Demand forecasting data preparation
Planners repeatedly rebuild demand datasets from inconsistent calendar, weather, and consumption sources.
The challenge behind the workflow.
Planners repeatedly rebuild demand datasets from inconsistent calendar, weather, and consumption sources.
Connect meter, asset, customer, outage, and planning data across the enterprise. Support reliable analysis and review without using an analytical workflow as a substitute for certified operational control systems.
Data to bring together
- Consumption histories
- Calendar references
- Weather data
Source systems are examples of the data required. Confirm connector availability, permitted access, refresh timing, and the authoritative owner before implementation.
How Genedata supports the work.
Configure one connected workflow, then reuse its mappings, definitions, and review process as the business grows.
- 01
Connect and prepare
Align reporting intervals and flag incomplete or anomalous input periods.
Build the preparation as a reusable visual workflow or reviewed code, with explicit source mappings and validation checks. - 02
Investigate and validate
Prepare reproducible planning cohorts and compare scenario assumptions.
Keep shared definitions and source versions with the analysis so another team can reproduce the result. - 03
Publish and review
Publish a versioned forecasting dataset with validation and source references.
Make the output available to the right people with appropriate access, ownership, and review evidence.
A demand forecasting dataset
Make the next run easier.
Reusable input preparation makes model refreshes easier to repeat.
Start from one approved example. Save the agreed mappings and definitions, publish the reviewed output, and let the next team follow the same evidence instead of rebuilding the preparation.
Measure your own improvement
Time to prepare a validated forecasting dataset
Record a baseline before the pilot and compare like-for-like work afterward. Results depend on source quality, configuration, and adoption.Review and responsibility
Qualified planners validate forecasts and approve their operational use.
AI with professional judgment.
Use AI to summarize asset and service evidence. Engineers and authorized staff approve operating, billing, and customer decisions.
Try the workflow with your team.
Use representative, approved sample data. Agree the expected output and a review owner before extending the workflow to a live process.