Customer stories: Food manufacturers turn data into action with Titan
Real customer stories across planning, operations, finance, and IT. See what they started with, what they delivered first, and how they scaled.
Not sure which story is relevant? Share your situation and we will point you to the closest match.
One daily decision
Start with a concrete question tied to planning and production rhythm.
One trusted model
Shared definitions so dashboards, exports, and AI answers match.
Shared ownership
Business validates weekly, IT keeps boundaries and access under control.
Trusted by food manufacturers across Europe
How we helped our customers with their Data and AI ambitions
A planning team that got hours back
Planners ask Ask Titan questions in Microsoft Teams and get direct answers on orders, stock and capacity, powered by a governed model in Titan. Less manual work, fewer meetings, more predictable decisions.
- Faster decisions in the daily rhythm
- Answers on governed data, not spreadsheet logic
- Scenario checks in seconds, with feasibility guardrails
- Planning meetings focus on trade-offs, not validation
Meyer QSL
Better visibility on stock and flows across multiple hubs, with faster response to demand swings.
- Central view of inbound and outbound stock
- Faster planning decisions for key lanes
- Less manual reporting and spreadsheets
Mola BV
More stable production planning and less waste by connecting factory data and sales orders in one model.
- Better alignment between sales and production
- Clear overview of stock age and slow movers
- Support for daily planning meetings
PG Kaas
End to end insight from intake to packed product, with views on yield, waste and margin per product.
- Live yield overview per product and shift
- Earlier detection of process losses
- Support for investment and improvement decisions
Luiten Food
Better control of stock, ageing and margin in a complex meat portfolio, with clear signals on risk and waste.
- Stock visibility across locations and categories
- Earlier detection of stock at risk of expiry
- Insights for pricing and customer mix
Goodlife Foods
More reliable planning and stock insight across multiple sites and customer channels.
- Unified view on demand and production
- Clear KPIs for planners and operations
- Foundation for later AI use cases
Clean Solutions Group
Insight into service performance, routes and consumption, with a shared view across sales and operations.
- Service performance per customer and region
- Early signals on issues in stock and routes
- Data foundation for commercial and operations talks
Frequently asked questions
How comparable are these cases to our situation?
The best comparison is the decision flow, the systems involved, and the plant complexity. If you share those three, we can point you to the closest case and explain the typical starting scope.
Are the impact numbers guaranteed?
No. Outcomes depend on scope, data quality, adoption, and the starting situation. We validate a focused use case first before scaling.
How were results measured in these cases?
Where possible, results are based on operational measurements and validation sessions with the customer team. If a metric is indicative, it should be presented as observed impact during rollout, not a guaranteed outcome.
What was the typical first use case in these rollouts?
Most cases start with one daily decision: stock risk, production planning, downtime, service risk, yield loss, or margin visibility. We start small, validate definitions, and deliver something usable quickly.
How fast did teams see the first live output?
Typically within weeks. After kickoff we confirm access, connect the first source, and deliver a first live output with validated numbers.
When does Ask Titan make sense in the rollout?
Often after the first governed Titan model and dashboards are stable. Then Ask Titan can answer questions on the same definitions inside Microsoft Teams.
Want a similar outcome in your organization?
In a short call we map your plants and systems, pick one daily decision to improve, and suggest the simplest first step based on the cases that match your situation.
No slide deck session. We talk concrete plants, systems, and decisions.
What we cover
- 1 Discover: your plants, systems, and the decision behind the KPI.
- 2 Prove: pick the first use case, success criteria, and owners.
- 3 Scale: outline a practical rollout path based on what worked in similar cases.