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Voltra Lighting: forecasting production when the date lives at the wrong level

A maker of high-end portable lighting for luxury hotels and restaurants. Production starts ahead of time: every month, they need to know how many units of each product to make, and for which delivery month. A simple question to ask, and impossible to support without first fixing the data structure.

Hong Kong, management in LisbonHigh-end lightingManufacturing and distributionProject run in English
3
workstreams run in parallel
2
custom developments
1
date moved down to the right level
0
spreadsheet rework
The context

A forecast that goes wrong as soon as an order is spread out

Voltra Lighting designs and distributes rechargeable cordless table lamps. Production starts before firm orders come in, so everything depends on a forecast by product and by delivery month. At the same time, the sales team needed individual targets, not a global target that means nothing to anyone. The whole project is run in English, with a small team and management based in Lisbon.

What Odoo doesn't do out of the box
  • The commitment date lives at the level of the whole order. As long as it stays global, you cannot spread the volumes of a single order across several delivery months.
  • The sales target only exists at team level. There is no way to show salespeople how they are doing against their own target, or to compare two salespeople over the same period.
  • Warranty replacements are not traced back to their original order, so the real cost of after-sales service stays invisible.
What we built

Three structural fixes, not one more dashboard

1
Commitment date moved down to the order line
This is the technical prerequisite, and it does not show on screen. Without it, no forecast by delivery month is reliable as soon as an order has several delivery dates. It is exactly the kind of detail that makes a top-down reporting project fail.
2
Forecast by product and by delivery month
Expected volumes are aggregated by product and by month, which directly gives the baseline for launching production. No spreadsheet rework, no intermediate export.
3
Individual sales targets
Each salesperson has their own target and sees it progress on their screen, with no parallel reporting tool to maintain. Out of the box, Odoo can only hold a team target, which means nothing to anyone.
4
Warranty linked to the original order
Warranty replacements are linked to the initial sale. The cost of after-sales service becomes visible product by product, which changes how you negotiate with suppliers.
Everything delivered

Project details

  • Workstream 1: end-to-end redesign of the sales process
  • Workstream 2: data and inventory, with bill of materials management
  • Workstream 3: KPIs and management summaries
  • Commitment date carried by the order line
  • Production forecast by product and by delivery month
  • Individual sales targets for each salesperson
  • Warranty replacements linked to their original order
  • Project run entirely in English
The result

A forecast that feeds production runs directly

Expected volumes come out by product and by delivery month, with no intermediate export and no spreadsheet rework. The cost of after-sales service becomes visible product by product.

Do you launch production ahead of time?

A forecast almost never starts with a dashboard. It starts with the data missing at the right level, and it is almost always a date.

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