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Self-Service Analytics. Advantages and keys to success.

Until a few years ago, BI Analytics projects were always related to IT teams in all their phases: from the installation of the platform to the generation of reports. These projects could take a long time to get results, and even these results could not conform to what users really wanted.

Nowadays, Self-Service BI Analytics is getting more and more important in the different companies and sectors, driven, in my opinion, by two main factors:

  • Analytics tools are getting easier to use and more intuitive, improving the user experience, who does not need a great technology background.
  • Business users are more “open-minded” with new technologies, and there is a growing awareness of Analytics for organizations.

So, what are the benefits of BI Analytics Self Service platform? Let`s see the main advantages:

  • Users are more involved with the platform and its entire implementation process, as they develop the reports by themselves.
  • Shorter development times, by reducing analysis in the reporting phase.
  • Cost reduction. Since we reduce phases in the project, times and support costs with self-service BI are significantly lower
  • Flexibility and independence for users, who can generate new reports according to their needs
  • Better results: Users can generate the reports as they need, without loss of information in phases of analysis. They know better than anyone what they need.

But, does Self-Service mean that IT is not longer needed? Nothing is further from reality. IT is as necessary as ever, but the approach may be different.

From my experience in projects of implementation and empowerment of self-service platforms, some keys to the success of a Analytics self-service platform are:

  • Design and data modelling acquire a vital importance. For users to be autonomous in the generation of reports, it is necessary to have a stable platform, and a data model that allows its exploitation in an intuitive way and covering all the cases.
  • Enhance the platform, work with users for greater acceptance and adaptation.
  • Training on the technology used, as well as the data model and the maintenance policy.
  • The communication with the users is vital to detect new improvements that allow to use the platform in the most complete way possible.

In a business world ruled by immediacy and agility, self-service BI Analytics are a great alternative for the analysis of data. With a good analysis and implementation of the platform, as well as a commitment between business users and development teams, self-service Analytics can become a powerful tool that contributes to the improvement of our company.

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