TLDR: Transform your data vision into reality using Initiative Mapping, Capability Assessment Matrix, and balanced execution frameworks. Get exclusive access to the Initiative Priority Calculator MVP and help shape its development into an AI-powered decision support tool.
In This Deep-Dive:
Philosophy & Foundation
Note on Technical Deep-Dives
Where Philosophy Meets Practice
The Tools at Your Disposal
Core Framework
Initiative Mapping Overview
Priority Calculator Explanation
Scoring System & Weights
Practical Example: Data Validation System
Technical Implementation
Model Overview
Technical Specifications
Installation Guide
Best Practices
Supporting Frameworks
Capability Assessment Matrix
Balancing Exploration & Execution
Managing Your Initiative Backlog
Getting Started
GitHub Access Instructions
Implementation Guide
Next Steps & Future Development
Reading Time: ~20 minutes Technical Level: Intermediate to Advanced
Happy Friday, data Shokunin-deshi!
First, thank you for being part of our growing paid subscriber community. Since launching paid subscriptions before the Christmas break, we've grown to six subscribers, each choosing to join this journey of data enlightenment. Your support and engagement will help shape the evolution of these technical deep dives and tools.
A Note on Our Technical Deep-Dives
These technical companion pieces will arrive twice per series: once at the beginning to provide implementation tools and frameworks, and again at the end to explore advanced topics that emerge from our discussions. This approach ensures immediate practical value and the opportunity to influence future development.
Where Philosophy Meets Practice
Before diving into our technical frameworks, let's embrace a core truth about data strategy: perfection is impossible, but excellence is achievable. This is where our Wabi-Sabi philosophy becomes particularly powerful.
Just as a Zen garden is never "finished" but constantly evolving, our Initiative Board isn't about achieving perfect prioritization. Instead, it's about creating a framework that frees us from decision paralysis (Mushin - "no mind") while acknowledging that our understanding will continuously evolve.
Think of the Initiative Board as your data strategy's rock garden – each initiative is a carefully placed stone, influenced by quantifiable factors but ultimately serving a larger harmony. When we accept that our plans will evolve (Wabi-Sabi), we can move forward decisively with the tools at hand.
The Tools at Your Disposal
Today, I'm excited to share the first version of our Initiative Priority Calculator. As an MVP, it embodies our Wabi-Sabi philosophy – it's not perfect, but it's a powerful starting point. Your feedback and experiences will help shape its evolution toward becoming an AI-powered decision-support tool.
Core Framework: Initiative Mapping
TLDR: Initiative Mapping organizes your long-term vision into clear, prioritized steps by evaluating monetary value, user impact, risks, and alignment with strategy. This ensures focus on high-value initiatives while addressing dependencies and risks.
Why it matters?
In today’s fast-paced data landscape, it’s easy to get caught up in the race for quick wins. But true success comes from balancing innovation with execution. This tool helps you:
Avoid burnout from chasing shiny objects.
Build alignment within your organization.
Drive sustainable, meaningful results.
What’s the Initiative Priority Calculator?
The calculator blends Zen principles like kenshō (seeing deeply) with practical data strategy frameworks to help you:
Quantify the complexity of your initiatives (1-10 scale).
Assess impact using a weighted logarithmic model.
Foster collaboration between business and data teams.
Visualizing trade-offs enables you to prioritize initiatives that deliver maximum value—without losing sight of your long-term goals.
How to Get Started
Here’s your action plan:
Replay to this email to get access to the GitHub Repository
Test the Calculator: Download it here.
Provide Feedback: Reply to this email or fill out this quick form. Let’s collaborate to refine it together.
Book a Call: If you’ve tried the tool and want personalized advice, schedule a free, no-obligation session with me here.
Deep Dive For the Technical Minds
The Fields:
Here are the fields included in Initiative Mapping:
Priority: [Calculated field] Rank initiatives based on importance.
Initiative: Define what needs to be done.
Dependencies: Identify what’s required to unblock progress.
Monetary Value: Estimate the financial impact.
Monetary Impact Area: Specify where the value will be realized (e.g., cost savings, revenue growth).
Users Relevancy: Determine how important the initiative is for your users [rank 1-10].
Vision Relation: Ensure alignment with your long-term goals [rank 1-10].
Strategy Triangle Category: Classify the initiative as part of business, technology, or data strategy.
Risk: Assess potential challenges [rank 1-10].
Blocked: Indicate whether the initiative is ready to proceed or requires further preparation.
Deadline: When we have a deadline to deal with something, for example, our Looker version will be deprecated and we need to do a few operations by Q3 2025 to ensure constant use of it.
How does it work?
Use a priority score formula to rank initiatives:Priority Score = (Monetary Value × 0.4) + (User Relevancy × 0.25) + (Vision Relation × 0.25) - (Risk × 0.1)
Include fields like dependencies, monetary value, relevance, risks, and deadlines.
Example: A data validation system saving €500,000 yearly might score 6.6, making it a high-priority initiative.
Why these specific weights?
Monetary Value (40%): In my experience, initiatives with clear financial impact are more likely to maintain support and resources. This higher weight helps us stay grounded in business reality.
User Relevancy (25%): Equal weight with Vision Relation because successful initiatives need both strategic alignment AND user adoption.
Vision Relation (25%): Balances immediate user needs with long-term strategic goals.
Risk (-10%): A negative weight that tempers ambition with pragmatism. Too heavy a weight here can kill innovation; too light can lead to disaster.
Best Practices:
Reassess monthly with updated data.
Standardize scoring for consistent evaluation.
Provide context with linked documentation.
The weights I am using in this formula are based on our main KPI, which in this case is ROI. This means we value more cost savings or higher revenue, which is why I have given the monetary value a higher rate than others.
Practical Example: Data Validation System
Let's work through a real calculation:
Monetary Value: 8 (€500,000/year savings)
Reduced manual checking time
Fewer data quality incidents
Faster issue resolution
User Relevancy: 7
Impacts all data teams
Daily usage in workflows
Reduces frustration
Vision Relation: 9
Core to data quality goals
Enables advanced analytics
Supports automation initiatives
Risk: 6
Moderate technical complexity
Some process changes needed
Multiple team dependencies
Final Score = (8 × 0.4) + (7 × 0.25) + (9 × 0.25) - (6 × 0.1) = 3.2 + 1.75 + 2.25 - 0.6 = 6.6
Do you agree with the metrics used in this tool for prioritization? What would you add or change?
Technical Depth Additions
Model Overview
The model aims for alignment with business goals while factoring in risks, blockers, and impact.
The current version (1.0) includes fixed weights but could evolve to allow user-defined weighting.
Calculation Logic
A simple decision tree with point-based scoring.
Plans to improve calculations to better reflect organizational challenges.
Integration:
CSV/Excel export is currently available, but Jira integration is under consideration.
Scalability:
MVP supports ~2000 initiatives locally.
Customization and Suggestions:
Customization of weights and company-specific suggestions (e.g., based on revenue and data costs) are part of the roadmap.
Managing Your Initiative Backlog
Here's where mindfulness comes into play. The board isn't meant to capture every possible initiative - that would defeat its purpose. Instead:
Regular Reviews: Monthly priority recalculation keeps scores current
Documentation: Brief notes explaining each score help future reviews
Capacity Planning: Group initiatives by score ranges for quarterly planning
Dependencies: Track blockers and prerequisites clearly
I've attached the full framework template for you to use and adapt. While it might seem complex at first, remember that the goal is to reduce mental overhead, not add to it. Start small, perhaps with just your top 5 initiatives, and expand as the process becomes natural.
Best Practices for Initiative Mapping
Update Regularly:
Reassess monthly based on new data.
Ensure Consistency:
Use standardized scoring and document rationale.
Provide Context:
Link supporting documentation and assumptions.
💡 Example:
If your vision includes becoming a data-driven organization, prioritize initiatives like automating reporting, identify dependencies (e.g., data pipeline readiness), and assess monetary value (e.g., time saved by analysts).
By structuring your initiatives this way, you’ll see what’s actionable now and what needs work to align with the big picture.
Capability Assessment Matrix: Are You Ready to Execute?
TLDR: Use the Capability Assessment Matrix to evaluate whether your team has the skills and resources to execute initiatives. Identify gaps and prioritize readiness to ensure successful implementation.
Key Components:
Link required skills to initiatives and assess readiness (ready, in progress, or blocked).
Highlight gaps in tools or expertise in comments.
Example Usage:
For each initiative, evaluate:
Team’s skills vs. required capabilities.
Readiness and blockers.
Actionable next steps to fill gaps.
The Capability Assessment Matrix helps you evaluate whether your team is prepared to deliver on key initiatives.
Here’s what’s included:
Capability: Define the area of expertise required (e.g., data engineering, analytics).
Available Skills: Assess your team’s current skill set.
Key Initiatives: Link capabilities to relevant initiatives.
Status: Mark whether the capability is ready, in-progress, or blocked.
Comments: Add insights about gaps, challenges, or next steps.
💡 How it works:
For each initiative identified in your mapping:
Check if the required skills and tools are available.
Document the status—ready, blocked, or in-progress.
Highlight gaps, like missing tools or training needs, in the comments.
By using this matrix, you can focus on initiatives that are realistically achievable while creating a roadmap to address gaps in capability.
Balancing Exploration and Execution: Avoiding the Innovation Trap
TLDR: Balance creativity with actionable results by setting structured timelines for exploration and execution. Define clear outcomes for each phase to ensure progress.
How to Balance:
Set fixed intervals for review.
Allocate time for innovation within limits.
Transition from experimentation to action with deadlines and defined outcomes.
Workshop Idea:
Choose an innovation project.
Divide into “explore/play” and “build/test” phases.
Define outcomes for each phase to ensure tangible progress.
It’s easy to get lost in innovation without delivering results. Here’s how to balance:
Set fixed review intervals: Regular check-ins ensure alignment with goals.
Define exploration time: Give freedom to innovate within clear boundaries.
Decide and execute: Set deadlines to move from experimentation to action.
Define required functionality: By the end of the innovation “we can move data from the raw container to the analysis container and remove all PII1 and none consented data”
Workshop idea:
Pick one innovation project.
Break the timeframe into “explore/play” and “build/test” phases.
Define outcomes for each phase to ensure tangible results.
This approach keeps teams creative while ensuring meaningful progress within set timelines.
Implementation Guide & GitHub Access
The Initiative Priority Calculator is available now in its MVP form. While we'll be adding more features and refining the interface in the coming weeks, the core functionality is ready for your use and feedback.
To get access:
Reply to this newsletter with your GitHub username
You'll receive an invitation to the repository
Follow the installation instructions below
[Installation instructions...]
Current Status & Future Development
This is an MVP release focused on core functionality. Planned improvements include:
Enhanced UI with our brand colors and design schema
Refined calculation algorithms based on user feedback. In the upcoming weeks I will also test different approaches and keep you updated with findings and possible changes
Progress toward AI-powered decision support capabilities
Your feedback will be invaluable in shaping these developments. Feel free to:
Reply to this email with questions or suggestions
Start a chat in the Substack app
Submit issues or suggestions through GitHub
Getting Started
Access the Initiative Priority Calculator:
Reply to this newsletter with your GitHub username
You'll receive access to: github.com/Cooking-Data/Data-Initiative-Priority-Calculator
Follow the installation guide in the repository
Implementation Tips:
Begin with 3-5 key initiatives
Set up regular monthly reviews
Document your scoring rationale
# Installation Guide for Initiative Priority Calculator
## Windows Installation
1. Install Python:
- Download Python 3.8+ from [python.org](https://python.org)
- During installation, check "Add Python to PATH"
- Verify installation: `python --version`
2. Install the Calculator:
```bash
# Clone repository
git clone https://github.com/yourusername/Data-Initiative-Priority-Calculator.git
# Navigate to directory
cd Data-Initiative-Priority-Calculator
# Create virtual environment
python -m venv venv
# Activate virtual environment
venv\Scripts\activate
# Install requirements
pip install -r requirements.txt
## Mac Install
# Install Homebrew if not already installed
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
# Install Python
brew install python
# Clone repository
git clone https://github.com/yourusername/Data-Initiative-Priority-Calculator.git
# Navigate to directory
cd Data-Initiative-Priority-Calculator
# Create virtual environment
python3 -m venv venv
# Activate virtual environment
source venv/bin/activate
# Install requirements using pip3
pip3 install -r requirements.txt
# Make sure your virtual environment is activated
streamlit run app.py
Let me know what you’d like to see in future editions!
Looking Ahead
As we progress through the Data Strategy Triangle series, we'll explore more technical aspects including:
Maintenance and customer support frameworks
Roll-out design strategies
Automation opportunities
Each technical deep-dive builds on the previous ones, creating a comprehensive toolkit for implementing effective data strategy.
Next Steps
ROI Information Additions
Framework Usage: Aimed at fostering alignment during meetings rather than saving time directly.
Cost-Saving Metrics: Not available until the user base grows.
Impact on Data ROI:
Focused on initiatives with monetary value impact with the goal have a direct influence on the Data ROI metric.
Potential to improve team NPS and initiative success rates.
Adoption Metrics: Unknown until further testing is complete.
Value of Insights: Helps teams identify high-success initiatives and areas requiring effort.
Shape the tool's evolution:
Test the MVP version
Share your implementation experiences
Join discussions for future features
Look for updates in upcoming deep dives
Remember: Like a Zen garden, your data strategy will evolve. These tools help you maintain clarity while embracing that evolution.
Let's embrace the journey of continuous improvement together. Your experiences and feedback will help shape not just the tools we're building, but the future of data strategy implementation.
May Your Data Flow with purpose
Until next time,
Lior
Personal Identifiable Information (PII) is defined as: Any representation of information that permits the identity of an individual to whom the information applies to be reasonably inferred by either direct or indirect means.
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