Alysia Green, Chevron

An interview with the Chief Information Officer of Chevron's exploration business

 


The following is a transcript of the audio available via the player above.  The audio file is the definitive source.

Ali Tabibian:    Welcome, welcome, welcome everyone to this episode of tech cars machines. My name is Ali Tabibian. I'm with GTK partners and you can find out more about me and the firm via the links in the episode notes. Today, we have an exciting addition to our technology and machines theme. Our guest is Alysia Green who is the general manager of upstream information technology for Chevron. [00:00:30] Now in Chevron parlance that means the chief information officer for the very important upstream business. Alysia has been a friend of our firm for some time now. She's spoken at some of our conferences and I was recently a panelist at a Big Data and Analytics Conference for energy executives that Alysia was hosting in Las Vegas earlier this year. The interview itself offers a fair bit of explanation on Alysia's background and the business unit and operations of Chevron. So, I won't do what I frequently do here [00:01:00] which is provide two or three minutes of color. 

    But while I was reviewing the interview for editing I was struck. Really once again if you've listened to some of our other episodes that involve large companies how large an industrial business can be in general and specifically in the case of energy companies how geographically diverse they are and how that diversity directly shapes the careers of the executives. Compare Alysia's geographical assignments that you'll hear about in this episode. Towards very typical in my industry of finance. [00:01:30] For example Jamie Dimon who is the chief executive of JP Morgan Chase the largest bank in this country has spent his entire career in New York with a few years in Chicago and he's probably close to 15 years more tenured than Alysia. A quick few facts that demonstrate the scale point. Chevron last year had revenues of 150 billion and its recent peak was 220 billion a year of revenues in 2013 when oil prices were higher. 

    Each year the company spends [00:02:00] about 15 to 20 billion on capital expenditures and that helps it extracts ... At least last year extracted 2.7 million barrels a day of oil. Just to give you a point of comparison each of China Iran and Iraq produce about 4 million barrels a day. By the way that business of extracting oil from the ground is called the upstream operation. And these days the upstream operations are not only the big offshore or onshore operations with a single giant drill [00:02:30] going down into the earth but also a lot of short cycle high return operations which are sort of more diffuse in their number of drilling points and that's been brought about because of the progress in the world of fracking. The business of actually selling the fuel and other petroleum products is called the downstream business just in case you hear the term during the podcast episode. Without further ado, here's Elysia Green general manager of Upstream Information Technology at Chevron.

GTK Announcer:    Tech, cars, machines. [00:03:00] Subscribe here or at gtkpartners.com.

Ali Tabibian:    Alysia Green, thank you so much for agreeing to be on our podcast today. We really appreciate your time. 

Alysia Green:    Happy to be here. 

Ali Tabibian:    Great. And today we're actually in San Ramon which is Chevron's headquarters just north of San Francisco. You used to be here for a few years I think and then you left the sun went to Houston. And so I'm happy that we managed to catch you on a day when you're back, back at headquarters. Alysia maybe give us a little bit of your personal history. [00:03:30] I sort of joked around with you a little while ago that you've got a unique for these days LinkedIn profile with one company name on it. So give us a sense of what that means because I know this is much more than really one company, one logo. 

Alysia Green:    Yeah I know. Very true. So I have been with Chevron just about 27 years which is a bit unheard of these days. I've had many different roles in the company so I started with the company right out of school and in programming and [00:04:00] was in the downstream piece of our business. And that piece is defined as the part that goes for manufacturing plants through our terminals into our gas stations. And so I have responsibility for supporting various applications and scheduling, areas scheduling vessels and pipelines with refined product. And so I've done numerous IT type roles, programming, project management, business analysis. [00:04:30] I've also done business roles have been, refined Products scheduler, been a business development and planning manager and then really spanned the entirety of our value chain. 

    So from downstream to midstream to upstream our midstream really is that connection point with our pipeline company power and shipping company. And then the upstream is where we look for find and then produce oil and gas. And [00:05:00] I have moved around quite a bit so I started here in California. Then in Houston in New Orleans in Bangkok. Now like on my second loop. So I was just previously I was in California and now I've just since the beginning of year have moved to Houston. 

Ali Tabibian:    You've already give us a little bit of the upstream midstream downstream designations. Take us a little bit further into the asset and geographic scopes and the personnel and activities of your current [00:05:30] responsibilities. 

Alysia Green:    Yeah so my current responsibility. I am a General Manager of IT for upstream business and as I said that's the part that looks for finds in it and produces oil and gas. And so we have business units around the world. We have four different regions. We have a North America region, we have an Africa Latin America region, Asia Pacific and Europe Eurasia and Middle East. And so the way that it's organized [00:06:00] is geographical. And so each of those business units is doing that upstream business. But just in a different basin and so you have both geographical difference as well as geologic difference. So it's whether our operations are what we call onshore like you'd have like in the San Joaquin Valley here in Southern California. Or it could be offshore like we have in the Gulf of Thailand in Bangkok. And so [00:06:30] there are various functional disciplines, we've got drilling disciplines, We have the geological disciplines, operational disciplines. So the similar functional disciplines that are in those business units they just keep carried out in Various location and also geopolitical differences as well across the world. And so then there are the IT that's associated with all of those varying business units. I have the responsibility [00:07:00] for the oversight.

Ali Tabibian:    On a global basis.

Alysia Green:    On a global basis.

Ali Tabibian:    And GM of IT, I think is the way you ... The phrase you use that. Is that equivalent to what other companies will call a CIO for the upstream business? 

Alysia Green:    That is correct. So I had piers you know for downstream and then the midstream area. And we have a portfolio, we know as we look at our overall portfolio from a Chevron perspective. We are in different bases the pitch for different basins different asset class. And so there's a strategic look that we [00:07:30] take to determine what the investment is in each of those areas. And so we don't invest evenly across. But we do have a what we consider to be a very advantaged and diverse portfolio.

Ali Tabibian:    What are the revenues or the capital spending of the upstream business? How many employees you have that work for you? What is the capital that's deployed when you go [00:08:00] build an offshore platform or onshore facility. Just kind wow us a bit Elysia with those numbers. Whatever is available off the top of your head. 

Alysia Green:    Yeah. So I guess yes. From a scale size from upstream perspective yeah. We spend ... And this is just total not an IT. Total kind of capital spend where we are right now is probably in the ... It kind like the high teens of the billions. [00:08:30] Just kind of leave it there.

Ali Tabibian:    Yeah, That's right.

Alysia Green:    And that's per year. So yes. And from IT standpoint. I think there's probably about somewhere in the probably 1000 to 1200 range of IT employees that have crossed the world that are working on upstream. [00:09:00] And you talked about ... Yeah, our upstream projects are long term projects. And so again our what we call our major capital projects, they are again if you're talking about the life of the major capital project, can range anywhere from 10 to 40 billion dollars. And then over. And it takes a while, some of the stuff it is ... I mean it's an engineering feat, go [00:09:30] put a offshore platform out 100 miles out I'd say or more. In the Gulf of Mexico, in 7000 feet of water. And then drill down even more thousands of feet. And so that that takes a little while. 

    And so when you talk about our projects from, we talk on them from our exploration all the way through to veto. It being [00:10:00] on production that could potentially be a decade. 

Ali Tabibian:    Wow that's incredible. And it's interesting because people typically in Europe Chevron's been a public company for a long long time and people like to ... There's a trope that public companies are short term oriented, every quarter. And it's just not the case for a very large number of the businesses out there and Chevron and oil and gas is a great example of what the durations are. 

Alysia Green:    Well. We do have  a bit more of a diversified portfolio now. It's what we talk about with the [00:10:30] unconventional. So the unconventional much more of short cycle. And so we have put that into our portfolio. So we do have the short cycle. And then it balances with these longer cycle. 

Ali Tabibian:    Great. And then from an IT perspective especially since you've been in other parts of the business as well. Does the IT associated with the upstream business have a particular character that you can give it or is it so diverse that you've got a little bit of everything in [00:11:00] the I.T. infrastructure? Or is there a little bit different from what it would be let's say for the pipeline business? 

Alysia Green:    I think that the true infrastructure is quite similar. We talk about being able to have connectivity, the difference between having say connectivity in office versus in a field location that field location connectivity is very similar whether you're an upstream midstream or downstream. Because where we operate are usually in places that don't necessarily have a lot [00:11:30] of connectivity because you're not necessarily near people. So in that way that piece is similar I think where you get into that variety would be more in the application space. And the applications that are supporting the different functions. And so the functions are quite different with an upstream versus a downstream or midstream. Some are similar. But say for instance the geological function that is very specific to upstream and so the type [00:12:00] of IT applications there are really helping our geo scientists really Interpret seismic imaging so that we can find where there is oil and gas. And so it's a marrying a very complex like geophysical models with visualization techniques some in 3D to really help those geo [00:12:30] scientists do their work in analysis, would be one example. 

Ali Tabibian:    Okay great. Now for in my mind's when I think about let's say that downstream business which helps, kind of say is the part that kind of gets you to the gas stations. That as you mention is essentially the whole point of it is getting to the oil to where the population is. Therefore connectivity all these things are available of electricity even right is a little bit more easier to come by. But a lot of your assets presumably people are drilling for oil in the middle of Manhattan. So [00:13:00] you start with essentially building all your own infrastructure literally from the ground up. And so that's pretty ... That's one of the interesting things we'll keep in mind as we go along here that you do deal with a lot of. When things like connectivity and power are scarce or at least expensive it makes people think a lot differently about how much sense or how much information and where do you where do you call the information before you have before you start transmitting with that, would be interesting [crosstalk 00:13:27]

Alysia Green:    Yes, yes. Well and it becomes an enabler to that. Or [00:13:30] a barrier to being able to do something about that. But if you're out kind of in a remote location and you do not have the connectivity then how do you get some of that the sensor data actually back to say the mother ship. 

Ali Tabibian:    Right. Right. And I think another interesting thing that if I recall correctly from the exploration side which is a part of the upstream businesses, is that unlike a lot of other [00:14:00] assets operating assets which generate essentially time series data every now that they report something. The sonograms essentially that they perform generates staggering amounts of information episodically and instantaneously when they do the site. Is that still the case?

Alysia Green:    That is still the case. So very large data sets. We ... Terabytes, petabytes and very graphically intensive. And so the need to have high performance computing [00:14:30] to allow the analysis of that dense data is very much something that is a necessity. And that we've worked overtime. 

Ali Tabibian:    Well, supposing so far for, your portfolio essentially is satisfy that scientist who wants to crunch petabyte of data instantaneously. Needless to say versus somebody on the operating side who basically wants a few bits of information that tells them whether. I'm exaggerating or conveyor belt is about [00:15:00] to break. 

Alysia Green:    Yes yes yes. So there is definitely diversity in the range yes. 

Ali Tabibian:    Okay great. Alysia one of the things when we've had a couple represents from Chevron speak at our conferences over the last few years, that always striking to me is how much the word safety shows up immediately when you ask about the objectives. So talk to us a little bit about the integration of the IT infrastructure, the interaction of the IT infrastructure with safety and then sort of other so compliance related items whatever you find interesting. 

Alysia Green:    [00:15:30] Yeah I think in our industry safety is the first and foremost value that we have. We take it very seriously that we want to protect not only our employees and contractors who are doing the work for Chevron also making sure that we are operating in a way that protects the environment [00:16:00] and the communities where we work. So we are very methodical when it comes to that and I'd say the use of IT to help, create, safeguards to ensure that we do not have incidents. Is that's kind of the key, is how do we have things that we'll have sensors to [00:16:30] ensure we understand. You said before how equipment is operating or to do ... To detect if there are any emissions. And then so that we can take immediate action. But mainly to prevent those types of things. 

    So that is something that we look at. So whether it's Howard designing you know say a facility that we're first putting it up to make sure that it's designed [00:17:00] robustly and we have automation to ensure that we have those safeguards in place. Or it's story of the maintenance and say folks are doing maintenance activities that that's automated and they actually understand kind of, What are the steps that they should take to perform maintenance in a quality and safe way. So there's a couple of examples but that's something we have a very large [00:17:30] health environment and safety group and so then there's IT components, to that to ensure that we do that in a quality way. IT can help bring more knowledge into the field. 

    For instance say if you think about from a digitization standpoint instead of having the operating manual be an actual like physical manual how do you give a person out in the field a handheld where they can easily go [00:18:00] through and understand what it is there they are working on. Or being able to have say like remote experts. So if there is a area that they're not as familiar with that in some ways you could phone a friend utilizing various devices to be able to have somebody kind of see what you see and then to be virtually giving you kind of consulting advice. So [00:18:30] it's more that we do not see it as a degradation that we're automating and people don't know what's being automated. It is to get the information into the hands of the fieldworker. 

Ali Tabibian:    Interesting. So it's a fairly conservative in terms of impacting the workflow but you're trying to make that work for existing workflows as [inaudible 00:18:48] as possible. Then just given the life safety impact of what happens. [crosstalk 00:18:52] 

Alysia Green:    Yeah. We have to have knowledgeable trained experienced employees that are out in the [00:19:00] field that will not change. We may automate some things but then you will still have that experienced worker. And it's just how do you make that experienced worker even more effective by giving them the information they need at their fingertips so that they can then do a quality and efficient job. But quality safety comes first over anything. So we're not going to look at efficiency [00:19:30] at the detriment of safety. 

Ali Tabibian:    After safety. How do you view the IT organization? Is it more about efficiency essentially improving processes and controlling costs. Or is there a revenue driving component to the IT organization as well. In other words are you extracting the data and saying you guys and marketing whatever you want to should be doing something differently? 

Alysia Green:    I believe there's both. And the way that we look at it the efficiency [00:20:00] piece really is focused on the IT assets that we run. So those IT assets how can we run them as efficiently as possible. I think the revenue generating is on the innovation. And so it is in those pieces of what I talked about of being able to get information into the hands of whatever worker it is and to make them more intelligent. Then that [00:20:30] drives better decisions which should ultimately lead to revenue. So it is a bit of a buy model. We do want to make sure that when we build IT tools that we're building them as efficiently as possible. We're running them as efficiently as possible. But the innovation comes from the tools that we're building. What is that enabling. How is that helping the company to generate cash or earnings. [00:21:00] Those focus have to be there. And we have to be disciplined right, So you don't, we don't want to have when you think about that the overall kind of IT budget we have to run it as a business as well. Right.

    And so we need to look at our base business of the running of these assets and making sure that hey how are there more efficient ways like what automation can we put in safer patching of servers. Or for doing upgrades like just life cycle upgrades and [00:21:30] applications. Like that's the piece where we look to get efficiency and then from the innovation standpoint it's really having our IT professionals really understanding the business areas that they are supporting and then being able to make the recommendations for the various solutions that we could deliver to help drive the business strategy of that area. 

Ali Tabibian:    So one interesting thing that we talked about last time we saw each other, it's movement into unconventional [00:22:00] for Chevron had actually been a very exciting avenue for deployment of tough technologies that you manage. Maybe talk to us a little bit about what is unconventional? What is the Permian Basin? 

Alysia Green:    As I talked about before, there are different kind of basins where we operate and then different asset classes and the unconventional is one of those asset classes. And the Permian Basin is a place in the middle of kind of the country [00:22:30] here in the U.S. and we have a very large acreage position there. And we're one of the I think amongst the super majors, we have the largest kind of acreage position and so our competitors are more independents, they're smaller they're nimble. And so. It has caused us to think differently about as a large company how do we compete in that one area. And technology both information technology [00:23:00] as well as other types of technology have played a great portion whether it's here for us. There is drilling technology there's reservoir technology but then there's also information technology. How do we bring all of that together to ensure that we can be successful there. And with these unconventional as we call it, there's a term called the factory model and it's where you're drilling quite a bit kind of [00:23:30] in series. And so you have to have speed of learning. And so as you're drilling a well need to understand was that well successful was it not how much that cost and then that learning needs to go very quickly to the next one. 

    And so again being able to pull together all that information getting it back into the right folks hands whether it's the drilling engineer or the operations or the reservoir management so that they can understand what is it that is either going well or that could be [00:24:00] improved so that they can then bake those learnings into the next one. And because it's a factory and you're kind of drilling in pretty rapid succession the speed to which you do that analysis and make those decisions is crucial. And so it's a different one. Like where before where we're talking about the crunching of this massive seismic data for the geological space that's computing power. This one is just more of how do I combine information [00:24:30] more quickly. So the information's always been out there but the ability to actually combine it to present that to our engineers as opposed to them having to go look for it, combine it on their own, massage it and then by the time they do the analysis that data is old and then we've probably also missed the opportunity on a number of wells to actually inflate. 

    So that's I think that's really been the big [00:25:00] thing because the margins are quite tight and so you really look at both your operating costs as well as the production. And we obviously want the operating costs to go down and we'd like our production to come up and then you are able to affect the margins. 

Ali Tabibian:    So in a conventional environment kind of what the image a lot of people I think would have in their mind is there's a lot of imagery work et cetera. To find this one big deposit one there's one [00:25:30] big container under the ground essentially and you basically drill once into it and then you suck everything out and then you're done. And it's, I'm simplifying. But it's sort of find once, straw once, extract for, I don't know 10, 20 years and then you're done and then you got to move on. But it seems like in the Permian Basin where you're basically drilling ... Where the oil I'm assuming is more diffuse through the entire area. So you basically are trying to find the right concentrations as you go along and drill in the right-

Alysia Green:    And [00:26:00] the pace. 

Ali Tabibian:    And the pace. I see. Interesting. So you're competing with the what in the old movies they used to call wildcatter or something like that. 

Alysia Green:    But there's actually and it's been quite interesting. I think there's been a bit of a digital war as well. I mean if anybody can go out and Google the Permian Basin and you will see that technology is being brought to bear. It's kind of a bit of a technology war that's happening and it's quite fascinating.

Ali Tabibian:    What do you mean by that?

Alysia Green:    Well and so [00:26:30] the other wildcatters are ... Yeah they're not just going by intuition they're using technology as well. And so it is that pace, it is how you implement and utilize the technology is also a big thing about winning in these unconventional spaces. So and it is different technology. We ... Our industry sometimes get a bad rap that we're kind of old slow and like not very technologically advanced. I mean [00:27:00] we've been using technology for many many many decades very complex technologies, like I said for us technology means much broader the various drilling technologies. We couldn't drill some of these wells either in the unconventional or the conventional without very advanced technology. The imaging that we do with our seismic wouldn't be able to find this oil and gas without a lot of that technology. But for us it's now the merger [00:27:30] of the technologies of what we'd call the petro technical technologies with the information technology merging that together to really be able to have scale and pace. 

Ali Tabibian:    So what people I guess frequently refer to as IT, and OT, right the end information and operational technology. let's say [inaudible 00:27:50] has to do something to particular location of our Permian Basin. To what extent does the choice of the equipment they make influenced by you saying that's great equipment [00:28:00] we can process, it doesn't have the right data, it doesn't give us the right data, it's hard to connect to, is there interaction like that?

Alysia Green:    Not quite that because again if I go back to with what I was saying about the history of our industry. Our equipment, We've had sensors on our equipment.

Ali Tabibian:    Forever. 

Alysia Green:    Forever. And so when you think about kind of the Interactive things are desiderative things, whatever you want to call it. In a lot of other industries. It's about getting the sensors there [00:28:30] for us it's been more that we've had the sensors there forever. It's just how do we actually connect. As you were saying that OT to the IT or like our operational network to our business network. Because we have been again from a safety standpoint again. We have always had a demarcation separation. Because our operations network is hard and in a very different way. [00:29:00] In the past have been hard in a very different way than our business network and we've kept it separated. And now it's how do we bring the two together. And that data together and a safe, secure, and speedy way. That's what I'd referred to before in the past it's been yeah the data is there. We've had a lot of data. The data comes across, kind of gets dumped somewhere and then it's [00:29:30] been our engineers who instead of doing the analysis they're doing data manipulation.

Ali Tabibian:    I see.

Alysia Green:    And so it's really how do we turn that data into valuable information automatically and not have our engineers doing that manually. So that's been the big thing for us between the kind of the combination of the IT and the OT. 

Ali Tabibian:    Interesting, interesting. It is fascinating at the conference in Vegas that we were [00:30:00] together a few weeks ago when I was preparing for it. It really struck me that in the last 20 years whenever the word data has come up data warehouse all the way through big data AI et cetera, no matter what generation you're talking about 90% of the effort is just trying to get the data cleaned up, in the right place, connected with each other. The people even understand what we were measuring when we collected data. 

Alysia Green:    Exactly.

Ali Tabibian:    And then there's that tiny little bit that comes in at the end where somebody actually gleans it inside. It sounds like it's [00:30:30] still substantially a big part of the challenge.

Alysia Green:    Now definitely. And as you said we've had these sensors that O.T. out there. So we've been collecting data forever but it's like how much of it have we've been using. And so that's really where we're at now is like let's actually use more of this and then it is the connection of data. So again connecting say the drilling data that's coming off the drill bit with financial or procurement data. [00:31:00] To again be able to make those analytical decisions. In the past where we actually using all of the data coming off of the drill bit, probably not. And then we're combining it maybe or maybe not. But it is the insights and that's what I mean about providing the ability for our workforce to be more intelligent because it's like let's have the engineer do the job that we hired the engineer for, which is analyzing [00:31:30] and designing. We really don't want our engineers spending time looking for finding and massaging data like that. That is not the high order of skills. That's a low level task. Like, so how can we let the computer do that for them and then get them to the higher order of the work that they were trained for. 

Ali Tabibian:    And you know what's interesting too is a lot of the Artificial Intelligence concepts that we come across. [00:32:00] What's fascinating there is a couple of different ways they're doing it but when you look into under the hood, quite a few of them are really what they're really doing is cross application data integration. 

Alysia Green:    When you think of artificial intelligence of truly mimicking the brain. I mean we're not there because we don't even understand how our own brains work. And I think once we get that I think that's when you'll get more towards I guess the [00:32:30] true definition of artificial intelligence. That's why I've said several times that I do think that really when we talk about artificial intelligence now. It's more about how do you make your worker more intelligent. How do you let the computer do a lot of this combining and so that you give the information in the way that the worker can consume it and it makes them more intelligent. So that is you are artificially increasing their intelligence. I mean that's the way [00:33:00] that I kind of think about it. 

Ali Tabibian:    So it's an enhancement of human intelligence rather messily replacement.

Alysia Green:    Yes, Exactly.

Ali Tabibian:    It's interesting because I think that's a very insightful way of describing it in the sense that it ties to what works. What we've seen works in these startups and some of these other entities which is the following. Whoever the vendor is better understand the workflow extremely well because otherwise you're just burning up compute power and delivering once again a bunch of data to people. What part of it is more [00:33:30] than that when you're trying to make your Intel work or more intelligent. Is it also trying to suggest things they wouldn't have thought about even doing before. Is that where you're trying to push it as well right now?

Alysia Green:    Now, that's correct. And while because it's those insights because some of the things when you combine say data sets that have never been combined before. You're not exactly sure what results you're going to get out. And so you know you look at this combined data and you start you potentially start thinking in a different [00:34:00] way and perhaps that actually transforms that workflow. And so I think that's also the trick as well is how do you work in an environment that really fosters that innovation and that you may or may not know what the end answer is going to be. But let's see what insights we get and let the insights kind of guide you towards what the transformation is. 

Ali Tabibian:    You know what's really fascinating about that [00:34:30] answer Alysia is a few years ago when we started our IoT conference, most organizations would say you know what we want to have a specific question we're trying to answer that we're not going to really pay for discovery. But the Percentages are changing. There are more organizations are saying you know what maybe we will. Obviously not in an  unbounded fashion but in a much more expansive fashion than we used to. See maybe on an unsupervised basis essentially [00:35:00] whether the application of some of these data analysis techniques can point to trends and features and clustering in the data that we hadn't really bothered even looking for before. Is that something you see yourself and your organization as well? 

Alysia Green:    Yeah I think the key to what you said is it's not unbounded there. There is an area that we are exploring. I think what you mentioned it's being open for the secondary or tertiary insight that you get out of that. That kind of the area, so leaving [00:35:30] it open a bit not having it your aperture so narrow that you're only answering this very narrow question. But you do have to understand kind of what space you're working in and so that's kind of a I guess path that we've been following. 

Ali Tabibian:    I'm sure you get solicited a lot by vendors, traditional or new that say "We've got AI got ML supervised unsupervised." All these stuff. What does that mean to you? What's been exciting? Somebody who's listening to the startup who is into [00:36:00] this podcast from a startup as a venture investor would like to sell stuff to you just what actually from your experience seems to be working?

Alysia Green:    Well you mentioned a bit ago. It is really the understanding of the workflow. And so to get anybody that's out there listening I think doing some research on our industry and really understanding kind of what are some of our challenges. And having [00:36:30] those maybe even the fresh eyes looking at access to a bus was one thing that we do is how do you potentially look outside of our industry to other industries to some learnings that they've had and how can you bring it back. I think there have been some of the interesting things. Because you have to get out of your own head. But I also think on the flip side of that for folks that are trying to sell into our industry you do have to learn a bit about our industry but you can come in with those fresh eyes [00:37:00] and say "Hey did you think about this and this." We could have a blind spot there that we weren't. 

    And so for us we definitely have an R and D arm within Chevron. And so we have folks that are out researching there. There are problems that we can't solve. And so we're looking to partner with others to help us solve those problems and then bring that kind of back in to the larger organization to see where [00:37:30] it's applicable. And so that works really well because we have kind of like their internal consultants right. 

    And I think the piece that makes them very effective is that they do understand the different parts of our value chain. And then there are mechanisms for having the feedback on areas where we would really like to be able to do this but we can't right now. And the can't maybe from a technical standpoint it also could be from a commercial standpoint and can technology [00:38:00] help with the commerciality of a specific thing that we're trying to do because the current technology It's hey that's funny. Yeah I could go and get that oil and gas or I could manufacture X Y and Z. But commercially it just doesn't make sense. And so then what can technology you bring to bear to change even the commercial outcome.

Ali Tabibian:    Right. Now in health care for example. They realize that going to people [00:38:30] who are developed natural language processing technologies for the smartphone environment do much better than their current vendors are trying to come at it from inside the healthcare industry. So that's probably a number of example-

Alysia Green:    Similar type of things.

Ali Tabibian:    Similar type of thing for you. What in the end would you like us to add or focus on. 

Alysia Green:    Well I think what I would end with is really understanding that our industry is quite exciting and the value that we provide to the world [00:39:00] is immense. We do it in a very safe and ethical manner. And I do think that sometimes folks that are looking for industries to work in specifically in IT do not think of the energy industry to work in. The again, the scale and the scope of things that you could work on in our industry are massive. As I said the impact [00:39:30] the positive impact that you can have to the world. There's some parts of the world we don't even have they don't even have access to an energy. And so being able to be part of helping a country move from third world into first world. I mean that's real human impact and the things that we're doing now. This combination of the OT and the IT it's just [00:40:00] fascinating and exciting time to be in IT in this company. 

    And not only the scale and scope as we talked about. Then if you like to travel go around there as I said we have operations all over the world. And so, which is why I've stayed with the company so long. I mean I've been here for the 27 years I've had I think I'm on my 13th or 14th different role and those roles [00:40:30] have differed from a technology standpoint. They've differed from the value chain standpoint and they've also differed from the geographic standpoint. And so all of those things I think make for very exciting meaningful and impactful work. So hopefully I'll dig in a bit more to our industry those and of you that have startups that you'll learn more about us and maybe call us up and see if we can partner together. And those of you that might be looking for a career change [00:41:00] think about coming into the energy industry. 

Ali Tabibian:    Great thank you so much we really appreciate all the time and all the insights. 

Alysia Green:    Well thank you. I really enjoyed our conversation. 

Ali Tabibian:    All right thank you. Bye bye. 

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