pune Power Model in getting the model accepted and implemented. It raises questions regarding the appropriateness of such a model as well as the role of industry in solving social problems.

The case traces the entry of Volkswagen (VW) in India at a time when India will play a key role in fulfilling VW's global ambitions. The case describes the consumer research conducted by VW to identify consumer insights which pave the way for designing products to meet local needs and aspirations. The case describes VW's segmentation, targeting and positioning strategy for India against the background of its global brand values. The case traces the launch strategy of each of the models - Passat, Jetta, Touareg, Phaeton, Beetle, Polo and Vento. The case invites students to review the marketing and communication strategy of VW to enable it to fulfill its vision of being among the top three brands in India by 2018. The vision is challenging, particularly because VW is a very late entrant in the Indian market. The rich data in the case enables full-blown discussion on whether VW is differentiating itself enough in the competitive market place; or is it giving a compelling reason to the consumer to buy its brands.

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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Shree Cement Limited (SCL) is a unique company that has combined traditional Indian management practices and innovative initiatives based on emerging trends in contemporary management. SCL has always practised a ''people first'' policy that was informed by the ethos of a joint family and community, which is so integral to Indian society. By 2012, SCL was experiencing heady business growth and the top management was very keen to ''cement'' the culture of employee happiness and meaningfulness at the core of its human resource practices to avoid any people-related issues becoming a bottle-neck in the journey of growth. It hired Ernst and Young to conduct and employee perception survey which showed very high levels of engagement but also some areas of concern. Based on an analysis of the responses, and further focus group discussions, 18 improvement projects were initiated under the leadership of senior managers and volunteers from among the employees. Mahendra Singhi, Executive Director (ED) and Vikas Rai Bhatnagar, Chief People and Wellness Officer (CPWO) were examining the recommendations of the improvement project teams. They had to be careful to ensure that they took a holistic look at the implications of all the recommendations and implement an integrative set of initiatives that re-enforced each other's positive effects rather than proceed with a potpourri of recommendations that could potentially undermine each other's influences and worsen rather than improve the existing organizational climate.

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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The 5-year transformation at Guardian Life Insurance provides significant insights for organizations aspiring to enhance their IT-business alignment. Alignment is more than just organizational structure, there is no silver bullet; it requires effective governance, partnership, communications, value analytics, technical services, and people. Like most companies around the globe, Guardian recognized the importance of moving to a collaborative IT-business alignment relationship; IT-business alignment was a persistent pervasive problem that needed to be improved. In 2005, Guardian viewed IT as an ineffective expensive cost of supporting the business. Was improving the IT-business relationship as difficult as drawing 'a line' in the sand? Today, IT is enabling and driving demonstrable strategic business value. The approach that transpired this turnaround at Guardian will provide students and organizations with a clear understanding and set of lessons learned that can be applied to enhance IT-business harmony. More importantly, it will help organizations recognize the important role that IT and business leadership must play as they collaborate to address the important considerations necessary to attain a mature relationship. To demonstrate this transformation, the past and the current IT-business alignment maturity of Guardian has been benchmarked and analyzed to reveal the steps taken to enhance the impact that IT is having on the company. Were these initiatives all that are necessary to enhance the IT-business relationship? What are the important next steps to improve the relationship?

Gary Burnison had a lot of faith in Korn/Ferry's brand when he became a significant investor, back in 2001. The company was suffering in the aftermath of the dot-com bust, but he believed he could help--so he came on board as chief financial officer and worked with the rest of the executive team to lead a turnaround. A major portion of the problem was Korn/Ferry's near-total reliance on executive recruiting fees for its revenue. Burnison's ambition was to move the company into other aspects of talent management. He saw the growth of LinkedIn as an opportunity as well as a threat: It gave the firm an additional channel for gathering rich and individualized data on professionals. Korn/Ferry's close C-suite relationships, strong financial position, and that powerful brand aligned the company for success. And clients have embraced the firm's metamorphosis: One has increased its spending from $300,000 a year to $6 million; another's annual billing has gone from $700,000 to $10 million.

Attention is the basis of the most essential of leadership skills--emotional, organizational, and strategic intelligence. And never has it been under greater assault. If leaders are to direct the attention of their employees toward strategy and innovation, they must first learn to focus their own attention, in three broad ways: on themselves, on others, and on the wider world. Every leader needs to cultivate this triad of awareness, in abundance and in the proper balance, because a failure to focus inward leaves one rudderless, a failure to focus on others renders one clueless, and a failure to focus outward may cause one to be blindsided. The good news is that practically every form of focus can be strengthened. The author of "Emotional Intelligence," "Social Intelligence," and many other books on the power of cultivating awareness here explains why focus is crucial to great leadership. Focused leaders can command the full range of their own attention: They are in touch with their inner feelings, they can control their impulses, they are aware of how others see them, they can weed out distractions and also allow their minds to roam widely, free of preconceptions.

Those who study "data smart" companies believe that we've already lived through two eras in the use of analytics--we might think of them as "before big data" and "after big data"--and are entering a third. It represents a far-reaching resolve to apply powerful data gathering and analysis not just to a company's operations but also to its customer services and products. This strategic change in focus means a new role for analytics. Companies will need to recognize a host of related challenges and respond with new capabilities, positions, and priorities. Requirements will include: multiple types of data, often combined; a new set of management options; faster technologies and methods of analysis; embedded analytics; data discovery; cross-disciplinary data teams; chief analytics officers; prescriptive analytics; analytics on an industrial scale; and new ways of deciding and managing. These new capabilities can't be developed using old models for how analytics supported the business. The big data model was a huge step forward, but it will not provide advantage for much longer. Companies must once again fundamentally rethink how the analysis of data can create value for themselves and their customers.

High-performing knowledge workers often question whether managers actually contribute much, especially in a technical environment. Until recently, that was the case at Google, a company filled with self-starters who viewed management as more destructive than beneficial and as a distraction from "real work." But when Google's people analytics team examined the value of managers, applying the same rigorous research methods the company uses in its operations, it proved the skeptics wrong. Mining data from employee surveys, performance reviews, and double-blind interviews, the team verified that managers indeed had a positive impact. It also pinpointed exactly how, identifying the eight key behaviors of great Google managers. In this article, Harvard Business School professor Garvin describes how Google has incorporated the detailed findings from the research into highly specific, concrete guidelines; classes; and feedback reports that help managers hone their essential skills. Because these tools were built from the ground up, using the staff's own input, they've been embraced by Google employees. Managers say that they've found their training to be invaluable, and managers' ratings from direct reports have steadily risen across the company.

Fifty years after the expression "garbage in, garbage out" was coined, we still struggle with data quality. Studies show that knowledge workers waste a significant amount of time looking for data, identifying and correcting errors, and seeking confirmatory sources for data they do not trust. When data are unreliable, managers quickly lose faith in them and fall back on their intuition to make decisions, steer their companies, and implement strategy. They're also much more apt to reject important, counterintuitive implications that emerge from big data analyses. The good news is that improving data quality is often not as hard as you might think, the author asserts. The solution is not better technology: It's better communication between the creators of data and the data users; a focus on getting the process right going forward rather than on cleaning up existing bad data; and, above all, the shifting of responsibility for data quality away from IT folks, who don't own the business processes that create the data, and into the hands of managers, who are highly invested in getting the data right.

Why do companies have so little to show for their investments in big data? The biggest reason is that they aren't doing a good job using the data they already have. They don't know how to manage the information embedded in their operating systems, analyze it in ways that enhance their understanding, and then make changes in response to new evidence and insights. The few companies that have adopted evidence-based decision making ensure that all decision makers have performance data at their fingertips every day. They also follow four practices: (1) Agree on a single source of truth. Using performance data from just one source yields a more accurate view of costs and profitability. (2) Use scorecards. Perhaps the best way to teach people how to use data to create business benefits is to provide them with data about their own performance. (3) Explicitly manage business rules. Little data can have a big effect on performance when managers use the data to assess and improve the business rules that govern their operations. (4) Use coaching to improve performance. Adopting evidence-based decision making is a big cultural shift. Employees need help learning how to base their decisions on data instead of on instinct. Fortunately, companies that make the shift don't usually go back, and they improve their operations in ways that rivals can't easily replicate.