The Internet of Things (IoT) is here. Everybody knows this by now. Our estimates, recently updated, put the overall impact of IoT at 6% of the total global economy by the year 2020, with more than $370 billion in additional IoT revenues alone. What no one knows, however, is how this value is going to be realized and distributed, and where specifically it will come from. While there are many places where IoT can make a real impact, the asset-intensive industries are a prime candidate. O&G, with more than $700 billion in annual capital expenditures, is at the top of the list.
It is not just capital expenditures and capital intensity that make IoT and other digital technologies the true future of the industry. A few other factors play a role. The industry is more and more technologically advanced, yet still informationally poor. With assets distributed remotely and globally, core extraction, distribution, and refining processes highly data dependent, pricing extremely volatile; new sources having fundamentally different business models (shale); and human errors exceedingly costly, only the enterprises that find a systemic way to become smarter in how they operate are going to win.
In fact, the industry has recognized this imperative and has acted on it. The number of M2M-connected devices in the industry has grown close to five-fold in the last five years. Big data, smart machines, advanced analytics, and modeling have become four of the top ten trends, and investments in these digital and IoT technologies are expected to increase by 30% in the next three to five years. Yet, as Cisco recently reported, only half of the companies in the industry leverage data for effective decision making; fewer than one-third can deliver the right information to the right place in a timely manner; fewer than one-fifth are connecting people in more relevant and value-added ways; and only one in 14 companies is integrating the right equipment, devices, and machines to capture materially useful data. While unit costs continue to fall in many industries—by more than 30% in sensors, 25% in bandwidth, 33% in computing, and close to 40% in storage—O&G costs continue to rise, with the real cost of extracting a marginal barrel of oil increasing by 75% in recent years.
One wonders why. Arguments around sources becoming inherently more expensive (deeper, more aggressive environments; more source rock resources) offer only part of the explanation. Investments are not being made effectively and efficiently in terms of tapping into available and emerging IoT and information technologies. The way we see it, the industry has become really smart, but not yet truly intelligent. This is especially true in data usage, as opposed to data gathering.
What does this mean? Take a look at figure 1.
In taking advantage of IoT and other information technologies, the industry has thus far stayed close to what is comfortable: largely standard capabilities within individual functional domains. It is certainly easier to implement within the regular organizational and budgetary constraints, and there is no question that such an approach has delivered value. However, the real value resides outside of that space, in using more intelligent, connected systems that cover a broader scope of activities and decisions, and tap into and use more granular, more frequent, higher-velocity data.
Why hasn’t the industry moved faster or more aggressively in that direction? We think there are two reasons. First, there is a real inherent technological and business complexity that needs to be addressed. The volumes, variety, and velocity of data that need to be pulled together to enable such an intelligence is not a trivial challenge to overcome. But there is a second, more important reason: the inherent risk aversion that drives decisions and actions within most of the industry. The real barrier is the inherent belief that nothing beats human experience, wisdom, and judgement for dealing with both real and perceived risks—which leads to a reluctance to embrace more automated, intelligent, solutions.
While this risk aversion is understandable, it is unfortunate. It stands in the way of innovation, experimentation, and advancement. As many industries are embracing IoT, connectivity, data, analytics, and artificial intelligence (AI) in comprehensive and novel ways, they are changing the way they do business. There is a reason that most major enterprises are investing in IoT and that a group of technology luminaries recently invested $1 billion in AI. From autonomous cars to smart cities to digital manufacturing, the strides made in just the last couple of years in other industries are transformational. Even the national pastime, football, is starting to experiment with AI. Just recently, on Nov 8, as described in the Sports Illustrated magazine, an AI engine was able to perfectly forecast the next play in a Falcons game. When fully deployed such a capability will fundamentally change the game. While O&G is no football, the same opportunity to fundamentally change the game exists in O&G, to marry expanding IoT technologies and emerging AI for real breakthroughs in costs, performance, and risks.
Figure 2 shows several examples; with imagination and intelligent risk-taking, this list of opportunities could be expanded exponentially.
We understand that this journey will require a different mentality, a different approach to innovation, and different tolerance for risk. Regardless, we are convinced it is a journey worth taking. Or, put another way, it is a journey that will separate the winners from the rest. Which camp would you rather be in?