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StratePlan calculates the optimal portfolio where traditional tools reach their limits.
Instead of evaluating projects in isolation, we analyze all possible combinations - and identify the best solution.
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How behavioral economics, mathematical optimization and hybrid AI improve investment decisions
In companies, investment decisions are often made on the basis of experience, business cases and management discussions. However, research in behavioral economics has shown for decades that such decisions are regularly influenced by cognitive biases - such as WACC fallacy, loss aversion, status quo bias or escalation of commitment.
These distortions mean that investment decisions are often not made completely rationally and economic potential remains untapped.
The actual problem is mathematical in nature
In addition to psychological factors, the central challenge lies in the mathematical structure of investment decisions. Investment planning is a classic problem of combinatorial optimization. With several projects, there are not just individual decisions, but an exponentially growing decision space of possible project combinations.
With each additional investment option, the number of possible portfolios increases dramatically. This creates a complex decision space, that can hardly be fully analyzed by humans or traditional planning tools.
Why traditional decision-making processes are reaching their limits
Traditional planning tools or sequential evaluation processes cannot fully calculate this decision space. In practice, projects are often evaluated individually or prioritized in rankings. This results in decisions that appear to make sense, but only represent local solutions.
In many cases, the actual best investment portfolio remains undiscovered because the complete decision space cannot be analyzed.
Hybrid AI and multithreading as a new solution approach
Modern approaches combine mathematical optimization, hybrid AI and precise multithreading to analyse billions of possible project combinations in parallel. These technologies make it possible for the first time to systematically calculate very large decision spaces.
The algorithm evaluates an enormous number of potential project portfolios and identifies the combination that offers the greatest economic benefit under budget, risk and resource constraints The highest economic benefit under budget, risk and resource restrictions.
From the local optimum to the globally optimal investment portfolio
The result is a new quality of strategic decision support. Investments are no longer evaluated exclusively, but optimized algorithmically. This enables companies not only to evaluate individual projects, but also to view the entire investment portfolio as a coherent optimization problem.
For companies, this means that capital is deployed where it generates the greatest added value. This allows investment portfolios to be systematically improve investment portfolios and tap into new, maximum EBIT potential that often remains hidden in traditional decision-making processes.
Sascha Rissel is an entrepreneur, strategic advisor, and technology visionary with more than 20 years of experience in the development, scaling, and optimization of complex business models. He combines deep business expertise with a strong technological understanding, particularly in the areas of artificial intelligence, algorithmic decision models, and system optimization.
Through initiatives such as StratePlan and DeepAnT, he actively drives the advancement of data-driven ROI calculation, intelligent project prioritization, and predictive analytics. His focus is on measurable impact, robust decision foundations, and translating highly complex mathematical models into practical, deployable solutions for business, public administration, and industry.
Sascha Rissel stands for a clear principle: consistently aligning strategy, technology, and impact.