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Customer story

Goodlife Foods Group reporting and 1-day month-end close

Goodlife Foods needed one governed view across procurement, inventory, production, sales and finance. Titan became the shared group data model to reduce manual consolidation and steer on consistent margin and yield KPIs across business units.

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Convenience foods Group reporting Margin and yield steering
Case snapshot
Group reporting for performance, margin and yield

Results

Month-end close

1 day

From 1.5 weeks

Delivery cadence

20 to 30

Days per domain

Data exchange

Stable

Less rework

A shared definition set reduced manual consolidation and made group performance discussions consistent across finance, operations and management.

Challenge
Manual close

Group reporting required manual consolidation and inconsistent definitions, which slowed month-end close and limited steering on margin and yield.

Solution
Governed model

A governed group data model with reusable definitions for procurement, inventory, production, sales and finance, enabling faster close and consistent performance insights.

See what we built
Want this for your operation? We can scope it in one call.

Stewart Henderson | Group IT Manager @ Goodlife Foods BV

“Food For Analytics demonstrate a clear passion and skillset when it comes to data. whether its architectural design, strategic support or building a sustainable Data Analytics infrastructure platform, there guidance, support and execution on such projects is excellent.”

Context

Group reporting across business units needs one trusted model

Goodlife Foods operates across multiple business units and decision cycles.
Goodlife Foods operates across multiple business units and decision cycles. When consolidation is manual and KPI definitions differ per entity, month-end close slows down and teams cannot compare performance with confidence. The goal was a governed group model and repeatable reporting so finance, operations and management steer on margin and yield from the same numbers.

Scope

Group reporting across procurement, inventory, production, sales and finance, with shared steering KPIs for margin and yield.

Users

Finance, management and operations teams aligned on one definition set and consistent performance views.

Foundation

Titan consolidates ERP and operational data into governed models, keeping margin, yield and performance KPIs consistent across business units.

Outcome

Faster month-end close and clearer group steering through reliable consolidation, reusable KPI logic and fewer manual steps.

Challenge

Manual consolidation and KPI definition drift slowed month-end close and group reporting

Before the rollout, data exchange between ERP systems and group reporting required manual steps. That slowed down the month-end close cycle and increased the risk of mismatched margin and yield definitions between business units.

Manual work

Too much time spent collecting, reconciling and reformatting data for reporting.

Definition drift

Different interpretations of margin, yield and KPIs across subsidiaries.

Slow cycles

Month-end cycles and steering meetings depended on late, manual, error-prone inputs.

Solution

Titan as the governed group data model for reporting

Food For Analytics implemented Titan for Goodlife Foods to create one governed data model across domains and business units. By enriching master data with business unit attribution, consolidation became faster, KPI definitions stayed consistent, and group reporting became easier.

  • One governed model for procurement, inventory, production, sales and finance
  • Master data enrichment to enable consistent consolidation across business units
  • A repeatable delivery framework that spins up new domains in 20 to 30 days
Delivery rhythm

A repeatable loop that makes scaling predictable.

Align

Confirm KPIs, owners and definitions for consolidation and steering.

Connect

Deploy pipelines and environments using the automation framework.

Validate

Reconcile numbers, then publish reports with shared definitions.

Scale

Embed the routine in month-end and steering cycles and extend with new domains.

ISO 27001 controls and Azure native deployment
Repeatable delivery framework

Results

1-day month-end close and clearer group steering

The rollout reduced manual consolidation and helped teams align on the same numbers across business units. Month-end close shifted from around 1.5 weeks to 1 day as an observed result during rollout and validation.

Month-end close

1 day

From around 1.5 weeks

Observed shift from around 1.5 weeks to one day for consolidation and reporting steps.

Shared definitions
Less manual steps

Delivery cadence

20 to 30

Days per domain

Repeatable delivery approach to roll out new domains with predictable lead time.

Repeatable rollout
Predictable scaling

Data exchange

Stable

Less rework

Data exchange between ERP systems and reporting became more stable, reducing manual rework and corrections.

Governed controls
Fewer corrections

What we built

A repeatable foundation for group reporting and steering

The focus was to standardize KPI definitions across business units, reduce manual consolidation in month-end cycles, and deliver reporting that matches steering meetings.

Governed group data model

Conformed dimensions and KPI definitions that work across domains and business units.

  • Procurement, inventory, production, sales and finance domains
  • Shared definitions for margin, yield, revenue and cost
  • One set of numbers for management, finance and operations

Master data enrichment

Business unit attribution and consolidation logic to compare performance reliably.

  • Business unit attribution for products, plants and flows where needed
  • Consolidation rules that stay consistent across reports
  • Less definition drift between subsidiaries

Automation framework

Reusable deployment patterns for pipelines and environments to scale domain by domain.

  • Standard ingestion patterns and quality checks
  • Template-driven environments for faster rollout
  • Repeatable delivery in 20 to 30 days per domain

Reporting and adoption routine

Dashboards that match steering meetings, plus checkpoints that keep numbers trusted.

  • Group performance view by business unit and portfolio
  • Reconciliation checkpoints during month-end and reporting cycles
  • Ownership per KPI set and a backlog for next domains

Implementation

Phased delivery from consolidation pain to a stable group routine

The rollout started with a clear group scope and fast stabilization of data exchange. Then each domain was delivered in 20 to 30 days, with checkpoints that reduced month-end effort and kept definitions consistent across business units.

Phase 1

Scope and connect

Confirm the group KPI set (margin, yield, revenue, cost) and the consolidation logic. Connect the relevant ERP and reporting inputs into a single governed foundation.

Phase 2

Build and validate

Enrich master data with business unit attribution, implement conformed dimensions, and validate numbers with finance and operations. Publish the first group performance and portfolio views.

Phase 3

Run and improve

Embed reconciliation checkpoints into month-end, stabilize handoffs between systems, and extend the platform with new domains in 20 to 30 day increments while keeping KPI definitions stable.

Month-end checkpoints Domain rollout

Frequently asked questions

How did Goodlife Foods reduce month-end close to 1 day?

By replacing manual consolidation with a governed group data model and shared KPI definitions, then validating the numbers in the month-end routine. The 1 day result is an observed shift during rollout, not a guaranteed outcome.

What does 'group reporting' mean in this case?

One consolidated performance view across business units and domains, using consistent definitions for margin, yield and other steering KPIs.

What did Food For Analytics deliver?

A governed group data model for procurement, inventory, production, sales and finance, plus reporting outputs that fit month-end close and steering routines.

How do you prevent KPI definition drift across subsidiaries?

We align KPI logic with finance and operations once, implement it in the governed model, and publish reusable reporting outputs that keep definitions consistent.

What is a realistic rollout approach for a group like ours?

Start with one consolidation pain point and one KPI set (for example margin and yield), connect the first sources, validate with the teams involved, and then extend the model domain by domain.

Are the results guaranteed?

No. Outcomes depend on scope, data quality, adoption, and the starting situation. We validate a focused use case first before scaling.

Want group-wide performance insights without manual consolidation?

In a short call we map your business units, ERP landscape and reporting cadence. You leave with a concrete first domain and a rollout plan that reduces month-end effort and keeps KPI definitions consistent.

Practical session. Concrete data sources, owners and steering questions.