Optimal decisions based on combinatorial optimisation
In a world of scarce resources and growing budget constraints, it is not the quality of individual projects that matters – but the combination of these projects.
This is precisely where the central problem lies: Companies and public institutions make investment decisions based on isolated assessments, without taking the full decision space into account.
This is precisely where StratePlan comes in – not as yet another software tool, but as a mathematically sound decision-making platform for calculating optimal investment portfolios.
StratePlan is based on combinatorial optimisation and analyses complete decision spaces under real-world constraints such as budget, capacity and risk.
In doing so, the entire 2^N decision space is calculated and the project combination identified that generates the highest total value – the global optimum.
Whether public infrastructure projects, corporate transformations, R&D initiatives or growth strategies: StratePlan enables structured, transparent and mathematically sound capital allocation.
For decision-makers, this represents a structural difference: Decisions are no longer based on approximation, but on calculated optimality.
Capital allocation from prioritization to mathematical optimization
Companies usually prioritize projects based on business cases, rankings and committee decisions. This approach appears rational, but does not take the entire decision space into account.
There are already over 1 billion possible portfolio combinations for 30 projects, and over 1 quadrillion for 50 projects! Traditional methods cannot fully evaluate this space. They select a plausible solution - but not necessarily the optimal one.
Project Portfolio Optimization AI calculates the optimal project portfolio under your real constraints - including budget, resources, risk and strategic guidelines. The result is a comprehensible, mathematically sound decision-making basis for capital allocation.
For decision-makers, this means a structural difference: decisions are no longer based on approximation, but on calculated optimality.
Starting point: the complete investment list before the actual human decision
The decisive difference of this new calculation method lies in the time of application: it is not used for validation after the decision has been made, but before the actual decision is made, based on the company's complete investment and project list.
Typically, there is a list of potential CAPEX projects - e.g. plant modernizations, IT transformations, product developments, Infrastructure measures or efficiency programs. At the same time, there are fixed restrictions such as a limited overall budget, limited engineering capacities, Production windows, risk budgets and strategic framework conditions.
This is precisely where the real decision-making problem arises: not all projects can be implemented. The question is therefore not which projects appear to make sense in isolation, but rather which combination of these projects forms the globally optimal overall portfolio under the given restrictions.
The new calculation method therefore does not evaluate individual projects in isolation, but calculates from the complete project list the optimal portfolio, taking into account all budget, capacity, risk and strategy limits. The result is a mathematically sound Selection of those projects that together generate the maximum total value added - before the actual human investment decision is made. Deviations from the calculated optimal starting position are made with explicit visibility of the resulting opportunity costs and their quantifiable impact on the overall portfolio value.
This transforms CAPEX planning from a sequential selection process to a consistent portfolio optimization, in which opportunity costs, restriction bottlenecks and portfolio effects are fully taken into account.
Projects do not disappear - they are better positioned and optimally planned over several years
In a mathematically optimized investment system, projects are not discarded. Instead, they are reprioritized, postponed or strategically repositioned, so that they make the maximum economic contribution to the overall portfolio at the optimum time under given budget, capacity and risk restrictions the maximum economic contribution to the overall portfolio.
The decisive factor here is the multi-year perspective. Investment decisions are not made in isolation for a single year, but are optimized in the context of 2-, 3-, 5- or 10-year plans.
Liquidity generated by optimization in the start year is systematically carried over to the following year transferred to the following year. This increases the available investment budget for the next period. This subsequent year is then also optimized again.
The effect: projects can be added as soon as they fit into the globally optimized portfolio under the new budget, capacity and return conditions, Capacity and return conditions fit into the globally optimized portfolio. This creates a dynamic multi-year optimization in which each optimization period Optimization period structurally improves the investment opportunities of the following years.
Comparison of conventional method vs. StratePlan calculation
Infrastructure strategy optimization ex ante:
Understanding the math behind StratePlan
Mathematically, investment decisions are not a list, but a combinatorial decision space. With each additional project, the number of possible combinations doubles(2^N).
- 10 projects → 1,024 combinations
- 20 projects → 1,048,576 combinations
- 50 projects → ≈ 1.125 quadrillion combinations
Classic methods evaluate projects in isolation. This results in local optima, but not the global optimum of the overall portfolio.
The mathematical model
- Decision variables: xᵢ ∈ {0,1}
- Goal: Maximization of value, effect or NPV
- Secondary conditions: Budget, risk, CO₂, capacities
Maximize: ∑ (valueᵢ × xᵢ)
under: ∑ (costᵢ × xᵢ) ≤ budget
xᵢ ∈ {0.1}StratePlan models this space completely and calculates the combination with the highest overall impact - the mathematical global optimum the mathematical global optimum.
Proof Case: Klybeck Areal Basel
- Initial project evaluation: ROI 7.0 %
- Optimised with StratePlan: +4.4 %
- More revenue: +30 mn. CHF
Same projects. Same framework conditions.
Different portfolio logic.
Validated in practice: How decision-makers make better investment decisions with StratePlan
Urs S. - CEO Real Estate Dev.
It was not only the result that was astonishing, but also the transparency: StratePlan showed why our solution was 4.4% below the optimum. We had calculated a 7% return and the optimization with StratePlan increased the real estate project to 11.4%, which represented a monetary increase of around USD 37 million within the overall portfolio.
Stefan H. - PPM Manager
We were convinced that our planning was already optimal. StratePlan nevertheless showed 32% more ROI than we had calculated ourselves - comprehensibly and mathematically clean. We are thrilled!
Stefan F. - Head of Operations
Based on traditional portfolio analysis, we assumed that there was no further scope for optimization. However, the calculation with StratePlan revealed 24.3 % additional added value - a result that we could hardly believe at first. The calculated entry was many times higher than our own calculation, and even under conservative assumptions with external discounts, the result was significantly higher than anything we had previously calculated.
Kay M. - IT Operations Manager
Our portfolio team went into the analysis with a very confident plan. The fact that StratePlan nevertheless showed 19% additional profit was initially irritating - but after reviewing the logic, it was absolutely compelling and comprehensible. The tool makes visible what human planning in combination with spreadsheets structurally overlooks. We can only recommend mAInthink.