Fireside Chat on Technology Trends in 2022 with Francis Hintermann
[Music] hi good afternoon to those of you joining from new york and elsewhere on the east coast and good evening or good morning depending on where else in the world you are i'm rob siemens i'm director of nyu stearns center for the future of management and today it's my great pleasure to welcome you to our first strategy speaker series event of the year and my honor to introduce our our two speakers accenture researchers francis hinterman and nyu stern vice dean and professor jp eggers francis hinterman is the global managing director of accenture research a team of 300 researchers based in 20 countries around the world in this role francis is responsible for shaping and delivering the thought leadership agenda of accenture an i.t professional services firm with over 500 000 employees worldwide francis a graduate of sciences po in paris joined accenture paris in 1998 to create the strategy research team he then developed it across europe latin america africa and asia pacific before taking his current role in parallel francis has been supporting financial services clients in various research consulting roles both in france in europe and at the global level francis has been the sherpa of accenture's ceo at b20 and g20 young entrepreneurs alliance summits between 2011 and 2018 representing accenture at b20 g20 summits in france russia australia turkey china germany and argentina his current area of focus is analyzing strategic and economic impacts of new technologies such as artificial intelligence on companies priorities in public policy making and it's a topic that we're going to dive into in a lot of detail today in addition to the many other things that francis does i'm honored to say that he currently serves on the external advisory board for nyu stearns center for the future of management so we're very excited to have francis join us today excuse me to join us today jp edgars is my colleague he's the catherine and peter kellner professor of entrepreneurship and management and organizations here at nyu stern he is also currently the vice dean for mba and graduate programs and the director of the one year tech mba program jp received his phd from the wharton school he studies both the behavioral processes of innovation and the evolution of organizations technologies and industries his teaching includes strategy innovation and business analytics with a focus on a blend of the three before uh turning the floor over to our speakers i just have a couple of very brief announcements first um you know welcome to all the audience that's here please feel feel free to submit questions for francis and jp throughout the session using the zoom q a function we'll start with a discussion between francis and jp um and then we'll turn to audience questions after that second we would love to welcome you back to future programs and keep you updated on the research that we're generating so if you're not already on our mailing list and you would like to join please sign up on our website which is stern.nyu.edu cfm all right without further ado let me turn things over to my nyu colleague jp edgars thank you rob uh really exciting to get a chance to be here thank you everyone for joining us for this conversation today and most importantly thank you to francis for for taking the time to uh to chat with us today and talk a little bit about predicting the future and trying to think about where things are headed uh for all of these interesting topics um maybe before we get started in too much detail can you maybe spend a little bit of time tell us about the work that you do at accenture research and how this fits into accenture overall yeah thank you jp and rob for inviting me today my pleasure to be to be with you um at the core of it uh accenture research is part of the office of a chief strategy officer of accenture the chief strategic officer is currently named bashkar gosh he's the one who is really thinking about the next steps of a strategy for accenture as a corporation and as you know accenture is a corporation of around 50 billion dollars in terms of employees we've got more than 600 thousands around around the world and hence there are many questions around next steps in terms of technologies businesses geographies that the company shall investigate so uh we are uh finance uh by accenture it's an investment of accenture uh and then of course on on the back of that uh we are also sharing some of the insights that we develop with our clients around the world with our communities of course and more generally speaking all our shoulders in the sense that accenture being a a large company is as good as an intent to help the communities around you know us uh to grow as well because we know that to be successful we need to live in thriving ecosystems and the the way we distribute our research our fault leadership is a way as well to support our steps around the world so maybe actually just to help kind of frame some of these discussions actually i might ask about process for a second so um you know i think i think when people think about trying to do research or think about the future of technology or technology trends um you know there's there's anything that ranges from like uh you know maybe specific research driven ways to do this versus to you know prognostication and you know guesswork by uh by numbers of people why why don't you tell us a little bit about how you go about these things and like what is it that makes you confident that you're that you're that anyone is able to do a good job at trying to predict these things uh it's a it's a good question it's a very good question uh i would say first of all in terms of the positioning of accenture research within accenture and the specific value that we aim to bring is really looking at the business impacts of emerging technology so we are convinced at accenture that technologies generally speaking grow exponentially the way that businesses organizations absorb these technologies is not growing exponentially so there is a gap in between the evolution of technologies and the way that companies absorb them and we work on that gap part of our job is to help organization to close that gap or at least to reduce it as much as possible and as we are convinced that accenture that the waves of technology changes are getting stronger and faster along the years it means that we have to be extremely precise on the way we assess these waves the way they impact businesses the way they impact different industries different functions and how different function leaders c-level executives can actually absorb that into their own organization and create value with it we are not uh as such a technology organization at accenture research we've got accenture labs which is an organization dedicated to really studying researching developing new technologies we are working on the absorption of technologies by businesses and so the way that we develop methods and tools to enable that is really to develop a portfolio of of techniques and the the ones we work on right now which to me are the most exciting for the future of business research is on one end uh to develop ai at the core of the research as we do we've been speaking of course about data-driven business research for a while it's happening now and it's happening not only in terms of big data it's happening in terms of putting ai at the core of it when you think about all the the data that you can leverage uh not only on social media people speak a lot about social media but look at the you know all the comments put by employees on on job site put look at all the the way that people put their profiles on internet and then you can see them evolving from one country to another one type of job to to another there are lots of high frequency data that we can now absorb model in order to attempt to show the way that it's going to be for for companies going forward so for me it's really putting ai at the core of it that's the first thing and and right now if you ask me you know who are in the team compared to five years ago we've got a lot more data scientists than we we used to have former consultants we used to have industry experts now at the core of it we've got data scientists working with the rest of them so that's one one leg there is a second leg and the second line is all about experience experience what we call experience for research is that we used to have you know focus groups in the old days now it's really focused group online at scale at speed and and that is changing a lot we we may speak today about the metaverse to me that's part of what the metavest can bring in terms of research is that we can actually run experiments real time in environment online that we could not use before and when when you combine the insight that you've got for this data-driven insight with the experiential research then you can at least we think we can develop some uh direction for for our company first of all and then for for our clients as well you know when you ask me how confident i am i'm confident about the way we analyze uh the way technologies evolve because we've seen that over the years as i mentioned we've seen the waves we measure the waves we look at them and on that i'm confident and if we have made some mistakes in the past and of course we've made some uh been more by um being cautious on the way that technologies were evolving rather than being too optimistic and and so we we that's that's where i think we we are we are careful about now that technologies are progressing at a speed which is uh which is amazing but of course there are issues to to look at issues to look at in terms of the way that companies can absorb these technologies and create value with with these technologies uh issues about um you know digital nationalism to use an understatement of course that can impact the way that companies can absorb that uh across the world and last but not least uh the the inclusion and diversity uh which may seem uh unrelated to that initially that actually we think is at the core of it is that at the core of research we speak about data but it's talent it's about people and the way to develop efficient research team these days we need to get a diversity that frankly we didn't have even five years ago and that we want to have in the us in the uk in south africa and and in other countries where we've got an emphasis now on being making sure that we're bringing that diversity angle from the very beginning of the defining the research protocol and that's something that we didn't have so much in the past and that we want to have at the core of it because it's a way as well to enable our research community to to thrive in the future cool um so what you're short short of it is a little more robust than armchair prognostication hopefully so but no no clearly clearly clearly it is which is which is great um and the whole reason to have the conversation um i i am going to selfishly go off script for a second here um you talked about this gap between uh the rate at which technology is changing and evolving and the rate at which companies are able to absorb and kind of get benefit from those technologies uh without going into too much detail because i do want to move on to some other some other topics why why does that gap exist in from your from your perspective why why why why are companies struggling to absorb these new technologies and take advantage of them or at least what are some examples of of ways in which you've seen that happen yeah yeah it's a it's a it's very it's a very good point uh just on on the term prediction uh one interesting thing i've seen and in in the past few years at least a lot in scovid is that scenarios are back so it's it's a bit less about prediction there is only one feature it's a little bit more about let's envision the different features that may happen uh and and i used to work on scenarios 20 years ago to me there is a revival of a scenario approach now powered by data powered by everything we do online which is bringing some new insights uh to the way we can look at at the future without necessarily being you know extremely focused to a point of being stuck on one view of of of of the future on the uh on the point of of i mean at the core of it change is hard that's what it is when uh when you look at large organization and as a large company we work not only but predominantly with large organizations in large organization you've got legacy processes you've got legacy i.t system and when you deep dive on legacy i.t
system you've got a fair amount of technical debt and so that means that lots of uh services we would we which would genuinely like to change are in fact facing obstacles in terms of the the legacy systems the legacy processes uh and and the fact that lots of uh people have to be uh re-skilled upskilled uh and interestingly uh enough in in most of our research on on these obstacles uh when we speak to uh c-level executives overseas suites uh they quite often mention the issue of talent first that the people do not have the right skills anymore actually when we speak with employees in most cases employees are eager to learn they're eager to learn more and generally there is this gap between the c-level executives who are extremely focused around to create value in the short term let's focus on the system let's focus on the processes whereas in fact part of the solution is in upskilling rescuing employees who are a lot more ready to do it than generally assumed so to me it's it's a lot uh it's a lot connected to that um certainly you know i think for for me certainly as someone who's spent a lot of time working with big companies trying to be innovative um you know this this gap and the reasons for its existence and why firms struggle to kind of take advantage of the technology that's out there um is i think a fascinating and important question um so um but as we talk about technology evolving and we talk about some of the the key trends that are out there um i i feel like i'd be remiss if i didn't start with one of the bigger buzzwords in the in in that's out there these days and talk about the metaverse a little bit um you know the the cynic in me feels like whenever we start seeing new terms like this uh signs of vaporware just instantly come to mind and i'm just like who knows what like no i don't even know how to define this let alone what it's actually gonna do what what's what's what what's the there there when we talk about metaverse what is it and especially if you think about kind of both short and longer term what is this going to mean for businesses like what is this going to mean for for the way work gets done or education or all kinds of things that could be relevant for thinking about here yeah no no no it's it's a fair it's a fair point uh jp and uh we just finished uh a survey of c-level executives about the vetavers of course and and uh what we've seen is that uh there is a polarization on one end you've got 80 percent plus of c-level executives who have heard about it you know because it's the buzz has been so big since last fall that really nearly all of them have heard about it so they've got questions now if we ask about them a few more technical questions about you know what's their understanding of it what they want to do in it then we've got a tiny minority uh in our survey it's something like 15 percent of them who said you know i'm familiar enough with it that i know exactly where i want to to invest going forward uh and so we've got to to to address that uh about the the metabolism um your your point is of course uh uh a fair point in terms of being uh cautious about it our position is slightly different uh in the sense that uh uh we understand there are a series of obstacles that uh we we can discuss in terms of technologies in terms of talents and readiness in terms of as well uh what we would call a responsible metabolism right and uh i'm part of a generation who helped to promote internet uh from you know from the the early uh beginning of this century uh there are some aspects of it which we do not want to see in the metaverse and and we are extremely careful about that and it's part of the way we look at it at accenture so there are definitely obstacles risks that have to be assessed uh properly having said that we believe that that approach that this series of technology combined in the metaverse is really going to change the internet and that we're going to see something happening which is going to be at the scale of what we've seen 20 25 years ago uh with the internet because the the possibilities of it the potential potential of it is so strong in multiple dimensions that it's going to revolutionize enterprise at the end of the day now we can speak about the pace we can speak out where it's going to start and succeed or and how we can learn from you know early failures potentially but we we can see at least three areas where it's really going to change the way enterprises are going to function in the future uh the first one is the one where people are a lot focused today is around customers it's around you know we can see things happening in branding we can see some cells started to happen we can see there that there is there is a big potential of course but that's to me that's just the tip of the iceberg uh very a lot more to to come uh in the enterprise world first of all in terms of production thinks about think about digital twins for instance think about lots of things which are in the physical world today which can be a mirror in the uh digital world and for the metavest combined and connected and that's that's the potential that metavez can bring there and we are convinced that in terms of production is going to potentially bring lots of value to to companies and the third dimension is around everything which is connected to two employees actually uh at accenture uh we have already uh in in the u.s uh distributed uh through you know during the covet time uh sixty thousand headsets oculus at sets to enable a better integration experience of our new employees of course our offices were were not open across the us during the coveted time and we have been recruiting lots of people we could not welcome them in our offices uh to offer them an experience of getting connected to their colleagues through the metaverse has been one way of developing this experience of belonging to a team belonging to a company and then contributing to it so that that's just one aspect of it but you can think about training you are mentioning education uh in the enterprise world it's about training we're convinced that lots of the training is going to happen in in the metaverse uh in the future we you know maybe on on your end you have started to to use it on our end we've started our training we're learning work from what works what doesn't work but we are starting our trainings uh in in the metaverse as we speak so so you would so it's interesting thinking about these these three kind of broad ways or areas right you talk about customers production and employees um i think maybe in line with this i mean the customer piece feels intuitive right i think people have a sense of what this might look like um uh to some extent and i think the employees thing almost feels like an extension of that to me the production one is the most maybe the maybe the least obvious of the three um you mentioned digital twins like you know can you give us a hypothetical use case or something like that for for the way work might get done in the future if uh down one potential path for how this might this might look they get a sense of how how is the metaverse how might the metaverse affect the production the the actual process of creation and production and business activity yeah now i can give us you know without going to specific times the examples on which we are working right now uh think about uh factories uh uh factories of um suites for instance uh and if you end up at the end of the production line uh you may end up with some defaults you end up with some boxes where you don't have the right uh components and uh the the point of having these digital twins in the metaverse is that if you build that in a way which is reproducing what is happening in the real world so to speak you will be able to identify a lot faster where we should happen on on the value chain and how to repair it and that's that's that element of uh identification of the issue then repairing it faster of course is you know enabling more productivity uh for the world factory and therefore for for the company and that's just just one example of of the the type of uh use cases on which we work today i think it's fascinating thinking about you know this idea of a digital twin and and the way we you know for all of us who uh grown up with in some sort of video game basic culture where the idea of you know sliding around a room to investigate different things that are in a space you can do that very quickly but if you imagine trying to do that in real life it would take a lot of time to crawl over machinery and look under this and look at that and this idea that you could do that um i to me that's a very interesting and intuitive way to think about one of the benefits of being able to make that happen um i'd have to think that there's got to be a lot of other technologies that would have to play a role in some sort of a process like that i mean in the sense of you know how i understand the the the metaverse would be a way that you interact with that digital twin to try and understand it but how does the digital twin get created that's still not not a trivial process i would think and i'd have to think there's other technologies that have to feed into that potentially correct yeah absolutely and i like the way you think about it because that's the way we look at it is that it's not one metabolism in one technologies a combination of various technologies which brought together can enable to to create more value and there is not one single metaverse today in one single solution it's really around this combination that things are going to happen in the future so if you are um if you were going to start and and if i can push you a little bit on this if we imagine that uh that the metaverse and obviously if you talk about um employees i think we could imagine that this may affect uh all companies relatively similarly at the same time right training on boarding like things like that obviously companies that are engaging in more virtual work may make more of it take more advantage of it than than ones that wouldn't but i'd have to think that things like the customers and production elements of this are going to affect some industries and some types of firms far faster than other ones who's at that front edge who should be nervous if they're if they're in that 80 that you talked about and not in the 15 uh at this point in time any any thoughts on that yeah no it's a very good point because that's part of the work we do is you know we always trying to map on the s-curve first of all how steep is vesco right and and second what is the the path of different industries and which industries are are in front of others and i think the the uh what we have found so far and it's a little bit counter-intuitive is that uh generally we think about you know it's going to be the tech industry first because it's it's all digital anyway and you've got lots of early adopters of new technology so that start somehow the usual business process and and what we have found so far in terms of our research into our relation with our clients is that actually you've got a fair amount of over industries we are which are now experimenting now let's be let's be precise experimenting doesn't mean to scale up right it's experimenting uh but you know if you think about the retail industry if you think about the consumer goods industries you've seen plenty of examples in in the news of these uh large players getting involved in creating a shop in building some real estate in selling some products and even more interesting than selling the digital products is you know offering a combination where when you buy the physical product you've got a digital product as well and they both combine and typically it may it happens now with some car manufacturers where you can buy your physical car if you like and you've got your digital car in the middle at the same time and and uh and to me it's a it's a it's an interesting example because you know you would you would not necessarily think about the car manufacturing industry as being a front runner in the metaverse but actually some are already there and and already investing there so when you look at all these industries you know consumer goods retail automotive you can look at all these um consumer oriented industries on top of the the technology industry and then uh it's there you've got the group of manufacturing industries where as i was mentioning uh earlier on with you know the digital twins and some of these aspects we can see some experiments going on as well so if if you know if if you look at the broad picture i would say that the b2c the consumer goods you know consumer industries definitely yes and maybe a little bit more counter-intuitive but in the enterprise world in the manufacturing world lots is happening as well so in other terms no industries immune jp so if i can maybe uh in this this kind of looking at one of the questions that came in from stephanie in in the in the chat and just a quick reminder to everyone feel free to put questions you have in sorry in the q a in the q a in there we'll we'll try and look at them um you know i can almost or maybe i can try to visualize a way in which the the idea of a digital twin right a digital version of some sort of a physical process or or activity feels like it could play a role in some sort of like distance uh healthcare practice or something like that is that something that you is that a connection that that feels real there or is are you thinking that healthcare may be um i mean it's a lot harder to attach sensors to a person the way you can attach it to a machine so it would be hard to create that digital twin i don't know what is is healthcare some somewhere on that spectrum or is that is that a very different kind of a of a use case for something like that in your mind i love your question because uh you know if uh always when we look at these new technologies we try to look back at different technology waves and what was happening at the time but maybe a lesson for this wave and when we look at digital and some of the previous waves systematically we find two large industries first one is health second one is education no offense gp but uh it's it's because of the complexity of it uh of course uh education the complexity of uh teachings complexity of the organization as well so you know the evolution is all most often step by step and then really revolutionary uh and and second health because of the complexity of the organization as well and because you are speaking about the life of people right and and and so it's uh you can mess up things in consumer goods to some extent uh you know you've got to take over uh um security when you deal with with health help and what we have seen uh throughout kovid is that these two industries which tended to be laggards in previous waves with the acceleration of digitalization since the start of kovid there's been lots of ketchup actually and education you can speak more about it than i can but i've seen some things happening which we thought were not possible actually been happening in education online and similarly with health there have been lots of examples where there were some regulation which were preventing something to happen online which have been happening online so long story short there is lots of potential here and we are confident that things will happen but again we have to be extremely careful in terms of regulation and in terms of the uh the the responsible approach in this industry and that's making health a particularly complex industry to address it okay um i'm i'm sitting here looking at some of these questions debating whether to spend the entire time we have here talking about the metaverse or not but maybe at least a little bit i'd like to kind of shift um though obviously as we were kind of getting it all of these technologies are intertwined to some extent um i'm thinking about that intertwining i i feel like for a long time there's been a discussion of automation as kind of one set of processes um and then just lots of talk about big data and analytics for a while and those have been kind of separate but as we move into an ai world whatever one's definition exactly is of ai those two things start to become more and more intertwined um what if if if you know you gave us a thumbnail on on the metaverse side of things talk a little bit about kind of ai and the way in which this you could imagine this reshaping businesses um in in the types of businesses in coming years yeah yeah now ai is a very interesting one very complex one of course depending on what part of the value chain you you want to address uh we've we've done a research on the way that companies were absorbing ai in 2019 so just prior to kovid and we are completing one just now that we're going to publish in a in a few weeks so just to to see how it has evolved in between 2019 and now and where our predictions right at the time and and and what's happening now and by and large um what was happening at the time in 2019 is that we had lots of uh promising pilots around the world in lots of industries in lots of large companies the big issue was around scaling up there was lack of examples on scaling up ai speaking about big data as you were mentioning but in terms of really combining that in business model in business processes with the right talent and creating value at the the level of a company and not the business units or just one subsidiary that's something which was not happening fast forward three years uh we were cautious because of you know everything which happened throughout kovid and actually what we've seen uh in the earlier results that we are analyzing now is an acceleration of the absorption of ai by companies and that's connected to the acceleration of digitalization that we have seen uh in in the past three years so it's been a lot about zumba it's not zoom only right there is a lot more uh going on in terms of uh investing in data investing the talent that goes with it in order to to create some some value and in in our analysis we tend to isolate uh two groups of companies one group is that we call the leaders companies which were already ahead of others some in the technology industry of course not necessarily all of them but you know big technology group who were ahead of a pack in 2019 three years later they still invest they still create some more value they've got platforms most of the time it's platform business models and they've got ai at the core of it of course everything is in the cloud when you've got cloud ai and platform combined and these companies are continue to be the leaders and and i've been growing much faster than the rest of companies so that that you could expect uh what was less expected is that we found there is a group of companies that we've been calling the the leapfroggers and these companies were not ahead of a pack three years back but actually throughout you know all this coffee time all these last crisis in terms of reducing their investment or focusing them on small parts of a company they've been doubling down on technology investment reducing uh operating expense and investing more uh in developing the capital connected to technology and what we've seen is that they're reaping the rewards now and this this group of progress for us is is very interesting because it's uh it's a kind of a sign of a times that in terms of acceleration of technology changes you've got some companies which are actually finding the right way to do it for investment of course and and putting in place the right key success factors to make it happen uh but that that change is uh is to us seems uh very interesting to look at again selfishly for a second if i can push on the leapfroggers and this idea does this kind of i'll try and put words in your mouth does this suggest that is this potentially a suggestion that trying to adopt a technology or get involved in a technology too early could actually be a challenge in the sense that you kind of get maybe you get stuck in version one of the technology but if you come in a little bit later version two is the one you really want to adopt and the leapfroggers kind of get to come in at the right moment am i reading that the right way or is that a mischaracterization of the of the comment or maybe at least a too strong of a statement it's a little bit too strong of a statement uh in in the sense that uh uh we used to look at uh fast following being a recipe for success some years back we do not believe that fast following is a recipe for for success uh right now uh because the the changes are going so fast that just wait and see is is in our view too dangerous these days so bad news for higher education okay fair um i feel like i can make that crack right that that seems like when i want one i can kind of do there to some extent um uh so when we think about ai and we think about kind of you know this the ways in which companies are kind of investing in the in in a set of tools to help them to help them run their business um you know i think one of the big the big questions is how much of an ai process or any sort of kind of data driven processes is meant to kind of augment the decision-making of human beings versus to replace the decision-making of human beings there's big advantages to replacing even ignoring kind of costs or things but like the speed of decision making and things like that can obviously be dramatically enhanced with with automating but i think there probably are still a lot of people a lot of managers and leaders concerned about the risks and downsides like how are how are you seeing people think about the the ways that they might plan to try to use the technologies and who's are there certain types of companies back to our kind of different verticals who maybe are more focused on augmentation versus kind of automation and replacement um that you're seeing out there yeah no no it's it's very important debate of course uh um and uh we've been working ourselves and working in in partnerships with uh some uh external researchers on on that to to get you know both views of a debate as as much as possible um what i would say is this is that um you know all our use cases and the way we work with our clients on automation and we work a lot on automation cases with our clients speaking of the chief strategy officer of accenture earlier bash cargo she just published a book called the automation advantage so it's uh the message is clear is that for the cases that we work on with our clients we believe that intelligent automation when it is you know fought and implemented in a way which is creating value uh is is creating business advantage for uh and competitive advantage for for companies and and we've got that across uh all the industries with which we work and we work with 19 19 industries around the world now if we look about the your question around productivity and job so as we had these questions uh we wanted to look at micro data because there is a world macro debate of course but the the point is for us as we work in a company we look at micro data so we work at company level with company data and we decided to do a deep dive on our own company and so we've been doing some deep dives with some of my colleagues with our lead economy instagram when we look at an automation process that we implement for a client it's you know part of his outsourcing uh deals where uh we take the employees of clients right and we run the operation for for the clients and we look at that and we've been automating uh some processes for a large client and we look at the way that the automation has changed uh the number of jobs and has changed you know things around in terms of qualification in terms of skills of the unit for which we were working and and what is interesting here is that you can have all the best uh business cases of the world you've got to look at a longitudinal study right you need to look at what is happening at year one and then you look at year two year three to see how it is implementing and what are the consequences and long story short uh i can show you the all the details that you and the colleagues here are interested in to stress test and we can open them long story short there is a rise of productivity there is not necessarily a decrease of jobs because by rising the productivity the unit the company is gaining competitive advantage and then it's growing its revenue so it's more a kind of positive story than just you know cutting cost and that's it i think that's we we need to look at the big picture across several years and when we look at the big picture across several years and we try to isolate the specific effects of you know putting ai and automation at the core of these processes that's that's a result we we found so we are we are positive we are optimistic about that and we think that by and large when it's it's done well uh it is uh not only creating productivity but creating value for the company and creating value for the employees as well um looking at some of these questions and trying to make sure we we we tackle some of these um there was a couple questions that came in um on a kind of on a related theme when i think about the disruptions of the last two years you know obviously the first and foremost is the public health kind of issues um healthcare uh then the need for for a vaccine and treatments and things like that i think one other very common thing we saw a lot of on twitter and elsewhere out there was uh big questions and complaints about supply chain um so you know it's taking me months to get this or we can't build those or you know car prices are through the roof because we can't get enough chips and things like that um you know supply chain is obviously a big issue and it's one of those it's one of those ones we probably don't pay a ton of attention to most people don't pay attention attention to until there's a problem with it to some extent uh but i feel like the last couple of years has really raised the elevation of this are there technologies that you see that will affect kind of the global logistics and supply chain industry uh in in important ways in coming years either to help address or avert kind of the the impact of future crises or to kind of augment the way in which supply chain is going to play out are there are there cool topics there that we should be paying attention to and thinking about cool topics i do not know but it's definitely a hot topic that's that's that's for sure uh i i agree with you and uh for the reasons that we can see in the news of course uh and some of them are pretty daunting uh it means that lots of companies have got to look at their supply chain and that supply chain is becoming a strategic topic again uh where it's it's in this case i would say it's not only a question of technology of course technology can help but it's a lot around the strategy put in place by by the companies the way they develop the the resilience of their operation uh and there's lots of other factors which at this point in time have got a more predominant impact than technologies themselves okay um another question that came in that i actually that came out of i think a relatively quick comment that you made earlier that that susan perkins brought up that i i want to come back to here you talked about inclusive inclusion wow inclusion and diversity um as kind of having impacts and relevance for these discussions around technology to some extent can can you say more there because that's that felt like a relatively brief but a pretty provocative kind of statement to be thinking about i don't think a lot of us kind of would make that leap necessarily to thinking about how some of this work that you're doing directly relates to discussions of inclusion and diversity uh but it's clear that this is a topic that you've thought about and that's relevant for for you in accenture research yeah no it's uh let me pick up just two examples first one is in terms of the research that we produced we produced a research last fall with a professor at another university in this case about what we call hidden workers and hidden workers is in the u.s but not only in the u.s we look at some european markets as well it's a lot around the workers who are excluded from the labor market right now and when you put and lots of companies put ai at the core of their recruitment processes because it's a way to you know go very fast in terms of selecting the potential right candidates based on certain criteria you've got a group or to be more precise an addition of multiple groups which get excluded uh think about uh women we may have stopped they carry for a while because they have to care about their family and not only their children can be parents now of course uh and then you know there is something not smooth in the carrier reject it think about someone who's had an issue and is leaving jail uh you know that's a stigma rejected thinking about someone who's got you know did not graduate from stan school of business only of one of these fabulous universities rejected and so on and so forth and what we found by looking really at regular level is that you've got millions of workers that companies need and that they cannot find right now in the labor market because of the processes they put in place so we've got this mismatch uh between you know the need of companies to work with more and we know that in in the u.s there is a big mismatch right now in terms of you know having more than 10 million job opens and uh people not companies not fighting the the the right people and people just being excluded and you've got ai i mean ai does not explain all of it but actually the recruiting processes with ai at the core explain some parts of it and and we've been uh happy to see that lots of organizations that we've been speaking with i've been listening to that and addressing that right now and some of my colleagues actually been speaking to the u.s congress as well recently because
u.s congress decided to look at that as a serious matter so to me that one example of uh research done on ai looking at this question of inclusion and diversity and hopefully having an impact on on our community uh ultimately now that's our first example a second example is just uh within the work we do i was mentioning the research protocols we we put in place for years the type of research that we're doing on everything and anything did not take into account uh the diversity of consumers uh in in the us uh according to certain criteria ethnicity was not a criteria for many years uh now we have decided that systematically it becomes a criteria and that means we've got the proper sample that means we look at what are the specificities that have to be taken into account if you want to produce some research which at the end of the day is relevant not only for the majority group but as well for you know groups which have been not researched so much in details for for many years i think that's uh it it's it's great to hear that you're thinking in those ways and i think it's uh it is that challenge right we often look at kind of the aggregate data and we look at the average or we look at something like that and then it because it's easy but it's hard but it's easy then to miss so much of the of the the the range and the diversity that we're talking about for for all of these things heterogeneity and preferences backgrounds uh opportunities things like that so um kind of on that theme you were kind of mentioning in on some of this and i i apologize for coming bringing metaverse back in a little bit um but we often you know from a regulatory perspective we often make make make comments uh and and it's easier for people like me to say it as opposed to someone like rob who's actually been in a regulatory related role uh to some extent um that that industry is always one or two steps ahead of the regulators in terms of thinking thinking about the implications of these things um and that puts regulators in a difficult situation as we think about the metaverse specifically is there anything that makes you nervous in in a way that if you had the direct pipeline to be speaking to regulators in the us or the eu or elsewhere what should they be paying attention to now before it's too late uh or before something bad happens is there anything here that that you're aware of or thinking about or worried about from from that perspective no it's a it's a great discussion and as we do some some research part of it in north america part of it in europe we can see that even the mindset of people is different and in in you know some people work with in in north america being more concerned about letting innovators innovate and and regulate when you can really harvest what's going right what's going wrong and then you can regulate however in europe we're dealing a lot with uh people who think that it's important to regulate first right and and and and avoid you know things to to happen uh so we are we are moving in between these two poles i would say and and uh and speaking with both uh and so uh our point is always that uh we innovate in the context where we operate uh and you know what is in the u.s context is with the u.s regulation what is the in europe is with the european uh regulation uh i would say at this point in time the the focus for us is to make sure that some of the uh daunting aspects of what is happening on on the internet is is not happening in the metaverse and that whoever it's the regulator or whether it's companies together find ways to make it safe secure for for people who are going to join the internet because it's going to be critical to make it to make it a longer lasting success um and then i you know i i feel like given that we are in an educational environment and i've you know at least looking a little bit at who's who's here today i feel like i i kind of need to end with or maybe end with uh a question around what's relevant for students right so and in a business school professional environment most what most people care about is jobs right so if you're thinking about advice to students today what are the things that they should be investing time and energy to learn more about what are the types of skills that they should be trying to develop that will be important for their careers three five ten years down the road and maybe if i can sneak in a bit of a side question what does it take to get a job and accenture research right uh what are the kind of skills that you're looking for there uh but just kind of again thinking through uh the advice that you might offer career-wise to to a bunch of students undergrad mba but kind of you know starting or restarting their careers kind of coming out of a place like this yeah well to me the the uh the first point which may seem a paradox you know because of everything we're living through this week is that there's never been such a good time to be a student because the just the possibilities in terms of jobs that students going for your school in particular but you know new york university in general just the opportunities are are enormous and they never been so good when you look back 10 years 20 years never been so good never been so open uh when we look i'm sure a lot of your students end up working for for startups so we just finished a study on unicorns in europe and we can see the number of students going to to startups now is it's pretty amazing and it's great way to have a to have a first experience uh of course and often a very valuable one so i would say you know to me it's all about passion and and and i would my only point when students ask me and i'm teaching in some instances and when students ask me about what they should do is not to give them you know you should do this and that but follow your passion first of all to me that that's that's a thing which matters because they've got plenty of of opportunities the the other thing i would say uh just reflecting on what we've been going through in the past three years uh and what i see around me uh is uh just just be careful about two things uh that we're not so careful about in the past at least by generation uh maybe not yours but mine it's the the first thing is mental health uh i've seen so many cases of people not taking care of it mental health and then facing issues uh which are really moving at the end of the day so we always speak at school about heart skills uh to me right now the way for you know every one of us to look at our mental health to take care of that is absolutely critical for the future because we live in a world with you know many things happening and and that that that is uh um in my view uh absolutely uh absolutely critical uh uh right now uh to uh to to to look at um and and then um then i think it's a it's a matter of of trying you know uh as you were mentioning accenture you were kind enough to mention accenture and accenture research we we are recruiting at accenture uh something like one 100 000 people a year so it's big big number of recruitments in different worlds and different uh different functions that accentuate research is a lot smaller of course uh but the the you know and the point is that reflecting to what i was mentioning earlier is that we try to be less focused on actually the the actual degree even if degree and education matters of course but we try to look at personalities people and the way they they are curious about things and in research it's a lot about curiosity the the other things we we can teach them people can learn them that that type of things is uh is a is a lot more is a lot more difficult especially now that uh the big thing in front of us is how to be creative online uh we've proven for the the last three years that we can be all extremely productive online now the question is can we be as well as creative as we are productive uh and that going back to the metaverse of course but not only zoom of course but not only uh it's it's a lot around that and i think that that for those of us students who are going to you know crack that and manage to get creative online with others in a collaborative manner there are going to be a lot of opportunities ahead so what you're saying is to be successful people need to understand how the technology works they need to understand human social interaction they need to understand the regulatory environment so like so a little bit of everything is that's sorry not not to put too much but it's i mean and this is important right it is this is about this interaction of you know this is not a this is not about technology only it's not about people only it's about the interactions between the people and the technology and those and you know that that's what makes a lot of these things so complicated in my perspective yeah can i ask can i add one more thing it's a long list i know one more thing uh because i was speaking with students at the business school last week and uh the the the one thing i told them in terms of question to ask to their future uh recruiters is what are they measuring in terms of their progress towards being net zero in terms of carbon footprint and how is that in their business model not some type of lose glossy corporate citizenship report at the core of their business model because if you think 10 years down the line i do not know what businesses will like will be 10 years down the line what i sense is that that sustainability topic is only going to grow and if we want to leave something uh here uh in our jobs it's it's a lot about the way we contribute to the future right and the way to contribute to the future to me now it's a lot around sustainability so net zero is a way to just crystallize it in one indicator but it to me it's a it's a lot about that these days and and i can see that lots of students are very passionate about that and of course for the right reasons and they should not be shy to ask this question to their future employers and how they put that at the core of their business model i'm sure many students are happy to hear that i'm sure many recruiters are a little less happy to hear that request that that they should ask that question but i think i think you're right that's a great it's one of the kind of questions students who care about this should feel empowered to ask those types of questions um we are out of time um this has been a true pleasure to to have you here um thank you so much for taking the time to come and share with us and really personally i really enjoyed the conversation so uh so thank you um and and i think i'm handing it back over to rob now to wrap us up but thank you again francis so much thank you uh jp and francis thank you both so much that that was truly a fascinating conversation i i learned a lot and i really enjoyed it and francis i really appreciate that you ended on that note of looking to the future right because of course this is the center for the future of management so we are very intentionally trying to be sort of setting our eyes you know 5 10 15 or more years into the future and sort of understanding the trends that are going to get us from right now to that point so thank you again francis and jp thank you to everybody who joined us today we really appreciate the audience participation uh one quick note so i just want to highlight that the next event in our speaker series is on april 7th at noon that's new york time when we're going to welcome three distinguished speakers uh mit's darrone assamoglu mckinsey's jacques bowien and harvard business schools rafaela saidun they're going to be discussing the organizational economics of ai for more information and to sign up please visit our website stern.nyu.edu cfm that's it for today thank you very much and goodbye to everybody thank you again francis thank you jp [Music]
2022-03-20 13:45
