Stakeholder Tokens


Difficulty Level:

Method Overview

Stakeholder Tokens is a playful and versatile toolkit for identifying stakeholders and their interactions. Stakeholder Tokens facilitate identifying stakeholders, distinguishing core from peripheral stakeholders, surfacing excluded stakeholders, and articulating relationships among stakeholders.

Framework of ethics used:

pragmatist

Method Intentions:

Getting Started

Steps:

  1. Select Participants Select Token Materials: A token is a tangible, visual marker that represents stakeholders in this design activity.
  2. Create A List and Labels: Prompt the participant to think about those who are more central to the issue at stake as well as those who are left out of mainstream: Who are the important people, groups, or communities involved? Who else do you think would care about this issue and why? Is there anyone who is left out?
    Attach Labels To Tokens: Depending on context, facilitators can prompt participants to either prioritize their tokens (e.g., bigger tokens mean more important stakeholders) or randomly assign labels.
  3. Sketch A Stakeholder Map: Ask participants to place the tokens on a large sheet of paper and to use pens to map out the relationships among those stakeholders (Figure 3)
  4. As appropriate, prompt participants to enact a short scenario to illustrate the interaction among stakeholders:§ What are the relationships among these stakeholders? Please make a drawing to show their relationships. § Please act out a short scenario using your tokens to illustrate some of these relationships.

Further Reading

    Daisy Yoo. 2018. Stakeholder Tokens: a constructive method for value sensitive design stakeholder analysis. Ethics Inf. Technol. (2018), 1–5.

    Citation

    Daisy Yoo. 2017. Stakeholder Tokens: A Constructive Method for Value Sensitive Design Stakeholder Analysis. In Proceedings of the 2017 ACM Conference Companion Publication on Designing Interactive Systems (Edinburgh, United Kingdom) (DIS ’17 Companion). Association for Computing Machinery, New York, NY, USA, 280–284. https://doi.org/10.1145/3064857.3079161

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