Data Monetization: Making Data Work for You
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.
