Evidence

What we can show you.

inolarity is early-stage and we would rather say so. What we can put in front of you: a food-grade reuse system the founder modelled and ran himself, the patterns we have seen reuse systems break on, and the variables that decide whether the numbers work.

Worked example

A food-grade reuse system, modelled and run

Before inolarity existed, our founder modelled and ran a food-grade reuse system. Cost per cycle, wash capacity, loss rates and food-contact compliance were built from the ground up and tested against reality rather than assumed. It shows he has run rigid food-grade reuse systems in practice, not only on paper.

The example is based on a food-grade reuse system that the founder modelled and managed in his earlier operational work. It is not a client mandate of inolarity GmbH. We can name the counterparty only under a confidentiality agreement, but we are happy to talk through the substance in a call.

Patterns from practice

Where reuse systems usually break.

How to read this. These patterns come from the founder’s two decades of operational work in European reuse and pooling networks, described in anonymised form. They show the problems inolarity was built to solve, and they are not client projects delivered under the inolarity name.

Growth pattern · several countries

Wash capacity that held at 50,000 cycles fails at 200,000

One wash partner and ad-hoc cross-border arrangements cannot carry contracted volume. Throughput slips, containers go missing, and management spends the day on calls with wash centres.

The fix is structural: audit capacity and hygiene documentation, pre-qualify back-up partners on a common service-level framework, and redesign the return routing so vehicles stop running empty. Daily oversight then moves into a defined partner-management process.

Cost pattern

The plan says € 0.65 per cycle

Business cases usually assume best-case utilisation and best-case return cycles. In practice, transport routing, longer return cycles and lower wash utilisation push the real cost up and the container pool with it.

What helps is a cost-per-cycle model built from the bottom up on real partner capacity, with a source and a date behind every input. That gives customers, lenders and investors a basis they can rely on.

Diligence pattern · investors

The plan reads well. The operations decide.

Most reuse ventures do not fail on the product. They fail because the operational layer quietly gives way.

Independent operational due diligence tests the cost-per-cycle model against real wash capacity in the target region. It checks whether the return-cycle assumptions hold, and compares what partners promised on service levels with what they actually delivered. All of that before the money is committed.

What drives the cost

What actually moves cost per cycle.

Regulation creates the demand. The operational infrastructure decides whether a model works. These are the variables we model first, because they move the number most — and they are the ones business cases tend to set at their best case.

Return and transport

  • Return time: every extra day adds to the container pool you have to finance
  • Distance between customer, wash centre and the point of return
  • Empty runs in the routing — usually the cheapest thing to fix

Pool and losses

  • Loss rate: it drives replacement purchasing and the capital tied up in containers
  • Pool size follows from cycle volume multiplied by return time, plus a buffer
  • Sensitivity: what two extra days of return time, or three points of loss, do to the result

There is no single right answer. The result depends on volumes, distances, return rates and how partners actually perform. So we model the range rather than pick a figure, and we show you which assumption the outcome hangs on.

Try the sample model

Tell us what you are working on.

You do not need to have every answer before speaking with us.

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