Finite-capacity Optimization Algorithms: the new Black Gold of Business

Frederic Dufour / Sep 09 , 2022

Our Society is built on the illusion of infinite resource capacity. Strange as it may seem, business models have been designed on this simplification/illusion of “unlimited resources”.

What does this concept mean and what are its implications in today’s business life?

To design an infinite capacity plan or budget is to assume that the level of resources is capable of dynamically adapting to demand. In infinite capacity models, resources are not a constraint and prices are stable.

Advantage of this approach: when capacity limits are still far away, production lead times and costs are easy to calculate, as they can be based on stable standard lead times and costs.

Shortcoming: when resources become scarce and/or projects are rushed, these models are ineffective. Worse, they amplify the problems caused by resource scarcity by creating inflationary spirals and causing chaos in supply chains.

At the level of business management, these infinite capacity models prove incapable of helping decision-makers answer such important questions as:

Where should priorities be placed?
How to optimize the added value of resources?
How to make time and cost calculations more reliable?
Which processes are the most expensive in relation to the value produced?
Which management indicators should be optimized in priority?
How to set realistic objectives?
How to involve more effectively the different stakeholders?
How to reduce operational risks while seizing new business opportunities?

Finite-capacity models, a source of value

In finite-capacity models, the company designs realistic business scenarios based on a precise description of the resources it can mobilize to create value.

This helps to create a “digital twin” whose purpose is to design and simulate different operational strategies with the objectives of :

defining an optimal portfolio of resources
making the most of internal resources
balancing the workload between different sites or departments
reducing the intensity of raw material use
selecting high value-added activities
reducing scrap and machine breakdowns
negotiating master agreements with contractors
identifying diversification opportunities
negotiating prices and lead times with customers
…

When bottlenecks and misuse of resources are eliminated, or when high value-added orders are prioritized, when raw materials are saved, or scrap and machine breakdowns are reduced, then results naturally improve.

The role of finite-capacity optimization algorithms

The goal of the algorithms is to quickly compute optimization solutions to the complex and multidimensional problems that decision makers face.

These algorithms are more organic, less mathematical and therefore also closer to human reasoning than those developed to solve infinite capacity problems.

What are the particularities of finite capacity optimization algorithms?

They combine different techniques that perform arbitrations between actors with competing interests and expectations (e.g., prioritizing one order over another)
They allow to define several types of objectives simultaneously (e.g., increase the productive time, reduce the scrap rate and the frequency of machine stoppages, etc.)
They allow to impose strong constraints (e.g., cap overtime) and to find the best balance between weak constraints (e.g., choice of working hours)
They calculate quantitative and qualitative indicators that help set progress objectives from one period to another
They are both specific and easily adaptable to changing constraints and management objectives
The results produced are intelligible because they are based on human reasoning. They can therefore be better defended to the various stakeholders

Conclusion

Companies are rich in their resources. These resources are the basis for innovations that give the company technical competitive advantages. With finite-capacity optimization algorithms, these competitive advantages are coupled with operational advantages.

Companies that base their decisions on such algorithms naturally and effortlessly increase their productivity and operational efficiency while respecting their most valuable asset: their resources.