Forecasting Technology Innovation

Using Data for a Strategic Advantage

Download brochureRegister

Forecasting Technology Innovation

Using Data for a Strategic Advantage

Download brochureRegister


Leveraging data-based decisions for a competitive advantage

Decision-makers who are skilled at forecasting technology innovation have a competitive advantage. By gaining knowledge in forecasting technology, you can provide businesses with up-to-date data and analytical insights that can inform decision-making. Explore analytics tools to help companies analyze past trends and accurately predict future trends, allowing them to make more informed decisions.

MIT Professional Education’s online course Forecasting Technology Innovation: Using Data for Strategic Advantage explores the data-informed process of measuring, predicting, and influencing technological innovation.

$103 billion

is projected to be big data’s worth by the end of 2023.

Source: (Entrepreneur, 2021)


of IT professionals plan intend to up their spending on business intelligence tools to improve big data analysis.

Source: (Forbes, 2019)


of global spending on IT services has reached $1.3 trillion in 2022.

Source: (Gartner, 2022)

An online course to predict technological trends and shifts

MIT Professional Education’s 8-week Forecasting Technology Innovation: Using Data for Strategic Advantage course helps professionals make informed decisions backed by data. Forecast more accurately and leverage data for better technological innovation.

Obtain data-based knowledge and tools to drive better technology investment and design effective decisions.



The skills you will develop


Develop and understanding of how large data sets at various levels of detail can be used to gain insights into the dynamics of technological innovation


Learn how to compare rates of progress of various technologies and products


Explore state of the art theories of technological innovations and their applications


Discover how to apply data analysis and theory to guide investment and design decisions


Improve decision-making to support technological innovation when designing financial portfolios, research and development portfolios, and public policy

In addition, you will receive a Certificate of Completion

All participants who successfully complete the program will receive an MIT Professional Education Certificate of Completion.

Students in the MIT Professional Education Digital Forecasting Technology Innovation: Using Data for a Strategic Advantage program will also receive Continuing Education Units (CEU*).

To obtain CEUs, complete the accreditation confirmation, which is available at the end of the course. CEUs are calculated for each course based on the number of learning hours.

* The Continuing Education Unit (CEU) is defined as 10 contact hours of ongoing learning to indicate the amount of time they have devoted to a non-credit/non-degree professional development program.

To understand whether or not these CEUs may be applied toward professional certification, licensing requirements, or other required training or continuing education hours, please consult your training department or licensing authority directly.

certificate forecasting technology innovation

This course is aimed at

Although the expertise found throughout this course can be applied to a wide series of industries, it is especially beneficial for those working in sectors such as chemicals, life sciences, manufacturing, investment, energy, and public policy. Though not limited to any job level, the most common roles that will benefit from the course include:

  • Research and development managers
    looking to advance their organization’s technology portfolio decision-making through data-informed insights
  • Production or manufacturing operations managers
    who wish to incorporate data collection and analysis to anticipate technologies changes and prioritize their investments in innovation.
  • C-suite and executive level management
    in technology-related firms in charge of establishing a data-informed technology plan for their organization
  • Public policy makers
    from technology-related sectors who want to discover how technological progress can be measured and predicted to help meet societal goals
  • Private investors
    interested in optimizing technology-related portfolios based on technology performance data, allowing them to improve technology investment decisions

Meet the instructor of this course


Professor, Institute for Data, Systems, and Society, MIT

“Mitigating climate change is unavoidably linked to developing affordable, low-carbon energy technologies that can be adopted around the world.” – Prof. Jessika Trancik

Learn more

Jessika Trancik is a professor in the Institute for Data, Systems, and Society at the Massachusetts Institute of Technology. Her research examines the impacts of technologies and the reasons behind technological change. Trancik has developed theory and predictive models to understand why some technologies improve faster than others, and what technology features enable rapid innovation. In particular, her work focuses on accelerating clean energy development by informing decisions made by engineers, policy makers, and private investors. This work spans all energy services including electricity, transportation, heating, and industrial processes. Trancik’s theories and models have been applied to new and developing energy technologies, such as solar energy and batteries, and to electricity and transportation systems.

Her models have also been used to inform government innovation policy, and applied in diverse industries, including finance, healthcare, manufacturing, software, and consumer products. Trancik’s work has been published in journals such as Nature, Proceedings of the National Academy of Sciences, Nature Energy, Nature Climate Change, and Environmental Science and Technology, and has been featured by news outlets such as The New York Times, The Washington Post, Financial Times, and NPR.

Professor Trancik received her B.S. from Cornell University and her Ph.D. from the University of Oxford as a Rhodes Scholar.
Trancik develops data-informed models to evaluate the economic and environmental impacts of energy technologies over time and space.
Trancik’s models for forecasting technological change have informed engineering design, public policy, and investment portfolios.

Discover the experience of our participants

Are you ready to forecast technological innovation?

Download brochureRegister