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Without Uncovering Dark Data, You’re Not Uncovering Business Opportunities

In this special guest feature, Odhrán McConnell, Chief Technology Officer at Trint, points out that according to recent estimates, approximately 90 percent of a company’s data is dark, meaning it hasn’t been analyzed or leveraged to the benefit of the business. Odhrán has more than 20 years’ experience developing software, leading technical teams and providing leadership up to board level. Before joining Trint, he spent 9 years working with The Guardian, one of the UK’s leading and best-known publishers. At the time of leaving The Guardian, Odhrán was the Head of Software Development, where he led a team of 80 developers and held responsibility for producing The Guardian’s website, as well as The Guardian’s multi-award-winning app for Android and iOS. Most recently, Odhrán was CTO at 101 Ways, a product-focused technology consultancy. Odhrán is a passionate advocate of all-things-tech. Among his favorite topics is his much-loved Commodore 64, the machine he first learnt to code on.

If you’re a business that uses any type of technology (which, in the year 2020, is likely almost everyone), you’re sitting on mounds of unstructured – and highly valuable – data. According to recent estimates, approximately 90 percent of a company’s data is dark, meaning it hasn’t been analyzed or leveraged to the benefit of the business. This is especially true for those who frequently use tools that generate voice or audio-based information. Digging through this content manually is nothing short of a time suck, requiring employees to watch or listen to the files in full – not to mention pay extreme, close attention to every detail and decide on its worth to the business. This type of focus over a long period of time is almost inhumane; by not analyzing it, it’s no wonder that dark data continues to grow by 55 percent every year.

Here’s the truth – without tapping into the potential value of unstructured data, companies are missing out on huge opportunities to use and recycle content for monetary benefit. And in the age of peak digital transformation, this analysis doesn’t need to be managed by the IT team, or the new tech-savvy intern. An inhumane task requires a tech-driven analysis strategy: that’s where artificial intelligence (A.I.) comes in.

We’re living in the age of audio and video

As we adopt more tools that help save time and create connections across the workforce, businesses are turning to video and audio more than ever before. This is only increasing as the circumstances trend toward a long-term remote work environment, and captured audio and video content could hold crucial, strategic information. Businesses are continually adding to their archive of data that could have a massive impact on their success; without analysis and understanding, it’s information with no direction toward the goal.

This is also true for businesses looking to increase engagement with their customers; a goal that is always relevant, but is especially pertinent now when thinking about how to get ahead in this tough market landscape. A recent study found more than half of consumers reported they want more video content from brands they regularly interact with. So if a business is generating hours of content that could be usable for engagement, but not properly analyzing it, there’s a serious opportunity they’re missing out on.

How AI can help

With massive – and growing – amounts of unstructured data, it’s almost impossible to rely on the human eye to seamlessly analyze it successfully. But the task is no sweat for A.I. A.I. tools can examine all of this information with a low margin of error – and can also do so in a fraction of   the time it would take a human. Not only will companies be privy to new, valuable insights from the data, they’re receiving it sooner, and can therefore act on it faster. Business needs and consumer preferences are changing rapidly, and the window of time to execute cutting-edge ideas is growing smaller in order for a company to be truly competitive in 2020.

With A.I. managing this tedious but beneficial task of analysis, employees can then use up the time to figure out how to best implement the new information – an activity that requires a human lens. This could play out as a fresh creative marketing strategy that incorporates the uncovered video files or the execution of ideas from an audio file from an old brainstorm session. It’s this mix of data-driven analysis with employee-led execution that will result in the full-fledged business benefits that come by uncovering dark data.

The benefits of analyzing dark data

There are countless ways companies can leverage newly uncovered data for their benefit. For example, larger corporations that are spread out across departments – or locations – can use the new information to connect the disparate dots between siloed departments and create a more cohesive company strategy. Direct to consumer brands can leverage insights based on market and user analysis to create more personalized experiences for their customers. Security enterprises can proactively build predictive models that flag and manage incoming risks. There’s virtually no company – across different industries and sizes – that wouldn’t benefit from uncovering more company data and increasing their bottom line.

In our new normal, there’s little to be certain about, and it’s becoming even more difficult to prepare for the future of work. However, it’s clear that businesses can’t go wrong with adopting new technologies to save time and money. As more enterprises adopt new tools to prepare for what lies ahead, we’ll look back at this period as an inflection point for digital adoption and readiness in the business world. There are countless new workplace technologies to consider, but to be most effective, you should start by adopting tools that can analyze and help you fully understand all of the data and assets you already have.

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Comments

  1. This article is a very nice discussion, but it deals with only one type of dark data (the Gartner definition), “data that organizations create and store as a part of regular business operations and processes, but never use”. Other types of dark data can lead to much more serious problems, especially for corporations. In general, dark data are data of which you are unaware. It might be that you want today’s data, but all you have is yesterday’s. It might be that your sample is distorted – perhaps certain types of cases are missing. It might be that the recorded values are inaccurate – no measuring instrument is perfect. It might be that you have only summary values, like averages, which tell you nothing about extremes. Or it might be, as you describe, data that has been collected but not analysed. Dark data of these other kinds can have huge adverse consequences for organisations, and can lead to commercial and financial disasters, even fatalities. Many examples are given in my recent book, “Dark Data: Why What You Don’t Know Matters”, published by Princeton University Press earlier this year, where I give a taxonomy of fifteen kinds of dark data. The book illustrates how ignorance of dark data can lead to problems but also shows how to detect and overcome the problems. Indeed, it goes even further and shows how through the strategic application of ignorance one can take advantage of unknown dark data.

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