Masterclass & Best Practices in Data-Driven Decision Making

Course Introduction

This course focuses on one question: how do teams in business-analysis, requirements and decision-support work apply Data-Driven Decision Making consistently and safely under real constraints? Five days of discussion, exercises and case work provide practical answers you can adapt to your own organisation.

Training Objectives

• 01Build a shared vocabulary and framework for Data-Driven Decision Making that your whole team can use
• 02Apply proven methods for Data-Driven Decision Making to realistic scenarios drawn from business-analysis, requirements and decision-support work
• 03Anticipate the failure points and compliance issues that most often affect Data-Driven Decision Making
• 04Communicate Data-Driven Decision Making decisions clearly to colleagues, clients and management
• 05Prepare a personal action plan to apply Data-Driven Decision Making in your own organisation

What You Will Take Away

• A checklist of common pitfalls and how to avoid them
• Benchmarks and KPIs to track your own results
• A negotiation and communication cheat-sheet

Who Should Attend

• Business Analysts
• Project & Product Managers
• IT & Systems Analysts
• Managers Making Data-Driven Decisions

Prerequisites: Best suited to experienced practitioners and team leaders.

Training Methodology

The format is conversational and case-driven: participants bring real challenges and test them against regional and international experience. Case material and examples are drawn from business-analysis, requirements and decision-support work.

Day-by-Day Programme (5 Days)

• Day 1
  Where Data-Driven Decision Making fits

  How Data-Driven Decision Making connects to wider operations in business-analysis, requirements and decision-support work, plus the essential vocabulary.

• Day 2
  Working with the standards

  Interpreting and applying the codes and good-practice guidance that govern Data-Driven Decision Making.

• Day 3
  Tools and techniques lab

  Guided practice with the tools, checklists and templates used for Data-Driven Decision Making.

• Day 4
  Risk, compliance and case review

  Analysis of incidents and cases to see where Data-Driven Decision Making succeeds or breaks down.

• Day 5
  Consolidate and plan

  Capstone discussion, action planning and a closing assessment.

Upcoming Sessions