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Series of Blog Posts on Data-Driven Management (1/5); Efficiency and Productivity

Improving Efficiency and Productivity Through Data-Driven Management


Data-driven management has emerged as a key factor in the management of sports facilities and properties. This is because data provides valuable insights that help optimize resources, enhance services, and reduce costs. In this first post of our blog series, we will discuss how data-driven management can help improve efficiency and productivity in these environments.


Resource Optimization

One of the biggest challenges in managing sports facilities and properties is the efficient use of resources. Data-driven management helps identify usage patterns and predict future demand, thus enabling the optimization of resources such as spaces, equipment, and personnel. For instance, analyzing heat maps and visitor numbers or profiles can reveal which areas are overused and where resources can be reduced or reallocated.

In practice, this could mean gaining a precise understanding of customer profiles and using factual data to highlight quiet times. For example, identifying high-demand services offered before quiet periods can help alleviate pressure by offering the same services again during quieter times. Alternatively, if a quiet period occurs close to the current closing time, the overall opening hours could be reconsidered.


Reducing Energy Consumption

Energy consumption in properties is a significant cost factor and source of environmental impact. Data can help identify inefficient systems and processes that consume unnecessary energy. For example, smart systems can adjust lighting and heating in real-time based on usage rates, reducing unnecessary energy consumption and saving costs.




Additionally, even without further investments, savings can be achieved by considering usage times, such as in the settings for air conditioning. If the analysis identifies times when ventilation can be reduced from full speed to a lower setting (and I do not suggest that ventilation should be turned off), energy can be saved. In many large properties, ventilation systems are quite robust, and thus the savings can be significant over time.


Supporting Decision Making

Data-driven management provides an objective basis for decision-making. Rather than relying on traditional experience, intuition, or gut feelings, data enables making justified and measurable decisions. This is particularly relevant for investment decisions, such as constructing new facilities or renovating existing ones. Data analytics can predict demand trends and ensure that investments are appropriately directed.

In the case of renovations, a tangible benefit could be derived from analyzing identified customer and usage profiles to understand who uses the spaces and when. This information can be used to combine the activities of different groups into the same space, thus saving on construction costs. Ultimately, the cheapest square meter is the one that is not built.


Enhancing User Experience

Data collection is not limited to devices and spaces; it also includes customer information. Analyzing this data can help understand customer behavior and preferences, allowing for the personalization of services and improvement of user experience. For example, if data shows a growing popularity of certain group exercise classes, the offering of these classes can be increased.

As data accumulates on customer behavior, it can also facilitate the acquisition of different services, for example, by productizing services through payment methods or procurement channels. These changes can increase the sales of some products and services by several tens of percent.




 


The efficiency and productivity of data-driven management are not just buzzwords; they are a necessity in the modern management of businesses, such as sports facilities and properties. Through data-driven management, smarter decisions can be made, leading to significant improvements in efficiency and productivity. The most crucial aspect is that data collection and analysis must be continuous and systematic to stay up-to-date and respond quickly to changing conditions. Thus, the success of future businesses increasingly depends on how well they can leverage the opportunities provided by data-driven management.


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