In this week's Industrial Talk Podcast we're talking to Humera Malik, CEO of Canvass AI about "The Power of Data to Accelerate your Sustainability in your Industrial Operations".  Get the answers to your "Data Sustainability" questions along with Humera's unique insight on the “How” on this Industrial Talk interview! Finally, get your exclusive free access to the Industrial Academy and a series on “Why You Need To Podcast” for Greater Success in 2020. All links designed for keeping you current in this rapidly changing Industrial Market. Learn! Grow! Enjoy!

HUMERA MALIK'S CONTACT INFORMATION:

Personal LinkedIn: https://www.linkedin.com/in/humera-malik/ Company LinkedIn: https://www.linkedin.com/company/canvassai/ Company Website: https://www.canvass.io/ Twitter: https://twitter.com/CanvassAI IIoT-World:  https://iiot-world.com/

PODCAST VIDEO:

https://youtu.be/u0TPMSmVsS8

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PODCAST TRANSCRIPT:

SUMMARY KEYWORDS industry, data, ai, sustainability, industrial, mandate, assets, technologies, scott, creating, world, operations, Canvass, running, plant, workforce, malik, waste, institutionalize, carbon emission 00:04 Welcome to the industrial talk podcast with Scott MacKenzie. Scott is a passionate industry professional dedicated to transferring cutting edge industry focused innovations and trends while highlighting the men and women who keep the world moving. So put on your hard hat, grab your work boots, and let's go all right, another great day in the industrial talk world. This is your woman warm and fuzzy place for all things industrial you industry hero, we celebrate you because you are bold, brave, daring greatly. You're changing lives, you're solving problems and in essence changing. Although world about that, man, you are absolutely wonderful. And this is a no legacy thinking. So do not come to me with your legacy thinking and say, hey, it's got to get some legacy thing and don't even go there. All right, in the hot seat in the industrial talk, hot seat, we have Humera Malik. Okay. And she is the CEO of Canvass. AI. And that is spelled ca n VA s s AI, you got that? Right. And the website, the wonderful website is Canvass.io make a note of that, make a note of that. We're going to be talking on this podcast, accelerating sustainability in industrial operations and a lot more because there's gold in that data. Let's get cracking. Yep. Data. Gotta love data. Right? It's there's so much that can be done with data. And I think the bright, the future, the that whole silver lining type of thing within data is, is interesting to me, geeky ish, and love it because we don't have any issues grabbing, definitely data. Now her stat card is quite impressive out on LinkedIn. You got to reach out to her Humera Malik is the individual. And I'm telling you, she's got mad street cred. I like it, man. I like it a lot. All right, paper and pencil time. The first one out of the gate, we're going to be talking about IoT solutions World Congress, brought to you by IoT solutions World Congress out of Barcelona as well as the industrial internet Consortium. And this event is scheduled for October 5 through the seventh. If you've never been to Barcelona, yeah. Yeah, that's that's a must trip. And the second thing and if you've never been to the IoT solutions, World Congress, yeah, that's a good thing, too. They're going to be talking about IoT, Ai, 5g, digital twin robotics, everything. And one that is sort of interesting to me quantum computing. Hmm, that sounds impressive. All right. The next one, the manufacturing and technology show that is in Cleveland, Ohio. Again, if you've never been to Cleveland at some much trip, great people, great food, great location, great everything. It's beautiful up there. And this is November 9 through the 11th 2021. right around the corner, the sword up is down in November, but it'll be here when you least expected. But anyway, both of these events are important. let's get let's get our lives back in order. Let's just do it. Let's let's, let's take the trips. Let's start learning from these leaders. Because they're there. There's some great stuff in this whole industry for Dotto world that we're we're venturing into, as you all know, it is, but it's just an exciting time to be a part of what we're doing an industry. And that is water. That is oil and gas, that's manufacturing, that's utilities, we had a great conversation of the utility transformation journey, because they're going to have to do it too. They're just going to have to do it. Alright. Humera is on the hot seat. We got a great dog on conversation. I mean, she starts to really lay the lumber and there's, and I could go on and on and on. But I'm telling you, you're gonna enjoy this conversation. So here's your marriage. Humera, thank you very much for joining the industrial talk podcast. Absolutely. I'm telling you listeners right now we're going to I'm going to geek out on this particular conversation. We've been having a wonderful offline conversation about AI about the world and, and really just changing the world and changing the world. Through insights into data. I Humera and the team Canvass AI leading the way. Fantastic. Hey, man, how you doing? I'm doing great, Scott, thank you for having me. All the way from Toronto, give us a little background, little 411 into who you are and why you're such an incredible professional. 04:48 Well, I'm a I call myself a disrupter because I've gone in and picked some of the hardest things to solve in the world I think and it's yet not to a place where I'm very proud. About the industry we work in. And just like yourself, I think we're all on a mission here. And the mission that I've gotten myself in Canvass on is really looking at how we make a difference in the industrial world, and empower the people and augment them to transform the operations that they do in their day to day up in their day to day activities, and empower them with some technologies like AI so that they can take control of their data, so that they're not reliant on anybody else to come in and perform any of the data related functions for them. 05:39 Yeah. 05:40 And we're here to make a difference. But that difference can only be made once to actually take the charge and start calling out what this industry's challenge has been, and how we're going to all work together to transform it. 05:54 Yeah, I'm a big fan of that education, collaboration and innovation. And you cover all aspects of that. And I believe that that is a key to whatever how you want to survive, how do you want to prosper in this whatever next normal? And I I don't know about you, listeners, but I'm getting old Tingley about that explanation. Because I believe the future is, with people like Humera, and others at team Canvass, by the way, I need to make sure that there's clear Canvass is c a n v a s s, make sure make a note of that. And it's dot IO is the website. So anyway, I'm all tingling about this particular topic, because I think there's golden data. And I think that is transformative. And I believe that companies as a whole will tremendously benefit by what your focus, your disruption, your view of how to solve problems. So give us a little background, because I think you guys are thought leaders, I know you guys, your thought leaders, because you're in the game, you're in the game to be able to come up with solutions that actually mined that data. So let's talk a little bit about sustainability and how data can help us with that. Talk to us a little bit about that. 07:03 So one thing I would say is we're thought leaders, but we're executing on it, not just talking about it, right? We're making a difference. That's like, making a difference. 07:13 So noted, absolutely. Put it in in action. Forgive me Humera. totally understand. But I love that because you're killing it, man. You're doing it. All right. 07:25 So what Candace really. So before we get into sustainability, for the sake of the viewers, Canvass AI is really a software platform. And it's on a journey to transforming this industry, it's on a journey to disrupt this industry that has been so scared and reliant on people from outside to give them control of their operations of their data. And so this is really a journey that we undertook about four years ago. And now we're at a place where we see this, this industry just at the tip of that transformation. It's first is about awareness. And then it's about after you what after you've gone through that awareness and recognition is then really about how and where do I go about implementing things like AI. And that's where this industry is, it's at that edge of where it's ready and implementing. And it's not just, you know, the big guys out there, it's not just talking about the fortune 100, we have had the opportunity to see the guys that are in the mid market as well now who are ready, they've actually been running very efficient operations, they're ready to get out of just efficiency, move towards productivity, and eventually into automation. And so that fear is now there. They're getting over that fear. That challenge they have this industry has if you look at you know, any any of the big objectives that are in front of this industry, related to sustainability, related to efficiency, the challenge that this industry has, it still doesn't have a roadmap, how cool You're 08:57 right. You're spot on on that one that is so brilliant and insightful, because you're right. We hear it, we hear AI, we hear edge, we hear cloud, we hear all of this stuff. We hear industry for Dotto, and still, it's just it sounds cool. It sounds good. But I love the fact that you're actually executing I have to ask the question. You said four years ago, you started this particular company ish, give or take a few. What was the dream at that time? What made you say, Yeah, I want to start this What did you see at that time? 09:33 I, I saw a problem I went on to solve every engineer goes out to solve a problem. And without recognizing where you will end up what what irked me and got me started with I was working with industrials to help them basically provide connectivity and help them collect data. Then I realized that that data was becoming basically adjust information For them where they were just, they were good at hoarding that data. But that information that that really needed to be used wasn't happening. Yeah. And then I also saw that even though it was their data, it was the data that the industrial companies own and collect, they still were unable to access that data. All they got was for some fancy charts at times, and trends and analysis. But were they really using all of that data, so that their own workforce could really do something with it. There was no buzzwords in my mind, at that time, I wasn't necessarily looking at it could be AI, it could be other technologies, what I went in to do really was to look at solving a problem. The reason AI becomes important, is because if you look at the industrial world, it generates a lot of data, if you look at, you know, your different figures, you know, like the the oil and gas industry is creating terabytes of data, you know, every day and so that data is so huge in that volume. When you look at large volumes of data, veracity of data, different frequencies of data, what comes to mind, how do I how do I look at that data? And how do I actually start to work with that data, that's where then the technology comes in. And that's really where starting to looking at AI and starting to, you know, look at how AI then can be used to, to look at and transform and work with that data. But then there's a third element to it, you can build all of the AI. But if the people still are not able to use that technology, then there's no point then I've created further more problems to it by making them further dependent on how to no leverage that AI. So where I ended up with was creating an interface between the operator of the plant and their data by providing them an interface where all of the AI was engineered and made available to them in a usable format. I made AI approachable, made AI usable, and made AI available for an industrial operator for a plant engineer for a process engineer for a reliability engineer. So they are empowered to look at their own data work with their data, just like how they have been used to working in spreadsheets, but let's allow them to scale, let's allow them the extensibility so that they can now work with that large volume of porosity, frequency of data, and work on large complex datasets. 12:27 I we're going to talk about sustainability. And there's some targets that are out there. And industry has to be aware of that. That's just without a doubt. And we're going to go down that road. But I have this one question. Because of the tsunami of data because of that the leveraging technology innovation in a way that allows you to look at that tsunami and just pull out what is relevant? Do you pull the data out prior to going into the cloud? Or do you do that analytics and saying, No, no, no, yes, this is data. How do you how do you analyze your data? Where do you do it? 12:56 So we are all about operational data. It's all about the data that's coming out from their edge systems, it could be coming out from their their controllers, it's coming out from the sensors that are basically providing them the information of what's going on. And all that data is a lot of this industry has has actually put in the instrumentations, about over a trillion dollars has been spent just an instrumentation of this data. And now that they're able to collect that data, they're hoarding that data into different operational systems, that could be historians, that cloud systems that could be even from AARP to homebuilt operational systems that data is being collected. And then from an analytics perspective, what these industrials have been doing is leveraging a lot of analytics capabilities to basically look at that data. And that's really related to looking at some trends and analysis. But now what? And so we went in and solved that problem of now what now what do I do? And the next thing is, okay, how can I start using this data? If I have this data? Can I start to look at forecasting what my yield would look like today? What my yield would look like four hours from now, can I start to predict if I wish to change or you know, any of my ambient conditions or any of my parameters? If I can start to tweak, you know, a little bit of the moisture levels? What would happen? What would be the ideal state I want to be running this line on? And so that's the those are the things when the operatives think about they think, oh, that's I can't you know, I don't have the technology, I don't have access into my data. That's where they would tap into, you know, they would bring in some heavy hitter consultants, they would bring in data specialists would come in, and they might have the expertise on the data, but they don't have the subject matter expertise. And that's really where the this industry needed to change the approach and we started to basically put the operator in the center of the universe and say we need to be operator and Scott. There are multiple reasons for it. One of the major reasons is because this industry needs to institutionalize this knowledge, there's a gap of these resources, there is a gap in terms of that expertise that's going to hit this industry in the next decade, because a lot of this workforce is about 30, more than 30% of this workforce is aging workforce. So as you see that shifting out, there's a huge gap that gets created. So it's very important to institutionalize that knowledge and start preparing the organization's for that shift. 15:33 So what I hear you saying, which is interesting, you are able to provide that tactical data...