Critical
Carbon fiber prepreg
- Required
- 1 482 kg
- Available + in transit
- 910 kg
- Shortage
- 572 kg
- Shortage probability
- 92%
Action
Order 800 kg today
AI Demand & Purchasing
Know what you'll need and how much,before you place the orders.
INVO combines future orders, configurations and bills of materials with the history of actual consumption, inventory levels and deliveries in transit to forecast component requirements and prepare a purchase recommendation.
Units
26 400
Configurations + bills of materials
Carbon fiber required
1 482 kg
- In stock
- 610 kg
- In transit
- 300 kg
- Missing
- 572 kg
Recommended order
600 kg
Why this is hard
Component requirementschange every single day.
How much you need to buy doesn't depend only on how much you used last time. The production plan changes, the configuration changes, actual consumption changes and so does the stock you already hold.
- 01
The number of units changes
New orders, call-offs, rework, cancellations and contract changes all affect production volume.
- 02
The configuration changes
A different configuration means different bills of materials and different requirements for specific components.
- 03
Actual consumption changes
The bill of materials doesn't always match what production really uses once scrap and rework are counted.
- 04
Available stock changes
Deliveries, issues, waste and leftover stock all change what actually needs buying.
So the question isn't
How much did we buy last time?
but
How much will we need under the current production plan?
From demand to component
From a number of units to a concreterequirement for every component.
INVO combines the demand forecast with configurations and bills of materials, then converts it into specific material requirements.
01 — Demand
How many units will we produce?
26 400
units
- Standard
- 12 800
- EO/IR payload
- 4 200
- Extended range
- 3 400
- Other
- 6 000
The volume forecast can account for program, customer, variant, delivery lot schedule and order history.
02 — Configurations & bills of materials
What will we produce?
Bill of materials #284
per airframe
- Carbon fiber
- 180 g
- Epoxy resin
- 120 g
- Aluminum parts
- 150 g
- Adhesive
- 10 g
The configuration plan and bills of materials determine which components future production needs.
03 — Material requirements
How much of each component will we need?
18 420 kg
total
- Carbon fiber
- 1 482 kg
- Aluminum stock
- 1 240 kg
- Epoxy resin
- 830 kg
- Adhesives
- 620 kg
INVO converts planned production into material requirements at SKU level.
04 — Purchasing need
What actually needs buying?
672 kg
net requirement
- Required
- 1 482 kg
- Available
- 610 kg
- In transit
- 300 kg
- Safety stock
- 100 kg
Only after accounting for stock and deliveries do you get the real purchasing need.
Control center
Demand, stock and purchasing riskin one place.
A planner shouldn't be analyzing thousands of SKUs by hand. INVO shows the forecast and the items that actually need a decision.
- Forecast units
- 26 400
- Material requirements
- 18 420 kg
- Recommended orders
- 42
- Stock coverage
- 3.2 days
- SKUs needing attention
- 7
Items requiring a decision
| SKU | Required | Available | In transit | Risk | Recommendation |
|---|---|---|---|---|---|
| Carbon fiber prepreg | 1 482 kg | 610 kg | 300 kg | High | Order 800 kg today |
| Aluminum 6061 bar | 1 100 kg | 340 kg | 500 kg | Medium | Order 300 kg tomorrow |
| Copper wire | 420 kg | 95 kg | 0 kg | Critical | Order 400 kg today |
| G10 sheet | 280 kg | 310 kg | 200 kg | Excess | Hold the next order |
Management by exception
Don't analyze every product.See only what needs a decision.
INVO can monitor thousands of items at once. The planner focuses on the exceptions — shortage risk, excess stock or a delivery timing problem.
Excess
PA12 powder
- Expected demand
- 420 kg
- Available + in transit
- 610 kg
- Expected excess
- 190 kg
Action
Cut the next PO by 200 kg
On track
Epoxy resin
- Expected demand
- 830 kg
- Available + in transit
- 860 kg
Action
No action needed
AI analyzes every item. The planner decides where they are genuinely needed.
How it works
From a unit plan toa recommended order.
- 01
We know what has to be produced.
INVO uses future orders, the configuration plan, build counts and bills of materials.
- Orders
- Units
- Configurations
- Bills of materials
- 02
We predict the real requirement.
Models use the history of actual consumption to determine how much material will likely be needed under the current plan.
- Planned requirement
- 1 420 kg
- Historical patterns
- +4.4%
- Expected requirement
- 1 482 kg
- 03
We check what is actually missing.
The forecast requirement is compared against stock, deliveries in transit, safety stock and supplier terms.
- Required
- 1 482 kg
- − Available
- 610 kg
- − In transit
- 300 kg
- + Safety stock
- 100 kg
- Net requirement
- 672 kg
Models & technology
Different questions requiredifferent models.
The models draw on data collected in the INVO data warehouse: the history of orders, configurations, bills of materials, actual consumption, stock and deliveries.
- Orders
- Configurations
- Bills of materials
- Consumption
- Inventory
- Suppliers
- Deliveries
Forecasting model
How much will we likely need?
The model analyzes earlier runs and checks which factors influenced actual consumption. When a similar production plan appears, it uses those relationships to predict the future requirement.
Planned
1 420 kg
Forecast
1 482 kg
Benefit: A more realistic forecast based on actual execution.
Gradient Boosting
LightGBM · XGBoost · CatBoost
Time-series models
How will the requirement change over time?
The models analyze recurring patterns and changes over time, so they can forecast demand for the coming days or weeks.
Mon
1 482
Thu
1 340
Benefit: You see future requirements with enough lead time.
Time-Series Forecasting
N-HiTS · Temporal Fusion Transformer
Risk model
How high is the risk of running out?
Production is not fully predictable. That's why the model can show not just one forecast, but a range of possible requirements and a level of risk.
Expected range
1 400–1 560 kg
Stockout risk
82%
Benefit: The planner can match inventory levels to the actual risk.
Probabilistic Forecasting
Quantile Regression · Conformal Prediction
A more complicated model does not always mean a better forecast. We pick the model that best predicts the real requirement on the client's own data.
From forecast to action
The forecast says what you'll need.INVO works out what to actually buy.
How the recommendation is built
- AI forecast · required
- 1 482 kg
- Inventory · available
- 610 kg
- In transit
- 300 kg
- Safety stock · min
- 100 kg
- Net requirement
- 672 kg
- Supplier · MOQ
- 200 kg
- Supplier · lead time
- 24 h
Recommended order
800 kg
The recommendation doesn't come from the forecast alone. INVO also accounts for what is already in stock, what is in transit and the supplier's constraints.
The optimization engine can account for
- MOQ
- Lead time
- Supplier availability
- Safety stock
- Warehouse capacity
- Shelf life
- Purchase cost
From alert to purchase order
Alert
572 kg of carbon fiber may be missing within 48 h.
Recommendation
Order 800 kg today.
Approval
The planner approves or adjusts the recommendation.
Purchase order
The order moves into the purchasing process.
The goal isn't another dashboard. The goal is an earlier and better purchasing decision.
Business impact
A better forecast means less excess,fewer shortages and fewer emergency buys.
Overbuying ↓
Fewer excess purchases
Match prepreg, cell and resin purchases to expected demand.
Emergency buys ↓
Fewer last-minute purchases
Detect future shortages before you have to buy at the last moment.
Inventory ↓
Less capital frozen in stock
Hold stock that matches expected demand and the level of risk.
Stockout risk ↓
Lower risk of running out
Identify the components the future configuration needs earlier.
Planner time ↓
Less manual analysis
The planner focuses on exceptions instead of reviewing every item.
Service level ↑
Better component availability
Make the supply the production plan depends on more predictable.
ROI calculator
Work out the potential on your own costs.
The two most common sources of cost: excess purchasing and last-minute emergency buys.
Current cost: 280,000 USD
Savings potential
56,000 USD
/ year
≈ 4,667 USD a month
The simulation shows the potential scale of the effect and is not a guarantee of results. The actual outcome depends on processes, data quality, purchasing structure and the scope of the implementation.
AI Demand & Purchasing
See what your production will need,before you place the next order.
In the demo we'll show how INVO combines the production plan, configurations, bills of materials, actual consumption and stock to forecast future requirements and prepare purchase recommendations.