1. Abstract
A well-organized Workbench helps users quickly understand relationships between variables, identify patterns, and communicate insights. Logical structure improves both analysis efficiency and stakeholder confidence.
2. Context
Apply this best practice whenever building or updating a Workbench with multiple indicators, particularly when models are shared across teams or revisited over time.
3. Content
3.1 Why It Matters
Disorganized Workbenches slow analysis, increase onboarding time for new users, and make it harder to explain results. Clear organization reveals structure in the data and supports more coherent storytelling.
An organized Workbench helps:
- Surface relationships faster
- Reduce cognitive load when reviewing models
- Ensure consistency across analyses
3.2 How to Apply
- Open your Workbench and click Manage Indicators (cog icon).
- Create category filters using the “Add Category” option to create custom categories.
- Group indicators by logical driver types, such as:
- Macroeconomic
- Income and Employment
- Prices and Costs
- Sentiment and Expectations
- Optionally use Set Default Indicators to allow Foresight to auto-group indicators.
- Periodically review the Workbench to remove outdated or unused indicators.
3.3 Example
A finance team organizes its Workbench into three categories: Income Drivers, Price Drivers, and Sentiment Drivers. This structure makes it immediately clear how each group contributes to demand forecasts and simplifies review discussions.
3.4 Common Pitfalls
- Mixing unrelated indicators within the same category
- Inconsistent naming across Workbenches
- Allowing categories to grow unchecked over time
- Forgetting to reorganize after adding new data
3.5 Expected Results
- Faster analysis and model review
- Clearer narratives when presenting results
- Improved collaboration across teams
- Workbenches that remain usable and understandable over time
