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Fostering Effective Leadership of Engineering and Science Teams in a Data-Driven World

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Successful businesses are fueled by deep expertise and passion to enable them to thrive in any economy. Deep expertise requires knowledge and good decision making to enable workers to maneuver changes and obstacles effectively in today’s data-driven world. But without the prudent use of appropriate statistical methods and empirical modeling, you can’t leverage the maximum value of your data to lead your teams in making better decisions and achieving greater outcomes.

Who Should Attend 

Senior managers who lead teams of engineers and scientists in R&D and Operations in various industries

Duration 

6 hours total, generally divided into two, 3-hour sessions

Delivery Method 

Standard course delivery is conducted live and online through a webinar platform. The course format can be modified to accommodate your schedule, if needed.

Agenda 

Session 1 introduces the general concepts of statistical methods and describes your role as a senior manager in enabling your team to excel in making better decisions by using data science.

Session 2 covers statistical methods in more detail to enable you to:

  • Communicate about statistical methods effectively
  • Ask the right statistical questions of your teams, and
  • Know what to hold your teams accountable for

Expected Learning Outcomes 

When you have completed this course, you will be able to provide an effective leadership approach for integrating data science into your team’s work processes to:

  • Speed up innovation.
  • Deliver superior products.
  • Reduce development timeframes and product costs.

You will be able to understand the following key learning outcomes and assess the required skills, attitudes, and abilities to achieve them:

  • Understand why statistical methods and empirical modeling are vital to your business.
  • Identify the roles of statistical methods, systems thinking, and empirical modeling in effective decision making.
  • Describe the strengths and limitations of statistical methods and empirical modeling.
  • Learn key terms in data science to communicate effectively with your teams and know the right statistical questions to ask your teams.
  • Define the metrics to measure accountability by scientists and engineers. Set expectations for the types of results from empirical modeling and statistics to steer your teams in a direction that is quantifiable and clear.
  • Recognize the essential steps in achieving optimal processes and products.
  • Foster an organizational culture of inspiring new ideas for adopting the use of statistics, and motivate your teams to spot opportunities to leverage statistical methods.

Request More Information about This Course

Please get in touch with us if you have questions or would like more information on how to register a group from your organization for this course.