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Project networks provide the expertise to handle complex, knowledge-intensive team projects.

All companies collect data, and they want to act on that data, but they also want to make sure it is accurate. Better to wait on a decision until you have the absolutely correct information than act based on partial information. That might make sense, but it's the wrong way to go, say the top two executives at Attivio, a privately-held enterprise software company. The problem with focusing on getting the numbers too right is that most companies sacrifice speed for accuracy. Companies have been trained to think about data all wrong, say Ali Riaz and Sid Probstein, CEO and CTO respectively of Attivio. Analytics don't have to be based on super-precise data, they say. "The report doesn't have to be perfect. It needs to capture the behavior, not the totality of it." For analytics to work, companies need a new philosophy around leadership, decision-making, and performance management. One important element is the ability to consider a bigger picture and frame within which to consider the new kinds of data that is being gathered. Riaz and Prostein spoke with MIT Sloan Management Review editor-in-chief Michael S. Hopkins about the stifling downside of the quest for perfect data, why "eventually consistent" is a concept every company should take to heart, and how to deal with the need for speed.

The 2010 Sustainability Report by MIT Sloan Management Review and BCG sees two camps of companies.

Companies need to understand and manage the rising threat of online public complaining.

Sustainability assessment tools are increasingly becoming a predictor and opportunity finder for efficiency in a company's business practices. Duke Energy, a Charlotte, N.C.-based electric power company that supplies and delivers energy to approximately 4 million U.S. customers, uses something it calls the Duke Energy Sustainability Filter to encourage innovation and resource efficiency throughout the company. The tool has already saved the company millions, including over $2 million over six months in startup process for their combustion turbine plants. Roberta Bowman, who has served as senior vice president and chief sustainability officer for Duke Energy since 2008, says that the filter is a lens through which every decision in the company is made. "It's is the tool for conversation and decision-making," she says. The filter employs a series of questions around four key areas: "connection," "efficiency," "balance," and "grandchildren." The filter is one of the tools Duke shares with other organizations looking to evaluate their own risks and practices from a sustainability standpoint. "There is an openness to sharing approaches and techniques that works," says Bowman. "There is sharing and learning at a utility level, and also at a global industry level, from the World Business Council for Sustainable Development to Corporate Economic Forum." In this MIT Sloan Management Review case-study interview, Bowman explains how the filter developed, and why she hopes it puts her out of a job some day.

Ten years ago, executives looked to IT for technical solutions to support business units. Today, analytics has dramatically changed that function. As Monsanto Co. has pushed for analytics adoption throughout its organization, IT managers have become sought after for the answers they can provide to build competitive advantage and guide strategic decision making. Beth Holmes' job is to answer questions for the company through exploratory analytics -- and to advance Monsanto's organizational strategy of embedding analytics more deeply into all corners of the company's operations. Using analytics, her group has scoped out high-value sales targets, done cost modeling, improved the accuracy of sales forecasting and used multiple methodologies to aid long-range planning. The "exploratory analytics" team routinely tests assumptions about such things as commodity prices and agricultural trends. Building an understanding of potential scenarios is a critical component of the company's ability to operate profitably. Holmes spoke with MIT Sloan Management Review editor-in-chief Michael S. Hopkins about myth busting, why the simplest solution is often the smartest, and what it means to push for analytics adoption by using the IT function for leverage.

To understand the challenges and opportunities associated with the use of business analytics, MIT Sloan Management Review, in collaboration with the IBM Institute for Business Value, conducted a survey of more than 3,000 business executives, managers and analysts from organizations located around the world. The survey was part of the 2010 New Intelligent Enterprise Global Executive Study and Research Project, which attempts to understand better how all organizations are trying to capitalize on information and apply analytics today and in the future. One of the most significant findings is that there is a clear connection between performance and the competitive value of analytics. Survey respondents who agreed that the use of business information and analytics differentiated them were twice as likely to be top performers. Three stages, or capability levels, of analytics adoption emerged from the research: aspirational, experienced and transformed. The article provides a comprehensive description of each, enabling organizations to identify where they fall in the continuum. In addition, the authors include suggestions for the best entry points and techniques for each level, and measures to avoid the most common pitfalls. Based on insights from the survey, case studies and interviews with experts, the authors also describe an emerging five-point methodology for successfully implementing analytics-driven management and rapidly creating value–as leading businesses are already managing to do. These include (1) focus on the biggest and highest data priorities, (2) within each of those priorities, start by asking questions, not by looking at the available data, (3) embed insights into business processes to make them more understandable and actionable, (4) keep existing capabilities and tools while adding new ones and (5) develop an overarching information agenda that enables decision making and strategy for the future.

Outsourcing complex product development work subjects companies to significant uncertainty.

Managers must understand which competencies they can safely outsource and which they should manage internally.

Increasingly, innovation is being applied to the development of new service offerings, business models, pricing plans and management practices.