Data is the New Oil
By Joel Semeniuk
If you enter “Data is the New Oil” into Google you’re going to get results that go back as far back as 2006 regarding a broad spectrum of industries and problems. Some suggest it was coined by Clive Humby, a UK Mathematician and architect of Tesco’s Clubcard who stated:
“Data is the new oil. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.”
I interpret this phrase a bit differently from most. Of course I see oil as being the fuel that powered the industrial revolution. I also see oil as being relatively rare and hard to get at. Its rarity and its ability to be transformed into both energy that powers our world and products we consume underscore its value.
However, I see oil as a catalyst of innovation rather than simply a natural resource that acts as the raw material for our vehicles and lifestyle. Like it or not, our use of oil has enabled us to reshaped our planet and human civilization more in the past 150 years than in all human history combined. The byproduct of oil isn’t just energy or materials — it is the ability to dramatically increase the rate of innovation and change, and that’s exactly what data also is enabling today, and how I see data relating to oil. Only data can be the catalytic agent for the next, more expansive, era of human expression.
Evolving Uses of Data
Data isn’t new. We’ve relied on data for a very long time — even longer than oil. The insurance industry, for example, is one segment that has relied upon data and statistics to drive its entire business for a very long time. How does an insurance company know how to insure an asset or a piece of property? Quite simply, with a whole lot of data and statistical analysis. The more data, the more accurate the statistics, the less risk an insurance company has of losing money.
Our use of data, interestingly, has shifted from helping us understand the past to be able to predict the future to that of using data to _manifest_ the future we desire.
Data as Oil in Marketing
Marketing is a great example of a field that has come to rely upon data to influence human behaviors. In the good old days, marketing focused on basic advertising via billboards and print advertising — employing wit and graphic design to capture the attention of a potential buyer in the hopes of influencing sales. Early Coca-Cola advertising is an excellent example of this. It wasn’t too long before marketing executives realized how much more power data gave them to help make their efforts much more effective. Ever wonder why you have a customer loyalty card from your local grocery chain? Hint: It isn’t to save you money to make you happy. Loyalty cards exist so that the grocery chains can access your buying patterns to increase the effectiveness of supplying and selling goods. Target, for example, used data analytics to find items statistically bought together and placed them next to other impulse buy items to show you items you might want, while you are buying items you might need.
Used in this way, data was not just consumed to create fancy reports (for example: “what were last quarter’s sales numbers?”) but to predict and even manipulate future outcomes. Today, digital marketing relies upon apps and websites that track your every click to ensure marketing teams have the data needed to analyze the effectiveness of their efforts. Marketing teams run experiments with online marketing assets, such as producing multiple versions of a website to measure the effectiveness of each variant (something called A/B testing), and using the resulting data to influence the behavior of customers to get better results (… to sell more).
Data as Oil in Software
A little closer to home, another great example of customer focused data mining is found in the software industry. Once upon a time software teams spent huge amounts of effort performing “business analysis” that resulted in binders full of requirements that would eventually get translated into software (poorly). We, in the world of software, spent months writing specifications because it seemed wasteful to “get it wrong” — if we could just think of everything we needed ahead of time then build the software, we’d reduce waste, right? The way we develop software today is much different. Modern software engineering teams don’t spend time completely designing software. They release software in little pieces as if each piece was an experiment. Software teams monitor every aspect of their software, from how the software uses computing resources to how users interact with the software. This data is then continually fed back into the future designs and subsequent software releases. In this way, operational data produced by a running application would help determine the future of that piece of software by helping software teams to dial into value in real-time. We call this mindset of development “DevOps.” I simply call it the best way to deliver value to customers through software since it helps to minimize the guesswork of software requirements.
Data as Oil in Manufacturing
Today, similar techniques are emerging throughout manufacturing and is commonly referred to as Manufacturing 4.0 or Data-Driven product lifecycle; a model almost identical to DevOps in software. This is a completely reconsidered model of manufacturing that leverages data at every stage of a product’s manufacturing cycle. Manufacturing 4.0 employs data captured by sensors during the manufacturing process as well as data captured by sensors once the product is in production to help continually tune and adapt both the manufacturing process and the product itself. Tesla’s manufacturing processes and its vehicles are a shining and commonly referred to example of this new way of thinking. Data is central to this new model so that manufacturers can more readily respond to the demands of shorter delivery times, volatile markets, 24/7 service, shorter product lifecycle, and more individualization.
The Refinement of Data
In a sense, data is a raw material, as Huby describes in his quote. Data must be transformed to produce value. What data can get transformed into can yet again be combined with other “raw materials” in even new ways.
Data, however, isn’t like oil in many ways. Data accumulates and is exponential. The more data we have, the more data we produce. Oil depletes. Data can be shared without creating a loss or a cost. Data can easily be consumed by others without impacting supply, unlike oil which has a single path of consumption and of usefulness.
The data I speak of is the same data that powers our traditional business dashboards and pie charts — and can now act as the fuel for other emerging technology. Take machine learning as an example. Machine learning wouldn’t be possible without data. Machine learning can never get enough data in fact — the more data we feed it — the more accurate the learning. For example, machines are far better at diagnosing breast cancer (30x faster with 99% accuracy) than human doctors. Machines can do this because of the massive amounts of data we have amassed over decades used to train the computer to perform this task. Passive data, that might have sat idly on servers for decades or powered attractive graphs, now becomes a fuel for innovation and change — and yet, even after it is consumed it is never depleted.
Data as Oil — the Fuel of Modern Innovation
Unlike oil, data is something we continually produce versus extract from the ground. Modern innovation (manufacturing, traditional software, ai, etc) is now dependent upon this data. The better the data, the better the resulting innovation and impact. The companies who will survive and thrive in the future are the ones who will outlearn and out-innovate everyone else. It is no longer “survival of the fittest” but “survival of the smartest.” Data is the element that both inspires and enables this new form of rapid innovation.
Data is Innovation’s muse.
Joel Semeniuk is a founder and Chief Innovation Officer/Incubation Director at Imaginet Resources Corp., a Canadian based Microsoft Gold Partner and the #1 Small to Medium Sized Employer in Canada. Joel also served as the Executive Vice President of Innovation and Agile Project Management at Telerik. Joel has a degree in Computer Science and is also a Corporate Microsoft Regional Director (of only 13 word wide) and Previously a Microsoft Most Valued Professional in the area of Application Lifecycle Management and previously Software Architecture.
With over 20 years of experience, Joel specializes in bridging technology to business needs by applying “outside the box thinking” and passion to everything he touches across an extremely broad set of industries. Joel is globally recognized for his knowledge of Application Lifecycle Management as well as team and organizational change. Joel regularly speaks at conferences around the world on a wide range of ALM, Agile, Lean and Customer Development topics. Joel is a zealous Lean thinker, and works to apply Lean Thinking strategies to the delivery of customer value and business development.
Over the past 10 years, Joel has dedicated himself to the establishment of his unique approach to innovation and business development, drawing from Customer Development, Lean Thinking and Growth Hacking practices. Considered by his peers as an “idea hamster”, he now works exclusively in emerging and new business development/consolidation at Imaginet. Joel worked as a mentor at AcceleratorHK, Hong Kong’s most successful Startup Accelerator and Mach5 in Silicon Valley. Joel a serial entrepreneur helping to establish a number of startups.
Joel is well published, coauthoring four books and hundreds of articles over the past 20 years. Joel is also regularly engaged by industry press for quotes and insight.