In 2006 respected data scientist Clive Humby famously referred to data as “the new oil”.This phrase went viral and got lots of media attention. Experts agreed and disagreed, some went as far as calling data the new bacon – “an unhealthy obsession”.
Whatever funny word we use to describe it, the fact remains the same – data is officially the most valuable commodity of the modern economy.
But it wasn’t always like this. There were times when oil was the world’s most valuable resource. During the 19th century, oil companies ruled markets globally.
In recent years however, oil companies were replaced at the top by data-driven companies. Microsoft, Apple, Amazon, and Google leveraged the power of data to become leaders in the global marketplace.
What allowed these giants to scale to heights never seen before was relying on the ‘data beats opinion’ mindset. Asking interesting questions and pulling the right answers from data helped them make excellent business decisions.
Data is probably much more valuable than oil. Oil is finite and once it’s used it disappears. Data is created every second and can be reused over and over again to draw new insights and possibilities. Data is infinite in scope and potential. The more data we have, the bigger the problems we can solve and the more powerful our solutions can be.
But having tons of data isn’t enough. We have to do something meaningful with it. To quoteJack Dorsey, founder of Twitter and Square:
“Every single action that we do in this world is triggering off some amount of data and most of that data is meaningless until someone adds some interpretation of it or someone adds a narrative around it.”
In our experience helping companies find meaning in data, we understand why Humby compared data with oil in the first place. Both are extracted from a source and refined before being turned into value. We often reference these similarities and refer to them as ‘Data Oil Refinery’. This helps us and our clients better understand data.
Here’s our 4-step process for turning data into value:
Extraction/Gathering
American oil history began in 1859 when Edwin Drake drilled the first oil well. He drilled down a 70 ft whole, extracted oil and stored it in barrels for sale. The same process is done today by major oil companies, only much faster and with better technology.
Similarly, the first step in the process of creating value from data is extracting/gathering data. Data is sourced from websites, social media posts, and others and stored into a database. For our marketing agencies clients for example we gather data across their entire portfolio of clients’ websites or marketing campaigns and store it in a SQL data warehouse.
Refining
Extracted oil isn’t very valuable if left alone. It needs to be refined in order to change into a range of useful products for industries and consumers. Rockefeller, the oil magnate, saw drilling for oil as a messy business and made himself the richest man on the planet when he built the biggest oil refinery in the world – Standard Oil.
Refining is the most important step in the process of extracting value from data. For example, one of our marketing agency clients recently needed help because they experienced a traffic conversion rate drop on four different web pages. Thinking like refiners, we extracted millions of data points and focused only on what’s usable to our client. We uncovered an issue with Google Indexing which our client fixed immediately and solved the problem.
In some cases a good data strategy is to ignore as much as 98% of the extracted data and focus on the remaining 2%, because this is where you often find hidden gems. We believe companies that focus on data refining will be the most prosperous in the future.
Building A Combustion/Analytics Engine
Extracted and refined oil is not where the process of turning oil into value ends. Refined oil requires a combustion engine to run on. Cars, trucks, tools, machinery, and others all run on refined oil.
Refined data needs its own combustion engine which is analytics. An engine built on top of refined data comes in the form of dashboards or audit checklists. These engines can be integrated with your business systems and processes to help you make better decisions and generate more profit.
The Road
An amazing car with a tank full of gas has no place to go if there’s no road ahead. It doesn’t matter how fast, big or strong the car is.
Data is the same way. No amount of extraction, refinement or action engine can make data work unless there’s a vision. Whether that’s scaling, improving labor efficiency or solving other business problems, you need to have a vision in front of your data system in order to realize the full potential of your data.
Few Additional Tips:
- Don’t hire a data guy/gal
One know-it-all person cannot extract oil from the ground, refine it, and turn it into various products by himself. One person cannot single handedly take care of data extraction, refinement, and build an action engine. Each step in the process requires its own creativity and knowledge.
- Don’t buy an app
There is no app that can do this process because it’s custom for every company. We speak from experience, because we cannot use the same template across our entire client portfolio. We have to understand each client individually and create a system for each client separately.
- Don’t skip straight to automation
Most companies understand the importance of data but sometimes want to skip the part of data refining and go straight to automation. Can oil be turned into plastic without refinement? Data has to be refined first before automation can be implemented.
Food For Thought:
Process of extraction, refinement and action engine is applicable to other areas of life as well. In investing for example, there’s a never ending supply of investment information one can read about (gathering) and refine to form his/her own investment philosophy (refining), which can be applied when selecting stocks (action engine), leading to great investment opportunities (road).
Similarly, in nutrition there’s an endless supply of health data like BMI, heart rate, weight and so on, one can use to determine his/her own health criteria and decide where he/she wants his blood sugar or heart rate level, take action and achieve desired outcome.
Ready to generate value from data?
If you’re thinking about implementing a “Data Oil Refinery” process into your organization, now is the perfect time to reach out to Data Factory. We’re experts in data science and have years of experience in the field. We’re the best of the best at gathering, refining and turning your data into ROI. If you have any questions feel free to reach us at info@datafactory.net
