By Alvin Wong, Product Marketing Manager at Logi Analytics

While much has been written about the consumerization of the enterprise, a similar trend has emerged in the way consumer Web applications are utilizing data and analytics.  For years, consumers have enjoyed the way purchasing decisions become more and more data driven.  By taking similar approaches within the enterprise, workers benefit from working smarter and more efficiently.  In turn, software and SaaS providers who embed analytics directly into their core processes will improve the user experience and create more competitive products to serve these businesses.

Let’s take a quick survey of well-known consumer Web properties.

• Amazon presents product reviews, suggests related products, and sends e-mail ticklers (which are all data-driven functions) to create a complete consumer-friendly experience, engender trust, and engage the customer.
• Kayak is a one-stop comparison site for travel reservations with a simple interface for consumers to find just the right itinerary for them; once an itinerary is selected, the user is sent to the booking site to complete the reservation process, and Kayak pockets a lead generation fee.

Many of today’s consumer applications (e.g. Zillow, Trulia, OpenTable, Yelp) successfully merge informational services with transactional functions as a way of creating smarter consumers.  This concept also forms the basis of their business model (note that all the aforementioned companies have IPO’d in the past 2 years, with the exception of Amazon in 1997).

Enterprises should be asking themselves whether their business applications help people work smarter.  The key to the question is in the combination of two words, “work smarter.” The “work” usually is performed in a process application, which manages transactions through a business process—for example, a CRM, ERP, Financial, or HR system.  The “smarter” aspect is often provided by a business intelligence application, which offers reports, data visualizations like dashboards, and self-service data exploration.  The answer lies in a concept called Embedded Analytics, which is the integration of business intelligence capabilities within business process applications.

There are a variety of ways that this integration can occur, but taking a cue from consumer applications, the most valuable would be:

• Providing analytics at the point of action (analogous to reviews placed next to the Amazon BUY NOW button).  An enterprise example would be providing data on Lifetime Value and Churn Probability in a customer service application.
• Creating application functionality with the use of visual analytics (analogous to the Kayak approach).  An enterprise example would be the ability to visualize geographic sales performance on a map, and being able to perform territory re-assignments on the same map in the same screen.

Software providers who adopt Embedded Analytics in these ways will create more valuable and competitive products.  Forrester Research has named a category of enterprise software called Smart Process Applications, which they expect to grow significantly faster than the overall software application market, as noted in their 2013 Global Tech Market Outlook.  From the perspective of analytics, Forrester states that these applications offer:

• Embedded awareness data relevant to the business activity (sounds like Amazon), and
• Embedded analytical tools designed for the task at hand (sound like Kayak)

This research further validates the valuable approaches taken by consumer applications, and how software providers can benefit by adopting these types of capabilities in their applications.

If consumer applications are any indication, the future is bright for analytics and the enterprise.  Embedded Analytics can establish a Win-Win-Win scenario: end users have data and analytics to guide their work, businesses have a more informed and efficient work force, and software providers create more desirable and valuable offerings.

Alvin Wong is the Product Marketing Manager for Logi Analytics.  He is focused on Embedded Analytics and the OEM practice, where software and SaaS providers utilize Logi products to develop and integrate analytic capabilities within their software applications.  He has an extensive background in solution architecture and implementation of SaaS applications.  Alvin earned his MS in Engineering Management from Stanford University and BS in Electrical Engineering from Cornell University.