Imagine a man strikes oil in his backyard. Excited, he bottles it up. He tries to sell it, but no one is buying his jars of raw crude. He is frustrated and confused. He knows he is sitting on something valuable, but he cannot seem to extract any money from it.
Data is the new oil. Over the last decade, companies have scrambled to invest in data technology, hoping to grow rich. But like our friend with his jars of crude, many of these companies do not know what to do with raw data once they have it.
Cracking the Code
For proof that data has become one of the most valuable assets on the planet, look no further than the world’s top companies. According to Global Finance (https://www. gfmag.com/global-data/economic-data/ largest-companies), only one of the five richest companies in the world—Saudi Aramco—is a traditional energy company. The other four: Apple, Amazon, Microsoft and Google parent, Alphabet, are technology based.
Hoping to follow in the footsteps of these marquee names, organizations spend millions on data collection tools. But without investing in the right talent and implementation, these tools live up to only a fraction of their full potential.
In a recent survey (https://hbr.org/2019/02/ companies-are-failing-in-their-efforts-to-become- data-driven), 92 percent of executives said their organization was accelerating investments in artificial intelligence, yet 77 percent reported challenges adopting AI into the company culture. Fewer than half the executives recognized data as a business asset.
They are waking up to the reality that it takes more than technology to succeed in the Information Age. Only a handful of companies today are using data to its full potential. Amazon is leading the way, followed by retail giants Walmart and Target, financial innovator Capital One and internet juggernaut Google.
No other company today can touch Amazon when it comes to using data—though Walmart has the leader in its sights. Amazon’s data engines are constantly refining data on the fly, giving users the best possible offer in real time. Every action a user takes on Amazon’s platform is captured and analyzed. The platform rapidly reads these trillions of pieces of data and uses them to understand, predict and guide customer behavior.
The customer is blissfully unaware of all the data churning behind the scenes. From the user standpoint, Amazon is a place where they can quickly find and take advantage of the very best offer on the thing they want when they want it.
Strategy Is Crucial
Successful companies do not follow crowds. An organization that invests in a data system only because that’s the one its competitor uses is bound to be disappointed by diminished results. Data that generates real value addresses specific needs to move a company closer to its unique goals.
Despite being one of the simplest and most critical facets in creating a data strategy, goal setting is often neglected. Many companies spend millions on data collection efforts that do not align with their own strategic principles. It’s natural for goals to exist at both the corporate and department levels. In a successful strategy, these goals align. The first step in creating a data-driven organization is documenting goals at every level and identifying how data can be used to achieve them.
Organizations using data successfully understand that data strategy is iterative by its very nature. It is not a one-and-done effort. A data strategy evolves, matures and scales. It needs to be revisited regularly to ensure it remains aligned with the company’s changing goals and market trends. One of the advantages of a flexible and scalable data structure is the freedom it allows a company to recognize and react to change quickly and efficiently.
Data Collection and Storage
Once a company knows what it is trying to achieve, it can create a framework to collect the data it needs. Every action a customer takes is a datum. Every email they open, link they click or phone call they make is an indicator of what they want and how they behave. The key is knowing which of these data points is important and how they can be referenced against one another to create a three-dimensional view of the customer journey.
The importance of collecting good data cannot be overemphasized. The best and most complex algorithm cannot create good results from low-quality data. Yet even the simplest analytical tools can provide reliable results when fed rich information.
The data framework establishes not only where the data will come from but also how it will be stored once collected. Many of the reservations that consumers have about data collection come from a fear that the companies they trust will be breached and their data sold to the highest bidder. Companies must design their data storage so it is secure yet can be easily accessed by authorized users when needed.
Putting Data to Work
Amazon’s data platform changed the game for everyone. Gaining and retaining customers now means being ready with the right offer in the right format at the right time. Speed is critical; the company that can present its offer first is often the winner in capturing customer attention.
A good data strategy does not forget that information can be gleaned from every interaction. Did a customer ignore an email but click an SMS link? Did a phone call to customer service result in a bigger purchase or a cancelation? Every new action is a new piece of data to enrich the system’s understanding and enhance its ability to predict and respond to customer desire.
While the system is collecting, analyzing and using data to present good offers on the fly, at the end of the day, humans are the ones determining the data strategy. A good data architecture will provide ways for people to extract insights and visualize data patterns so leadership can make informed decisions about where to go next.
This is the true power of data: showing leadership in real time which efforts are having the biggest impact. A company that observes high engagement in email and low engagement in direct mail knows where to focus its marketing dollars. A company that tracks the searches typed into its website knows what features customers are looking for. One that uses social listening to track social media conversations knows what customers love or hate about the brand. These are insights that can change a company’s entire direction if leveraged effectively.
Privacy Concerns
As the speed of technology has outpaced the culture’s ability to adapt, controversy has flared at times regarding companies’ collection of personal data. Google, Facebook and other tech giants have come under fire for the sheer volume of data they collect about their users.
Some people are wary of being tracked. They may fear their data will be stolen, sold or misused. A small but vocal community is uncomfortable even when their data is used appropriately; for instance, to show ads for products they might like.
Countries have responded with a patchwork of regulations that can create headaches for international companies. Data that can be collected from an American user can’t be asked of a German user, for example. While a customer in Connecticut can be automatically opted-in to promotional emails, a customer in Canada needs to ask to be added to the list.
It is important for organizations to establish data governance early in system implementation to assuage user fears and, often, to comply with financial or government regulations. The company needs the ability to monitor, audit and control its data assets and who has access to them.
In the coming decades, it will be necessary for nations to come together and establish international regulations over the collection and use of data to ensure it is used in the best interests of people everywhere.
In the past, losing assets to theft was a financial headache often eased by insurance. The repercussions of stolen data, however, can reverberate for years through identity theft and a sense of personal violation.
Despite these concerns, the data revolution shows no signs of slowing. Over time the culture will become increasingly accepting of trading information for convenience, particularly as data security tools improve.
Priceless Assets
In the latter half of the nineteenth century, the Industrial Age spurred an oil rush. For 150 years, oil was the commodity that moved the global economy. Today, data has taken the place of oil as the world’s most valuable asset. Unlike oil, data is in endless supply, and it can be harvested and used by anyone who has the right tools and know-how. While yesterday’s oil barons were those who owned the most assets, tomorrow’s data barons will be those who use their assets most effectively. EE
Sankul Seth is the Vice President, enterprise Data, at PsCu, where he is defining the company’s data innovation strategy. His current focus is on transforming technologies to simplify and define technology roadmaps and implementation. He holds an MBA in Data and Analytics from the university of south Florida. email: sankul.seth@gmail.com
