What We Can Learn from Expedia - Today’s Largest Self-Service BI Tool

When it’s suggested that Expedia is the largest self-service BI tool, people are often surprised at this analysis. Isn’t Expedia just a booking site?It’s true that it organizes bookings, but in order to make the right one, information is critical. It is Expedia’s power to deliver the right information from multiple data sources very quickly for decision-making that makes it the industry’s largest BI tool - and it does it as a self-service.

Before we delve into the specifics of Expedia’s offering, let’s take a look at self-service adoption in the BI space.

Self-service data discovery has been the buzz word in the BI industry for the past 3 years. It is touted as the solution to a number of problems: how to analyze ever increasing volumes and sources of data, how to squeeze more business insights from that data, how to provision BI to more stakeholders and make BI more pervasive as we strive for more fact-based decision making, and how to eliminate the IT backlog, to name just a few. 

According to a Harvard Business Review article “Kick-Ass Customer Service” (Jan-Feb 2017): “Across industries, fully 81% of all customers attempt to take care of matters themselves before reaching out to a live representative.”  For the BI industry, this would mean getting all the information that you need, in the form that you need it (report, dashboard, format, styling) without having to ask the IT department to do it for you.  

Yet, the BI industry has a dismal adoption rate of only 22%, which has plagued the industry for several years. In response to this grim number, we must look around for a solution in other sectors that provides self-service to millions of people without any IT support. In essence, we are looking for a self-service paradigm that can give us insights about how to solve the adoption challenge and learn from it.

This is where Expedia comes in. The company provides a game changing self-service as it eliminates the need for travel agents. For those who can remember booking a flight from Madrid to New York in the 1990s, it took multiple meetings with an agent, hundreds of pages of travel schedules, and many price checks. Today, most people do it themselves via sites like Expedia. They quickly generate several reports that inform them on prices, flight times, connections, and many other factors to make optimal decisions. Over 60 million people visit Expedia monthly and complete their business on average within six minutes—and the efficiencies this self-service environment engenders are evident to anyone who has used an online booking tool.

The 78% of employees who do not have direct access to BI need Expedia-like BI and analytics applications to find answers quickly to their business questions. To clarify further, imagine if you had to go to Expedia and you were given a data set containing information on various airlines that you could load into Excel to analyze and find the right flight. Would you use it? Would you be able to do it in 6 minutes? The answer is no. The reason being is that when it takes too long to do it yourself, you will trade your time for the services of someone else. In other words, if Expedia was difficult to use, lacked flexibility to get the right answers, and took too long to find the answers, consumers would prefer travel agents.

The same happens with operational and front-line employees. If the effort to get BI information exceeds the time threshold for making decisions, the employees will ignore the data and make gut based decisions. Operational employees are paid to make on the job decisions quickly and not to analyze data files. This is an important division of labor, because the analysts (those who support the 22%) are paid to do exactly the opposite – analyze data slowly and thoroughly, and provide recommendations.

Empowering front line employees with information for decision making is not done by distracting them with analysis from self-service tools, nor by pushing more reports as traditional BI does. In fact, the latter creates information overload. The right approach is to deliver an “app like” experience where operational users can get answers to questions in less than six minutes. As a result, front line employees can see the facts and successfully perform the operational tasks at hand. Productivity will increase as the time spent on answering questions decreases, but also the number of errors will decrease given the easy access to facts.

Expedia provides a unique design paradigm that enables flexible self-service information access for fast decision making, and it is this unique design that can play a constructive role in the BI industry. Organizations of all sizes, industries and levels of technical maturity are realizing the transformative power of equipping more enterprise stakeholders with better access to information. Because they can easily be deployed by non-technical users, both within and outside of the firewall, the benefits of these self-service initiatives are many and extend beyond those of traditional information management strategies. We have the opportunity to dig deeper to uncover significant indicators and metrics, explore information and discover its potential, interact with real-time data, automate the scheduling and delivery of vital information, and use the resulting insights to drive better business outcomes – all through the use of self-service analytics.

In order to achieve or even surpass a paradigm similar to Expedia’s, organizations need a powerful, integrated BI and analytics platform that provides the flexibility necessary for true self-service analytics. We can accomplish this by not only analyzing Expedia’s self-service approach, but by also considering the following checklist for an effective and comprehensive self-service analytics strategy:

  • Consider Usability: Provide a powerful, comprehensive, and accessible way to share and operationalize insights by offering an intuitive interface that influences people to use any app, even an analytical one. This leads to new heights of adoption and increases return on investment.
  • Ensure Scalability: To avoid increasing hardware and maintenance costs, utilize a scalable underlying architecture that will effectively support a growing user base. This will hold true even when the number of users reaches into the hundreds and thousands.
  • Think Security: Ensuring the integrity of confidential information is always critical in BI and analytics initiatives. When data is shared among outside user groups, like customers and partners, this becomes even more important. Make sure you invest efforts in data security as part of your self-service strategy.
  • Contemplate Data Services and Integrations: Use data services and integration to allow IT to expand the data environment and open up all information. This includes all internal systems such as CRM, ERP, and legacy applications, as well as social, cloud, mobile, and other sources.
  • Emphasize Functionality: Address end-users’ unique needs by delivering a single integrated platform with a broad range of capabilities.
  • Drive up Performance: Users will quickly abandon a self-service initiative if performance isn’t up to speed, and they aren’t inclined to cut you any slack due to large volumes of data or a high number of queries.
  • Keep it Personal: Give users full control over what they see and how they see it. This will deliver greater levels of BI pervasiveness, because information is only truly relevant when users can shape it to their own specific needs.
  • Check your Integrity: Ensure your BI and analytics initiative is supported by an underlying data quality platform. This will guarantee that all data is timely, trusted, and available for self-service access and ensure the data accuracy, consistency, and completeness that is essential when information is shared with a broad user base.

In the age of information, analytical insights are no longer reserved for data scientists and other elite groups. Following the steps outlined above will ensure the creation of an effective, comprehensive self-service analytics strategy—one which emulates Expedia’s own self-service approach.  

If the BI industry hopes to improve the utilization of self-service tools, it must look to other sectors that effectively provide self-service analytics to millions of people. While considering the above checklist and examining the capabilities of Expedia, companies can enjoy the same BI success that makes Expedia one of the largest self-service BI tools today. Its platform gives users access to thousands of data fields and hundreds of custom reports with zero training. Now that is an accomplishment that the BI and analytics industry can learn from.