MIT and Accenture today announced a five-year research collaboration to develop advanced analytics solutions. The alliance’s research aims to close the gap between the advance of analytics technologies and their successful application in specific industry and government environments.
The Accenture and MIT Alliance in Business Analytics combines Accenture's industry and analytics expertise with MIT's scientific and technological leadership. Its two streams of collaboration cover the challenges of harnessing big data and new approaches to improve the science of decision-making. The alliance will be headed by Narendra Mulani, senior managing director for Accenture Analytics, and David Simchi-Levi, professor of civil and environmental engineering and engineering systems at MIT.
“Organizations recognize the need to develop analytics capabilities that turn data into actionable insights in order to attain a competitive edge and growth,” Mulani says. “The challenge comes in fine tuning and applying analytics technologies to very specific issues and our studies show that organizations are not currently satisfied with the return on their analytics investment. Our alliance with one of the world’s most prestigious research institutes will help our clients achieve better outcomes driven by their analytics efforts.”
A recent Accenture study of organizations in the United States and the United Kingdom revealed that the adoption of analytics is growing and that, compared to a similar analysis conducted three years ago, the use of analytics as a primarily predictive tool has tripled. However, only 22 percent of the respondents said they were very satisfied with the business outcomes delivered by their analytics investments and only 39 percent said that the data they generate is relevant to their business strategies.
“Through our collaboration with Accenture we believe we can make important progress in creating new knowledge and in tackling some of the many data challenges faced by organizations today,” Simchi-Levi says.
"This initiative is an example of one of MIT's great strengths: bringing people from industry and academia together to make a positive impact on some of the world's greatest challenges," says Ian Waitz, dean of the MIT School of Engineering.
David C. Schmittlein, The John C. Head III Dean of the MIT Sloan School of Management, observes that "the Alliance will enhance the collaboration between faculty of the two schools, leading to innovative solutions to real-world engineering and business problems."
The research on big data will cover how organizations can exploit the insights available from the growing volume of external, unstructured data. MIT, Accenture and Accenture clients will explore innovative uses of various data types and develop practical applications of advanced analytics. The parties will also identify ways to combine disparate data sources, such as geolocation data, social media data and payments data, to solve unique industry problems in innovative ways.
The decision science research will explore differentiators of effective decision-making and identify factors critical for its successful execution. Projects in this stream will help companies apply trends in visualization, mobility and collaboration to improve decision-based processes. They will also look into the role cognitive science plays in decision-making.
Examples of projects include:
The Accenture and MIT Alliance in Business Analytics combines Accenture's industry and analytics expertise with MIT's scientific and technological leadership. Its two streams of collaboration cover the challenges of harnessing big data and new approaches to improve the science of decision-making. The alliance will be headed by Narendra Mulani, senior managing director for Accenture Analytics, and David Simchi-Levi, professor of civil and environmental engineering and engineering systems at MIT.
“Organizations recognize the need to develop analytics capabilities that turn data into actionable insights in order to attain a competitive edge and growth,” Mulani says. “The challenge comes in fine tuning and applying analytics technologies to very specific issues and our studies show that organizations are not currently satisfied with the return on their analytics investment. Our alliance with one of the world’s most prestigious research institutes will help our clients achieve better outcomes driven by their analytics efforts.”
A recent Accenture study of organizations in the United States and the United Kingdom revealed that the adoption of analytics is growing and that, compared to a similar analysis conducted three years ago, the use of analytics as a primarily predictive tool has tripled. However, only 22 percent of the respondents said they were very satisfied with the business outcomes delivered by their analytics investments and only 39 percent said that the data they generate is relevant to their business strategies.
“Through our collaboration with Accenture we believe we can make important progress in creating new knowledge and in tackling some of the many data challenges faced by organizations today,” Simchi-Levi says.
"This initiative is an example of one of MIT's great strengths: bringing people from industry and academia together to make a positive impact on some of the world's greatest challenges," says Ian Waitz, dean of the MIT School of Engineering.
David C. Schmittlein, The John C. Head III Dean of the MIT Sloan School of Management, observes that "the Alliance will enhance the collaboration between faculty of the two schools, leading to innovative solutions to real-world engineering and business problems."
The research on big data will cover how organizations can exploit the insights available from the growing volume of external, unstructured data. MIT, Accenture and Accenture clients will explore innovative uses of various data types and develop practical applications of advanced analytics. The parties will also identify ways to combine disparate data sources, such as geolocation data, social media data and payments data, to solve unique industry problems in innovative ways.
The decision science research will explore differentiators of effective decision-making and identify factors critical for its successful execution. Projects in this stream will help companies apply trends in visualization, mobility and collaboration to improve decision-based processes. They will also look into the role cognitive science plays in decision-making.
Examples of projects include:
- Life event monitoring: Events such as marriage, home purchases and small business expansion are likely to change people’s financial needs. This research aims to identify new analytics methodologies that help predict life events in advance of their occurrence. These methodologies could help a financial services firm refine its ability to approach consumers or small businesses with tailored offerings, just when these offerings are becoming highly relevant for a customer.
- Behavior data integration and offers platform: A company that knows which locations in a city its clients are likely going next could target its offerings accordingly. The project will develop a real-time system to achieve that goal, based on an analytical framework that relates daily trip routes extracted from big data to statistical behavioral models of people’s activities in cities.
- Social media casual monitoring: This project explores how product launches impact social media activity and how social media monitoring can help forecast demand and improve product pricing, placement and distribution.
