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Data-Driven Coaching for Teams Deep-Dive Workshop

How to use data to optomize team performance and flow


This deep-dive workshop (delivered via Zoom and Miro) looks at all aspects of capturing, visualizing, and discussing team metrics to improve team performance and maximize the flow of valuable work to customers. Performance isn’t just about “more” “faster”, it’s about sustainable delivery of value.

This workshop is for you if you want to drive team performance using a balanced set of metrics and data. By the completion of this session, you will have a full understanding of what metrics to show, and how to help teams find ways to improve holistically given many competing forces. If you use Flight Levels, this workshop addresses the data and measurement needs for the FL1 systems.

The learning outcomes for this workshop are -

  • To understand how to create a safe environment for metrics to be used in “good” ways.

  • To know what data to capture, why

  • To identify and manage outliers and missing data

  • To understand how many samples of data are enough to make decisions

  • How to balance the six competing dimensions of data that all flow-based systems must manage

  • How to facilitate teams awareness and resolution of complex trade-off decisions using “Polarities” (for example, quality and speed)

Workshop design and agenda

This workshop has four parts that match the learning outcomes with two or three group exercises in each to give you a way to explore the topics with peers, and also to give you tools to use within your organization to facilitate dependency management, some of these are -

  • Safe measurement environments and team dynamics

  • Data capture and sanitization

  • Six performance dimensions

  • Polarity coaching (AND versus OR thinking and optimization)

The workshop is a mix of theory (20%) and exercises (80%). We will practice using the collaborative tools for facilitation and also explore a simple team dashboard spreadsheet as a demonstration of working and coaching with team data.

Typical agenda -


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