Methods & Techniques

  1. Establish a Vision and Strategy
    • What’s a vision?
    • What’s a strategy?
  2. Understand Problems & Opportunities
    • Problem Statement with examples
  3. Build Consensus
    • Collective Consciousness – Align on Outcomes, not problems
    • Turn subjective concept into objective metrics – modified Delphi Method
    • Value of a central player (agnostic of teams)
    • List of Questions to identify overlaps, dependencies, and critical path
    • Be MECE – Mutually Exclusive and Collectively Exhaustive (MECE)
  4. Apply Prioritization Methods
    • Unearth the Top 5 – Aggregate Individuals Stack Ranking of Opportunities
    • Risk Priority Number (RPN) Method
    • Start with 80% of a Proposal, align on core direction (avoid detours)
  5. Size and Scope
    • Define the scope with a process, a population, or product
    • Need quick wins – Focus on what you can control with the resources you have
    • Scoping a process
    • Scoping a population
    • Scoping a product
    • Art of the Scope – balancing ‘collective consciousness’ and ‘moving fast’
  6. Storytelling that sticks
    • Start with ‘The Why’, establish ‘Key Outcomes’, focus on ‘time to impact’ & ‘control-ability’
    • Human think in Magnitudes, Comparisons, Anomalies, and Emotions
    • Make it Stick – How you make them feel over specific knowledge on topics
  7. Establish and Track Success
    • Containing the definition of success – Financial Resources, Time, People, Experience
    • The world of metrics
    • What can’t be measured, an alternative approach.
  8. ‘Must-Have’ Technical Skills for Modern People
    • Acquiring Data (Python, SQL, APIs, web-scrapping, spreadsheets)
    • Storing Data (databases, data ingestion methods)
    • Transforming Data (Python and SQL)
    • Extract Insights (Hypothesis Testing, ANOVA, Anomaly Detection, Optimization, etc)
    • Automating Tasks (Python, Task Schedulers, Alerts)
    • Applying Machine Learning (use-cases, purpose, pros/cons, limitations)
    • Selecting best visualization (fit for use visualizations)
    • Harnessing cloud resources (containerization, AWS, GCP, Docker)
  9. Useful Analytics Techniques and Concepts
    • Forecasting
    • Classification
    • Anomaly Detection
    • Linear Programming
    • Stochastic Programming
    • Decision Trees
    • Modern Portfolio Theory
    • Expected Value
    • Fitting Distribution
    • Probability Density Functions (PDF)
    • Cumulative Distribution Function (CDF)
    • Mean, Variance, Standard Deviation, Coefficient of Variation (CV)
    • Exploratory Data Analysis (EDA)