Demand Forecasting Software Development

When spreadsheet forecasting stops scaling with your business

Most supply chain teams start forecasting in spreadsheets. For a small, stable product range, a well-maintained spreadsheet works. The problems appear as the range grows, as the business adds channels with different demand patterns, and as promotional activity becomes more frequent. Planners spend more time maintaining the model than improving the forecast, and when a planner leaves, the institutional knowledge embedded in the spreadsheet leaves with them. We build demand forecasting systems for manufacturers, distributors, and retailers managing product ranges where demand variability, lead time uncertainty, and seasonal patterns make spreadsheet planning impractical.

  • Statistical forecasting models, moving average, exponential smoothing, and seasonal decomposition, selected and tuned per SKU based on demand history and variability

  • Seasonal adjustment capturing recurring demand patterns so forecasts reflect actual peaks and troughs rather than a flat trend line

  • Safety stock calculation based on lead time variability, demand variability, and target service levels, recalculated automatically as inputs change

  • Replenishment suggestions generated from the forecast, safety stock position, and current inventory, with planner approval before order creation

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4.9
on Clutch
See our work

The problem

Sound familiar?

  • Planners spending most of each week manually adjusting system forecasts because the model doesn't account for promotions, seasonality, or known demand events?

  • Safety stock levels set by gut feel or outdated rules of thumb, leaving the business either over-stocked on slow movers or regularly out of stock on fast movers?

Short answer

RaftLabs builds custom demand forecasting software for supply chain and operations teams who need statistical forecasting, seasonal adjustment, safety stock calculation, replenishment suggestions, and forecast accuracy tracking in one connected system. Most demand forecasting software projects deliver in 10 to 14 weeks at a fixed, agreed cost.

Key takeaways

  • Model selection runs per SKU based on demand history and pattern, moving average, exponential smoothing, seasonal decomposition, or ensemble, with confidence intervals shown instead of a single false-precision number.
  • Safety stock recalculates automatically from demand variability, lead time variability, and target service level, so it adjusts as a supplier's performance or demand pattern shifts.
  • Forecast accuracy is tracked with MAPE, WMAPE, and bias metrics by SKU, category, planner, and supplier, surfacing systematic over- or under-prediction rather than random error.
  • Exception alerts prioritise the SKUs with the largest stock or cost risk, so planners work the highest-impact problems first instead of scanning the full catalogue.

Trusted by

Vodafone logo
Aldi logo
Nike logo
Microsoft logo
Heineken logo
Cisco logo
Calorgas logo
Energia Rewards logo

Demand forecasting delivery, by the numbers

software products shipped
100+
cost delivery
Fixed
week delivery cycles
10-14
industries served
24+

When spreadsheet forecasting stops scaling with your business

We build demand forecasting systems where the model per SKU, the seasonal capture logic, the safety stock formula, and the replenishment workflow are all designed during discovery before any code is written.

Capabilities

What we build

  • 01
    Statistical forecasting engine

    Per-SKU model selection with confidence intervals and historical back-testing showing the rationale behind each choice.

  • 02
    Seasonal adjustment and event capture

    Recurring pattern indexing and a promotional/event library so demand impact is estimated automatically for repeat events.

  • 03
    Safety stock calculation

    Recalculated automatically from demand variability, lead time variability, and per-category service level targets.

  • 04
    Replenishment suggestions

    Supplier-grouped order suggestions applying MOQ and order-multiple rules, with a planner approval step before order creation.

  • 05
    Forecast accuracy tracking

    MAPE, WMAPE, and bias metrics by SKU, category, planner, and supplier, with trend reporting after model changes.

  • 06
    Exception management

    Impact-prioritised exception queues with configurable thresholds per category and a recurring-exception trend report.

How we work

From scope to live forecasting system

  1. Week 1
    01

    Planning cycle and pain-point scoping

    We map how your team forecasts today, your product range, and where the current process lets you down. You leave week 1 with a written scope document and a fixed-price quote.

  2. Weeks 2-4
    02

    Model and safety stock design

    Forecasting method selection, safety stock formulas, and replenishment logic designed against your actual demand patterns.

  3. Weeks 5-11
    03

    Build and integrate

    Forecasting engine, safety stock, and replenishment suggestions built in parallel, tested against real demand history.

  4. Final 2-3 weeks
    04

    Launch and planner training

    Planning teams trained on the new workflow before full rollout.

Why us

Why supply chain teams choose RaftLabs

  • 01
    Senior engineers build what they scope

    The engineers who assess your demand patterns also build the solution. No bait-and-switch, no offshore handoff after the contract is signed.

  • 02
    Fixed price before development starts

    We scope the work, calculate the cost, and lock it in writing before any development starts.

  • 03
    9 years and 100+ products shipped

    Clients include Vodafone, T-Mobile, Aldi, Nike, Cisco, and Lockheed Martin. Track record building supply chain and logistics platforms.

  • 04
    We'll tell you when your ERP module is enough

    Custom is justified by real forecasting complexity, not recommended by default.

  • 05
    Model rationale is visible and auditable

    Back-testing and confidence intervals mean planners can see why a model was chosen, not just trust a black box.

Have a demand forecasting project?

Tell us how your team forecasts today: your product range, your planning cycle, and where the current process lets you down. We'll scope a forecasting system built around your actual demand patterns and replenishment requirements.

Talk about your demand forecasting project

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Demand Forecasting Software Development, scoped in one call.

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Frequently asked questions

Custom is right when your SKU range has enough variability that a single forecasting method produces poor results, when your promotional calendar materially affects demand and the ERP can't model it cleanly, when you need forecast accuracy reporting the ERP doesn't produce, or when your exception management workflow doesn't match what the module offers.

At minimum, two to three years of sales history at the SKU and location level, a product master, and a supplier master with lead times. Promotional history significantly improves quality. Inventory on-hand and in-transit data is needed for replenishment suggestions.

Yes. Common integrations include SAP, Microsoft Dynamics, NetSuite, and major WMS platforms, pulling sales history and inventory positions in, and pushing approved replenishment suggestions back as purchase order requests.

A focused build covering statistical forecasting, seasonal adjustment, safety stock, and replenishment suggestions typically runs $35,000 to $70,000. Adding accuracy dashboards, exception management, and ERP integration brings the total to $70,000 to $130,000.

Work with us

Tell us what you need. We'll tell you what it would take.

We scope Demand Forecasting Software Development in 30 minutes. You walk away with a clear cost, timeline, and approach. No commitment required.

  • Scope and cost agreed before work starts. No surprises. No obligation.
  • Working prototype within 3 weeks of kickoff.
  • Pay by milestone. You see progress before each invoice.
  • 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
  • All conversations are NDA-protected.

Go deeper

Browse our case studies

Supply chain software by area