In March 2009, Steve Fowler, vice president of strategy and client service at full-service advertising agency Ayzenberg, had just completed what he considered to be one of the most innovative campaigns he had ever handled. Capcom, a leader in the video gaming industry, had just launched Resident Evil® 5 (RE5), the latest release of one of the industry's most valuable game franchises. RE5, a powerful asset with a passionate fan base, had warranted the use of an online viral, or word-of-mouth (WOM), campaign for its worldwide game launch. Although the creative work and appropriate media for the RE5 launch had been meticulously planned, Fowler was also interested in measuring the effectiveness of the campaign to better serve his client. In the past, measuring WOM was practically impossible. However, a software company named Meteor Solutions had found a way to do exactly that. Fowler and his team had worked with Meteor to execute several campaigns for other clients, but he had never applied Meteor tools on such a large scale. Fowler knew Capcom would want to hear specific WOM figures. What was the return on investment for the RE5 campaign and the implications for future campaigns? Had the Meteor tools provided comprehensive and actionable information, or was more work needed before these solutions could be widely used in advertising?
By 2009 Netflix had all but trounced its traditional bricks-and-mortar competitors in the video rental industry. Since its founding in the late 1990s, the company had changed the face of the industry and threatened the existence of such entrenched giants as Blockbuster, in large part because of its easy-to-understand subscription model, policy of no late fees, and use of analytics to leverage customer data to provide a superior customer experience and grow its e-commerce media platform. Netflix's investment in data collection, IT systems, and advanced analytics such as proprietary data mining techniques and algorithms for customer and product matching played a crucial role in both its strategy and success. However, the explosive growth of the digital media market presents a serious challenge for Netflix's business going forward. How will its analytics, customer data, and customer interaction models play a role in the future of the digital media space? Will it be able to stand up to competition from more seasoned players in the digital market, such as Amazon and Apple? What position must Netflix take in order to successfully compete in this digital arena?
In 2001 Accenture took the bold step of separating from its parent, Arthur Andersen. The new firm that emerged had a bright future ahead, but it also faced the challenge of building a new IT infrastructure that could support a global organization that consults on leading-edge technology. Accenture's CIO at the time, Ed Schreck, knew that becoming a master of your own trade was not an easy task. Frank Modruson, Schreck's successor and the person responsible for carrying forward the IT transformation challenge from 2002 on, had ambitious plans for the new technology infrastructure that was to replace Arthur Andersen's legacy systems. Difficult decisions had to be made. Should the firm continue with a decentralized approach to managing technology platforms, in which each country chooses its own IT platforms and has autonomy to run them? Or should the firm take a mixed approach, in which the same standard applications would run throughout the enterprise but would be managed independently by individual offices? Or should Accenture espouse a "one-firm" approach and boldly shoot for a centralized implementation of its most critical systems, with all its offices interconnected on the same "instance" of a software platform? Furthermore, should the firm retain its traditional conception of IT as cost center, or should it migrate to a scheme that recognizes IT as a service provision center that generates measurable value for the organization? These questions and many others drove Accenture's CIO team to undertake one of the most remarkable IT transformations in a global organization in recent years.
Rob Griffin, senior vice president and U.S. director of search for Media Contacts, a communications consulting firm, is faced with the task of optimizing search engine marketing (SEM) for Air France. At the time of the case, SEM had become an advertising phenomenon, with North American advertisers spending $9.4 billion in the SEM channel, up 62% from 2005. Moving forward, Griffin wants to ensure that the team keeps its leading edge and delivers the results Air France requires for optimal Internet sales growth. The case centers upon Air France's and Media Contacts' efforts to find the ideal SEM campaign to provide an optimal amount of ticket sales in response to advertising dollars spent. This optimal search marketing campaign is based on choosing effective allocation of ad dollars across the various search engines, as well as selecting appropriate keywords and bid strategies for placement on the search result page for Internet users. In determining the optimal strategy, the case presents background information on the airline industry as well as the Internet search options available at the time, including Google, Microsoft MSN, Yahoo!, and Kayak. Additionally, background information is provided on SEM and its associated costs and means of measuring the successfulness of each marketing effort. The case illustrates how one must first determine the key performance indicators for the project to guide analysis and enable comparison of various SEM campaigns. Cost per click and probability to produce a sale differ among publishers. Therefore, using a portfolio application model's quadrant positions can be used to determine optimal publisher strategies. Additionally, pivot tables help illustrate campaigns and strategies that have historically been most successful in meeting Air France's target Internet sales. Multiple recommendations on how Media Contacts can assist Air France in improving its SEM strategy can be derived from the data provided.
This case is designed to teach how to structure information technology (IT) infrastructure outsourcing deals from both the outsourcer and the client perspective. Office Supply Incorporated (OSI) is a company in crisis, with challenges in its cost structure and poor IT performance. Outsourcing to Technology Infrastructure Solutions is an opportunity to both reduce costs and complexity for the firm, but students first must consider whether outsourcing is a good strategic fit for OSI. Detailed spreadsheet templates are given that are based on a real outsourcing client engagement for a major infrastructure outsourcing company. The spreadsheets are complex but have been simplified so that they automatically calculate when populated, allowing the students to quickly move to answering the management challenge: how should TIS price and structure the outsourcing deal? Answering this question provides deep insights into the business case for IT outsourcing and how outsourcers financially engineer a deal structure to ensure a win-win outcome for both the client and outsource service provider.
A major barrier for growth of large multi-business-unit firms is the inability to resource the critical initiatives to win-both in terms of dollars and people. The underpinning of the challenge involves the conflict between resourcing current cash-generating legacy businesses vs. new initiatives which may not, in the short term, produce positive financial results. Most companies do not have a formal portfolio process to deal with this fundamental issue. The Healthcare Solutions business unit of Danaka is a fictional business based on real business experiences. The principle challenge is the need for this business to free up $300 million of current, budgeted R&D projects to fund new, unfunded initiatives to meet its five-year growth objectives. Tools and processes are introduced via interactive spreadsheets that show how to make the tough portfolio decisions on a project-by-project basis.
In 1992 Joe Jackson, former manager of DuPont Motorsports for twelve years, was angling to get the paint business at Rick Hendrick's sixty-five automotive dealerships across the United States. In order to win the Hendrick car dealership paint contract, Jackson and Hendrick met to discuss the possibility of sponsoring Hendrick's new team and rookie NASCAR driver-Jeff Gordon. As a result of that meeting, DuPont signed on to be the primary sponsor. By 2006 Gordon was a NASCAR superstar, and the DuPont logo-viewed by millions-was a household brand. While this level of exposure was exciting for the company, executives at DuPont could not help but wonder if they were fully leveraging this tremendous marketing opportunity. Gordon was on fire-but was DuPont maximizing the heat? The DuPont-NASCAR case tasks students and executives with designing a creative marketing campaign to activate the NASCAR sponsorship opportunity and maximize value beyond conventional sponsorship marketing. This open-ended challenge encourages students and executives to think outside of the traditional marketing tactics typically employed by business-to-consumer (B2C) NASCAR sponsors. Additionally, the nature of DuPont creates the need to develop a multi-dimensional plan that caters to a breadth of brands. Beyond designing a new marketing campaign, a key objective of the case is to focus students and executives on designing metrics for measurement of the return on investment (ROI) into a campaign plan. As a first step, it is important to clearly articulate the campaign, business strategy, and key business objectives mapped to the strategy.
A major barrier for growth of large multi-business unit firms is the inability to resource the critical initiatives to win-both in terms of dollars and people. The underpinning of the challenge involves the conflict between resourcing current cash-generating legacy businesses vs. new initiatives which may not, in the short term, produce positive financial results. Most companies do not have a formal portfolio process to deal with this fundamental issue. Danaka is a fictional company based on real business experiences. The company has strong growth markets as well as markets that are commoditizing. Unfortunately, the latter represent a sizable portion of the company's business. A framework is given that establishes a matrix to analyze the Danaka businesses using their critical financial criteria-cash generation and top-line growth. Projects are divided into four categories based on how they fit into the matrix, and resource allocations are then analyzed. Students discover that the current allocation does not enable Danaka to meet its aggressive growth goals. The case incorporates an interactive spreadsheet model in which students can dynamically change the various resource allocations and see the impact on future top-line growth. The essence of the case is how to manage the resource allocation for a multi-business unit firm when present allocations will not meet future growth goals.
On April 6, 2005, Sony Corporation announced the signing of a global partnership program contract with the Federation Internationale de Football Association (FIFA) and the organizer of the FIFA World Cup. The contract, which represented the first global marketing and communications platform for the Sony Group, would run from 2007 to 2014 with a contract value (excluding services and product leases) of 33.0 billion yen (approximately $305 million). This was a very significant marketing investment for Sony, since the cost of event sponsorship with advertising was typically two or three times the cost of the sponsorship rights; hence, Sony was potentially investing a billion dollars or more on FIFA-related marketing campaigns over the next several years. Many Sony senior executives were questioning the return on investment (ROI) of the FIFA sponsorship opportunity.
Technology projects are inherently risky; research shows that large IT projects succeed as originally planned only 28 percent of the time. Building flexibility, or real options, into a project can help manage this risk. Furthermore, the management flexibility of options has value, as the downside risk is reduced and the upside is increased. The case is based upon real options analysis for an enterprise data warehouse (EDW) and analytic customer relationship management (CRM) program at a major U.S. firm. The firm has been disguised as Global Airlines for confidentiality reasons. The data mart consolidation or EDW marginally meets the hurdle rate for the firm as analyzed using a traditional net present value (NPV) analysis. However, different tactical deployment strategies help mitigate the risk of the project by building options into the project, and the traditional NPV is expanded by the real option value. Students analyze the different deployment strategies using a binomial model compound option Excel macro, and calculate the volatility using Monte Carlo analysis in Excel. A step-by-step tutorial is provided to teach students how to accomplish the real options analysis for a simplified project, and this tutorial is easily generalized by students to the case scenario. In addition to the tactical options, the case also has the strategic growth option of analytic CRM. Students must therefore analyze both the tactical and strategic growth options and make a management recommendation on funding the project and also recommend an optimal deployment strategy to manage the project risk.
The case concerns a real $25 million program consisting of nine concurrent projects to deliver and implement a custom-built in-store customer relationship management (CRM) system and a new point-of-sale system in 400 stores of a national retail chain. The name of the company has been disguised for confidentiality reasons. Once deployed, the new system should give Clothes 'R' Us a significant strategic advantage over competitors in the marketplace; it will increase in-store manager productivity, cut costs, and ultimately drive increased sales for the retail chain. The program is in crisis, however, because the product managers have just left to join a competitor. The explicit details of the program are given, including examples of best practice program governance and the real activity network diagram for the program. Detailed Excel spreadsheets are also provided with the actual earned value data for the program. Students analyze the spreadsheets and the data given in the case to diagnose the impact of the most recent risk event and past risk events that occurred in the program. Ultimately students must answer the essential executive questions: What is wrong with the program? How should it be fixed, and what is the impact in time and money to the program? In addition, qualitative warning signs are given throughout the case-these warning signs are red flags to executives for early proactive intervention in troubled projects.
Technology projects are inherently risky; research shows that large IT projects succeed as originally planned only 28 percent of the time. Building flexibility, or real options, into a project can help manage this risk. Furthermore, the management flexibility of options has value, as the downside risk is reduced and the upside is increased. The case is based upon real options analysis for an enterprise data warehouse (EDW) and analytic customer relationship management (CRM) program at a major U.S. firm. The firm has been disguised as Global Airlines for confidentiality reasons. The data mart consolidation or EDW marginally meets the hurdle rate for the firm as analyzed using a traditional net present value (NPV) analysis. However, different tactical deployment strategies help mitigate the risk of the project by building options into the project, and the traditional NPV is expanded by the real option value. Students analyze the different deployment strategies using a binomial model compound option Excel macro, and calculate the volatility using Monte Carlo analysis in Excel. A step-by-step tutorial is provided to teach students how to accomplish the real options analysis for a simplified project, and this tutorial is easily generalized by students to the case scenario. In addition to the tactical options, the case also has the strategic growth option of analytic CRM. Students must therefore analyze both the tactical and strategic growth options and make a management recommendation on funding the project and also recommend an optimal deployment strategy to manage the project risk.