Data drives efficiencies, increases profitability, and bolsters innovation. Yet analytics skills remain outside the wheelhouse of many business leaders, who don't always have a clear view of what data sources and analyses are necessary to formulate the insights they are seeking.

How organizations can gain an analytics edge: The latest in leading and managing with data from MIT Sloan experts.

In a new series, "The Analytics Edge," published by MIT Sloan School of Management's Ideas Made to Matter, MIT Sloan faculty, alumni, and industry experts share practical tips for developing and cultivating a strong analytics practice designed to give companies and organizations a distinct advantage for the future.

Data literacy for leaders

While data scientists may be in demand, data literacy starts with leaders who trust and understand data enough to make their best business decisions. For optimal success, leaders must also drive literacy efforts throughout their organization to create a culture of trust in data. MIT Sloan data experts share how best to move forward.

Featuring: Barbara Wixom, principal research scientist, the MIT Center for Information Systems Research; and Rama Ramakrishnan, MIT Sloan professor of the practice, data science and applied machine learning.

Try this data framework for analytics advantage

Dimitris Bertsimas, associate dean of the Master of Business Analytics degree program at MIT Sloan, has developed an approach to help nontechnical business users to gain confidence using data to improve their decision-making. Bertsimas, a professor of operations research, lays out an analytics framework designed to help businesspeople determine which analytics approach is best suited for their application while improving their ability to leverage big data for better business outcomes. The framework is built upon data, models, decisions, and value, with an emphasis on decision-making.

In-demand data and analytics skills to hire for now

Hiring managers from Netflix, Pfizer, Comcast and MFS Investment Management share their "must-have" lists when it comes to hiring for data and analytics roles. In this article, they discuss essential technical skills and soft skills, and finding the elusive "super unicorn" data scientist.

Featuring: Trace Hawkins, senior vice president of strategic analytics at Comcast; Jonathan Lowe, data science lead for Pfizer's PGS Operations Insights; Nadine Kawkabani, global business strategy director at MFS Investment Management; and Yichen Sun, (MIT SM '13), data science manager at Netflix.

What is synthetic data — and how can it help you competitively

Technological research and consulting firm Gartner estimates that 60% of the data used in artificial intelligence and analytics projects will be synthetically generated by 2024. Indeed, synthetic data offers the opportunity to test new ideas and develop new products without putting personal or health data at risk, preserving the correlations among data variables. This article explores MIT research into the topic and how to apply it to your company. It also provides access to a free Synthetic Data Vault to guide organizations in building their own synthetic data sets.