In today’s data-driven world, unstructured data poses both a rapidly growing threat and a potentially game-changing opportunity. Agile, digital-born competitors are winning market share because of their ability to use data to create and deliver personalized experiences that customers demand and the products/services they need. But legacy organizations find it hard to compete because so much of their content is unstructured and not consumable by analytics engines or usable in automated workflows. They are at a do-or-die decision point—faced with the need to enrich and leverage their unstructured data stores, or slowly whither on the vine.
Read on to see how digital-born organizations have raised the stakes when it comes to structured vs unstructured data, and how legacy enterprises can fight back.
The Battle of Structured vs Unstructured Data
Structured data contained in orderly rows in a database can be easily accessed, queried, analyzed, sorted and filtered. But, contrary to this structured data that powers fully digital companies, unstructured data is dark content that can’t be readily found or used in a meaningful way. It comes in a wild variety of formats including emails, Word documents, images and scanned files among others. It makes up around 75 percent of the existing information housed in all the repositories of an enterprise, while newly created data continues to flood into organizations at an alarming rate—slowing workflows, customer interactions and product development.
On the flipside, digital-born companies are able to use their structured content to feed analytics engines, generate better insights and business intelligence, develop new highly targeted products, and create seamless customer experiences. For them, data is an innovation accelerator—whereas for many traditional organizations, their overwhelming volume of unstructured data is simply a drag on the business.
Here’s a deeper dive into three ways unstructured data makes a difference in the battle between the digitally born and the traditional enterprise.
1. Improve the Customer Experience
Customer expectations have radically evolved over the past 10 years as a result of more interactive and self-service channels. The top-notch digital interactions provided by industry leaders such as Amazon, Zappos and Apple have conditioned consumers to expect world-class customer experiences at every turn – whether it’s with “one-click” shopping or tracking a pizza from the restaurant to their front door.
Saddled by legacy systems and decades of unstructured data, traditional businesses simply can’t provide these exceptional experiences – yet. If we look at insurance providers as just one example, older enterprises require new consumers to endure broker calls, meetings, paperwork and a lengthy approval process. But digital insurance start-ups like Ladder, Fabric and Lemonade are quickly capturing market share by being able to generate quotes in seconds and approvals in minutes. The difference? Their interactions are fueled by structured data that can be leveraged to power RPA and other process automation solutions that streamline customer-facing workflows and make policy, billing and claims processing lightning fast.
To deliver the great experiences customers expect, insurers are just one example of an industry that’s facing a dire need to convert unstructured data to a format usable by modern policy administration systems, claims management systems, illustration tools and client portals—as well as by RPA bots and other process automation solutions that contribute to improved customer touch-points.
2. Drive Analytics, Insights and Intelligence
In the energy sector, pressure from newer, more innovative oil and gas companies (such as Seven Lakes, EMXT and JP3 Measurement*) who are leveraging structured data has brought some industry giants to a tipping point. To improve the profitability of their drill sites and lower the cost of production, they need to either leverage their unstructured data, or see their market share shrink. Major oil and gas enterprises have a huge potential advantage in the decades of data from test sites around the world, but the data is locked in millions of unstructured historical documents like land lease agreements, permits to drill and well logs. To leverage this legacy data and compete with digital-born businesses, energy organizations must discover, access and transform their unstructured data to structured data their data primed for process automation, insight system and/or other digital business initiatives.
3. Speed-up R&D and Product Development
When businesses have easy access to their data along with a complete and accurate view of what their fileshares contain, they’re better positioned to identify new product and service opportunities, and create them quickly. This agility and ability to respond to changing customer preferences on a dime further enables them to increase overall market share. In the banking industry, for instance, digital upstarts like Wealthsimple (investments), Payfirma (payments) and Borrowell (personal lending) offer personalized products and services directly as a result of the consumer data they collect at various touch-points.
In the case of some national banks, their 100-year history has stood as a solid brand benefit, but the century’s worth of unstructured data that they’ve accumulated is a liability. It can’t easily be accessed or used to identify customer needs, trends or new product opportunities. Further, it clogs up workflows, slowing the development process. The irony is if a bank is able to convert and clean its historic legacy content, it will turn that Achilles heel into a massive competitive advantage.
Amid the rise of digital-born competitors who are not held back by legacy data, the need to access, enrich and leverage unstructured data is at an all-time high. For traditional companies, finding ways to effectively harness the potential within their volumes of unstructured data is a do-or-die proposition. Without a plan in place to address the access, quality and efficiency of structured vs unstructured data, businesses will be limited when it comes to improving customer experiences, driving analytics, accelerating product development, or even taking advantage of RPA and process automation tools. Given the vast volume of data that they have amassed, companies that take proactive steps towards data enrichment along their digital transformation journey are going to not just compete, but thrive.
*Digital Transformation in Oil and Gas
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