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Data Culture: a pillar for business success

Data culture

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It is now recognized that data represents a crucial element for businesses. Major international organizations such as Gartner and OCSE highlight in their annual reports how the ability to navigate the digital revolution will be a key indicator in determining a company’s future relevance.

Data-Driven Evolution

The OCSE asserts that companies can achieve excellent performance, both in terms of cost reduction and value creation, by leveraging the “knowledgeof data, and the most performant enterprises will be those that have implemented more advanced data management practices.

However, one of the main obstacles preventing organizations from evolving towards data-driven structures lies in the culture of approaching data. To make quick decisions, data must be easily accessible even to non-experts, presented effectively, and shown in a context that highlights the elements to be monitored.

The evolution of companies towards a data-driven culture is not a natural transition but requires time and transformation. This process involves a series of challenges, including resistance to change. The past, and for many companies still the present, is characterized by the presentation of predefined, vertical, unintegrated reports that depict past situations of days, weeks, or even months and require external interventions to incorporate new sources or generate new indicators.

The self-service analytics approach changes this situation: by placing governance at the center, easy-to-use tools are offered directly to end users; this approach reduces analysis times, allows the use and representation of data in real time, if available, without unnecessary delays, and enables the elimination of one of the most significant hidden costs for businesses: that of indecision.

Real-Time Analysis

At Blue BI, we are aware that technology alone is not enough: we believe that corporate culture is an enabling factor to fully develop the potential of companies aspiring to become data-driven and how real-time data analysis can be a powerful tool to overcome uncertainty in data interpretation.

Data Real Time

Our perspective on the use of a data-driven strategy is based on 5 points:

  • Responsiveness to trends: real-time analysis allows companies to immediately identify new trends and variations in data, enabling rapid adaptation to changing market conditions or customer needs.
  • Early anomaly detection: the ability to detect anomalies and issues in real-time is crucial to prevent significant damages or losses; companies can continuously monitor data to identify abnormal behaviors and act accordingly.
  • Dynamic optimization of operations: real-time analysis allows for dynamic optimization of business operations, leading to cost savings and increased efficiency.
  • Personalization of user experience: real-time analysis is essential for providing a personalized user experience; companies can gather data on user behavior and immediately modify the experience based on their preferences and needs.
  • Integration with AI and ML: the integration of artificial intelligence and machine learning algorithms into real-time data analysis allows for the identification of complex patterns and trends in real-time; these models can be used to make immediate and automated decisions.

Real time in Power BI

An example of using real-time streaming with Power BI could be a company wanting to monitor sales in real-time: as mentioned earlier, having this type of analysis can help the company quickly identify trends and make informed decisions.

Other types of use cases could include:

  • Launching advertising campaigns when there is a drop in sales within a retail location (physical/virtual)
  • Informing process managers of monitoring processes when particular situations occur based on monitored elements (e.g., temperature, error counts, etc.)
  • Improving customer retention by monitoring their experience on apps and websites, especially those who have had an unpleasant experience
  • Assisting logistics companies in identifying lost shipments by proactively initiating an investigation workflow when the status of a package remains unchanged for a specific period
  • Sending alerts to administrative teams when customer payments are overdue, with customized time or value limits for each customer

Finally, by adding Q&A services, it is possible to significantly improve the user experience by providing immediate answers to questions, saving time and effort, and using only natural language.

Contact us to learn more!

We realize Business Intelligence & Advanced Analytics solutions to transform simple data into information of freat strategic value.

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