August 5, 2014 - Top 3 Challenges Affecting BI Success

A recent report by Gartner stated that between 70% and 80% of all corporate Business Intelligence (BI) projects fail. So, how can you ensure that your project isn’t one of them? The main reason for such a low success rate is that most businesses fail to ask the right questions, and look at BI as just another IT project that needs a specific package solution. IT departments must not think of BI as one-time solution, but as a constantly evolving one that differs from stand-alone solutions. This post outlines the major challenges that affect the success of BI projects:

1. Driving User Adoption

A large part of successful BI implementation depends on how it is received by end-users. Organizations must keep in mind that no matter how well a BI tool is built and implemented, the end-user is the decision maker in most cases. They must consider these factors and resolve any issues that the user might have before he even realizes the problem existed. For example, user involvement in design can increase adoption and encourage them to become advocates for future expansion.

2. Justifying BI Investments

Traditional BI solutions are based on the development of large IT infrastructure, and fail to deliver information efficiently. Upgrading from traditional BI to more agile dashboard solutions will require additional investment and changing existing business processes. When implemented properly, BI projects can help an organization improve business agility, drive down operating costs and increase customer satisfaction.

3. Adapting to Big Data

Enterprises must build a strong foundation that can manage increasing data volumes, rapidly expanding user bases, different data types as well as support the integration of additional data sources effectively. We are witnessing a tremendous increase in data volumes being analyzed and stored in data warehouses across the globe. This data can provide advanced analytics, which means that existing BI architectures must evolve to meet the demands generated by big data.