Report Rationalization with Data Science drives 25% cost savings in BI consolidations.

Industry estimates that building and managing a single report costs between $4,000 and $10,000. With innate increases in demand for more reporting coupled with the explosion of data, the number of reports have grown substantially over the years. This has obviously resulted in increased costs of building and managing reports. Moreover, having many reports does not translate into better insights.

Hence organizations undertake Business Intelligence (BI) consolidation programs to derive better insights with a smaller, more efficient report set whilst optimizing modernization and/or maintenance costs.

The first step in any Business Intelligence Consolidation is a rationalization exercise. In our experience, manual rationalization of reports requires an average effort of about 10 hours per report thus rendering the traditional approach of manual analysis by Business Analysts as time consuming and cost prohibitive even for a small set of about 100 reports.

Another alternative that organizations have used is in building a metadata connector to a specific Business Intelligence platform like BusinessObjects or MicroStrategy and then using it to evaluate overlap of fields. This metadata approach is also ineffective as organizations have reports in different versions of a BI tool, on different BI platforms and in different formats – PDF, MS Excel, Word and PowerPoint, etc.

Optimize Cost of Rationalization with Data Science

An innovative approach would be to apply the tools and techniques of Data science to simplify and achieve rationalization. Text analytics and clustering methods can be used to extract report headers or data labels additionally ensuring that rationalization can be BI tool agnostic and format agnostic. Our solution for BI consolidation leverages machine learning (ML) and natural language processing (NLP) techniques to provide a comprehensive review of all the existing reports and documents – identifying duplicates and/or similar reports with the objective of consolidating the reports to only the ones that are required and used.

In a matter of weeks, Iris can bring in a comprehensive view of the reports and documents to provide a clear set of rationalization recommendations critical to a business intelligence consolidation initiative. Additionally, these consolidation results can be leveraged in the execution of a BI transformation – an initiative to migrate reports from a traditional BI platform to a modern one.

Applying Data Science in Transformation Projects

Iris’ Data & Analytics Practice offers comprehensive services across the competencies of Data Management, Business Intelligence & visualization and Data Science. Our approach to provide solutions for Business intelligence consolidation through Data Science (ML, NLP) based accelerators has helped customers transform their legacy enterprise reporting platforms to a modern visualization solution. These solutions have yielded immense benefits by optimizing costs of over 25% for our clients. To learn more, contact us at [email protected]

For more information, please contact [email protected]