Resource Item_Values Activity

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Overview

The resource.item_values_activity view provides a structured, item-level representation of planned resource effort, linking employees to project activities through planned hours.

It expresses resource planning as measurable activity, enabling clear visibility of how effort is distributed across projects, activities, and time-based snapshots.

Purpose

This view standardises planned resource effort into the CDM item_values pattern, allowing:

  • Consistent tracking of planned hours by project and employee
  • Alignment of resource effort to activity structures
  • Support for capacity planning, utilisation, and delivery forecasting
  • Integration into reporting models for resource management and PMO insight

It forms a key bridge between project structures and people-based effort attribution.

Grain & Structure

  • Object Level (OBJECT_SEQ)
    Represents the resource assignment context, defined by:
    • PROJECT_ID (Object Class)
    • EMP_NO (Object Code)
    This establishes a clear and stable relationship: “Employee contributing effort within a specific project.”
  • Item Level (ITEM_KEY)
    Represents a specific activity instance, defined by:
    • ACTIVITY_SEQ
    • SEQ_NO_KEY (derived from LOAD_DATE)
    This captures temporal snapshots of planned effort, without requiring a separate dates view.
  • Item Type (ITEM_TYPE)
    Fixed as HOURS, representing effort-based quantitative values
  • Attribute Level (ATTRIBUTE)
    Currently:
    • PLANNED → planned hours for the activity instance

Key Features & Behaviour

1. Activity-Centric Resource Modelling

Effort is anchored to ACTIVITY_SEQ, making activity the primary driver of structure and timing.

  • No separate meta_dates view is required
  • Time context is embedded within the activity snapshot (LOAD_DATE)
  • Aligns with delivery-focused planning models

2. Temporal Snapshot via Load Date

The inclusion of LOAD_DATE within:

  • ITEM_KEY (as sequence)
  • VALUE_METADATA

…provides a lightweight history mechanism, enabling:

  • Trend analysis of planned effort over time
  • Comparison of planning iterations
  • Foundation for future RPV / history expansion

3. Clean and Constrained Data Set

The view enforces strong data quality rules:

  • Excludes:
    • Null or invalid PROJECT_ID and ACTIVITY_SEQ
    • Zero or null planned hours
    • Non-relevant records (e.g. absence-related entries)

This ensures:

Only meaningful, actionable planning data is surfaced

4. Employee Resolution via DIM_EMPLOYEE

Resource identifiers are resolved through:

  • ifs.DIM_EMPLOYEE_OL → EMP_NO

This provides:

  • A stable, human-readable employee reference
  • Alignment with the wider Employee domain

5. Metadata-Enriched Values

Each value includes:

  • CODE_VALUE → numeric planned hours
  • VALUE_METADATA → JSON containing:
    • LOAD_DATE
    • HOURS

This supports:

  • Auditability
  • Lightweight temporal context
  • Flexible downstream shaping

Typical Use Cases

  • Resource planning and forecasting
  • Project delivery effort tracking
  • Capacity and utilisation modelling
  • Time-phased workload analysis
  • Supporting PMO and operational reporting

Design Notes & Considerations

  • Activity as the Temporal Anchor
    The design deliberately avoids a separate dates structure, using: Activity + Load Date = Time context
  • Object Model Decision
    The use of:
    • PROJECT_ID as OBJECT_CLASS
    • EMP_NO as OBJECT_CODE
    reinforces a project-first resource model, aligning with delivery and cost attribution
  • Snapshot-Based Planning Model
    The inclusion of LOAD_DATE reflects:
    • A planning snapshot approach rather than transactional history
    • A foundation for future historical expansion if required
  • Separation of Concerns
    • CDM layer → structure and meaning
    • Reporting layer → aggregation, trend analysis, and shaping

What This View Is Not

  • Not actuals (does not represent booked or consumed hours)
  • Not a full utilisation model (requires enrichment with capacity/availability)
  • Not a standalone time-series model (relies on activity snapshot context)

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