Data Analytics · Demand Forecasting

Forecast demand from patterns in your data, not opinions in a meeting.

Your demand planning process runs on last year\u2019s sales adjusted by a gut-feel percentage. ML models trained on your actual order history, seasonal patterns, and market signals produce forecasts that are measurably more accurate \u2014 and they improve automatically as more data accumulates.

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The Problem

Demand Forecasts That Nobody Trusts

Annual forecasts built in a conference room and never updated as the year progresses
Sales team forecasts inflated or sandbagged depending on how quotas are set
No SKU-level or customer-level forecast granularity \u2014 just top-line revenue targets
Stockouts and excess inventory coexisting because the forecast doesn\u2019t match actual demand patterns
What We Deliver

Service Scope

01
Historical Pattern Analysis

Analyze 2\u20135 years of order history to identify demand patterns by product, customer, channel, and geography. Detect seasonality, trends, and cyclical patterns automatically.

02
ML Forecast Models

Time-series and regression models trained on your data to produce SKU-level forecasts. Multiple models compared and the best-performing selected for each product segment.

03
Forecast Accuracy Measurement

Track MAPE, WMAPE, and bias metrics continuously. Compare ML forecasts against your current method so improvement is quantified, not assumed.

04
Collaborative Forecast Adjustment

Sales and operations teams can review and adjust ML forecasts with their market intelligence. Adjustments are tracked so you can measure whether human overrides improve or degrade accuracy over time.

05
ERP Planning Integration

Forecasts feed directly into Odoo\'s MRP and purchasing modules. No manual re-entry between the forecast and the plan.

06
Demand Sensing

Short-term forecast adjustments based on recent order velocity, leading indicators, and market signals. Catch demand shifts weeks before they show up in the monthly forecast.

How We Work

Engagement Process

01
Data Assessment

Evaluate order history depth, quality, and granularity. Identify supplementary data sources \u2014 pricing, promotions, market indices \u2014 that improve forecast accuracy.

02
Model Development

Build and validate forecast models against historical data. Benchmark ML accuracy against your current forecasting method for a direct comparison.

03
Integration & Workflow

Connect forecast outputs to ERP planning modules and establish the S&OP review workflow. Define roles for forecast review, adjustment, and sign-off.

04
Production & Improvement

Deploy with accuracy dashboards and continuous model retraining. Monthly accuracy reviews drive model tuning and feature engineering improvements.

Common Questions

Frequently Asked Questions

Work with Metrotechs

Every engagement starts with an assessment.

Not a proposal. Not a sales call. We tell you what we find, not what you want to hear. The Launchpad assessment maps your operation before any software work begins.

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