Twitter Facebook LinkedIn Flipboard 0 Flashy modern developments like cryptocurrency, blockchain, and the IoT have been billed as the currencies of the future. When you break it down, though, there is one digitally-driven area of business that has been operating as the “new oil” of the tech era for far longer: data. Data has taken the world by storm in the wake of the commercialization of the internet. But where does data stack up in comparison to the other developing technological wealth of the modern era? How important is it for businesses to treat their data as an opportunity rather than a limited marketing or business ploy, strategy, or operations tool? These questions must be answered to understand the true value of data as a business asset. The Importance of Data Data was transforming the business world well before the first Bitcoin currency was ever mined or a chip was loaded into a dishwasher or television set. By that time, data had already spent years establishing itself as a critical part of the business landscape. This trend has continued to the point where, two decades into the 21st century, 50% of the top 10 companies are data-based enterprises. Jane Barratt of MX Technologies points out that the top 10 biggest companies in 2009 were primarily makers of products and services. In 2019, just ten short years later, the top 10 list was dominated by data mavens like Google, Facebook, and Tencent. Barratt clarifies that the “data-as-currency world” is still in its infancy, but there’s no doubt about the growing importance of data. Nowhere is this more true than with those who are gathering, consolidating, and analyzing that data. While data may be the new currency, though, many companies have yet to take advantage of that fact. This isn’t always readily apparent. After all, many organizations are becoming capable of gathering massive amounts of data. Companies of all sizes have failed to tap into the endless data-driven value at their disposal. Even as technology has made this information available in increasing levels of detail, most companies continue to do little more than scratch the surface. They utilize certain aspects of a data set and often leave vast quantities of facts, insights, and other details untouched. In many ways, it feels akin to Laszlo Hanyecz’s iconic purchase of a pizza with 10,000 bitcoins back when the cryptocurrency was in its infancy and appeared to be worthless. And yet, modern businesses must be ready to harness the power of new practices in the realm of data operations and data analytics. Why Data Matters on Every Level Most companies are aware of the importance of high-level data. We’re talking about poster-child information — things like social media likes, click-through rates, and customer retention levels. These splashier items have obvious, real-world value. A company can apply these things to a their decisions in plain, obvious ways that don’t require a great level of buy-in or convincing. But the value of data goes much further than those surface-level concerns. This is where dark data and data lakes come into the picture. Dark data is data that organizations gather on a regular basis but fail to process or leverage for business insight. Datumize and similar platforms capture dark data to then absorb the results into your correct format and destination. The amount of dark data has only grown over time, especially with tech like AI and machine learning generating an increasing amount of data on their own. This data is often left untouched, even when taking the time to turn it into meaningful information could yield powerful results. The Issue With Ignoring Dark Data A huge part of the problem with ignoring dark data comes from intent. Most companies start with an objective to harvest specific data that they perceive as valuable. They search for that data and that data alone. To use the “data is the new currency” analogy, it would be the same as identifying that a twenty-dollar bill was the only valuable piece of cash and eschewing all other bills in search of that one form of tender. However, there are still times when targeted forms of data are valuable. On the contrary, studying specific data sets can be an instrumental part of success. Dwell time and bounce rates can help target SEO efforts. Identifying abandoned shopping carts can help trigger email follow-ups. However, finding the value in all of your company’s data is where the nuance comes into play. It requires more than just starting with an objective and locating the data to match. Cultivating Data Strategy and Observability It’s not surprising that companies have no difficulty gathering data at this point. Modern software and data analytics tools make it easy to effortlessly capture incredible quantities of data. This can apply to shopping habits, internet activities, and numerous pieces of personal data scattered across the internet. It can take place on a mobile device as well as a laptop, desktop, or even an IoT gadget. Once captured, companies typically have to decide what they’re going to do with so much seemingly random, disconnected information. Often this is where they hit a wall and end up leaving the data stored in a program, where it gathers metaphorical dust either on a local system or in cloud-based storage software out on the interweb. There’s nothing wrong with storing data that isn’t necessary at the moment. However, if you leave it unstructured and unused, over time data becomes irrelevant and can even be a liability. Handling Data Right Away Instead, companies must learn to handle their data the right way from the get-go. This doesn’t mean they need to find an applicable use for every piece of information that flows through their programs. However, they should, at the least, process their incoming data by: Identifying it: This is a critical first step. You want to be aware of all of the data that your business is generating. At the least, this is for compliance and security purposes (i.e. you don’t want to possess sensitive customer or client data without even knowing you have it.) In addition, identifying data reveals the potential value said data could have either now or in the future. Gathering and organizing it: Your company must gather and place data in predetermined categories. This categorization of information preserves its usability in the future, as you will know where you can assess it if and when you will need it. Analyzing it: Once your data is identified and organized, it can be used. This requires analyzing whatever sets of data you find may be useful to your enterprise. Your business must observe and analyze this data to find the potential value that it possesses for your organization. Properly harnessing the value of all of a company’s data begins with a concrete data strategy. This should take a step-by-step approach to identify, clean, and utilize your data. Leverage Your Data If you go about processing your incoming data in this manner, you can also find ways to democratize your data. In other words, rather than leaving the data siloed or hidden in the dark, you can turn unstructured data into information that is able to be used throughout your organization. From there, you want to leverage a data observability application. Comprehensive platforms like Acceldata not only give you insight into data across the organization (i.e. let you know what’s actually in that data lake) but can validate and reconcile data at rest or data in motion in your organization. Using ML/AI, data observability goes beyond monitoring to detect and prevent issues. It offers continuous data reconciliation and manages data pipelines. This positions the tool and others like it as full-blown data managers rather than just a formula or algorithm that sorts data without going any further. In short, data observability gives organizations better insight into their data operations, which improves data identification, continuity, and consistency. So, What Yields Results? Investing in great technology won’t yield results if there isn’t a company culture that embraces the power of data. Remember, a strategy is nothing without a solid, supportive culture to back it up. The need for a culture that attracts rather than attacks data is paramount. One recent study of Fortune 1000 senior executives found that cultural resistance and challenges were the number one reason why companies are not becoming ‘data first’ companies. The report cited elements like legacy data environments, dated business processes, and traditional cultures as primary barriers of resistance. This makes cultural acceptance and employee and employer buy-in a necessity. If your organization does not commit to getting the most out of your data, it isn’t going to happen. Currency of the Future Becoming a data-driven company doesn’t happen overnight. Nor is it a process that can happen on its own. It requires a serious commitment of time, energy, resources, and focus. Employers and employees alike should share this goal. C-suite execs, middle management, and staff must all be shown why data matters all on its own, regardless of what it is impacting at the moment. In addition, you must be willing to maintain this data-positive position over time. Cultivate an accepting, growth-oriented company culture that perpetuates an understanding of the inherent value of data. Integrate cutting-edge data technology. Update data strategies to keep up with your organization’s current needs. If your company does this, you can truly become capable of harnessing the power of data as the currency of the future. Twitter Tweet Facebook Share Email This article originally appeared on Due and has been republished with permission.Find out how to syndicate your content with B2C Author: Peter DaisymeView full profile ›More by this author:Gig Economy Retirement PlanningWhat Is the Median Age of Retirement Savings?Are You Putting Money Down For Retirement?