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Blog series about the world of data-driven management (2/5): Data-driven management as support for decision making

Information to Support Decisions

The power of information in decision-making is undeniable. In today's fast-paced world, the importance of data is increasingly emphasized. Data-driven management is not just about collecting information; it involves analyzing, understanding, implementing, and utilizing it in decision-making. In this part of the blog, we delve into how data-driven management can support decision-making, particularly in the maintenance, investment, and development of sports facilities, as well as in risk preparedness.


Decisions Based on Data

One of the most important aspects is, of course, what questions we want to answer with data. What is the dilemma, problem, or goal we are trying to solve? Naturally, one logical sequence here is strategy – objectives – metrics.


In managing sports facilities and properties, data collection and analysis can provide significant insights that guide effective decisions, align with metrics and objectives, and follow the strategy. For example, user data can reveal which services or facilities are in high demand, thus helping to prioritize investments in their improvement or expansion. Additionally, using data to demonstrate your findings makes the basis for decisions highly credible and complements your professional expertise.



 

Another concrete example is deciding on the purchase of a new piece of equipment for a sports facility. By analyzing data on user behavior and feedback, an informed decision can be made that supports customer needs and increases satisfaction. Instead of making an investment decision based on intuition, collected data is used to ensure that the investment serves both the customers and the business objectives.


Risk Preparedness

Data analysis also helps in identifying potential risks and issues before they escalate. For instance, monitoring energy consumption data can reveal hidden problems in a property’s heating, cooling, or ventilation systems. If a particular area of the property or one property in a comparison consumes significantly more energy than other similar-sized spaces, this may indicate issues such as malfunctioning ventilation systems or insulation problems. Early identification of such information and determining/implementing corrective actions can prevent energy waste and significantly reduce operational costs. At best, it prevents a long-simmering issue from leading to massive repair measures or even demolition in the long term.

It is especially important to identify and manage risks that can affect an organization’s reputation. For example, customer feedback analytics can help detect negative trends in user feedback, enabling swift actions to resolve issues before they damage the business or the reputation of the sports facility.


In this blog, I discussed a few simple ways to harness data as part of the bigger picture, including strategic objectives. This enables data-driven investments, improves customer satisfaction, and minimizes risks. The most important thing is that organizations invest in skills, systems, and processes that allow continuous data collection and analysis, thus ensuring that decision-making is based on up-to-date and relevant information. This way, organizations can be confident that they are making the best possible decisions both now and in the future.




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