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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.

Credit insurance and debt protection product seller Assurant Solutions ran a classic customer service call center–operationally optimized, “skills-routed,” managerially enlightened. But when it explored analytics-based approaches to rethinking how the center worked, a strange thing happened: The success rate for customer interactions tripled. According to Cameron Hurst, vice president of Targeted Solutions at Assurant, the result surprised them. “We learned that operational efficiency and those traditional metrics of customer experience like abandon rate, service levels and average speed to answer are not the things that keep a customer on the books.” They found instead that technology could assist the company in retaining customers by leveraging the fact that some customer service reps are extremely successful at dealing with certain types of customers. Matching each specific in-calling customer to a specific customer service rep made a huge difference. Science and analytics couldn’t quite establish why a particular rapport would be likely to happen, but they could look at past experience and predict with a lot of accuracy that a rapport would be likely to happen. In this SMR case-study interview, Hurst explains how Assurant Solutions figured out the right questions to ask, used analytics to focus on new ways to match customers with reps and figured out the best ways to solve the problem of conflicting goals.

Too little attention from head office executives can cause problems in global operations.

Six practices can help companies implement licensing as part of an open innovation strategy.

People with optimistic dispositions get jobs more easily and get promoted more, research suggests.

A global survey by MIT Sloan Management Review and the IBM Institute for Business Value sees threats and opportunities in the data deluge.