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Four European markets. Multiple systems. One operating layer.
Bredent Medical ran four EU markets on disconnected systems. Orders placed by hand, no unified view.
- Client
- Bredent Medical
- Sector
- Healthcare, commercial operations
Growth goal
Run four European markets as one commercial operation, with each market keeping its local systems.
Operating constraint
Orders, warehouse activity and reporting needed manual coordination between disconnected systems in every market.
Measured result
60% less manual entry and the first real-time operating view across all four markets.
We ran four markets on systems that did not talk to each other. SIEL connected them without replacing anything, and for the first time we see all four in one view. The forecasting came on top of that.
The full story
- Baseline
- Four markets, each on its own systems. Orders were placed by hand and nobody had a single view of stock, orders and reporting across the group.
- System
- One integration layer connecting Dynamics 365 and the legacy systems, then AI demand forecasting on top of the unified data.
- Controls
- Every integration step is logged. Forecasts are suggestions that planners review, not orders that place themselves.
- Result
- Manual entry down 60%. A current commercial view across the four markets, and a way to add a market without replacing its systems.
In depth
Four markets with one growth ambition
Bredent Medical saw clear room to grow across Europe. The plan was simple to state and hard to run. Four national markets should work as one commercial operation, while each market kept the local systems its teams knew. Growth meant more orders, more stock movements and tighter expectations from clinics and distributors. The leadership wanted to move faster on pricing, stocking and product launches. To do that with confidence, they needed an operating view that reached across all four markets and into the systems doing the daily work. The ambition was regional, the tools were local. That gap was where friction lived.
Inside each country, teams did what they could. They took orders, checked stock and arranged shipments. They compiled reports and shared updates. The work kept customers supplied, but it depended on people stitching together information by hand. Every extra customer and every new product meant more coordination. That was the limit the company would hit first. To serve more demand without constant fire fighting, Bredent Medical needed a way to run its existing systems as if they were one platform, not four separate ones.
Manual coordination as the operating limit
The operating constraint showed up in everyday tasks. Each market ran its own systems, with different ways of recording orders, stock and shipments. Dynamics 365 was in the mix, as were legacy applications that were stable and trusted but isolated. There was no single place where anyone could see current stock, open orders and warehouse activity across all four markets at once. When customer demand shifted in one country, planners in another might not see the impact until it reached them as a shortage or a rush order. The business relied on people to spot patterns across disconnected views.
Orders were often placed by hand. Staff keyed data from one system into another so that warehouses could act and reports could be compiled. Warehouse teams waited for email instructions or spreadsheets. Commercial leaders waited for end of week or end of month reporting runs. Any change to a product line or a promotion increased the manual work needed to keep systems in step. The result was an operation that worked, but only by leaning on experienced staff who knew how to reconcile discrepancies market by market. That experience was valuable, but it could not be cloned to handle more volume.
Connecting existing systems into one operating layer
Bredent Medical needed more capacity without ripping out systems that worked. SIEL AI’s role was to connect those systems so they could act as one operation. The first step was to build a single integration layer that linked Dynamics 365 with the legacy systems in each market. This layer became the place where orders, stock movements and other key events were exchanged and aligned. Instead of staff retyping information, the integration handled the movement of data between systems. Local applications stayed in place, but they no longer lived on islands. They were part of a wider network that mirrored how the commercial operation was meant to run.
Once the integration layer held a reliable picture of activity across the four markets, SIEL and Bredent Medical used that unified data to support better planning. On top of the connected systems, SIEL added AI demand forecasting. The forecasting system took in the combined history and current signals from all markets. It produced suggested demand plans that reflected cross market behaviour, rather than four separate guesses. With this in place, planners could see proposed order volumes that already accounted for trends and seasonality across the region. The AI did the heavy lifting on pattern recognition. Planners focused on the decisions that needed human judgement.
Keeping humans in control of a connected operation
For Bredent Medical, control was as important as automation. The company needed to know what the integrated system was doing, and to keep people in charge of decisions that affected customers and stock. Every integration step in the new operating layer is logged. When data moves from a legacy system into Dynamics 365 or another application, that movement is recorded. If a value is transformed or routed, the integration logs show what changed and why. This creates an audit trail that operations and IT teams can inspect. When someone sees an unexpected figure in a report, they can trace it back through the steps that produced it, across all four markets.
The AI demand forecasts are suggestions, not orders that place themselves. The system generates proposed demand figures and presents them to planners for review. A planner can accept, adjust or reject a suggestion based on local knowledge, supplier constraints or upcoming promotions. The AI does not bypass human approval. It supports it. This structure keeps the business in control of stock and service levels. It also makes it easier to refine the AI models over time, because there is clear feedback from planners on which suggestions worked and which did not. The company gains the speed of machine generated forecasts without losing ownership of the decisions.
A regional view and room to grow further
The result is a commercial operation that can serve more demand with less friction. Manual entry is down by 60 per cent. Staff spend less time keying orders into multiple systems and more time handling customer questions and exceptions. For the first time, Bredent Medical has a real time operating view across all four European markets. Leadership can see current stock, open orders and warehouse activity in one place, rather than piecing it together from separate reports. This supports faster, more confident decisions on where to hold stock, how to support product launches and when to adjust to demand shifts.
The connected operating layer also changes how the company thinks about growth. When Bredent Medical considers adding a new market, it does not need to standardise that market on a single global system before it can contribute to the regional view. The integration layer provides a way to connect another set of local systems into the existing operation. That preserves local flexibility while extending regional coordination. For a company in a similar position, the lesson is clear. You can grow into more markets and handle more volume by connecting the systems you already run, then adding intelligence where it informs real decisions, not by replacing everything at once.
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