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1. Decision-Centric Exercise: The 3-3-3 Method
Time needed: 30 minutes with your leadership team
Exercise:
List the 3 most frequent decisions your team makes weekly List the 3 highest-impact decisions that affect your business outcomes For each decision, rate the current decision quality (1-10) Self-Assessment Questions:
Which decisions appear on both the "frequent" and "high-impact" lists? For which decisions do you currently lack sufficient information? Which decision, if improved by 20%, would create the most value? Next Step: Choose ONE decision to focus your AI efforts on. This becomes your "Decision Anchor Point."
2. Data Connection Exercise: The Signal Mapping Workshop
Time needed: 45 minutes with cross-functional team members
Exercise:
Take your Decision Anchor Point from the previous exercise Draw a simple table with these columns: Data signals needed for this decision Where this data currently lives Who currently accesses this data How difficult it is to access (1-5 scale) Identify the top 3 data connection gaps Self-Assessment Questions:
Which critical data signals are currently siloed or inaccessible? Are there any data signals completely missing? Which data connections would most improve this specific decision? Next Step: Identify ONE data connection to establish first. Create a simple plan to connect these signals.
3. Operational AI Exercise: The Day 2 Reality Check
Time needed: 30 minutes with technical and business stakeholders
Exercise:
For your Decision Anchor Point, answer: Who will be responsible for data quality? Who will validate that outputs make sense? Who will collect feedback on effectiveness? How will we measure success? Place each responsibility in one of three categories: Build (internal capability) Partner (external help needed) Not Yet (future consideration) Self-Assessment Questions:
Do we have clear ownership for each operational component? Which operational aspects pose the biggest risks? Are we being realistic about our internal capabilities? Next Step: Create a simple RACI chart (Responsible, Accountable, Consulted, Informed) for your first decision intelligence initiative.
4. Context Building Exercise: Asset & Knowledge Mapping Sprint
Time needed: 90 minutes with domain experts, functional leaders, product/service owners
Asset Criticality Mapping: List your top 5 business assets (systems, data, capabilities) Rate each on a 1-5 scale for business criticality Identify direct connections to your products/services Map which teams/processes depend on each asset Decision Knowledge Capture: For your Decision Anchor Point, document: 3 key business rules that experts apply 3 signals that indicate "this needs attention" 3 factors that determine priority or severity Create a simple relationship diagram showing how assets connect to business outcomes Self-Assessment Questions:
Do we have a shared understanding of which assets matter most? How do our critical assets relate to our value proposition? What tribal knowledge about assets exists only in people's heads? How consistently is this knowledge applied across teams? Next Step: Create a simple one-page "Asset to Value" map that shows how critical assets connect to business outcomes.
Getting Started Today
Schedule these exercises over the next two weeks Start small with one specific decision Involve the right people from different functions Document everything simply but clearly Focus on progress, not perfection Remember: The path to decision intelligence doesn't start with algorithms—it starts with clarity about which decisions matter most to your business.
From Data Noise to Decision Intelligence: A framework developed by Karen Kim, CEO of Human Managed
