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Continuous development, increasing profits and improvement – these terms are indispensable in today’s business world. Companies analyze and evaluate their performance in order to achieve their goals and increase their competitiveness. Key performance indicators (KPIs) are essential for making corporate success measurable.
Companies define their goals and manage their strategies in a targeted manner by monitoring relevant KPIs. These not only enable the effective use of resources, but also the evaluation of the performance of teams and individuals – an important lever for continuous improvement.
Especially in management, decisions are made on the basis of KPIs on a daily basis. This makes it all the more important to interpret them correctly. It is crucial to distinguish between correlation and causality: While correlation merely describes a statistical relationship (e.g. increasing visitor numbers on a website lead to more sales), causality indicates an actual cause-and-effect relationship. Not every correlation is therefore also causal – a common misconception when dealing with company key figures.
The selection of suitable KPIs therefore requires a deep understanding of the data situation and its correlations. This is the only way to define KPIs that truly reflect the actual progress towards the business objective.
A precise definition of the company’s goals forms the basis. Only then can KPIs be developed that meaningfully measure whether and how these goals are being achieved. As these goals usually relate to different areas, it is essential that specialist departments work together on the KPI definition. Without this exchange, there is a risk of duplication, inaccurate measurements or even contradictory results.
The definition process should be clearly documented and regularly reviewed. Ideally, a central team should be appointed to manage all actively used KPIs and ensure quality and consistency.
Without the right IT infrastructure, precise measurement remains a mere wish:
Data quality (correctness, completeness, up-to-dateness) must be guaranteed
Systems and databases must be compatible and networked
Central data storage improves clarity and analysis capability
In addition, suitable analysis tools are required to identify patterns, trends and deviations. Tools such as SAS Viya are already using AI to automatically suggest correlations and possible causal relationships. This not only simplifies KPI definition, but also improves the tracking and optimization of performance.
Key performance indicators (KPIs) help companies to pursue their goals in a structured manner, make performance measurable and make well-founded decisions. In the future, technologies such as big data and artificial intelligence will further optimize these processes – and make the world of KPIs even more precise and dynamic.
So let’s see what the world of KPIs has in store for us in the future.
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