Over the last few decades we’ve witnessed the release of 3 distinct “generations” of Business Intelligence (BI) technologies, each of which has advanced insights available to enterprise businesses – and each of which has led to new disruptions and advancements.
THE PIONEERS
The first generation of BI tools offered largely thick-client reporting solutions, like Crystal Reports or Siebel Analytics, to replace the historically manual production of paper reports that were previously ubiquitous in every company. Many of these products are still widely in-use in today’s enterprise – multiple decades later – although we’re seeing a very fast migration to the second or even third-generation BI solutions.
THE NEXT WAVE
The early pioneers gave birth to the second-generation providers and, in many cases, were acquired by them over time. In this phase of BI history, solutions like Cognos and OBIEE adapted to the requirements of the larger enterprise, introducing rich sematic models, governance capabilities and targeting a far bigger audience inside the enterprise, by having different capabilities for analysis, pre-built reporting, and automated refreshing, amongst others. This strategy led to large scale adoption of BI and saw most of the major vendors being acquired by enterprise software providers like Oracle, IBM & SAP.
But did the success of the BI tools lead to better business insights for the companies that adopted them? If they had, why did leading analyst firm – Gartner begin to declare, as early as 2016, that traditional BI is dead? In fact, the approaches of these two generations of BI tools both introduced a problem and exposed a limitation.
THE PROBLEM
Implementing BI in the traditional manner requires a near-constant involvement from the IT staff and a complex IT environment. The model is slow and inefficient and keeps the power of business data in the hands of a skilled few. More importantly, traditional BI systems do not provide business users with full decision support while documenting the process of creating a successful decision. One could argue that the category itself is somewhat misnamed – the data analyst is responsible for applying business intelligence to the data visualizations and reporting; the general-purpose BI platform has no inherent business logic.
A NEW WAY OF DOING THINGS
The third generation of BI, Modern BI, shifts the focus away from IT and data scientist analysis and reporting and offers mainstream tools with self-service access and flexibility so that business users can produce reports and analysis on-the-fly and share data to make decisions and optimize business results. It supports the principles of DataOps and data democratization and offers a continuous intelligence stream consumable by business users. Key platform characteristics include integration, intelligence and ease of use.
Building on solid principles of digital transformation, your BI environment should strive to break down data silos rather than recreate them. To this end, it should support data from disparate sources, including legacy systems and hybrid ERP systems. In addition, it should be cloud-ready, and should support multi-cloud and hybrid implementation scenarios.
Data accessible from an ERP is often the most important information for business intelligence. However, it doesn’t always provide the full picture of a process or condition necessary for real insights without context or additional information. For this reason, the ideal BI platform should be built on real business context from a powerful data model and provide both cross-process and cross-application reporting.
For insights to be available to all business users within an organization, the BI and reporting environment must be simple to customize and run with little to no involvement from IT. And, to provide the business intelligence your BI tool requires, it must be flexible enough to work with the tool of your choice, both now and in the future.
In a fast-changing and unpredictable world, rapid insights and decisive decisions are the difference between market leaders and those struggling to react – those who outthink and outmaneuver the competition and those who get left behind.
About the Author:
Chad Cosper is a Senior Product Marketing Manager at Magnitude and focuses on the company’s analytics portfolios for ERP platforms. He is passionate about data management and has spent the bulk of his 20+ year career supporting enterprise companies who need to turn insights into actions. Learn more about Magnitude’s solutions for Oracle including the latest release – Noetix 7 by visiting: www.magnitude.com/noetix