Automated Demand Planning and Replenishment in Business Central
Forecasts, order proposals and inventory run directly in Microsoft Dynamics 365 Business Central – no Excel-Sunday, no separate planning tool. dicobis.planning forecasts demand by SKU, channel and location, factoring in growth, seasonality, events and lookalikes, and drives automated order proposals to suppliers from that. Performance marketing runs on the stock you actually have – out-of-stock and overstock become the exception.
Forecast for Growth, Season and Events
Forecasts by SKU, channel and location. Seasonality, promotions, new products and lookalikes are built into the model – planning no longer starts from zero.
Replenishment Automated All the Way to the Order
Order proposals are generated from forecast, inventory, lead times and supplier terms. Planners review and release – manual Excel tracking is gone.
Performance Marketing in Sync with Availability
Forecast, replenishment and marketing plan interlock. What's running low is prioritized and allocated, instead of being pushed out equally across all channels.
Bundles, Variants and Substitute Items in the Model
Sets, size and colour variants, and substitution chains are planned consistently. A sold-out variant no longer skews the forecast for the entire product.
From Forecast to Order in Clear Steps
dicobis.planning maps the entire planning process as a continuous standard – from demand forecast through safety stock to the triggered order. Every stage sits in Business Central, every assumption is traceable, and planners work from proposals instead of raw data.
Forecast Demand by SKU, Channel and Location
Forecasts are calculated at the granular level you actually manage at: item, marketplace or webshop, warehouse or region. Aggregates for reporting and planning are derived from that – not the other way round.
Bring Season, Events and Lookalikes into the Model
Seasonality, promotions, Black Friday peaks and product launches are explicit parts of the model. New products start with lookalike profiles from comparable items, instead of a gut-feel ramp-up.
Derive Safety Stock Dynamically
Service level, forecast uncertainty and replenishment lead time determine the safety stock per item. Instead of a flat coverage figure across all items, the system calculates per SKU – and adjusts as the business changes.
Generate Order Proposals to Suppliers
Forecast, current stock, open orders, lead time and supplier terms – MOQ, packaging units, discount tiers – combine into concrete order proposals, ready for the planner instead of a raw number.
Trigger the Order Directly from Business Central
Released proposals become orders in BC. Status, shipping notices and goods receipt flow back into the forecast – the next plan doesn't start from zero, but on an updated reality.
Assortment, Channels and Locations in Step
Growing retailers rarely have a forecasting problem on a single item – they have one across channels, warehouses and promotions. dicobis.planning carries this multidimensionality: multiple warehouses and locations are optimized together, scarce stock is prioritized by channel and rule, and promo and cannibalization effects are modelled explicitly.
Optimize Multiple Warehouses and Locations Together
Multi-echelon planning: forecasts and safety stocks are aligned across the entire network structure – central warehouse, regional hubs, fulfillment locations. Transfer orders and procurement interlock instead of each location planning on its own.
Prioritize Channels and Locations Under Scarcity
Allocation logic distributes scarce stock by rule: by margin, customer service level, strategic channel priority or region. Instead of first-come-first-served, the right orders get served – traceably and auditably.
Account for Price, Promo and Cannibalization Effects
Promotional pricing increases sales of the promoted item – and typically reduces sales of comparable items in the same assortment area. dicobis.planning factors cross-SKU effects and cannibalizing promotions explicitly into the forecast, instead of treating each item in isolation.
Plan Bundles and Variants Consistently
Sets, size and colour variants, and configurations are planned at their logical level: the bundle as the sales unit, the components as the procurement unit. Planning runs on the components, marketing on the bundle.
Spot Out-of-Stock and Overstock Early
Thresholds and trends are visible before they become a problem. Planners react to early indicators – not to an empty shelf line on a Monday morning.
One Meeting
to a Clear Decision
Book your free analysis session. You'll get an initial assessment of forecast quality, replenishment potential and the fit of dicobis.planning for your assortment.
Book a session now
Numbers That Make Planning on BC Tangible
Solid benchmarks from our projects and the platform world – as a point of reference for your decision. We'll get concrete in the analysis session.
Completed BC implementations per year
Months standard project duration from discovery to go-live
One system for forecast, replenishment and ordering – no separate planning tool
Planning levels from a single system: SKU, channel, location
Book a Free Analysis Session
In the session, we look at your assortment and channel structure, sort out forecast and replenishment needs, and identify what's covered by the dicobis.planning standard.
- Stock-take of today's planning processes – tools, responsibilities, volumes
- Feature match against the dicobis.planning standard
- Assessment of data quality, master data and forecast foundation
- Rough roadmap with effort, phases and risks
FAQ
We currently plan in Excel and native ERP tools – when does dicobis.planning pay off?
As soon as assortment depth, channel variety or performance-marketing pressure mean planners have to compensate on weekends for what's missing during the week. Typical triggers: multiple marketplaces and webshops running in parallel, lookalike maintenance for new items, seasonal and event peaks, out-of-stock rates that are throttling your performance marketing. Where the tipping point sits for you, we work out concretely in the analysis session.
What data is the forecast based on?
Your sales, inventory and movement data in Business Central – supplemented by season, event and promotion definitions, master data on bundles and variants, and lookalike assignments for new products. Methodologically, the module works with statistical time-series models that explicitly decompose trend, seasonality, events and promo effects. For high variant complexity or short history, ML methods – typically gradient-boosted regression – are added. The cleaner the master data and movement history, the more robust the forecast; we check the data foundations before model training.
How are new products handled when there's no history yet?
Through lookalike profiles: you assign a new product to one or more comparable existing items, whose history serves as a starting profile. With the first weeks of sales, the profile is automatically sharpened – the forecast is more reliable from day one than a gut-feel figure, without anyone maintaining a parallel spreadsheet.
How does dicobis.planning work together with dicobis.commerce and dicobis.connect?
dicobis.planning builds directly on your inventory and movement data in Business Central – regardless of how you currently connect shops, marketplaces or warehouses to BC. dicobis.planning is already included in dicobis.commerce; bundled with dicobis.connect, it uses the order and marketplace data that becomes available through it. dicobis.planning can equally be run standalone if your integration is solved differently today.
Do we need data scientists to work with it?
No. Planners and category managers work in the standard BC interfaces with forecast values and order proposals. The model logic – seasonality, lookalikes, safety stock – is configured via parameters, not code. If you want statistical depth, such as your own promo models, we build that into the implementation project.
How does the rollout work?
We follow the dicobis phase model: discovery and data check, ramp-up, project phase with design workshops for forecast hierarchies and replenishment rules, final testing, cut-over and hypercare. We adapt standard processes and only customize where you genuinely differ in the market. We work out effort and duration concretely in the analysis session – the methodology itself is described on our Methodology page.