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Mastering efficiency: Scalable processes in Data Analytics & Reporting

Written by Hanane Khiel

As organizations expand, their reporting and analytics processes become more complex to manage. What used to be a straightforward process can quickly turn into a complicated set of steps, with reduced efficiency as a result. Consider an organization that relies on business analysts to generate monthly reports for their workforce. The systems in place allowed the analysts to access the data on a specific platform, but using the data for reporting purposes was only possible after manually entering the platform data into an Excel file. With only a handful of employees, this was feasible; however, the process did not scale for a growing business with an expanding workforce.

Based on our analysis, we determined that the generation of these reports, which was consuming 80 hours of labor each month, could be drastically reduced to just 1 hour through automation using the appropriate tool. Consequently, we initiated an implementation process, addressing technical and organizational obstacles. Within a few weeks, a completely revamped reporting system was successfully established, and significantly enhanced operational efficiency.

The reason processes become large, and complex is because nobody is responsible for streamlining them. Rather than focusing on refining processes, we see a tendency to adhere to existing procedures. Even when alternative tools and technologies are available, the inclination to stick to familiar practices can discourage individuals from exploring innovative approaches fully.

The BrightWolves' way: Identifying scalable processes

Recognizing the need for a methodical approach to tackle these challenges, BrightWolves has developed a methodology for identifying scalable processes in data analytics and reporting:

  1. Focused Audit: Understanding the existing processes is crucial to addressing inefficiencies. BrightWolves initiates this by engaging stakeholders, observing the end-to-end analytics, and reporting workflows. We focus on understanding what data is available, understanding the application landscape that generates the data, understanding where the data is stored. We do not only look at the reporting, but also at the underlying data governance structure. With insights from engineers, analysts, and end-users, we uncover pain points and bottlenecks contributing to time wastage.

  2. Use-case based approach: The identified pain points are analyzed, prioritized, and implemented through a use-case that has direct visible impact. Instead of starting a big transformation tackling multiple areas and use cases at the same time, we focus our efforts around one use-case and tackle the transformation that can deliver a concrete deliverable and offer immediate value for the client.

  3. The impact lies in the implementation: Once a viable solution is identified, we focus on the implementation. This is where the direct impact lies for the organization. We collaborate closely with organizations to integrate new processes or technologies, providing support throughout the transition and ensuring desired outcomes are achieved. Our focus extends beyond deliverables, measuring the tangible impact of changes on productivity by comparing the previous and current agreed upon metrics and showing the impact quantitatively.

In Conclusion: Enabling Efficiency in Data Analytics & Reporting

In a rapidly evolving business environment, organizations cannot afford to overlook large inefficiencies in their data analytics and reporting processes. The complexity of operations that comes with growth makes it imperative to identify scalable processes for their various data analytics & reporting practices.

For organizations seeking to transform their data analytics and reporting practices and identify scalable processes, contact our data analytics expert Koen Vanbrabant to learn more about how we can help your organization thrive in the data-driven landscape.


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