Site icon Yellowfin BI

3 use cases for embedded BI

Much like the ongoing race for the White House – check out our 2012 US presidential election blog – chatter about embedded Business Intelligence (BI) seems inescapable.

Software vendors and organizations from across almost all major industries are beginning to embed analytical capabilities in their core applications and processes.

A recent article published by Information Management, Make BI More Pervasive with Embedded Analytics, highlighted the role integrated analytics was playing in driving pervasive BI deployments, and freeing decision management technology from the confines of upper management:

“In contrast, for the last few years we have witnessed increasing numbers of people within an organization making decisions at the operational levels, be it logistics operations on the ground, customer care center representatives interacting and resolving critical customer queries and complaints, or bank representatives at the branch opening accounts and cross-selling insurance and other loan policies to customers, or marketing teams doing promotional campaigns and providing customer offers on the spot.”

To learn more about making embedded analytics a reality, join us for our Embedded BI Best Practices Webinar.  Register Now >
 

What do you mean, everyone?

While it’s pretty easy to pronounce that ‘everyone’ is leaping at the chance to enhance and compliment core product capabilities with reporting and analytics functionality, this all-encompassing term is vague, and fairly unhelpful.

So here are three, out of many, potential use cases for embedded BI:

1. Logistics and supply chain management

Most organizations working within the logistics and supply chain management industries already use GPS technology to track the location of stock and transportation vessels / vehicles. Integrating analytics capabilities enables that location-based information to be layered with other relevant data to enhance operational efficiencies relating to:

Adding BI capabilities allows those in the logistics industry to:

2. Customer service and sales

Many call centers have integrated analytics competencies into their call tracking software. Embedded BI, in this scenario, enables employees to visualize the purchasing and product / service usage behaviors of the customer they’re currently speaking to, enabling them to identify optimum cross or up-sell opportunities.

3. Human resources

The ability for integrated BI technology to collate data from multiple sources is particularly pertinent for organizations or departments dealing with Human Resources (HR) issues and information.

Combing analytics with HR management software and techniques could enable:

How to make embedded analytics a reality

In our previous posts on embedded BI – 8 reasons why embedded Business Intelligence beats DIY and Benefits of embedded Business Intelligence – we’ve analyzed the pros and cons of the build vs buy argument.

Without reiterating all the pros and cons of the various options for acquiring integrated BI functionality, the Numerical Algorithms Group (NAG) summarized the ultimate advantages of purchasing a readymade BI solution in its Three Options for Embedded Analytics white paper, stating that:

“By embedding analytic functionality into their applications, software vendors can help their customers and users to extract new insights from their data, solve business problems and make informed decisions. Whilst building in-house solutions could be viewed as diverting resources from core application development, and borrowing from open source distributions raises issues of quality, using a commercial option provides an optimum solution for many vendors because of the way it leverages the supplier’s experience in developing, testing, documenting and supporting analytical algorithms. Vendors who incorporate commercial analytics into their applications free up their developers to concentrate on adding domain-specific value, whilst the analytical heavy lifting is being performed by someone else who can be relied upon to provide a more dependable solution than that offered by open source.”

NAG divided methods for embedding analytics into core software applications into three separate approaches:

Common delivery pitfall for embedded BI

No matter how, why or in which business applications or processes BI functionality is embedded, common pitfalls abound.

For a comprehensive understanding of what they are, and how to avoid them, join in the conversation during Yellowfin’s Embedded BI Best Practices Webinar series >

In an insightful interview (Best Integration Practices for Better BI) with ITBusinessEdge’s Loraine Lawson, principal for Deloitte’s Advanced Analytics and Modeling Sector, John Lucker, emphasized data governance and intuitive technologies as the two crucial project and product related stumbling blocks encountered by organizations attempting to implement and leverage embedded BI:

Where to next?

While it’s obvious that the use of embedded reporting and analytics technology – to improve the effectiveness and efficiency of processes and operations throughout the enterprise – is growing, it remains far from mature.

According to VP of Research at global analyst firm Gartner, Nigel Rayner, most of today’s BI functionality is utilized by analysts and managers to perform queries. He suggests that only a small proportion of analytical functionality is embedded at the “point of decision” (such as when workers in a telecommunications call center are prompted to offer a caller additional products or services based on their purchase and payment histories), or in existing processes.

"Today, 80 percent of embedded BI and analytics use is for inquiries, while 15 percent is for the point of decision and only five percent are embedded into processes," said Rayner. "In five to 10 years, 60 percent will be in inquiry-based, 30 percent in point of decision and maybe 10 percent in processes."