Recommendation engines are an easy way to reach new customers, but marketers may encounter unintended consequences due to the inherent biases in the algorithms.

Companies are looking to artificial intelligence to create business value, and as MIT Sloan Management Review's 2018 Global Executive Study and Research Report on AI shows, Pioneer organizations are pulling ahead of their counterparts. By deepening their commitment to AI and focusing on revenue-generating applications over cost savings, these early implementers are positioning themselves to reap the benefits of AI at scale.

The 2018 Data & Analytics Global Executive Study and Research Report by MIT Sloan Management Review finds that innovative, analytically mature organizations make use of data from multiple sources: customers, vendors, regulators, and even competitors. The report, based on MIT SMR's eighth annual data and analytics global survey of over 1,900 business executives, managers, and analytics professionals, explores companies leading the way with analytics and customer engagement.

IT alignment can produce inertia -unless it's accompanied by the right culture. Sure, closely aligning IT with the rest of a company's strategy can cut costs and improve the ability to collect data, facilitating the creation of early-warning systems and operational dashboards. But a less regimented approach has its place, too, allowing responses to changing business and economic conditions that are swift and creative.

Plummeting data acquisition costs have been a big part of the surge in business analytics. We have much richer samples of data to use for insight. But more data doesn't inherently remove sampling bias; in fact, it may make it worse.

Disruption from artificial intelligence (AI) is here, but many company leaders aren't sure what to expect from AI or how it fits into their business model. Yet with change coming at breakneck speed, the time to identify your company's AI strategy is now. MIT Sloan Management Review has partnered with The Boston Consulting Group to provide baseline information on the strategies used by companies leading in AI, the prospects for its growth, and the steps executives need to take to develop a strategy for their business.

This is an MIT Sloan Management Review article. The 2017 Data & Analytics Report by MIT Sloan Management Review finds that the percentage of companies deriving competitive advantage from analytics increased for the first time in four years. Incorporating survey results and interviews with practitioners and scholars, the report finds that companies'increasing ability to innovate with analytics is driving a resurgence of strategic benefits from analytics across industries. The report is based, in part, on MIT SMR's seventh annual data and analytics global survey, which includes responses from 2,602 business executives, managers, and analytics professionals from organizations located around the world.

This is an MIT Sloan Management Review Article. We found that obtaining business value using the connections the IoT creates between an organization and its customers, suppliers, and competitors depends on companies'willingness to share data with other organizations.

This is an MIT Sloan Management Review article. The 2016 Data & Analytics Report by MIT Sloan Management Review and SAS finds that analytics is now a mainstream idea, but not a mainstream practice. Few companies have a strategic plan for analytics or are executing a strategy for what they hope to achieve with analytics. Organizations achieving the greatest benefits from analytics ensure the right data is being captured, and blend information and experience in making decisions.

This is an MIT Sloan Management Review article. The 2015 Data & Analytics Report by MIT Sloan Management Review and SAS finds that talent management is critical to realizing analytics benefits. This fifth annual survey of business executives, managers and analytics professionals from organizations located around the world captured insights from 2,719 respondents. It finds that organizations achieving the greatest benefits from analytics are also much more likely to have a plan for building their talent bench. That talent plan includes (1) giving preference to people with analytical skills when hiring and promoting, (2) developing analytical skills through formal training, and (3) integrating new talent with more traditional data workers.

business value from analytics is not data management or complex modeling skills. Instead, the number one barrier mentioned by survey respondents involved translating analytics into business actions -in other words, making business decisions based on the results, not producing the results themselves. With more access to useful data, companies are increasingly using sophisticated analytical methods. That, the authors argue, means there's often a gap between an organization's capacity to produce analytical results and its ability to apply them effectively to business issues. Much can be done to make analytics more consumable for managers. At the individual level, data analysts can learn more about the business; in fact, about a third (34%) of the survey respondents reported that their organizations train analytics professionals to understand business issues. Organizations can also systemically improve infrastructure and processes; improved data quality, for example,can make it easier to turn data into competitive advantage. Managers can also take steps to become savvier at understanding analytical results. In fact, managers and executives are working to become more knowledgeable about data and analytics: Many of the survey respondents reported that their organizations develop analytical skills through on-the-job (58%) or formal (23%) training. Almost half the respondents (49%) reported that their organizations train managers to make better use of analytics. Beyond training, other known steps include: identifying trustworthy analytics professionals within the organization, requiring straightforward explanations and asking detailed questions. However, the authors'research indicates that, despite their efforts, managers continue to find it difficult to keep pace with their organization's analysts for two reasons: burgeoning analytics sophistication and competing demands for managerial attention.