Pick up tonight with oil and gas and agriculture, and then we'll move into operating systems in AutoSys. Here's what the market research folks had to say about the oil and gas segment, "IoT-based technology solutions and related services are being increasingly implemented in the oil and gas application. The solutions are primarily aimed at achieving convergence of machines and intelligent data to enhance the operational efficiency, it's that term yet again, targets being set by energy companies. The solutions also improved the analytics-based decision making by diminishing the threats and vulnerabilities of the market, I think I've added that oil and gas market, by the use of efficient tools and techniques. Benefits include increase in overall operational efficiency, cost-cutting, optimization of supply chain, diminishing the energy trading risk factors, data privacy and security of all affiliated industries spanning across the entire energy industry value chain". So, here's some info on their expectations in this segment. Again, you can see platforms, software solutions, and services is gigantic in relationship to revenue for hardware. They've got the projection out to 2022 at almost $91 billion, US, and the hardware comes in at 0.79. So, again, another opportunity for tremendous growth. So, here are those similar graphs that we saw on Tuesday. Software Solutions poised to grow quite a bit from 2016 to 2022. Services growing percentagewise by the highest compound annual growth rate, and platform is relatively small. I'm somewhat surprised by this, because of the importance of the platform that pulls everything together. I'm not necessarily sure I agree with that assessment. They took a look at the various sensors used in the oil and gas level sensors. Think about petroleum products being pumped out of the ground and shipped and stored in containers, and so forth. So, it makes sense that level sensors would play an important part, but also flow sensors are important. Temperature sensors, pressure sensors, those are the key ones. The machines are talking and they're telling us what they know. They're analyzing and interpreting data like never before. The machines are talking. They're finding new ways to share information and streamline processes. They're empowering people to make better and faster and safer decisions. The machines are talking. They're connecting to plantwise systems to determine what a problem is, what caused it and how to fix it. The Industrial Internet for us is really, we talk about it as being really the next big revolution. It's the industrial worlds colliding with the other worlds. But I think for us, it's really just as much about us transforming ourselves from an infrastructure company to a company that's really centered around customer intimacy and driving outcomes for our customers in the oil and gas industry. I would say ultimately it has three key pillars. The first pillar is around smart sensors which GE has the ability to provide. It's around big data analytics. Then, it's how you take all of our years of deep domain knowledge and expertise, and marry those three things together to drive better outcomes, more production optimizations, more uptime for our customers. Predictivity is a brand of solutions that our teams are creating on top of predicts, which is the industrial Internet platform. Predictivity solutions are modular, scalable, centered around driving value across oil and gas value chain. I'm going to give you a funny answer, and that's how I talk to people when they're like, "Predictivity. I'm not sure I know what that means." If productivity and reliability got together and had a baby, you get to this Predictivity thing that we're building. I think those are really the key hallmarks and the tenants of what predictivity is. Ultimately for me, predictivity is about how you partner with your customers to procreate solutions, help them drive solutions to problems that really matter to them. I think it's a different approach for the company and that we used to be in this space where we would go off and build, as an equipment company and come back three years later with a big to die moment in the market [inaudible] what we've done. I think what excites me about Predictivity is, GE is becoming an entrepreneurial company. We're in a space where we are now thinking about not perfection, but iteration. How do we really iterate with our customers, in solving real-time problems in very quick, fast ways. Yeah. The benefits are going to be massive for our customers in the oil and gas industry. They're facing unprecedented challenges having to go further offshore, deeper beneath the sea level, to go after hydrocarbon resources. As a result, you're seeing an unprecedented amount of spend in the industry. Our industry stands to get about just over a trillion dollars in capital expenditure this year, and it's not slowing down. Every year. A trillion dollars every year. So, when you think about, as a company, what we're doing to really center our solutions around the customer's asset, which is the hydrocarbon coming out of the ground, and moving away from us centering our solutions around the GE asset, which is really the core equipment that we supply into our customer base, if we can do this successfully and in partnership with both customers and ecosystem providers. There's also a value proposition around how we help our customers be better at what they do. So, Dan talked about the deeper, more harsher environment incredibly capitally-intensive. When we look at the major international oil companies, as recently as 10 years ago, they were spending about 60-70 percent of their free operating cash flow on big projects. The reality is, because these things have become so much more expensive, they're spending about 95 percent of their free operating cash flow on big projects. Those of us who are in the business world know that cash buys you freedom. Cash gives you the ability to do things. I think our customers are the real inflection point where they have got to figure out how to drive more productivity, not just on their plans that they have today, but on the projects that are to come. By being able to look inside across fleets of assets, by being able to take those things and package those and provide them to our customers. We're really at an interesting place to not only help the revenue generation making the number side of the business, but the cash and the health of the industry side of the business, which is just a really exciting place to be. I think what it gives for our customers is a integrated way to think about the pain points that they felt with us as a company historically, which is five different point solutions, five different screens to touch, five different backend systems, five different user experiences. It gives us the ability to really provide one integrated set of insights and a common platform that has the ability to pull in data from other places, whether it's transactional data, it's flow data, it's equipment data, and bring those insights together using Redux, to really be able to say here's how you fundamentally transform your businesses. I think the refreshing thing about this journey is we're humble about it. We've got a lot of resources that we can bring to bear. We've got tremendous expertise and talent that we're hiring into the company, but we're also reaching out and we're finding great partners throughout the supply chain in technology. I think having a platform mindset and going to market with Predicts as a platform along with those partners is ultimately going to be how we're going to be a successful industry. Absolutely. The machines are talking. They're providing data so that companies can optimize productivity. They're helping us take the problems of today and create solutions for tomorrow. The machines are talking. Here's what I learned, or heard. GE has changed themselves from manufacturing piece of equipment and now are centered around customer focus, or this intimacy with customers, driving outcomes rather than designing a big piece of equipment and just delivering it. Here are three pillars there; smart sensors, big data analytics and deep domain knowledge, oil and gas-based. You combine these three and you get this result of product optimization, you get more uptime, better efficiency, higher revenues, lower costs. Prediction and iterating predictivity. Iterating with customers. This was the big change for them, not just a single point in solution, but building integrated systems where all the data can be shared. As the woman said, there were systems where there would be customer installations where there would be five separate systems, five separate user interfaces, data couldn't be shared across. GE predicts can pull all of this together. They want to help customers get better at what they do. They want to help customers improve their revenue and their cash flow.
