Design contains the skills to identify possible futures, build bridges to customers and crack 'wicked problems'. For businesses to bottle the kind of experiences that rivet minds and run away with hearts, they need to do more than hire designers: they need to be designers -- to think like designers and work like designers. The narrow-gauge mindset of the past is insufficient for today's wicked problems. We can no longer play the music as written. Instead, we have to invent a whole new scale.
Make no mistake, the end of oil is on the horizon, and with it come significant implications for business and opportunities for the redesign of industry. The forthcoming end of petroleum-derived oil will fundamentally change the course of business on the scale of the Internet, the credit crisis, and perhaps even climate change. Three sets of ideas, explored here, play an important role: finding substitutes for oil; collaborative innovation between industries and sectors; and facing the fundamental socio-political implications of moving away from petroleum.
Kudremukh is a breathtaking mountain range in Chickamagalur District, Karnataka, India. Three rivers originate here and form an important lifeline for South India; the is ecologically very sensitive. The National Mineral Development Corporation (NMDC) conducted prospecting surveys in 1967 and obtained a mining license from the government of Karnataka for an area of 5218 hectares. In 1969, the government of India floated a public-sector undertaking, the Kudremukh Iron Ore Company (KIOCL), and NMDC turned over its 30-year mining lease to KIOCL. The majority of the surrounding communities were apprehensive about the possible impacts of massive mining operations in the virgin forest area. KIOCL's mining activities flourished, making it into Asia's largest mining and pelletization company. However, in 1985, the government of Karnataka declared Kudremukh region as a National Park under the Wildlife (Protection) Act of 1972, in order to provide effective protection to the rich flora and fauna in the region. The area leased to KIOCL was an enclave within the southern half of the national park and the mining operations started witnessing opposition in 1995, with wildlife conservationists and environment protection organizations staging rallies and agitations against KIOCL's operations. Activists filed numerous petitions in the Supreme Court, asking the court to end the activities of KIOCL in order to protect Kudremukh from the ravages of mining. The case focuses on important issues relating to shareholder vs. stakeholder responsibility in the context of ongoing ecological degradation, increased environmental awareness in Indian society, and consequent changes in legislation.
Berkshire Hathaway is known to many as the investment vehicle of Warren E. Buffett. To some extent, this reputation is well founded, given the investment success that the company has enjoyed under his leadership. Less attention, however, has been paid to the management success of Berkshire Hathaway. By 2008, the array of companies that Berkshire Hathaway owned was unique in its diversity. Even more unique was the operating structure that the company employed to manage these operations. It was a model based on extreme decentralization of operating authority, with responsibility for business performance placed entirely in the hands of local managers. While many public corporations implemented strict controls and oversight mechanisms to ensure management performance and regulatory compliance, Berkshire Hathaway moved in the opposite direction. Many of the company's operating principles were in stark contrast to those generally employed by most public corporations. Company shareholders would have to decide for themselves whether these operating principles posed a risk to long-term performance or whether, contrary to expert opinion, they were a source of competitive advantage that could be sustained in the future.
EnerNOC - a clean energy company -- sells energy-monitoring, management and efficiency services to utility customers, who agree to reduce consumption during peak-period emergencies in exchange for payments throughout the year. Utilities sign long term contracts with EnerNOC for delivery of "negawatts", i.e. the reduced consumption of electricity during peak periods, as a way to avoid adding power generating capacity. EnerNOC is undergoing explosive growth and must manage the build out of its energy management system, as well as the growth and evolution of its sales force. This case can be used in a variety of courses. In an entrepreneurship course, it can be the basis for a discussion of entrepreneurial opportunities in the clean energy sector, as well as the challenges of managing rapid growth. In a marketing class, it can be used to discuss the concept of adjacent markets. It can be used to stimulate a discussion of a broad range of issues in a sales management class: rewards systems; identification of sales skills in potential employees; entry into a new market; sales training; and so forth. It can be used in MBA level courses and in upper level undergraduate courses.
Decision Support, Analytics, and Business Intelligence is an eight-chapter book written by Daniel J. Power, Professor of Management Information Systems at the College of Business Administration at the University of Northern Iowa, and published by Business Expert Press in 2013. This revised and expanded edition targets MBA students and management professionals who need to quickly grasp the basics of analytics, business intelligence, and computerized decision support. Major topics include: modern decision support systems (DSS), business intelligence and data driven support systems, predictive analytics and model-driven support, as well as identifying opportunities for decision support. The author addresses 61 of the most fundamentally relevant concepts needed to build a solid understanding of the rapidly changing realm of computerized decision support. The first chapter introduces modern decision support, a broad concept that prescribes using computerized systems and tools to assist in individual, group, and organizational decision-making. The chapter covers the need for decision support, the technical skills and knowledge needed by managers, and provides a historical perspective on decision support. The characteristics of modern DSS are also addressed.
Decision Support, Analytics, and Business Intelligence is an eight-chapter book written by Daniel J. Power, Professor of Management Information Systems at the College of Business Administration at the University of Northern Iowa, and published by Business Expert Press in 2013. This revised and expanded edition targets MBA students and management professionals who need to quickly grasp the basics of analytics, business intelligence, and computerized decision support. Major topics include: modern decision support systems (DSS), business intelligence and data driven support systems, predictive analytics and model-driven support, as well as identifying opportunities for decision support. The author addresses 61 of the most fundamentally relevant concepts needed to build a solid understanding of the rapidly changing realm of computerized decision support. Chapter 2 defines fundamental decision support concepts and associated terminologies. The primary goal of the chapter is to examine the purposes, technologies, and targeted users of DSS, analytics systems, business intelligence, and knowledge management.
Decision Support, Analytics, and Business Intelligence is an eight-chapter book written by Daniel J. Power, Professor of Management Information Systems at the College of Business Administration at the University of Northern Iowa, and published by Business Expert Press in 2013. This revised and expanded edition targets MBA students and management professionals who need to quickly grasp the basics of analytics, business intelligence, and computerized decision support. Major topics include: modern decision support systems (DSS), business intelligence and data driven support systems, predictive analytics and model-driven support, as well as identifying opportunities for decision support. The author addresses 61 of the most fundamentally relevant concepts needed to build a solid understanding of the rapidly changing realm of computerized decision support. In Chapter 3, the author examines the decision support spectrum, including decision automation, five types of decision support systems, basic characteristics of DSS, and computer-supported special studies. A modern, systematic decision support framework that can help better describe decision support needs is summarized
Abstract (Maximum of 2,000 Characters): Briefly describes content of case. Decision Support, Analytics, and Business Intelligence is an eight-chapter book written by Daniel J. Power, Professor of Management Information Systems at the College of Business Administration at the University of Northern Iowa, and published by Business Expert Press in 2013. This revised and expanded edition targets MBA students and management professionals who need to quickly grasp the basics of analytics, business intelligence, and computerized decision support. Major topics include: modern decision support systems (DSS), business intelligence and data driven support systems, predictive analytics and model-driven support, as well as identifying opportunities for decision support. The author addresses 61 of the most fundamentally relevant concepts needed to build a solid understanding of the rapidly changing realm of computerized decision support. Chapter 4 examines a specific category of DSS: business intelligence and data-driven DSS. The chapter addresses data warehousing, key considerations for evaluating a BI data-driven decision support proposal, and best practices for BI reports. Introduction to SQL, pivot tables, and parallel databases are provided.
Decision Support, Analytics, and Business Intelligence is an eight-chapter book written by Daniel J. Power, Professor of Management Information Systems at the College of Business Administration at the University of Northern Iowa, and published by Business Expert Press in 2013. This revised and expanded edition targets MBA students and management professionals who need to quickly grasp the basics of analytics, business intelligence, and computerized decision support. Major topics include: modern decision support systems (DSS), business intelligence and data driven support systems, predictive analytics and model-driven support, as well as identifying opportunities for decision support. The author addresses 61 of the most fundamentally relevant concepts needed to build a solid understanding of the rapidly changing realm of computerized decision support. Chapter 5 focuses on predictive analytics and model-driven DSS. Analytic applications - broad sets of model-driven information systems - are discussed, as is analytical processing, or quantitatively transforming and summarizing relevant data. The tools and applications used for spreadsheet-based DSS, such as Microsoft Excel, are clarified. Sensitivity and "What If?" analyses are compared. Last, the role played by computer-driven simulations, which imitate the behavior of a human or physical system, is addressed
Decision Support, Analytics, and Business Intelligence is an eight-chapter book written by Daniel J. Power, Professor of Management Information Systems at the College of Business Administration at the University of Northern Iowa, and published by Business Expert Press in 2013. This revised and expanded edition targets MBA students and management professionals who need to quickly grasp the basics of analytics, business intelligence, and computerized decision support. Major topics include: modern decision support systems (DSS), business intelligence and data driven support systems, predictive analytics and model-driven support, as well as identifying opportunities for decision support. The author addresses 61 of the most fundamentally relevant concepts needed to build a solid understanding of the rapidly changing realm of computerized decision support. In Chapter 6, the author reviews the benefits and disadvantages of computerized decision support. Nine potential benefits and advantages of DSS are explored, as are claims that some systems provide a competitive advantage. Substitutions for computerized decision support and their applications are then reviewed. The final section examines the potential disadvantages of building and using DSS.
Decision Support, Analytics, and Business Intelligence is an eight-chapter book written by Daniel J. Power, Professor of Management Information Systems at the College of Business Administration at the University of Northern Iowa, and published by Business Expert Press in 2013. This revised and expanded edition targets MBA students and management professionals who need to quickly grasp the basics of analytics, business intelligence, and computerized decision support. Major topics include: modern decision support systems (DSS), business intelligence and data driven support systems, predictive analytics and model-driven support, as well as identifying opportunities for decision support. The author addresses 61 of the most fundamentally relevant concepts needed to build a solid understanding of the rapidly changing realm of computerized decision support. Chapter 7 discusses the search, planning, and implementation processes associated with DSS. The auditing decision process is clarified and the content of a feasibility study examined. Concerns surrounding the reengineering of internal systems are explored. The factors influencing DSS implementation risks, and the trade-offs of outsourcing enterprise-wide DSS, are also discussed.
What do followers want? A leader with a compelling vision of the future - which is not usually that leader's personal view. New research shows that followers respond to a leader who can articulate a vision that reflects their own aspirations.
Whether you want to or not, you need to start networking within the first couple of months after a promotion, when people in the new organization are deciding whether you're dependable - or a loser who should never have been hired.
New CEOs, mindful that poor stock performance is the primary reason boards fire chief executives, might be tempted to boost stock price immediately by adding a few pennies to earnings per share. But that would be a mistake. From day one, the new leader must establish objectives and rules that promote long-term value creation.
Although women are making slow inroads onto the boards of the Fortune 500, those who have arrived are gaining influence at a good clip. The percentage of women sitting on, and heading, crucial committees - such as audit, compensation, and nominating and corporate governance - is increasing markedly.
The first outsider to become CEO of Lego talks about the different approaches he's used to lead the 76-year-old, family-owned Danish toymaker onto a firm financial footing, then to reorient it toward growth, and now to open it to ideas and feedback from enthusiastic users.