A governed operating layer for finance data

Give Adaptive Planning the Data Foundation It Was Designed to Use

Connect operational transactions, governed dimensions, finance rules, and planning-ready datasets to create a trusted foundation for Workday Adaptive Planning.

  • Reduce manual data preparation and reconciliation
  • Preserve transaction-level lineage and drill-through
  • Create reusable data products for planning, analytics, and AI
OperationalTransactions
GovernedData foundation
AdaptivePlanning
DecisionsAction
Governed contractKeys · Grain · Rules · Lineage · Controls
The foundation Adaptive depends on—but should not have to rebuild
Trusted transactionsReusable dimensionsPlanning-ready dataExplainable results
Why it matters

Adaptive Does Not Fail Because of Planning Logic

Many implementations encounter friction because the data feeding their models is fragmented, manually prepared, difficult to reconcile, or disconnected from operational detail. These are common patterns—not universal outcomes.

Business impact

Inconsistent dimensions

Finance spends time aligning accounts, entities, products, customers, and cost centers before analysis can begin.

The architecture

A Governed Data Layer Between Transactions and Planning

The Adaptive Data Foundation is not a replacement for Workday Adaptive Planning. It gives Adaptive a governed, explainable contract so planning models and users do not have to reconstruct business meaning from raw sources.

Layer 02

Transaction master

Incorta joins detailed operational data while retaining source-system keys and transaction context. Summaries remain connected to the evidence behind them.

Source keysTransaction grainCross-system joinsAudit attributesOperational lineage

One governed threadSource keys and business meaning remain connected from transaction to decision.

Adaptive delivery patterns

Multiple Integration Paths, One Governed Contract

The connection can vary. The contract should not. Before delivery, define consistent column names, data types, keys, grain, and business meaning in the Adaptive Data Foundation.

Design integration option

Cloud Data Source

A strong Design Integration option when Adaptive can retrieve governed Incorta data through a JDBC-accessible integration pattern.

Use the standard path when it satisfies the data contract and operating requirements.
Specialized requirements

Custom Cloud Data Source

Supports scripted requirements, with additional implementation, testing, and maintenance responsibility.

Treat as the least-preferred option when a standard integration can meet the need.
Recommended design principleStandardize every Incorta data product around a consistent, pipeline-ready contract.NAME · TYPE · KEY · GRAIN · MEANING
The capability layer

More Than an Integration Layer

Four capability domains turn operational data into governed, explainable, planning-ready products.

Govern the foundation

Define reusable business meaning

Establish the shared structures and finance logic that keep every downstream planning model consistent.

Governed dimensions

Reuse accounts, entities, products, customers, workforce, projects, and other planning dimensions.

Stable member identifiers

Provide deterministic, durable identifiers so integrations and planning models remain stable.

Business rules and calculations

Apply reusable finance logic before data reaches individual planning models.

The operating shift

From Data Preparation to Decision Support

A foundation does not remove the need for governance or process ownership. It makes both visible, reusable, and easier to operate at scale.

Before

Every model solves the data problem again.

  • Repeated extracts
  • Spreadsheet transformations
  • Model-specific mappings
  • Manual reconciliations
  • Limited lineage
  • Slow onboarding of new models
  • Conflicting definitions
  • Administrators acting as integration developers
With an Adaptive Data Foundation

Teams reuse a trusted contract and focus on decisions.

  • Reusable governed datasets
  • Shared dimensions and mappings
  • Centralized business rules
  • Automated validation
  • Transaction-level traceability
  • Faster deployment of new use cases
  • Consistent definitions
  • Clear ownership across teams
Business value

What Success Looks Like

The value is operational: less avoidable data work, more reliable evidence, and a clearer division of responsibility across finance, planning, and data teams.

01

Faster planning cycles

Reduce time spent collecting, transforming, loading, and reconciling actuals and drivers.

02

More reliable forecasts

Provide planners with current, consistent, and explainable operational data.

03

Lower model complexity

Keep source translation, reusable logic, and delivery controls outside individual models.

04

Faster expansion

Add business units, dimensions, datasets, and processes using reusable contracts.

05

Greater trust

Reconcile results and trace values back to operational detail when questions arise.

Illustrative workload

Make the invisible effort visible.

Estimate only
Estimated annual effort associated with preparation and reconciliation2,304 hours
Illustrative labor cost$195,840

This is a workload illustration, not a savings commitment. Actual effort and improvement depend on scope, controls, process ownership, and adoption.

Focused value

Start With a Business Process, Not a Platform Program

Choose a bounded process where shared dimensions, controls, and transaction evidence can improve a decision that already matters.

Selected first-value pattern

Financial actuals and management reporting

Typical source data
General ledger, subledgers, chart of accounts, entities, and currencies
Governed dimensions
Account, entity, cost center, period, currency, and scenario
Planning-ready datasets
Validated actuals, management hierarchies, FX measures, and reconciliations
Adaptive use
Actuals loads, reporting, variance analysis, and forecast seeding

Expected business valueA repeatable actuals contract with transparent reconciliation and drill-through.

Illustrative patterns only. The right starting point depends on current data effort, control risk, lineage needs, and sponsor urgency.

The operating model

Clear Responsibilities Across the Architecture

The Adaptive Data Foundation improves the division of responsibilities. It does not move every calculation out of Adaptive or replace finance ownership of definitions and controls.

Incorta and the data foundation

  • Source ingestion
  • Transaction preservation
  • Data joins and enrichment
  • Dimension creation
  • Business-rule processing
  • Dataset validation
  • Lineage
  • Delivery contracts

Workday Adaptive Planning

  • Planning models
  • Forecasting
  • Scenario management
  • Planning workflows
  • User input
  • Management reporting
  • Planning-specific calculations
  • Approval processes

Finance and data governance

  • Business definitions
  • Mapping ownership
  • Control thresholds
  • Data stewardship
  • Process approval
  • Reconciliation ownership
Shared accountability

Finance owns meaning. Data teams own dependable delivery. Adaptive teams own the planning experience.

Getting started

Begin With One High-Value Data Contract

A clearly bounded first process creates a reusable proof of value without turning the work into a broad enterprise transformation.

  1. 1

    Assess

    Identify the models with the greatest preparation, reconciliation, lineage, or scalability challenges.

  2. 2

    Define

    Document dimensions, measures, keys, grain, refresh behavior, validation, and drill-through needs.

  3. 3

    Build

    Create governed Incorta dimensions and one process-specific, planning-ready dataset.

  4. 4

    Expand

    Reuse the foundation across more models, reporting, analytics, and AI use cases.

Strong first-value candidates
Financial actualsWorkforce actualsRevenue and marginCapital expendituresTransaction drill-through
Interactive assessment

How Ready Is Your Adaptive Data Foundation?

Score the current state from 1 (largely manual or inconsistent) to 5 (governed, reusable, and well operated). Results stay in this browser session and are not saved or transmitted.

Overall maturity3.0/ 5
Established
Observed strengths
  • Dimension consistency3/5
  • Data preparation automation3/5
  • Reconciliation3/5
Priority improvement areas
  • Dimension consistency3/5
  • Data preparation automation3/5
  • Reconciliation3/5
Recommended first-value use caseFinancial actuals and management reporting

Validate the recommendation with process owners, current controls, delivery constraints, and sponsor priorities.

A pragmatic first step

Start with the data contract your planners need most.

Identify one process where preparation effort, reconciliation friction, or missing lineage is limiting the Adaptive experience.