Data currency: are we leaving money on the table?
- Posted on April 25, 2016
The following blog post was written by Avanade alum Sayan Ghosh.
When 22-year-old Paul Simon penned the legendary lines “people talking without speaking, people hearing without listening,” computing and data processing was in its infancy. The times they-have-a-changed!
Today we’re in the midst of arguably the most significant wave of digital transformation, yet we’re missing what lies beneath the surface when it comes to data. An IDC survey reports that only 0.5 percent of the world’s data is being leveraged, analyzed or used. We are just scrolling through without realizing the underlying value, barely scratching the surface of the huge amount of data businesses generate today. And it’s only going to get messier as the industrial internet of things (IoT) and a fleet of sensors join the party.
When data becomes currency
In Avanade’s 2016 Technology Vision, we recommend that businesses relearn their approach to data. On its own, data provides little or no value to the business. What really matters is the insight gleaned from that data. That’s when data becomes currency – infused with new life with analytical perspectives and actionable insights. Businesses across the world recognize this potential, yet few have invested in practical, concrete actions to put this perspective into play. This, as the Economist Intelligence Unit points out, may amount to leaving money on the table.
It doesn’t take a big bang program to unlock data currency. An iterative approach to finding new ways to use data as a currency provides learnings that can help you chip away at the data landfill, and allows you to relearn and innovate using these insights. Such approaches benefit from the principles of Agile software development, from both a process and technology perspective, but they are all about the people, mindset and culture of the organization.
We also see organizations increasingly adopt a dual-velocity approach. With this approach, the core systems and processes follow a structured, well-governed lifecycle to empower users with analytical capabilities; at the same time, a lot of innovation happens around the edge, using rapid deployment capabilities in the cloud through big data, social and unstructured analysis. We also see organizations mashing up the data inside and outside the enterprise boundaries to uncover insights, often real-time and actionable.
Use data to drive outcomes
For customer-facing organizations, the more trusted a brand is, the more willing customers are to share their data and personal information. This can result in programmable business models, allowing an organization to be opportunistic, dynamic and predictive all at the same time, enabling it to capture the relevant business moments and turn them into measurable outcomes – transactions, revenue, cost avoidance.
Turning data into currency involves more art than science. It requires a blend of business, analytical and technical skills, and often means marshaling an augmented workforce that blends intelligent systems, things and people.
It is the right time for enterprises to bring data back from the dead. To analyze and then “spend” it in ways that deliver real business value.
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