Priority Matrix Canvas: PICK Use Case

Why to use?

Pick the next-best application / use case of data & AI according to cost-value ratio.

When to use?

If multiple use case ideas for analytical & AI applications exist within the same application domain and at the same analytics & AI maturity level, and it's unclear which to prioritize for further investigation during the workshop or for implementation afterward, use the PICK method. This method assists in making quick group decisions based on a 'guesstimation'—a guessed estimation of the complexity versus value of each application. The acronym "PICK" represents the four quadrants of the priority matrix: "Possible," "Implement," "Challenge," and "Kill".

How to use?

I. Preparation

① Fill the canvas header:

a) Label Focus on in the canvas header with a white sticky note for the application domain and the analytics & AI maturity.

② Label the axes and quadrants with white sticky notes:

a) X axis: "Technical, analytical and organizational complexity" - complexity can arise from various sources, including a fragmented data landscape, technical hurdles, or complex processes. Such complexity not only raises the costs of implementation and operation but also leads to delays which postpone the realization of value. Additionally, it heightens economic, ecological, legal, and technical risks.

b) Y axis: "Added value to the objective" - Evaluate the value of an application based on its contribution towards achieving the objective set during the workshop.

③ Label the quadrants: Each of the four quadrants should be labeled according to the "PICK" acronym. The order is shown below.

a) I. Quadrant: "I. Implement" - You should implement those low complexity, high value applications.

b) II. Quadrant: "III. Challenge" - You should challenge those high complexity, high value applications, before you implement them.

c) III. Quadrant: "II. Possible" - You could implement those low complexity, low value applications, if there are no low complexity, high value applications.

d) IV. Quadrant: "IV. Kill" - You should "kill" and therefore avoid or postpone applications that are high in complexity but low in value. Place them in your backlog (e.g., use case catalogue) until the necessary technical, organizational, and personnel structures are developed to reduce complexity.

II. Guesstimation

④ Anchor: Select an application from the "Sort in" field on the left edge that has medium complexity and medium value. Place it in the center of the canvas. This will serve as your anchor element, providing a benchmark for comparing all other applications as you categorize them based on complexity and value.

Tip: If you've previously implemented an application within the same domain and analytics & AI maturity level that has medium complexity and value, use this existing application as your anchor.

Now you start working with the quadrants you labeled at step ③: Have participants assess each remaining application against those already positioned on the matrix, particularly the anchor element. Adjust the placement based on this comparison:

• Complexity: Move the application to the right if its complexity is higher than the anchor's, and to the left if it's lower.

• Value: Place the application higher up if its value is greater than the anchor's, and lower down if it's less.

Additionally, use white sticky notes to note any assumptions made during your estimations, ensuring clarity and transparency in the decision-making process.

Tip: If one application depends on another, illustrate this dependency by connecting them with arrows. Place the dependent application further to the right and higher up, indicating increased complexity due to reliance on another application and higher value as it contributes additional benefits.

Optional: If there's a lot of debate or uncertainty about the fail likelihood or impact, use colors on the sticky notes to show how certain you are:

• Green: Absolutely sure

• Yellow: Moderately sure

• Red: Not sure at all

III. Next-Best-Application

Look out for applications in the I. Quadrant "Implement": those are your relevant set.

If this quadrant is empty, turn your attention to the III. Quadrant "Possible". Should both quadrants lack entries, reassess your anchor element—it may not represent the average scenario accurately. In such cases, redo the II. Guesstimation step using a more representative "average" application.

Important: The anchor element is also part of your relevant set!

From the relevant set, select one application that doesn't depend on any precursor or prerequisite applications as the next-best-application. Discuss its advantages and disadvantages. If consensus on the next-best-application is not reached, conduct a vote or defer to the decision maker for a final decision.

--

Copyright: All rights reserved by Datentreiber GmbH. For more workshop templates, transformation tools, and canvas tutorials, visit our Data & AI Business Design Bench. The Data & AI Business Design Bench requires a commercial licence per user per year. For more information, please contact Georg Arens via Email or make an appointment via Calendly.