Gain insights into performance management for engineering teams. Discover how to set clear expectations, design performance metrics, and provide constructive feedback to enhance team productivity and accountability.

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A manager is responsible for assigning tasks to the team members, keeping tabs on the progress, and analyzing their performance. A good manager must know their strengths and use them accordingly.

This course covers the essentials of performance management in engineering teams. You’ll learn the importance of setting clear expectations and the difference between individual and collective accountability. You’ll learn the importance of performance metrics and design them for your team. Next, you’ll explore ways to keep your team motivated and provide each team member with constructive feedback. You’ll learn how to decide when to let a team member go, including planning for a successor.

By the end of this course, you’ll have learned to apply processes and practices to monitor the performance of your team. You’ll be able to provide timely and constructive feedback to your team, including performance reviews. In addition, you’ll be able to balance a team with members having varying performances and competencies.

Effective Performance Management for Engineering Teams

The best example of autonomy---our inherent need to feel that we are "in control" and have choices as to what happens next---is to watch a three- or four-year-old child struggle with something, like tying their shoes, and then erupt into a fierce tantrum when their parent does it for them. "I do it!" is the rallying cry of the toddler, but the cry only gets quieter and more deeply internalized in the adult. We, all of us, crave autonomy, and we find ourselves chafing when our autonomy is taken away.

Keep in mind that autonomy doesn't mean "entirely hands-off" or "sure, do whatever you want"; it means that as managers, we should focus on the *results*, not the *process* (except in those cases where the process *is* the result---and even then keep an open mind). Employees need to feel like they have control over how they do their work. Can they tackle the story with their own approach? Do they get to do the class design? Is it up to them to figure out the algorithm or data structures to use? With relatively few exceptions, the clients/customers/users of what we build don't care about the internals, so long as the feature works as intended.

This, by the way, is where Drive Theory really breaks down: By externalizing the source of the motivational outlook, we essentially undermine their autonomy. They're doing this because they "have to," and are essentially now controlled by that external source. (Interestingly enough, one study shows that when a athletic training coach yells at their trainee to improve, performance is significantly lower than when the coach keeps quiet and attentive, allowing the athlete to find the drive within.)

Learn about the importance of autonomy in motivation and how it affects performance through Drive Theory.

Introduction

Overview of Performance Management

The Need for Clear Expectations

Accountability

Metrics

Motivation

Feedback

Performance Reviews

Corrections

Termination/Separation

Rewards

The Development of Talent

Conclusion

The Importance of Autonomy in Motivation