The Manufacturing Executive
The Manufacturing Executive

Episode · 9 months ago

Human Input in a Data-Driven World w/ Martin Cloake

ABOUT THIS EPISODE

Does technology have to be all or nothing? Is it possible that in our increasingly data-driven manufacturing environment, we're losing sight of the value provided by human input?

In today's episode, I talk about those questions with Martin Cloake, CEO at Raven.ai. Martin is an experienced executive and award-winning technology entrepreneur with a background in manufacturing, data science, IT, and operations management.

Here's what we discussed:

  1. How Martin merged his varied background experiences to create Raven.ai
  2. Creating balance between data and human insight
  3. Real stories of how Martin's clients blend the best of both worlds


To ensure that you never miss an episode of The Manufacturing Executive, subscribe on Apple Podcasts, or Spotify, or here.

First, you need to work on yourcontinuous approvement culture, and this needs to happen before eventhinking about investing in technology. youcontinues. Som Improvement once toonce is baked into our culture. Then view technology as a tool in the toketand every manufacturer should be looking for the right tool for the job. Welcome to the manufacturing executivepodcast, where we explore the strategies and experiences that aredriving midsize manufacturers forward here, you'll discover new insights frompassionate manufacturing leaers, who have compelling stories to share abouttheir successes and struggles and youwill learn from BTO B sales andmarketing experts about how to apply actionable business developmentstrategies inside your business. Let's get into the show, welcome to another episode of theManufacturing Executive Podcast, I'm Joe Sullivan your host and a cofounderof the Industrial Marketing Agency Garilla, seventy six. So let me kickthings off today by asking you this: Does technology have to be all ornothing do we have to either be on the Industry for point o bandwagon or offof it? And is it possible that, in this increasingly data driven manufacturingenvironment we're losing sight of the value provided by human input? Today'sguest has drawn on his career experiences to build a solution thattackles this issue head on. Martin cloak is the CEO and Co founder ofRaven Dot, Ai Raven diaes platform delivers increased profits and tnx plusry to top global manufacturers by guiding actions with real time.Insights Martin is an experience, executive and Award Winning Technologyand entrepreneur with the background and manufacturing datascience Ip anoperations, Management Barton, holds multiple patents and is a mechanicalengineering and business graduate from Thgilli University in Montreal Quebec,Canada. Martin welcome to the show yeah thanks thanks for Havingue Martin yyou've got a great story about how your...

Software Raven Dat ai came to be, and,in particular, how your experience and sales earlier in your career. It blindsto go influence your decision to build this company, so I was hoping you couldkind of start up by explaining what Raven Dotai is in the first place forlisteners and also to tell us a little bit about the journey that influencedyour decision to create it absolutely so yo. Now, at a high level, we helpmanufactures produce more efficiently hen. I can get in some of the detailshere, but you know fundamentally, if many factors can ununderstand what'shappening, what has happened? It's much easier to take actions to poveerformance in the future, so you know we help many factors make sure theyknow exactly what's happening at their plants and then we also help them takeaction. So you know at the Corse it's not that complicated, but you know itwas very much influenced by my early experiences working both in Techn AndinManufacturing, O. that's great. I want to quote something: You said in anarticle that you published late last year on Linkedin, so you said gettingexcited about manufacturers being data rich is like going on and on about howmuch paint PABLA Pacaso had in his studio, our obsession with data ismaking us forget who and what actually provides value. I think this was areally interesting and powerful statement. I'm just wondering if youcould unpack that for us a little bit if forsure and maybe what I can do is Ican kind of frame it within my experience that caused me to foundravend o allude to the fact that I started off my career at blinds to goso yeah. You know my background is in Hih Tech. I am at the core, a Hig Tech.You Know Engineer an entrepreneur and you know I graduated from Gi Universityin the early osands. You know, and tech and H, telecom had actually ou knowthere wasn't as much activity and telecom and as recruited by blinds togo, which is kind of not what I had expected to go into, but it was apretty neat offering and blinds to go. I'm not sure what part of the countryare you in I'm in St Louis Missouri, so, okay, so I'm not sure it plants to go,is actually all the way out to Sant Louis, but it's an east coastmanufacture with a hundred plants and really innovative way to look atmanufacturing kind of holistically ind, one of the first things that you know Idid when I went to work at Blans to go. Is they got me to sell blinds in ablind store, which was a really you know somewhat shocking, but kind of aningenious way to you know, connect...

...people to the reality of what it is towork in manufacturing. So now here I am graduate from theguilt Mgill University.You know full of confidence which you know, I think that's what they give youand good an mcgil thinking that I know you know know how the world works beingset to a line store in toto on New Jersey and and the idea is you work ina blind store until you get good at it and once you get good at it, then youget to come back and work in the plants. So I us remember, you know calling mywife within the first couple days there and sayng like what's going on here,I'm an engineer and I'm selling blinds at a retail blind store so anyways asit started to go, and I started to realize you know a couple interestingthings. First, off from a sales perspective, if somebody walks into ablind store, they're there to buy blinds right, so you should be able to.Then you know, work with them and get them to. You know, buy a blindwichwhich I realized pretty quickly, but the second thing was to reallyunderstand you know: What is the impact on your customers? If there's a qualityproblem, you know it's at some point in Manufacturin we see quality problems asa number, but you know you. I remember those cases where I missmeasure toblind and it came back to the customer and they say you know you know youscrewed it up and really, as on the retail sactor, to live that firstfirsthand experience of what you know the user experience is a manufacturing.It changes how you perceive those numbers if something's late and yourcustomers asking for them. So that was really a interesting experience to sortof show me what the consumer side of manufacturing was and I had neverworked in retail sales. You know I'd work to during mats and then, afterthat I went to work in the plants and I did all sorts of roles in in the plansfrom quality engineer, O product engineer and one of the first roles Ihad was as a production dupervisor of a couple lines and again you know full ofthat Megil confidence. I thought I knew what manufacturing was. You know. I'Mgonna get my Excell phile and I'm going to optimize the process and it's goingto be. I had this one particular excel pile that I really liked it was is anawesome file. I think it was about six or seven megs which at the time openedquite slowly, but it had all these neat. You know it was pretty neat file and Iwas also playing with data from Coknos, which is interesting because you knowwhate of I mean advisors was one of the key people at Cognis before acquisitionhere so anyways. I hell had all this...

...data and I was seeing all these thingsand at some point I went to my plant manager and I said, hey you know I youlook at my cell while I think I ah Y. U now I'd like to show you and HsaisMartin, he says. Yes, do you know the names of all two hundred operators atthe plant and say I said no, he said well, Oh, I want you to memorize thenames of all two hundred people in your plants and then and then once you'vedone, that you can come back and I'll look at your file and like what okay,so anyways, I'm still at the stage where you know I begrudgingly listenedto him and then I startd I started. You know, spending more time on the shopfloor and then realize that just by walking around it was clear where theproblems were. Somebody would ask me to help with a certain machine or theywould ask for help or something I just see stuff as like a natural problemsolver, and then what I realize that the way to drive improvement in mylives wasn't with my excelphile was by walking around asking questions lookingat the process, and so my day more from a day that was more focused on analysisand excel, where I was basically walking laps around the plant, so mymorning would start to get there ten to seven and I had meet with some of myteam lads and then I'd go and say good morning to all my operators and theysay ohl good morning, Mter Mout, then because it was was in Montreal. So Th Y.U Know Misse Him Maut than was my name, and you know I would notice something Iwould thank them for coming in and they'd askd me to do things so then I'dwalk around and at some point I had close to fifty operators at the plant,and you know it tooke quite a while. It almost take me to first break to dothat. First Pass and then I go, I go to break with them and then, after breakI', go I'd. Maybe go sit down to my desk because I absolutely had you knowsome duties to do there, but this method of just walking around and right.Now, apparently I don't know if you've heard of it's called management bywalking around there's actually an acronym, and if you you can see it onMukipedia, so so it sort of my my perception of manufacturing wascompletely different, going into it after Hav. You know working at yourfirst Tand, but one of the things that I was frustrated with was the fact thatI moved completely away from the data. So I moved from data centric to peoplecentric and I didn't I didn't do anything with the data, but that was Iwas able to drive. You know improvement in my lines, just by being there andsolving these problems so yeah, I'm not...

GOINGNA, go on on a ten minute, MONOOCyere, but that was kind of you know, setting the stage for you know thereason why I found it raven. You know my perception of manufacturing beforegetting to the shop floor and after getting the chole are completelydifferent. So you know here you know after working there for a few years, II kind of got a sense for what it took to provide value to my operators. Toyou know, I think the way that the way that my you know I perceived it is anoif I can basically as a supervisor at the time, it's my job to solve problemsfrom Ouparti t t. What my operators are doing is pretty clear, keep themachines running and I need to walk around, find those problems and fix it.You know in some ways the success of any business is not related to whetheror not you have problems it's related to how well and how quickly you solvethose problems so anyways. So that was really the my time, an manufacturingwhich was which is super exciting, and I know as a competitive athlete. Ialmost got some of that same feeling on a shop floor when, when things arerolling, it really feels cool to be part of the team and to be successfulso anyways after leaving, I followed my wife to Otto, what Towen Sho doin a PhDto- and I tried commuting to Montreal from Ottawa, which is a two hour, drivethree hours with traffic, and I did that for about three weeks and then Isaid you know what this is so than then I basically I put up my shingle and andstarted a consultancy which combined my background in high tech andmanufacturing and started consulting for this little startup scene in Ottawa.So this was two thousand and seven. So I got connected to a guy named Paul,Lam who's, a CEO of Spartan biosigncs, and you should check them in the newshere. They have real time DNA testing for covid testing. So I consulted foran I did some. You know a design work for first pot, an bioscience and thenthere's a small company in town at the time with ten people, collee Chopifiand we started hangngin Ow to chop in fies office and shop. Fi was doing somepretty cool things and slowly this group and we call ourselves- I thinkyoung Ou prener club at the time and now its fresh founders and slowly. Thisclub started doing some pretty cool stuff. So then shop an FI started,blowing up and then Paul's company...

Spartin bioscience started. You knowdoing really cool stuff and then we have then somebody sold this company.One of my other friends sold his companies to Surey monkey and thingsstarted going more and more and the's still a small group of entrepreneursand Ottawa began to tort. You know: Do some pretty amazing things and I'mrunning my consultancy im serving them. Do some work get around a company inSilicon Valley and with another one of the people in the club and then there'sa point at which they kick me out of the club so th. You know they kind ofpresented to me that you know the lowest form of ANCR. PRENIRSHIP isbeing CONSULTEDT. So here I am hang ing on e Ontr Printish Club. Not really youknow, I guess I'm an entrepeneur as a consultant and they say well t you notyou're, not sort of the caliber of entrepreneur that we're looking for inthis club, and I like really so anyways and I'm still consulting for them. Anat some point. I start getting frustrated going like yeah. I think youknow, being a consultant is not really what I want to do. I think I want tostart something- and I happen to have this problem- that I'm reallypassionate about solving, which is why don't manufactores use data in the waythat I think they should use data so then the first things. First, I go tomy buddy Paul and say: Hey Paul. I thinking o started his company in youknow. I think I called it Iot for manufacturing at the time and I saidPaul, you think I should do it and he's like. No, I don't don't. Do it you're agreat consultant. You know stick to what you're good at you know. Youwouldn't be good at being on to penner ans like so it's, so I most of the timeI listene to Paul, but in this case here I chose not to listen to him, andso then I started up when I called machine telemetry at the time andreally the idea was you know? How can you allow for manufacturers to usetheir data in a way that doesn't take out what's most special about being aleader in manufacturing and what's most special is the time that you areworking with your team to identify and solve problems anytime, that's notspent doing those things I feel is time not well spent and my frustration backthen at how much you know, leader time is fenced filling spreadsheetsreporting out data is just Min numbing and you know there had to be a betterway and I would say even today way too much time is consumed by technologyrather than unlocked with technology. So I founded the company at the time.As an engineer, I'd always heard that...

...you're supposed to name your company,exactly what you do so I called it machine telematree because becausewe're taking telematue from the machines at the time- and then I met upwith my cofounder Braiden PhD from Institute for Arospace StudiesUniversity of Toronto, which is where which is basically, I always say it's-The rocket science program in Canada. It's the top. So I awuld say that inyou know, Braden Brai is the rocket scientist and and Hes Zize glaze overwhen he sees that so yeah. And the idea here is that you know how do we combinethe best of technology with actual experience, running operations andthat's kind of been the formula for what wee built to date. So I stull youknow we found it. We start to do some work for manufactors and I say, HeyPaul. You know, because because I always go back to pall my buddy fromsparting bioscins check it out and he says: Oh, it's pretty cool yo shouldrase some money. He says Oh yeah, let's do it and but your company name SucksMisid Yeah Yeah machine telemetory is the worst name ever you. You shouldname the company Raven, and so you why Paul- and he was telling me with regards tothe company name like nobody's ever going to want to say hey the guys frommachine telemetry are here. You know so he said Raven because Odin, the NorseGod has hese two Ravens Hugan immune and they fly around the world, gettinginformation for him, which is kind of what you do and I said, boom. Let's doit. You know so change the company name reached up to some of my buddies. Whoare you know now quite successful in Ottawa and they're like this? Is this?Is Y? U Really Cool and that kind of started. You know we raised Te, bace,ofe money and we've raised a bunch of money since from effectively t thisnetwork that that we've had from the starts in Ottawa. You know that's now,basically given back and supported our community, so so anyway. So so I thinkyou know I mentioned so so we raised some money and and really the formulathat we we ha we've had for building the business. Todate is really bycombining the best that modern TEC has to offer with a you know, deepunderstanding of manufacturing. You know, and we built that to date. So,for example, you know on our executive team now we have Rob Lander, who wasPresident Co of stackpole international billion dollar, publicly traded, Auloparts manufacturer who spent his career.

You know transforming manufacturingoperation. So for us, it's really important to have that. You know thecore understanding of what it takes to transform manufacturing because in someways that people aspect of you know change management is the same. Peopleare the same. You know technology has advanced, but we haven't and reallythat's been the Fomula for you know what we've done so far and now you knowwe serve global manufacturers from Sanopi to Danaher to Hatachi. You knowand effectively it's really with the same vision that we've always had,which is how do you provide now clear understanding of what's actuallyhappening, which is a pretty big challenge and I can get into that laterand then, once with this information, how do you provide it in a way wherethey can actually take actions to improve? And you know the gold standardfor application of modern? You know technology in my mind, is no ways orGoogle traffic, so you think about how this technology basically cuts to thechaste. It doesn't dominate your attention. It doesn't, you know, drownyou in dashboards and you know constantly needing to you know you tolook at it or interact with it on occasion it provides guidance. If youlisten to that guidance, you will perform at a much higher level so thatthat is the gold standard. You know we're not quite there in manufacturing,yet where there is a place for Dashboars and other than reports, butbut really that that is the value that you know. Technology can provide, whichis to help to identify problems and make it easier to solve them morequickly, yeah and just to clarify for listeners when you said ways you'rreferring to the the APP right that that's right, traffic APP that were theinput comes from both you know real data, but then also you now liketraffic data, but also the input the people are physically, providing bytyping into the APP right absolutely and now now the way that it works is itgets data from your car and from traffic people contribute data, but oneof the core things is that data needs to be accurate. If that did as notaccurate, you know no matter what you do. On top of that inaccurate data, youwon't be able to provide good good guidance. One of the biggest challengestoday is that you know in the industry. FORIDADOS are in manufacturing. Todaythere are tons of companies out there...

...providing analytics maintenancesoftware. Now many of these systems rely on the data that's fed into them,and this data is, you know, has been collected from machines for decades,but the most valuable data is to understand when the process is notrunning when the process is not running the way to get. It is typically throughmanually entered methods. You know either somebody writes it down types,it an excel or pulls a dropdown menu. So all of these systems sit on this.This rickety structure, where you know humans, are entering data into thesystem and the fact that they're all sitting on top of this means that dataquality is one of the biggest issues that has has people haven't emphasized.So half of the problem with many of these systems is dad a quality and thefact that you know these other systems with analytics and dashbors are sittingon top of this pordita quality people get burned, people get burned bygetting pointed in the wrong direction and what happens when you get burned afew times you get disengaged, so you have these systems that Alwat thatexist to present metrics, that people don't trust on the shop floor and thenat the court. People are going back to doing what they've been doing forthirty years, which is you know, managing their day to day based oninstincts so to solve the industry. Forodo challenge. You need to make surethat sitting on a foundation of good data and then once people haveconfidence that the data is trustworthy. How do you give them a tool to allowthem to take actions to identify and solve those problems more quickly, yeah?So your really are bringing together kind of the best of both worlds. Therelike what are some ways that just to try to make it tangible for listenershere. What are some ways that y? U Your tool, Raven Dat, ai harmonizes, thebest of you know the data being collected from machines and the humaninput well at the core. I think what makes it really clear is that our clients work with us because theyget a return on their investment. So there is a cost. You know ourtechnology costs a certain amount, so they need to see that return. So youknow and what delivers that return...

Changeis based on where they are intheir evolution. So in example, we serve a IDATA her plant in California.You know large lership organization and, as I mentioned before, one of thebiggest challenges is to know: What's happened so this particular plant hadan issue where machines that were producing goods were down for a longperiod of time for unknown reasons, and if you were to look at the machine datethat it would highlight the fact that they are down because they're broken.So you know at a high level, the machines are broken. What do you do toaddress broken machines? Well, maybe you get engineers to try to make themachines run more smoothly right, but what we saw when we deployed ourtechnology was that when a machines breaks and goes down, there's actuallythree different segments of time. So there's the first segment at time,where you're waiting for maintenance to arrive, the second one you're fixingthe machine and the third one you're waiting for the operator to come back.So those three different segments of time require different things toresolve. So you know when we finally sliced it up and showed them. It wasshocking to see that they were losing six hundred hours machine hours permonth because of waiting for maintenance- and this is not that theydidn't have maintenance staff Hor. It was just you know, a slightmisalignment of their schedule. So one of the amazing things is that the firsttime you see data presented accurately. The types of things that you need to doto drive gains early on are often mundane, and so, in this case here youknow they reduced theire waiting for maintenance downtime by ninety percent,resulting in you know, significant oe games, and if you were to see whatthey're actually doing on the shop floor, it is not revolutionary. It justcomes like this is the kind of thing where, if you want to define thisproblem and give operators, you know this is the problem. This is your team,we're spending too much time waiting for maintenance like they know how tosolve this problem right. All you need to do is, and we don't solve problemswe just we just present them to people who know how to solve them on the shopfloor. So one of the exciting things is that you know often the kinds of thingswe see early on are you know you're spending too much time waiting formaintenance, you're spending three...

...times as much time as you should onsetup. Your machine stops and starts way too often, so there's tons of earlygains as soon as you, I guess in some ways, just flick on the lights for thefirst time. That's that's a really good example. You know it's. The data alonedoesn't tell enough of the story. You know without the human input right andinterpretation of what what it actually means absolutely- and I think at somepoint here, you'll notice that I never used the word o ee or all these othermetrics here, because at some point the problem was they are spending too muchtime waiting for Maitance, yeah, so e. let's eliminate that problem, and I somuch talk. You know the conversation oabout industry for Ido, and you know Iiot and Ai Cloud and all this kind of stuff here, it's so far removed fromyou, know: Supervisors and maintenance leaders having a conversation, but whatkinds of things they can do together to reduce how much time they're spendingwaiting for maintenance. So in some ways the most effective industry forATO projects right now are called industry. FORDATO projects, they'recalled continuous improvement projects, are not even projects, it's just partof continuous improvement. So for that particular example like in none of ourcommunication, where were mentioning Smart Manufacturing Industry Fordatocloud that wasn't there, you know, like Dannaher, has continuous improvementbaked into their culture. They are looking for practical ways to drivegains, and you know we're happy to be a tool in their tool kit to support themto make these gains and that's effectively what Industry Forado? Isit's not a movement? It's not this big transformation from one way to another.It is a pretty neat tool in the tool kit, but that's not the narrative,that's presented, you know on social media, a not unlinkedon and all thatare even in board rooms from you know large manufactores in another one ofyour articles, I'm liked in Marty reference to deliht study that showedhow labor productivity and manufacturing have been growing veryconsistently and rapidly from like the late s until two thousand and seven or so,and then since then, despite turning on what you referred to, is the real timedata firehouse, that productivity is...

...sagnated, and it was surprising for meto see this. I'm curious. If you could talk about why that has happened. Yeahit was it's pretty shocking to see it was by deloit and mappy. Okay, anorganization manufacturer organization, doing a study of Labor practivity and's. It's almost like the moment, the iphoners released. You know,prodactivity girlh, basically flatline, but really the thing that changed wasthis appetite for real time data? So up until that point now, we've always haddata. You know in manufacturing. In particular, you know. Data is just afundamental part of our lives, but the way we consumed it was in a amanageable amount. We would see performance, you know once a shift, youknow, as mentioned before, you know we would spend our time walking around. Soyou know you see your daily ship report, Youd internalize the problem thatyou're trying to solve and you go and try and solve it. So what you know astechnology advanced with the cloud, an Iot and access to all this data, theway that we implemented, you know solutions very much in I sor copied ourKPI report centric view of w how to drive improvement. So you know, ratherthan changing how you know how we perceive how we should use data. Wesimply took a report that we used to see you want to shit and just made itlive so the way you know, I would say the way we were used to using Datasonce a day. You get a report now when you flip to real time. If you makereports real time, here's a couple issues, one often with the onts a dayreports you have people getting in there to actually make adjustment sothat the numbers are trustworthy and the second one is. Our reports in Kpistypically aren't an effective way to guide action. So you know you go backto my ways. Example: Ways is not a series of DASHBOARDS and KPIS. It'ssimple instructions that tell you how to avoid traffic, and I think that'sthat's a big difference here. So you know, whereas we have this thistechnology, that's a lot able to collect and present tons and tons ofdata and real time our capability to consume data is twell still quite low.So you know how do you- and I think we struggled with this change that has,you know, impacted the two things that I mentioned earlier, which is dataquality and engagement? T you know, projecting a or presenting a dashboardin real time that has questionable data.

That's not directive is not helping.People on the shop floor take actions to drive improvement so, but at thesame time you know, there's been this movement over the last ten years toinvest in technology and there's been this. You know, companies are investingmassive amounts in pilots and different initiatives, often very very largeinitiatives, their disruptive organizationally. So in many cases withthese, with these implementations, the most complex part isn't thetechnological part. It is change management, so by taking these systems,which just are fundamentally flawed and are not helping you're, actuallydisrupting organizations and creating disengagement on the shop floor whichdoes not help, you know, nurture and improve a continuuson group improvementculture. So you know if I were to think of the formula for nufactors, bigg orsmall, if you know to deploy this technology properly. First, you need towork on your continuous approvement culture, and this needs to happenbefore even thinking about investing in technology. You know continues SOMimprovement once to once is baked into our culture. Then view technology as atool in the toket and every manufacturer should be looking for theright tool for the job and should be very you know where you have tools thatyou know the team is rejecting your tool, there's a probably a good reasonfor it. So the second thing is that often you know, because of the big thescale of how industry foder Florido is presented online, everybody thinks t athey need to go big where the reality is that the best way to deploy thiskind of technology is to deploy quick and small and manageable and accelerate,and you know double down on success, and you know it's amazing to see O onLinkdin t when anybody post, something that shows a whiteboard. So somebody isreally proud of their whiteboard and they say hey. I made a KPI work, boarcheck it out, linkedin and then people jump all over it. So there's the oldschool folks that say this is the way to go. It's so connected to theoperator creates engagement. It's like...

...it's perfect and then there's the thetechfolk hat. Go like no. What are you guys doing, you're stuck in the SEVN orsecond hts? That's not the way to do it when the reality is ther they're, bothrights. So one of the things that whiteboards do that technology oftendoesn't do is that it takes the operator and the production team alongfor the RIGDT. So you start it's white, there's nothing there! You come up witha concept if the operators- or anybody makes a suggestion- you can just youknow, take your wite Bor or tape and draw something new, and I there's thisneat way to create engagement and involvement with the people who areactually using. You know th the technology, the operators know if theydon't see value in it. You know if, if o payers don't see value in thesesystems, you're affto a bad start so like the way that operators benefitfrom technology. If the technology applies pressure to their leaders tofix their problems, so the great thing with White Por is it takes them alongfor the ride. Technology is likely a better way to implement the end state,but it misses that journey to get to that end. State, so what we've seenwith our clients is is that you can get the best of both worlds by startingwith an extremely simple and basic implementation and take the operatorsalong for the ride as they're beginning to you know, request complexity so were,and you know the first phase is what is happening and in some ways you can evencreate like, if you're thinking of how to categorize time, if you categorizetime in nine different ways, let's just categorize that time in nine differentways and let the operators push for added complexity. So once you knowwhat's happening, then the next thing is, you know what has happened what'shappening, that's kind of like the basics and then the next phase is. Whyis it happening and as if you take operators along this journey, then yourmaintenance team and your supervisors and plant managers are along for thejourney and that's how you actually integrate technology into yourcontinuous improvement culture by coming in with this end, states whichmay look the same and saying implement...

...this now, you've missed that part. That,actually, you know, creates that connection and glue between technologyand continues improvement culture, and without that connection it just doesn'tfit. It's all really really good stuff there, Martin is there anything that Ididn't ask you that you want to add to this conversation before we put a rapon it yea. I think we covered it all here and yeah. It's it's an excitingtime in manufacturing. I think over the last year, with all you know, theturmial and change brought on by Covid you manufactors are talking aboutdigital transformation, an industry Ford Ado more than ever. I think,there's a lot of talk, a lot of concern. There isn't a lot of practical guidance,for you know manufactors, showing them how to actually take action here. So Ithink if I wee to start sumewit up to one thing here, you know Y, U K W tostart off with industry for O Kno for any size manufacture. The best approachis to start quickly, start small start simply and with that foundation, andthis is with your operators and with that foundation, double down on successand accelerate. If you start too big- and you start from the top down, it'sjust going to, you know- be on the scrap heap of failed industry, Ofortito projects and kind of continue. The pilot purgatory that's been goingaround for a while now, so I would also say that you know there's a hugeappetite for this technology. It hasn't necessarily the solution hasn't beenarticulated in a way that's resonating with plant managers, but in the sameway, where you know there's an nuber moment where people you know wouldnever jump into a car with a stranger to say like actually it's, okay, Igoing Ta jump in a car with the stranger because they just got thatvalue prop just right. You know there's going to be that Uber moment inmanufacturing, where manufactors recognize that this is the way thatthey need to run their operations to actually keep up. This is the way to doit. You know twice as a fish and spend half the amount of money. So, there'sthat uper moment coming when people are going to realize and N, you know,because of how simply this technology can be deployed. Nowadays, it's goingto go quickly, so it's exciting to kind of see that coming and I'm not sureexactly what's going to trigger that that moment, but it's definitelyconversations like this, where you knoyou know we're talking aboutpractical applications of industry,...

Portido are going to help us get closerto that and it'sdefinitely exciting to be I in this space at this time, Marin,great conversation today. This is really valuable. I think we're going tohave. This will be a very popular episode. So I really appreciate youdoing this. Can you give our audience a sense for how to get in touch with youand where they can learn more about Raven Yeah? So the main way to get intouch with me is unlinkedin and now on club host you got to check us out onClup, post industry, forionon club host. It's going to be pretty awesome,beautiful and then Raven Dot. Ai is the URL for software. So that's right allright! Well, fantastic! Martin! Thanks again for taking the time to join metoday, really appreciate it and then for the rest of you, I hope to catchyou on the next episode of the Manufacturing Executive. You've been listening to themanufacturing executive podcast to ensure that you never missed an episodesubscribe to the show in your favorite podcast player. If you'd like to learnmore about industrial marketing and sale strategy, you'll find an everexpanding collection of articles, videos guides and tools, specificallyfor B to B manufacturers at grilla. Seventy SIXCOM AHWARN. Thank you somuch for listening until next time.

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