This is an MIT Sloan Management Review Article. As "big data" becomes increasingly integrated into many aspects of our lives, we are hearing more calls for revolutionary changes in how researchers work. To save time in understanding the behavior of complex systems or in predicting outcomes, some analysts say it should now be possible to let the data "tell the story" rather than having to develop a hypothesis and go through painstaking steps to prove it. The success of companies such as Google Inc. and Facebook Inc., which have transformed the advertising and social media worlds by applying data mining and mathematics, has led many to believe that traditional methodologies based on models and theories may no longer be necessary. Among young professionals (and many MBA students), there is almost a blind faith that sophisticated algorithms can be used to explore huge databases and find interesting relationships independent of any theories or prior beliefs. The assumption is: The bigger the data, the more powerful the findings. As appealing as this viewpoint may be, authors Sen Chai and Willy Shih think it's misguided - and potentially risky for businesses that involve scientific research or technological innovation. For example, the data might appear to support a new drug design or a new scientific approach when there isn't actually a causal relationship. Although the authors acknowledge that data mining has enabled tremendous advances in business intelligence and in the understanding of consumer behavior - think of how Amazon.com Inc. figures out what you might want to buy, or how content recommendation engines such as those used by Netflix Inc. work - applying this approach to technical disciplines, they argue, is different. The authors studied several fields where massive amounts of data are available and collected:

BGI has the largest installed gene-sequencing capacity in the world, and to Zhang Gengyun, general manager of the Life Sciences Division, this represented an opportunity to apply his training as a plant breeder and his early career work as a biochemist to improving important parts of the world food supply. But his biggest challenge was in scaling up his organization to address the multitude of opportunities he wanted to address. Along with its massive investments in gene sequencing machines and computing resources for data analysis, BGI had built a large cadre of data scientists who could develop and run programs to sift through the mountains of genetic data that were being generated every day. But the approach raised other questions. Could people trained in traditional fields of botany, biochemistry, and animal husbandry simply use the BGI sequencing platform as a black box, much as people in other industries relied on specialization and a modular division of labor? Or did it take the kind of cross-training and cross-boundary work in which Zhang himself had invested two decades of his professional career? Could the data scientists in BGI's "factory" grow sufficiently to understand the science, and was that now even necessary?

To Jonney Shih, Chairman of ASUSTek Computer, the introduction of Apple's iPad made clear the need to transition his company to a new cloud-computing era. But the company's roots in the manufacture of Windows-powered desktop and notebook PCs bounded the creativity of his design and engineering teams. The case examines the ASUS's efforts to get into the smartphone business, leveraging experimentation it has done in tablets and a range of hybrid devices. Will its experimentation and recombination of features lead it to market success, or simply confuse consumers?

As the world's largest producer of industrial enzymes, Novozymes had invested heavily for many years to bio-engineer enzymes that could break down cellulose into fermentable sugar. In 2010, the company had launched what it thought would become a breakthrough product for the conversion of crop residues from corn into fermentable sugars for the production of motor fuels. But the problem was that the company only controlled one piece of the value chain. To succeed in this nascent sector, should the company insert itself into an existing ecosystem? If so, how much coordination effort would be required to integrate the many pieces, including equipment and yeast suppliers? Or should Novozymes build its own ecosystem? And if so, how much control should it retain at each level of the value chain? The case seeks to expose students to the challenges of putting together value chain participation strategies in a setting where they can also learn about industrial biotechnology, including some cutting edge methods in directed evolution.

Senior managers at the LEGO Group are faced with a quandary: Should they patent inventions coming out of their manufacturing process development work, should they keep them as trade secrets, or should they publish them so that they would go into the public domain and nobody else could patent them? They wish to preserve their freedom to practice, but they are very concerned about competitors' ability to benefit from LEGO Group's R&D investments or alternately interfere with its freedom to operate.

Bristol Myers Squibb, a multi-national pharmaceutical company, is seeking to globalize its R&D strategy while managing costs. It has formed a joint venture with an Indian company, which has worked well, but now faces a strategic decision on how and whether to continue.

Gordon Zong is trying to teach Chinese universities and research institutes how to do effective technology transfer and IP licensing, but he is trying to do it in an environment with weak property rights and an underdeveloped support infrastructure. As the managing director of the Office of Technology Transfer at the Shanghai Institutes for Biological Sciences, he works with researchers at the forefront of biology and biotech, yet he faces seemingly insurmountable obstacles to getting the technology commercialized within domestic Chinese companies, so he has turned to global multinational pharma companies, for now. The purpose of the case is to help present and future managers at global multinationals who have responsibility for R&D strategy to understand some of the complexities of the Chinese intellectual property environment so that they can build effective participation strategies for their organizations. Understanding the misaligned incentives that result in the production of junk patents and the challenges of patent enforcement, as well as the direction of change are vital, because as the Chinese system evolves quickly, the implications of those changes will have important commercial consequences.

The learning objective of this case is to help students to recognize the interplay between intellectual property (IP) rights and corporate strategy. We do this by examining what is a fairly atypical circumstance today in which a single firm is able to secure what it perceives to be a frontier IP "estate" that blocks competitors from "practicing" in a significant part of the field. Those who elect to sign a license agreement must pay a high license fee and therefore help to fund the company's R&D. The company, meanwhile, must balance the immediate benefit of non-dilutive financing obtainable from the license fees vs. enabling a potential future competitor. The case setting is a lawsuit over a seemingly arcane issue: whether one of the co-owners of a key patent application is properly prosecuting the application. Understanding the issue requires students to progressively build up an understanding of some key aspects of U.S. patent law. Then by piecing together the strategy of the company and how it is driven by its IP position, students can understand why the litigation represents such a high stakes gamble.