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Data, Like Oil, Must Be Refined

In 2006, Clive Humby declared, “Data is the new oil!" at the ANA Senior marketer’s summit. Over ten years later, that analogy is even more accurate. As with oil, people are always searching for new and better sources of data, technology is evolving to find new and more efficient ways to use data, and collecting and refining massive amounts of data requires specialized processes and technology.

Refining data drives value

Crude oil is valuable, but it becomes more valuable when it is transformed into gas, plastic, chemicals, etc. A barrel of crude oil costs $44.55, but a barrel of jet fuel, after refining, costs $59.22 – increasing its value by 33 percent. Data is the same; you need to process it to gain the most value. Just as there are many sources of oil (onshore drilling, offshore drilling, fracking), sources of data (the internet of things (IoT), social media, ERP, spreadsheets) are numerous and growing every day.

A lot has changed since Humby made that declaration. In 2006, there were no iPhones, no one had heard of apps, and the Web 2.0 revolution was just beginning. A year later, the iPhone was introduced and the nature of the internet, including a new focus on developing apps for smartphones, started a transformation that continues today. The introduction of dynamic, personalized applications fueled the big data wave which created the need for big data analytics.

Since that time, the volume, variety, and velocity of data have exploded, and companies need advanced analytics to manage the deluge of structured and unstructured data. Without advanced analytics to sift through the noise, data contains interesting and sometimes useful information. With big data analytics, data is transformed into actionable insights, enabling companies to make faster, better decisions based on real-time information.

The power of analytics

Think of a farmer that adopted precision farming. Using IoT sensors and smart machinery, the farmer maximizes crop yields while conserving water, fertilizer, and pesticides. The sensors monitor soil conditions and crop health and development in real time, watering crops when necessary and adding fertilizer only to areas that require it. All of this happens automatically.

Applying advanced analytics to farming data enables the farmer to predict when the crops will be ready for harvest, and the quality and quantity of that harvest, so the farmer can proactively manage every step of the value chain, securing the most efficient and cost-effective transportation and ensuring food reaches the right destination quickly. Purchasers gain complete visibility into the when they will receive goods, enabling them to better plan. 

Advanced analytics empowers farmers, manufacturers, energy companies, and commodity traders to make better decisions faster.

Data, like oil, needs to be refined to maximize value.

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