In a perfect situation, everyone within the organization has easy access to the right insights based on reliable information. Yet, many organizations run into obstacles. The digital transformation means that organizations should be able to meet more and more of their information needs. More and more organizations are also seeing the potential of the digital transformation. Yet, in practice, we see that the BI environment does not (yet) meet the information needs.
Organizations spend an unnecessary amount of time on Business Intelligence (BI). On preparing reports, sharing insights, and maintaining systems. Recognizable? You have large amounts of data sources available, many Excel overviews, and reports via other tools.
In addition, your environment is constantly changing, and the need for new insights and information is increasing. At the same time, now more than ever, you need fast and valuable information due to the effects of the corona pandemic. The corona crisis is a clear example of how quickly information needs can change and sometimes even be of crucial importance for the continuity or growth of your organization. As an organization, you want to be able to change gears and adjust as quickly as possible.
In this blog, in collaboration with Plainwater, we share the top three issues that we encounter in organizations that have outsourced their BI support to us.
1. Poor performance
Unreliable performance is not only the most common issue but also the most tangible. Moreover, you do not only suffer from it in your own activities; it is widely noticeable within the organization. Poor performance, therefore, has a lot of impact. It causes irritations, and users lose confidence in the BI system.
2. High complexity BI-landscape
In practice, a BI landscape is often complex due to a combination of (obsolete or not) systems and the arrangements regarding those systems. After all, BI is at a crossroads between different departments. Who owns what? How do you determine the definitions? And who is responsible for data management? If the ownership of the various components of the BI landscape is not clearly defined, it quickly becomes complicated.
3. Insufficient data quality
The error sensitivity of data causes quite a few issues. In the best case, users realize that the data is incorrect. Hopefully, users will report this immediately so you can take action. However, users often opt for a different solution: they keep their own lists. A dangerous solution, as this data is not in the system, but is included in, for example, the monthly reports. Not a desirable situation. In the worst case, users do not realize that the data is incorrect. Reports are then based on inaccurate data, resulting in false insights.