Based on my experience, I estimate that between 90 to 95 percent of businesses are failing to derive the expected value or ROI from their business intelligence (BI) investments. It is time to decipher why this may be and how to change these statistics. In today’s data-driven enterprise, most companies know their information could work harder for them, but have difficulty discerning value among the many solution offerings. Businesses can practically drown themselves in data collected from various sources, but they still do not have the know-how or infrastructure to realize its full promise.
When data is used to its maximum potential, companies have the ability to enhance decision-making throughout the organization and even identify new revenue streams. To monetize information in this manner, however, businesses must take insights and put them into operational processes. This means not just reserving BI and analytics for business analysts and other power roles, but rather putting data into the hands of operational decision-makers across the enterprise.
For example, imagine how much more efficient a customer representative could be with instant access to customer information, transactional history, and products or parts availability. While this information has historically resided in different systems, arming customer support teams with the ability to intuitively access and make decisions from this data is a huge competitive differentiator.
For an organization to gain the full value of its information, it’s also important that self-service data access be extended to partners, customers and other external groups. Let’s take an airport restaurant’s use of table-side iPads as an example. While their primary function is to receive customers’ orders, they serve more than just this basic utility: They’re also an entertainment system—complete with games, fun facts about the airport, local history, etc. In this way, adoption (and thus, revenue) is driven by the entertainment enabled by data; not to mention that such a restaurant could end up saving on labor costs.
For companies to effectively extend self-service to all internal and external stakeholders, they must first understand the methodology for data monetization. To borrow an analogy from manufacturing, value is created by turning raw materials into finished products, and this specific methodology involves the management of a data value chain.
Beginning with raw data, an organization can use existing IT tools to capture all types of data—transactional, logistic, marketing, customer, etc. The more integrated this information is, the more complete the picture and the better the framework for data monetization.
Moving to the next section of the data-value chain, the insights are operationalized. The value of data is realized only by improving an actual decision process using informational applications. As such, operationalizing insights involves instantiating the data assets into either an operational BI application or a customer-facing BI application. The higher the potential loss or gain from a fact-based decision, the higher the value of the data-monetization product.
To really understand this process, we can look to nVision Global, a leading international provider of software, services, and solutions for freight payment, audit and logistics. As part of its main business, nVision was providing 5 to 10 percent savings to its customers through managing and auditing shipping invoices. The company identified an opportunity to drive additional revenue by building an information app that enabled customers to manage more of their own logistics. This was done by monetizing the data already contained in the shipping invoices, netting an additional 2 percent savings which, when applied to shipments of $150MM, adds up very quickly. nVision captured the data, integrated it, operationalized it, used an analytic application and then repurposed it to better serve its customers—perfectly illustrating the steps involved in data monetization.
Any organization can find itself with an enormous amount of data, but having a wealth of information by itself does not provide any opportunity. It is the value companies extract from this data that will lead to greater insights—both for the business and for its customers. Organizations must recognize this, and begin realizing the full return on their information management investments.
Dr. Rado Kotorov is the Chief Innovation Officer for business intelligence (BI) and analytics provider Information Builders and co-author of Organizational Intelligence: How Smart Companies Use Information to Become More Competitive and Profitable. He is responsible for analyzing market and technology trends, aiding in the development of innovative product roadmaps, and creating rich programs to drive adoption of BI, analytics, data integrity, and integration technologies. Rado strives to make BI and business analytics more accessible, intuitive, and collaborative through the adoption of innovative Web 2.0, advanced visualization, predictive modeling, search, and mobile technologies. He has a PhD in decision and game theory, and institutional economics from Bowling Green State University.
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