Analytics for the Business

The Power of Disparate Data Integration Delivered via Software-as-a-Service (SaaS) Business Intelligence

When speaking with prospective partners and customers I frequently talk about the power and value of a "360 Degree View of the Business".  I have come to use to this term to describe the importance of integrating disparate data into a meaningful data model in order to drive deeper insight into a particular functional area.  Of course, this idea is nothing new as it forms the basic premise of an enterprise data warehouse or data mart. 

Using Inventory Performance as an example in the diagram below, one can see that the key metrics required in order to thoroughly uncover opportunities (like Inventory Reduction) come from multiple places.  Further, the dimensions that an Inventory Planner may want leverage probably exist in more than one place.

My argument, however, in distinguishing a broad enterprise data warehouse from a purpose-built Business Intelligence solution delivered via SaaS, is that the former takes a lot of time, money, technology, and human capital to develop, deploy and maintain.  In addition, enterprise data warehouses seldom start with a specific end in mind (the goal is usually to build a comprehensive environment for lots of people in an organization to use).   Several SaaS Business Intelligence vendors have developed unique tools to significantly accelerate the data integration and data mapping process. This capability, combined with taking more focused scope, allows for the population of a warehouse with the associated linkage of analytics and reporting in one to two weeks versus many months for a traditional approach.  And these SaaS BI providers can deliver a complete production-ready solution in just six to ten weeks.

With the emergence of Business Intelligence delivered in a Software-as-a-Service model, there are now solutions available to line of business owners that are focused on delivering tangible business benefits in a rapid time-frame, at an affordable price point (often in a pure subscription model) and with minimal investment of human capital (sure, you still have to provide the data and provide requirements, test the output, etc.). 

What are some of the capabilities that should be considered when evaluating a SaaS Business Intelligence approach?

• Data Integration in the Cloud - the solution must be able to effectively and efficiently incorporate the disparate streams of data coming from the pertinent source systems
• The target data model must not only be designed to store the data, but it must also have context - not only in terms of the data itself, but also the relevant dimensions, behaviors, transactions and customer-specific business context (this being org structure, nomenclature, etc.)
• Security and data privacy - a high degree of both should be provided and well documented
• Comprehensive data representation - a broad mix of tools and capabilities for reporting and analysis - Dashboards, Exception Reports, Multi-Dimensional Reporting & Guided Analysis, Ad-hoc Query & Analysis, etc.
• Time to Value - The solution must be delivered in weeks, provide adequate flexibility to be changed as needed (the speed of business today isn't what it used to be...it's very fast!)
• Should compliment an organization's overall Business Intelligence strategy - allowing you to leverage existing investments whenever possible (tools, data sources, skills, etc.)

If you have been struggling with a limited view of your business, perhaps now would be a good time to consider such an approach.