Data is indispensable for effective decision-making, and data visualisation facilitates the transformation of data into clear, actionable insights.This blog will explore two primary approaches: univariate visualisation, used by tools such as Power BI and Tableau, and the more sophisticated multivariate approach, designed for detecting and monitoring complex patterns.

Univariate Visualisation: Tradition

Univariate visualisation focuses on one variable at a time and is a standard in traditional dashboards. A typical example is tracking a KPI such as monthly sales.

Advantages: This approach stands out for its simplicity and accessibility, allowing teams without advanced knowledge to interpret data with ease. In addition, familiarity with traditional metrics helps align business objectives.

Disadvantages: However, unidimensionality limits context and makes it difficult to identify critical correlations. In addition, it tends to be a descriptive rather than predictive approach. Gartner (2023) reported that 70% of companies that only use descriptive dashboards struggle to turn data into decisions.

Multivariate Visualisation: Innovation

Multivariate analysis considers multiple variables simultaneously to reveal hidden patterns and cause-effect relationships.For example, analysing factors such as pricing, seasonality and customer behaviour can predict product demand.

Advantages: This approach offers a more holistic perspective and makes it possible to anticipate problems or identify opportunities.McKinsey notes that companies that use advanced analytics are 19% more likely to outperform their competitors in profitability.In addition, its predictive capability makes it a key tool for optimising processes.

Disadvantages: However, it requires more investment in training and technology, as well as more advanced technical skills, which can initially be a barrier for many organisations.

Combining Tradition and Innovation

The key is to integrate both approaches. Traditional KPIs allow for quick and effective monitoring, while multivariate analysis provides deep insights. A good example is Netflix, which uses dashboards to track subscribers and multivariate analysis to predict which content will be successful. This combination allows them to optimise decisions and lead their industry.

Conclusion

It is not a question of choosing between tradition and innovation, but of finding a balance that turns data into a competitive advantage. By adopting a blended approach, companies can benefit from the simplicity of traditional KPIs while exploring the potential of advanced analytics to make a significant impact on income statement.