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!
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Company Website: https://www.canvass.io/
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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.
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.
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.
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.
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.
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.
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
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?
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.
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?
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.
So what I hear you saying, which is interesting, you are able to provide that tactical data for real time action, and that is, operationally I can look at the data, I can make decisions and and optimize my whatever manufacturing asset based off and, and that institutional side where I'm collecting that information. And whether we like it or not, it's going to happen retirement that knowledge out the door, be able to institutionalize that, let's shift gears a little bit here. Let's talk about sustainability. why that is important. From the perspective of AI.
I think it's one of the key, it's going to be one of the key drivers, it might not seem like it. But if you look at this industry, and you look at sustainability, have manufacturing the industrial side accounts for 25% of the global carbon emissions. You're responsible for 1/4 of the emissions?
Is that globally? said 25%.
Yes, got it. And, and out of that 25%, close to about 50, a little less than 50% of that just comes from the manufacturing of cement, steel, ammonia. And essentially, you know why that is because that's all infrastructure that we're building, right. And that's critical. But that is also important to recognize all that infrastructure that we're building is also creating an emission of 45% of the industry's carbon emission.
It's interesting. And it's one of those things that you need it, you can't stop it, right? You need the infrastructure, but you have to think about it differently. You got to have to figure that out.
And so if you look at some of the industry stats, it is why, you know, if you look at different industries, that's just one part of it. But if you look at metals and mining, you look at food, everybody is making a contribution there to those carbon emissions. I had some interesting things looking at, you know, we work very much in the food industry to in agriculture is estimated for over 70% of the global water use. It's one of the scar spaces that we would have if we continue on that path. Yeah, yeah. Food chip food supply chain is responsible for another 30% of the GHG emissions. Some interesting fact was that it food waste was a country, it would be the third largest emitting country in the world. Wow, US and China. Put it in perspective.
Yeah. This is the in we're gonna venture into this is a lot of that carbon being produced as a result of inefficiencies with the assets.
So, Scott, you have to really break it down. Yes, it's being produced in multiple ways. It every industry is obviously contributing to it in one way or the other in certain industries, over over utilization of the assets, any of the assets that they're running is causing that in certain industries. It's the high utilization of the fuel, because energy being one of their largest consumptions in our business, you would see or, you know, in the oil and gas sector as well. But every bit makes a difference for Scott, if you look at the amount of waste that gets generated through a production line and take, you know, any of the industry, take metals, take cement, or take food, if they can start to control the waste throughout the line, they can start to make a difference. I got some is not the theater, some somebody threw out some random stats of May. And they said, one of the large food manufacturers that develop that is producing the chips, they end up creating more than $30 billion worth of waste, and all that waste goes into landfills.
You would think that there's a financial incentive to be able to make your organization your operations as efficient as you possibly can, right? Makes sense.
In in most traditional ways, as they look at Yes, they look at energy as a huge cost. And they're all kind of optimize that. They look at raw materials as a huge cost and they're trying to optimize that is everything else on part of the CFOs agenda is yet I would say not really Scott, let's call it agenda is only looking at how am I looking at my margins today, and how we're going to improve those razor thin margins tomorrow so that I can sustain this business. And that's why this industry has has been always in a firefighting mode. And one of the big things that why I call it a movement is because this has to start transitioning from the top to the bottom, the mindsets have to start shifting the mindset about I'm always in a firefighting mode. That's because we're continuously doing the same things. If humans are looking at things and saying good and bad, we haven't get moved into the 21st century because a human has been doing that forever in this industry. Oh, it's good, it's bad. Let me get brambles at random sampling. And I'm going to find out what what's going on. That's not how this industry should be running. We have enough tools and technologies. And we have made enough progress, that we should be able to now leverage tools and technologies for that purpose, we should be able to leverage, you know, either platform like ours, where or technologies like this, where they can tell you anything before even that happens. So we're not contributing to the sustainability challenge that we're faced with right now. We shouldn't be able to control this well in advance not find after the fact. We've still been we have been and we continue to be operated in a reactive manner.
It's a human it. I mean, you're hitting on all the points. I mean, without a doubt. How does and how will AI help us with sustainability? If I'm a company?
Who also there? There are three ways of looking at this. And I learned this by from my customers really, it's not that, you know, it's it's earth shattering revolution that I'm going to do, I've actually learned by working with these customers, right? So what are the key sustainability is achieved in three ways. One is you look at your current operations, and you optimize that, that's where you can start to already gain and be improving this is you can already start to gain 20 to 30% off efficiency gains, just by optimizing your current assets and your current operations. The next thing that comes in that is the next phase that comes is then you go from optimization to looking at alternative sources of energy that can further now go from, you know, if you were at that 20%, you can start to further gain 30 to 40% by looking at alternative sources, and then over the course of time also start to embed New Tech, new technologies, as your as your assets are aging, and you're starting to replace this, what this industry would end up doing is start to bring in more energy efficient assets into into play as well. But that's actually the roadmap of how you gain sustainability. One of our customers just in one of their one of their plants, actually, it's a food ingredient manufacturer, one of their plants, they started to look at how they were generating energy through their cogeneration assets. And and realize that they were always running them at 100% efficiency, even when the plant demand didn't require them to run the assets at 100%. Because you know, it's still hard to keep on going back and forth,
to cycle those things down, up and down.
And then that requires, you know, more resources. And that requires then repeated intervention, that just they didn't have the ability to do. So that was the easiest thing. And then they recognize that and that's where, you know, it's I'm talking about a very simple way of how you start to optimize this. So they started to look at them, how we can use data, so that the data can tell us if the plant demand is X amount, how to run each of these assets that's supplying the energy. So they actually set that and they connected the, the the platform, and they have been able to they've been using it now for the past almost four years. And what they have been able to do is now create a completely closed loop system. So that the plant feeds the data and tells our system of what the plant demand is the system then connects back into these assets and say run asset one or run boiler one, that 40% efficiency boiler to at 70% don't need to run boiler three because the plant doesn't need it right now. And then takes that message back into the control system. So there's no human in the loop, right? And runs that system. And it's been running it for the past, you know, four years now.
And probably put in a lot of coin in the pocket too, as well as that whole sustainability. I mean, it's it's a it's truly Win Win everywhere.
I they have been reporting that year over year there has been they have been able to reduce their fuel consumption by more than 4% just by looking at the small assets I'm talking about. Yeah. And then over 20 million pounds of carbon emission reduced every year.
So So why what what are the forces that are requiring businesses to look at this? What what regulations are going to be in place? What what what are we doing here? Well, so
one of the mandates really is from the industry, if you look at the mandate is really to be achieved. Certain carbon efficiencies and or net zero emission mandate for 2030. And then further into 2015, where everybody is looking at, you know, zero carbon emissions zero,
by the way, I want to make sure that it 2030 is just still right around the corner, FYI, it's only nine years away. So if you look at 2030, and just go on, I got it. I know, it's nine years away, it's just like, right there, you, you know, you're gonna be on 2030.
That and that's why I talked about this as a as passionately as I do, because I think we all need to get on that on on that train of passion for this, then it builds on the passion project into the CFOs mandate. Now, the CFOs mandate, the CEOs mandate, it shouldn't just be in the operations team looking at, you know, how we're how we're improving on our continuous improvement projects. No, it's no more about that. It really needs to be as what are we doing about all the waste? What are we doing about energy? What are we doing about water? And we do this in a combined way. All contributes towards sustainability, right? Because right now, it's department by department. It's very segregated. And that's why a lot of the AI that also gets applied is very segregated. Nobody, nobody has looked at this, how do we apply different technologies that allow us to hit these kind of methods, nothing happens overnight, nine years, that would be gone.
Like a blink of an eye, I'm just telling you, when you mentioned this, and I'm thinking then you said it's nine years in our off conversation. And I just said, Oh, my gosh, I had the wrong perspective, that's right around the corner. And that's got
to happen now. Right. And the only way it can happen is when it becomes part of the mandate. It's no more about just a nice to have it's about and they can really those are the few things that can start contributing, how am I going to reduce my water consumption? How am I going to reduce the waste that I'm generating every day? And how I'm going to actually control my energy consumption and utilization throughout these, they can just start simply with looking at those things. That's really where I've seen customers, when they simplify it that way, they're able to then identify, hey, where can I start today? Then where can I go tomorrow? Yeah, that helps them get on that journey of sustainability. It's as simple as that. And I know, it's not easy for them to start to immediately all of a sudden prioritize it. But guess what, if the mandate is about reducing costs, as well, and how you're going to actually look at, you know, covering that labor shortage, as well, all of those things help you there as well. Because what you're going to end up doing is you, if you reduce the waste, you've already started to impact your bottom line, if you can start to reduce energy consumption and control it, that's helping on the bottom line too. And then if you can actually put the operator to control it, that's gonna help your labor shortages, all feeds into those mandates to
roadblocks in what you're saying. I mean, it's the money, but there that it's there, there are roadblocks. And I'm not saying don't, don't come to me, or whomever and complain about this. It's got to happen, because it's a mandate, and you got to figure it out. But what are the roadblocks?
So to be to be just very honest about this, Scott, I think one of the biggest roadblocks is the mental Roadblock, oh, it's too hard to it's the myth about technologies like AI that stops people from leveraging it to its full capacity. The other is the siloed transformation approaches. Every group, every organization looking at silo, there is the companies that I see the most successful that we have worked with are the ones that look at this edge scale, you will, you will learn certain places, you will fail at certain places. But the success that will that you will create through this journey is what's going to help you get ready and meet your objectives for 2030 and 2050.
And it's got to happen yesterday. I mean, you and I share the same sort of, you know, the passion and anxiety to saying, hey, we've got to do it. Now. I don't know why this is, but it is what it is. We have to wrap it up. Unfortunately, I can have this conversation for a long time in America. How do people get a hold of you and say, Yep, I like what she's talking about. Best way to get a hold of,
you know, just go to Canvass.io. Click on you know how to connect with us different ways to find a demo book a meeting. And that's the best way and you will find that our team, which is a combination of subject matter experts, as well as data people that actually know how to work the industrial data would be happy to work with it.
Excellent. I like that. Go out to our stack our two men, it's h u m. e r a. Malik. Did I get that right? Malik. I hope so. Ma l ik find her Reach out there too, as well. She's got a great stat card. See? Oh, Canvass is the company. Fantastic. Thank you very much for being on the industrial talk podcast America. It's been an absolute pleasure, Scott. It's been wonderful. It is the number one industrial related podcast in the universe. Just FYI. I think I've oversold it. Alright, listeners, we're gonna, you know, we're gonna wrap it up on the other side. So if you're not, we're gonna have all the contact information out on industrial talk. ca.com. And, of course, we're gonna wrap it up. Thank you very much for joining. Stay tuned. You're listening to the industrial talk Podcast Network.
All right, a big, big, hearty, thank you to Humera Malik, Canvass. AI is the company go out to Canvass.io. Find out more. I'm telling you right now, if you're not looking into data, as a way of solving some of your challenges. I mean, I like the fact that she brought up the point that it could augment your workforce. And I mean, it's really important, especially today when we have a real tight workforce. She's great. She's a rockstar data Rockstar. All right, again, IoT solutions World Congress in conjunction with the industrial internet Consortium. This event is in Barcelona. It's incredible. Got to put those two things on your bucket list, October 5 through the seventh 2021 right around the corner. And the next one is the manufacturing and technology show. This is in Cleveland, Ohio, November 9 2011. Let's get our life back in order. Let's visit these things. Right. Be bold, be brave, dare greatly change the world. Thank you very much for joining. We're gonna have another great interview right around the corner.