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Consortium for Service Innovation


To understand the success and impact of an Intelligent Swarming system, we need to pay attention to three perspectives.

  1. Impact: How is Intelligent Swarming impacting business outcomes? What are the benefits being realized by the organization as Intelligent Swarming matures?
  2. Health: Is the Intelligent Swarming implementation healthy? How do we measure the ongoing health of Intelligent Swarming?
  3. Contribution: What are the contributions to our overall success by individuals and teams?


Directly connecting any work to the impact it is having on business outcomes is critical to sustaining that work. Intelligent Swarming does not change the overall business objectives; it changes how we operate to deliver services to reach the desired outcome.


Understanding the health of Intelligent Swarming is informed by two different perspectives.

  1. Implementation Success: We need to design the measures and milestones to indicate if the adoption is going well. This may include program-specific goals, indicators that the efforts of a pilot team are working, or a number of leading indicators that the processes put in place are having in impact.
  2. Ongoing Success: Intelligent Swarming is not a project with an end; it changes how we function forever. There are a number of leading indicators that, over time, will help us monitor the activities, outcomes, and desired behaviors that have emerged in Intelligent Swarming.


Our goal is to assess who is contributing to overall success, not to count who is completing the most tasks.  Every individual and team has different skills and competencies, and therefore adds value to success in unique ways.  Contribution begins to look at how individuals and teams leverage those skills to reach an objective. Based on our defined organizational outcomes, skills, and job requirements, we can create a multifaceted view of contribution for our team members.

The discussions we have had on the challenging topic of measuring contribution has led us to the idea that a reputation model that reflects the history of value creation for an individual is a powerful method. A reputation model is fed by those who realize the value created. The combination of feedback (explicit) and the behaviors of the value recipients (implicit) will, over time, reflect the value created. This is a dramatically different way to think about assessing and recognizing contribution.

In the section on Reputation Models, we explore this concept more.


The three aspects of the the Practice of Recognize (Impact, Health, Contribution) depend on understanding the business and the people involved, and the ability to collect, analyze, and communicate information effectively.

Understanding the Business

A strong understanding of the business goals and desired outcomes at a corporate, organization, and team level are the foundation for connecting the work to the why. To measure the impact on the business, or the contribution to success, we need these objectives to be documented and connected to the implementation of Intelligent Swarming.

Skills and Competencies

To recognize the contribution of individuals and teams, we need to have a good understanding of the skills and competencies needed. We want to recognize people for all of the attributes required.

Collecting Data

As an Intelligent Swarming implementation starts and matures, the ability to collect data will most likely move from manual to automatic. We will need to be able to: 

  1. Capture, collect, and report on measures for contribution to the overall goals.
  2. Have mechanisms by which people can see the impact of their contribution (badges and/or distinctions). 
  3. Collect data and report on indicators that reflect the health of the system and interactions.  


The saying, "you get what you measure" could have easily emerged from services organizations, who love to count things. With Intelligent Swarming, the organization needs to be ready to change its measures from individual and competitive-based to team measures with a focus on optimizing collaboration and overall team performance. This does not mean measures are not required, but we need to be thoughtful about what we are measuring, how we use those measures, and what truly reflects contribution to an overall goal.

A word of caution: over-measuring, especially in the early stages of an Intelligent Swarming adoption, may cause problems. Modern tools make it very easy to count things and create robust visuals and dashboards. More data and more readouts does not equal the creation of value. Be thoughtful about what you are drawing attention to and be sure you are clear on why a measure is needed and how it will be used to avoid inadvertent consequences.

Measures around Intelligent Swarming continue to mature with every new implementation and as organizations gain more experience. We discuss some of the latest approaches in the Design Technique section on Measures: Contribution & Success.


Every organization has a different technology stack that impacts how measures are collected and displayed. This will be unique to every environment.

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