Good day, everyone. And thanks for taking the time to be with us today. My name is Olivier Bonneau, and I'm the product manager in charge of the Cogou Workplace solution. So before we get started, just wanted to be, to to thanks Sheriza, Rosanna, and Anna, for this great discussion, on the future of workplace and setting the stage so well for me. This is always a thing. I mean, when I'm asked to present, on the same session, on on the same webinar as Louie are, ladies like Sherry Zalruza, and Anna. It's always an honor for me, and it always set, the bar quite high. So I hope I find I I deliver you something interesting today. So let's start with with with this, actually, where we come from and where are we going. Basically, when they asked me to lead the workplace initiative, I was, you know, trying to to wrap my head around, what it means, you know, from a couple perspective, what it means what the workplace mean. And, actually, I was like, alright. So what is the different workplace I used to to to be, in my professional life? And the one that, the the physical office that we have here in Montreal, the Coveo office are beautiful, you know. And actually, as an employee of Covey, I was very proud to tell my father, tell my mother and friends, Coveo over. If you come to Montreal, come come by. Gonna show you the these beautiful office. We have them right by the Bell Centre downtown Montreal, where the Montreal Canadian, the hockey team plays. So it's inside the Windsor, train station. Beautiful area. So for me, the the the workplace as a physical place was, something very appealing, something that I was proud of, and actually was making me happy to go to work every day and engage, with other people, other coworker of mine. So, I I started to work this presentation actually, from that angle, basically, what actually the the workplace looked like over the past century, and what are the concept that were used, during this time, to increase employee productivity. So doing so, I'm not kidding. I I did some I I I made some interesting finding, and I hope you're gonna find it get find that interesting as well. So let's get started with with this here, the early workplace. Actually, I mean, if I can summarize that in the one line, would really be productivity to industrial efficiency. One of the first attempt, to answer the question, how to build a workplace was a very methodical and mechanic mechanical approach. And actually it was in line with the second industrial revolution. Basically, it was assumed that science alone could provide a solution to increase productivity. So basically, you you you had, like, mechanical engineer and industry leader that actually, thought that having all the workers line up in endless rows of desk and having all the manager actually in peripheral offices would be a beautiful way to drive employee productivity. So for them, the layout of their office was like that and it was the best actually the best way to bring productivity inside the workplace. So for them, even if it removed the human and social element, the main goal was to increase productivity of work of the workforce through a strict layout, basically. Actually and it was considered back in those day a perfectly fine solution. So let's say that we're pretty lucky that it's not the case anymore. So now let's let's go a little bit forward in time and look at this beautiful house. Let's look at this picture. And this house is named, Fallingwater, and it has been designed by the famous architect Frank Lord Wright around the nineteen thirty five. So around the nineteen thirties. So basically, Falling Water is one of the most iconic pieces, of architecture in the last century. And now, I mean, just so you know, I mean, this house is not part of the UNESCO World Heritage, and it's a museum that actually people, can visit, all year long. So now if you ask me, Olivier, why are you showing us this house? So do not worry. I won't make sorry. I won't make any kind of joke with the work from home because of COVID story. I think that storyline have been used quite a lot in the last eight months. So, basically, the reason why I'm showing you falling the this picture, of falling water is because since it has been designed by Frank Lloyd Wright in the nineteen thirties, and he was already very famous at that moment, basically, this masterpiece here, has been achieved very late in his career, but, actually, it was actually made by, it it it was a a house with already a, you know, a big name following it. So, basically, but we can all agree that it it would be a beautiful place to work from home. So I can I can give you that? But the real reason, why I'm showing you Fallingwater, I would like to to use that to lead on to this picture here, which is the great workroom. Basically, in the same area, pretty much in Spain in the nineteen thirties as well, Frank Lloyd Wright actually designed offices, just like this one. And the great workroom, the one on the screen here, is actually, has been designed for the SC Johnson headquarter, in Wisconsin, actually. So really the story behind this workplace was was quite simple. Basically, the CEO and, you know, the president of s of SC Johnson back in these days wanted to actually create the best office for the best employee, basically. So for him, creativity and productivity can get along pretty well. So, basically, if he could provide the nicest office possible, in his mind, his employee would be happier and perform better. So, basically, his idea was that an inspiring and a beautiful place will help employee to perform better. So, basically, he choose Frank Lloyd Wright to design his own office. So simple like that. For him, it was just this is the best architect. I want the best office. So that's a match made in Evan, basically. So and he'd even ask mister Wright to design special furniture for that office. So, basically, he wanted to move away from the very rigid and mechanical approach of the workplace that was the norm in this era. We're talking we're we're talking about a pretty drastic change, in the span of thirty years. We came from rows of worker to beautiful office highly or with a high level of architectural inspiration, in a span of, you know, pretty much three decades. If we carry on with our quick historical tour of the workplace, so sorry. This one, it's a very interesting one. It's called the action office, and it's really productivity through enclave personalization. And this is something that we we might relate to. This is something that we might be, more, you know, that that might be the older of us maybe have actually, been the pleasure to be sitting in that kind of office, but actually, this is the ancestor of the infamous cubicle, basically. But so did you know that actually cubicle office were actually cheerfully constructed? I mean, personally, I mean, my first job ever, was in an office with only cubicle everywhere. And for me, I was sure that just that concept was just someone someday somewhere just decided to put some panel just because it made sense, and you just put panels everywhere. And it was just so easy to change the layout that for him, it just makes sense. And here come the cubicle office were created, but that's not the way it happened, actually. Here, the designer, it was, you know, that that kind of office here, the action office is the conclusion of years of research by a designer named Robert Prost. Robert Prost wanted to drive productivity through autonomy first, through autonomy and independence. For him, if we gave the employee the right to move furnitures around, you know, put stuff on the wall and actually build these will drive productivity. If employees could move and stand on their own without having to disturb other employees all across, you know, they can do that in into their enclave area, their own tubical moving and stretching what would be for them, but another way to boost productivity. And finally, and that was a very interesting concept, actually. When I read that, I was like, really? That's that's that's pretty that's pretty cool. You wanted to increase, and I called him here, meaningful movement. You wanted to make sure that actually if you would have to move around the office to meet someone else, it was actually important. So we wanted to manage create the layout of the office in a way that actually people will only walk around for, for a specific reason, basically. And all of these three for him were the real way you can boost productivity. So we kind of we we all agree it kind of makes sense, and it can be good driver to improve for, to improve productivity in the workplace. But it also serves quite a lot with utopia. You know? And sadly, I think utopia won here, and it slipped and created, the cubicle form that we know today, basically. So if we continue and we we we we go to the to pretty much today, the office of the modern workplace that we're all used to to to work in, basically, this version of the workplace, you know, it's it's through digitalization and collaboration. You know, the new the the modern workplace is seen as a highly dynamic and interactive area, where collaboration and direction are central to everyone's task. You know, it's not it's we have, you know, open room with whiteboard. We can chitchat. We have, you know, it's highly mobile, so it's really dynamic. It's, so it is the idea here that if we if we can improve, you know, social interaction, we could improve, productivity in some way. It's still physical, yes, but still, mobility is becoming more of a reality now. You know? Small and big company have workforce scatter all around the world. So basically, the workplace as a physical space is not the norm anymore, even in the more even in the in the modern workplace. So when we look into that from from that point of view, from the workplace as an architectural spaces, we realized that in the last century, it was actually the key driver of productivity. How can we make sure that people are productive? So the area on which work would be, the the the, a vector, in that equation. But what happened what happened if the common place is not there anymore? So since the common the common denominator was to drive productivity through space organization, what if there is no dedicated space to for the employees to work in? So, basically, this question has been there for for some time, I think, And, basically, we we just saw saw it in the one hundred years of workplace, but, basically, the fact that we Coveo the space and, like, Louis, this was saying what Bozama, at the very beginning, you know, COVID just accelerate all of these change. So basically, we knew that, but COVID just put it, on the top of the priority list of everyone. So based on these assumption so if for years being grouped was a proxy for performance and efficiency. So now let's ask so now the question, you know, in the context of this presentation is how can Coveo technologies help to improve productivity and be a contributor into closing the productivity gap that was used to be filled by the space organization. If you remove space organization, you have a gap in productivity. How can we help you to bridge that gap now? And I'm not implying that Coveo will help people to interact with each other more. There are already great application out there for this, such as Slack, Zoom, Hopin, Microsoft Teams, so and so on. So but Coveo can help employee to access the right content from multiple sources in a highly personalized and contextualized fashion. And this is how the Coveo platform is built, is to deliver what is relevant to a specific individual at a very specific moment of need. So how would how do we do this? Just to make sure that we're all on the same page, basically, I just gonna cover three core, feature of the Cargill platform. And this is and then I I will expand on all are they used to actually provide relevance inside the workplace. So the first one so let's let's basically, let's draw, here a parallel between the workplace environment and the Coveo platform technology. So, basically, as I say, we have three core feature. So the first one is our analytics stack. Basically, we provide a rich set of analytic tracking API that track interaction between employees and content. Basically, in that example here or analytics track who searched, clicked and viewed what. So through analytics, we can extract what in video what individual are searching for and what are they consuming. So on the Coveo platform, we're gonna use these analytics, the relationship between people like these three on the screen here. They are obviously looking at the same document. They are interacting in the real world. But from an analytics perspective, we understand that as well. So we build reporting. We have advanced reporting capabilities. Basically, since we know who search and click and view what, basically, we can build report and we can help you guys to understand what is seen more often, is there any content gap in your internal doc documentation and so on. So, basically, this is a very useful tool to better understand your workplace, dynamic, basically. So moreover, we build machine learning on top of these analytics data. So here, without, I mean, without going into the all the details of how machine learning works and, how it's designed, basically, we use machine learning to extract the the trend of the moment. That's the easiest way I can say it, basically. Which are the document that seems to be the most popular at the very moment based on employees' behavior, basically. And so we build our machine learning on top of these analytics as well. And finally, for the workplace, and this is where it's really getting interesting here. It's for the workplace, we use our analytic to understand the inner relationship between employees. Like I said, these three people are obviously interested in the same document. And on your side, we are interested to get this relational information. The other part, the other feature is what we call the Coveo index. This has been there for for since the very beginning of Coveo. Some of you might be familiar with that concept, but, basically, the Coveo index, it's where we we index all the content from all the sources that are available to us. So SharePoint, Google Drive, Jira, etcetera. Basically, we can virtually index any type of content and centralize that, in the same area. So in other word, we know which document is out there and and available to your employees, which mean that we centralize not only the document, but we centralize the metadata as well. So we have a variety of connector that update and crawl your sources automatically from Oracle platform, and we bring all of that the this information inside our index, then now, you know, let's consider the author of a document in the time of creation as very meaningful meaningful information for the workplace. So basically, who is the author of this document that these three people here are looking at? Is it one of these three or is it that fourth person that is not there on the screen? So, actually, who created and who updated the document is for us is for us, again, very valuable information that we want to leverage inside the workplace content discovery experience. And finally, our content discovery API. Basically, we provide an API that allows you to retrieve content based on context, condition, persona, and other set of rules, basically. And just to, a little parenthesis here with, you know, Luis, he's saying, like, it's a persona anymore. It's person and he's totally right. It's a persona, it's employees pretty much as a person. So basically our API use that kind of information and fetch back the proper document. So basically, this API's job is to answer questions like this. Like, I'm Olivier. I'm working in the product team, in the Montreal office, and lately, I've been working on a new service with the machine learning team. What are the document that are the most relevant to me at this very moment? So this API will fetch the best content for me from the index based on the stated condition and machine learning will put a little bit of these magic inside this equation. And then I'm going to receive a set of document that are highly personalized to me, to my current need basically. So these are the basic concept that applies to every Coveo solution. The analytics, the Coveo index, and or content discovery API. But there is another part that, is unique to the workplace. And this is this is when I was I I start to really work on this project that it it became clear to me, and I hope I gonna, make it as clear for you, with my few next slide here. So, again, unique to the workplace. There is a a specific point that is, that is very interesting to look at here. Let's look at this slide here. So we have five individual obviously discussing a common topic around a central person. Back in the day, if one of them wanted to borrow a book or collaborate on a science paper, you know, they knew who to ask, but still they had to meet them in person to share the knowledge. You know? Their relational network was in their head. You know? They they they knew each other so they can interact with one another. But what if there is a sixth person that missed this meeting over there and wanted to know what happened? And what if that only that sixth person only knew one of these four student here? Basically, it will he will find the the the information he's looking at, but actually will have to ask around his network to find out what he missed, what was relevant to him, and, you know, he he he he he he will ask around his friends and and so on. So, basically, his relational network, I call that for the office, the the office relationship network for lack of a better name, let's say. So in this picture, these five persons share a common interest, which is what is on the blackboard, which mean that for that short period in time, they were all linked together by a common topic. This relationship network is as dynamic as the people and the interacting topic. So basically, it changed over time and basically what's insist, what is interesting for you today might be very interesting, may maybe might be very different for you in one month, basically. So the fact that people, you know, relational network change over time based on what they're working on, based on their different topic of interest change. This is a very interesting vector to actually use in the relevance equation. So let's take another jump in time here, and let's imagine the same meeting, but that would have happened, you know, last year. Let's see. So, basically, these folks would be interacting on the same project, but through PowerPoint and through a Zoom meeting, basically. So because this meeting happened virtually and they share a common working document, using Coveo technology that I mentioned earlier, we can record this valuable information and reuse it later. Basically, we know through a common point of interaction, which is, the PowerPoint and the virtual meeting, we can digitally build that office relationship network that is unique to each of these five individual, basically. So that's six person that missed the meeting. So, basically, if it was, using some kind of intranet portal, basically, through the Coveo technology, Cavio would automatically suggest them that PowerPoint presentation here because his relationship, his relational network will actually indicate that this individual is linked to to some way to one of the one of, or the other people in that meeting because maybe, they share a similar, they search for the same document, maybe because the the the edit or they created and they collaborate on the same document. So, basically, the Kavo platform will answer this question. Since you linked you are since you are linked to at least one of the attendees, because you interacted with them on another document, we think that this PowerPoint on the Hubble Space Telescope might be a good fit for you, basically. So this is an example that shows how Coveo technology can help you bridge the productivity gap in the simple use case of general document search and discovery. But, you know, the same concepts apply to every other workplace area, basically. And let's have a quick look at what could be these, the the the these other use case, basically. So, oops, not this one. Sorry about that. Here we go. So let me a little bit more specific here. So and I will highlight, you know, different ex employee experience based on the Cogu technology and the concept of office relational, the of the office relationship network where, the relevance can be improved, basically. So Internet portal, just like the example I just, I gave before with, our friend Richard Feynman, and he's a student. So basically when searching for general content, so let's show document from every available sources that are contextually aligned with you. So simply said, let's make sure your employees have the best information so they can start their day properly. So I call that as well the newspaper use case. You know, when you're reading the newspaper, you don't know beforehand what you would like to know, but basically when you read it, you enable yourself. So the intranet portal, you know, when we you want to, recommend document to your employee, this is really the idea behind that by behind this. By offering highly personalized document, we can enable better your employee. For instance, whilst while providing new knowledge, you know, organization are becoming more complex, with more employees. So scaling employee enablement, start is an ongoing challenge. So, basically, if we can unload that kind of the the the burden, at least a part of it, onto the Coveo engine, basically, we can, improve the overall, you know, personalization and content discovery experience in the use case of, you know, onboarding, enablement session, and so on. The other one would be internal self-service. And I know that, Rosanna had touched on that, briefly, basically. But, and she was basically telling us, I think the HR portal went three x, in volume, when college started, basically. So providing a meaningful self-service and make a lot of sense here. And it's on not only for HR, but for IT as well. So by leveraging so let's let's try to frame it like that here. Basically, using Coveo solution in the internal self-service, basically, you leverage content that already had success in the same office and which will improve the success rate of finding the right answer for a specific individual on a specific topic. So maybe a coworker of mine with similar interests and similar, you know, relation relational graph, had a task or an issue that he solved successfully. So I would like to leverage this, this information. So because we are related together, and they, self-service ex the self-service experience can benefit from that, new vector of information, basically. So so improving these different area can drive positive changes in, you know, various business metrics. Speaking of which, what would be these specific metric that we can improve, using a Coveo technology? First one, I think we covered that, pretty well, productivity. Reduce the time employee spend searching for relevant information across multiple sources. So this is already something pretty interesting here. The other one being cost, cost avoidance. You know, through the Coveo platform, you can scale your self-service offering inside the workplace. More content, more employee can be managed with minimal effort to our cloud platform. The third one would be cost saving. You know, having old and duplicate system that used to be your search engine can be now replaced by the Coveo cloud solution. Since you're gonna unify everything inside the same platform, you can, you know, remove, redundant system that are useless. And finally, driving revenue. You know, for for engineering consulting, firm, having a better, quicker, and more relevant access to knowledge can have a positive impact on output and time to review. So basically, that's good. Having positive impact on metrics is is awesome, but what does it look like, in action? So I will show you here, couple of example of how does it look like for real. You know, when you bring the Coveo API inside your solution, where what can it looks like, basically? So here, classic use case, the intranet portal. Basically, the idea here is that how can you blend the Coveo API functionalities inside your already existing, intranet portal? And like, Anna, Rosanna, and Sheriza were saying, I mean, they already use their own intranet portal framework. So the goal here is to bring Coveo inside of it. So let's imagine we have these two section here that are internally managed, news area activity calendar. You know, the the you you manage that. It's your own. But the overall experience could be improved if on the same page you bring the Coveo workplace API to bring content from multiple sources personalized to the to to to the employee that is currently logged in. So these two area here, these two gonna propose dynamically content based on the employee personal profile, network, and so on, basically. So as mentioned earlier, this is a newspaper use case. We want to recommend content so the employees is enabled with the latest and greatest information. And we do that by using, you know, or analytics or index or content discovery API and factor in that the relation the relational link that people have with one another in the same department, from a hierarchical point of view or simply because they view the same document or they edit the same document. Another use case, quite interesting, part of our, let's say, self-service in HR and IT, basically. We can integrate this concept inside an employee self-service portal such, as ServiceNow. We can improve, for instance, the case deflection rate by dynamically proposing solution based on the case description and the employee relationship network and other contextual information, basically. So here, when you have, you know, hundred and thousand of employee, you would like to make sure that your internal, you know, HR and IT people actually work on the very hard cases. And, you know, the simple one and the one that could be self serve are actually case deflect using the the Coveo service. So the issue is I can move my chair up and down. I'm sure there is pretty good document that can help you to fix that issue. So, basically, what if a Coveo a coworker within your professional network had a similar issue? Leveraging his already solved solution might be very valuable to the current employee. Let's say, that he's looking for a similar question. So the these are two example on on how you can leverage Coveo Workplace solution. And there is other, you know, there is many more use case to explore. So based on all all of that, based on everything that we've been discussing, our world has evolved and so has the workplace. We came basically from rows of worker lined up to a concept of a highly digital and decentralized workplace. Now companies big and small can have a workforce can have a workforce all around the globe, and everyone is interacting through technologies. The workplace as a physical space now has a lesser impact on productivity. So with Coveo, we try to bridge that gap by using various application, to get people to work better together while being in different places and time zone. This is why Coveo technology can be used to close this gap even more. We provide the platform that know who interact with who through content and analytics. Based on this, we can leverage employees' context, relational information, intent to deliver the relevant content. So, basically, we use machine learning and or API to propose the right content to the right employee at the right moment. And, actually, I call that the three r, the right content, right employee, right moment. And, basically, for us, this is this is pretty much the the main narrative line of our around which we build our product here. So, basically, the employees when involved into a content discovery experience, they want to know before they want to, you know, they want to know. They don't want to search. And I think it it makes a lot of sense, you know. Being part of, you know, an intranet or, you know, an employ, being an employee, you know for a fact that actually your your portal, your Internet portal know as a lot about you, and there is no excuses to not use that to to improve the the the discovery experience. At the end of the day, employees are consumer in their personal life as well. So their expectation, match that basically. So which is a way to say, how can you make sure you expose your employee to the best and most relevant content without having them to ask for it. Therefore, enabling them and setting them up on the day for for the day. So, again, this is the main premise of our workplace solution, and it drive how we build our product. Employ employees want to know, they don't want to search. So on that note, I hope you I hope this presentation helps you understand or view on the workplace and how our technology can help create a great employee experience. Thank you very much for attending my session. Hope you find this presentation as interesting as I had, creating it. If you want to learn more, about our the workplace offering, my friends, Juanita and Wim, work both of them work with me on this project. We'll host a webinar in two weeks from now. So, I encourage you all, to attend if you can. So, Juanita, any question? Anything else? Yes. Thank you, Olivier. Really great presentation. Thank you for taking us through the the workplace Coveo time, taking us through the innovations today and what Coveo can do. There were a couple of questions that came in that I think are important to bring up. So the first one, I'll ask is around the history, of the workplace that you just covered. So as a product manager, do you see or have you run into cultural pushback or any sort of resistance when using the technology, especially around machine learning? So any thoughts on that? Yeah. This is very good question. I I used, I used to be in charge of, the product management and the machine learning team as well. And that kind of question arise pretty much not only in the workplace and pretty much every time you would like to use machine learning as a driver of relevance, basically. And I would say it's it's a little bit less than ten. It's a it's a little bit easier now, basically. The early pushback, it's it it it was basically because people thought that machine learning was just, you know, some kind of crazy magic magician inside a box, basically, that would just randomly answer things and say things that you would not expect. So education was actually, the main challenge here. Once people start and, you know, stakeholders started to understand what was machinery exactly, what it does, and for which reason, and under which constraint, Actually, they they would accept that, and it just makes sense. At the end of the day, it just makes sense. But the biggest pushback was actually, the lack of trust in using machine learning to actually replace, you know, to to improve the content discovery experience. I would say that people wanted to have full control on what is being shown on the screen. So if you search for something, some company would like to control one hundred percent of every document. Having machine learning, they feel that they are not having the this whole control. So, basically, education was, the way to address this pushback most of the time. Awesome. Thank you for that. So a little a little, problems on the trust side and trusting that machine learning will make a difference and, exponential difference for organizations if people just sort of are a little more hands off. Okay? And yep. On the same topic, kinda related to trust, so Jay asked the question, which is, what do you think about allowing employees to make comments, apply metadata on documents to help improve that overall personalization. So what are your thoughts on that? Yeah. The the the classic thumbs up, thumbs down question, I feel. So, yeah, it makes sense. I mean, I and, you know, I'm not saying that's a bad idea, but, basically, it is what machinery does by itself. The actually, from the Coveo perspective, the fact that let's say that an employee would put a thumbs up or a thumbs down on a document if it if if it's the right one or not the right one for a specific question. It is, the the issue I mean, let's let's let's start with what I see as being the issue with that is it's it's, it's a feedback. It's a static feedback in time, basically. So as, your thumbs up or thumbs down just gonna remain the same in time. And even though if, you know, the train the trend changes, maybe you got it wrong. Maybe your thumbs up was actually you know, you've got you you the employee might have got it wrong. So it's very hard to change a relevant the relevance factor, when you you you put some kind of static rules like that. On the flip side, when you use machine learning, this is exactly what it does. When you're searching for a document, let's say, and you click on it, the fact that you click on it means this is a thumbs up. If you don't click on it, this is a thumbs down. So this is how machine learning is being is being trained here. We search for something. If you click on it, it means thumbs up. If you don't, it means thumb thumbs down. This is the positive of the positive outcome that we train the machine learning on. So, of course, when employee can't get it wrong, you know, we search for something, and it's you click on a document that wasn't a good one for him. But when you scale that to thousand of action, I mean, the the overall trend gonna give you the the right thumbs up and the right thumbs down at the right place. And over time, if the trend of the moment, social trend, employees trend, whatever Coveo around, that gonna that gonna change over time. So it's it's dynamic. You're so it it's really where, I draw the line between having, the employee, like, putting, tag on document, basically.