Navigating Between Disruption and Hype with J.P. Gownder

Navigating Between Disruption and Hype with J.P. Gownder

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Thanks. For coming. We're. Really excited to welcome every everyone, back, see. The experience with Brit technology, in tech Series for the second a little. Note this is actually our 10th anniversary this year. For. The second year term I know you've been to a lot of events already over the last year, or so for. The first year you know we run this series throughout the year. Theme. Year, so this year our theme was, really understanding the strategic, impact of our game technology. PRA, are yes other. Other emerging, technologies, what's the impact from a business perspective we're. Gonna be exploring that across, the year have. A number of great events already lined up and some, more that are in the works and to be very. Thank. You. Thank. You. Good. Afternoon Chuck I'm really excited to be here I'm going to be talking a bit about as Patrick. Mentioned some. Emerging tech stuff those. Of you who are, technologists. Will know a bit about this that. Technology. Is powerful. It can change your business model it can do all sorts of things for your customer, but. Actually, getting technology to work in a business context, in a real company can, be quite a challenge, those. Of you who don't have a technology background as, business. Leaders of the future you. Are increasingly, going to be tasked with using technology to. Drive those business strategies no matter what, vertical, you are in so, I'm trying to address both audiences, today those of you who have a lot of tech background and those who don't and, I want to talk about navigating, between, disruption. Which is the the potential of technology, and hype. Which is what, all too often, business, leaders get sucked into unknowingly. Along, the way so. Just to say a word about, Forrester. We were founded in 1983, we. Are a research, and. Consulting. Firm I do all different sorts of different things as an analyst, I write. Research reports, that are consumed, by my client, so it's very firewalled, and proprietary, I do a lot of public speaking I give speeches in you know both pain and and free contexts, but most importantly, I'm on the frontline of working with our enterprise, clients. Our vendor clients, to try to uncover what. Are the potentials, here what should you be doing what is your sort of your best strategy I happen, to sit on the CIO team but, I work with a lot of business leaders as well as technologists. So. My, agenda I want, to talk about the disruption of course and I bet a lot of you are excited, about the potential for technology, and and, you really should be but, I also want, to be. Pragmatic and, give you a glimpse, of what real, companies, are going through real, companies, can't. Flip a switch and, and, implement, emerging tech on a dime, they, have a legacy infrastructure. They, have legacy, business processes. They, have an ecosystem of how they create value and. And if the emerging tech isn't woven into that there's not going to be any value to it so that's what I'll start out with I don't want to talk about the, future of work and the future of jobs which, is intimately, related to, the adoption of technology you may hear about robots, or taking your job what, will you as leaders face as you lead companies, who, are tasked. With an increasing number of digital. Workers, in addition to humans I want. To talk then the truth of behind AI on automation so, I want to thread that needle between, disruption. And hype and I'll do the same for Augmented, mixed and virtual reality and, then, I want to give you something that I hope will be very useful a lot of my very, senior level clients are, finding, this storyline very powerful, it's about building a business case, internally. To, actually, be able to get others, to buy in to, your vision of using emerging, tech this, is critical, often, individual. Leaders have an idea they think it's going to be transformative, they, are unable to sell it within their own organization, and then they say well I told you so later when their competitor, does it and then, hopefully we'll have time for some questions. So. You, know all of you are probably excited. By technology, at some level right whether you're a technologist, or not it, can be a powerful force in, business and yes. Consumer. Adoption is faster, than ever before what, this depicts is sort. Of the the uptake, of the iPod, when it was released way back in ancient times in 2001, it took, about two years for, the iPod to reach to.

A Million, sales the, iPad, buy by contrast, actually, this is an Apple to Apple comparison. It, was you. Know taken up within a few months at a million units and this, was the percentage, of people who intended, to buy it we survey, millions, and millions of consumers over, the years so consumer, adoption is happening very quickly and, that changes your your job right because you have to be able to reach people on smartphones. Or maybe you know tablets, or whatever. Yes. Disruption. By technology, kills companies, you. May have heard or maybe not you guys are quite, young to know, of Tom Tom there. Was a time when Tom Tom was a very well-known GPS. Company, there, was an actual GPS, company we still have them Garmin and whatever but they. Sold you, know these units, that you would put in your car and it would sort of take you down the road wherever you wanted and, unfortunately. They ran smack dab into the release of the iPhone and, specifically, in 2008. When the iPhone opened. Up the App Store and allowed, people to do GPS, using maps and and other programs, Tom, Tom's first move by the way strategically. Was to say hmm. We're losing a lot of money to Apple, let's, put out an app on the phone and charge $99. For it not, $0.99. $99. This, wasn't a very effective move so what you see is this market, cap that, was once nine billion dollars, dropped, down to about, under. One the, company has diversified into, some other like, more, fundamental, areas of technology, and now they're they've, never recovered, right so technology if you miss a big revolution it, can disrupt your business and destroy your company and, of. Course everyone's thinking, about Amazon these days I I can't, swing a dead cat in a room without someone asking me about Amazon, because they. Are moving. Into seemingly, every area whether it is your home as. You can see from this you. Know the TV streaming, business music, business, obviously e-commerce. Voice enabled agents, even potentially. Healthcare with some early moves, so getting, Amazon, is a big issue this. Is clearly, a function of their technological prowess. The, assets, that they've built up like AWS. Amazon Web, Services, and the, ability, to create unparalleled. Scale and reach, many many customers, right so yes, all of these things are true and. What. Can happen at a company is if, you focus only on cost-cutting.

You, Don't invest in innovation. That will serve your customers more, effectively, if you fail to recognize. These technology, revolutions. As they, come along when they are very pertinent to your business as in, the TomTom example, or, if you don't have a function, at your company that, has as its remit, the, ongoing, monitoring, evaluation, and. Experimentation. With new technology. That's. When you become digital prey so. Some, of you may have worked at companies that you thought were a little bit digital prey ish many. Many companies do I like to say there's a bell curve of clients. Out there of companies and most. Of my clients are somewhere in the middle and many, of them are at risk of falling off to, digital prey so, the disruption, is real and and so when you read about this that. Is something to know but. Many of you probably worked for a couple years at a real company in some, real vertical industry, and you. Probably found that it wasn't as easy as flipping, a switch to. Embark, on some big new technological journey. Organizations. Have all sorts, of reasons why this is challenging, I'd like to highlight, the difference between two quotes one of them is from, the Google, CEO sundar Pichai in which he said AI is one of the most important, things humanity is working on it is more profound, than I don't know electricity, or fire that's. Quite a statement I don't know that we're there yet I'd, like to contrast, that with a real client at one of the biggest grocery, companies in the world who. Told me I have, data silos, everywhere, we, haven't even completed our move to that cloud we, have a huge infrastructure. Debt, we can't invest. In AI they, do not have the fundamental. Technological. Background. At their organization, the. The system's the people to, make AI work so. This is the contrast that sometimes, you may see you. May see organizations. Who go out and say I want to be like Google but they do not have the scale or talent, or background, or infrastructure, that, Google has so. Even if you're a business, leader who plans to go into grocery let, me tell you you, have to contend with technology. Transportation, and logistics happens. To be the business of this client. Using. AI to, actually optimize deliveries. Is a huge, huge area that is changing that area rapidly, so, what they have to do is overcome that technical, debt they have to figure out what, moves can we make to, be able to invest so that we can catch up to what, we think we should be doing I mentioned. Some of these issues technical, debt simply means we've, let, sort, of old technology, run our systems for a long time and we have not paid, to upgrade them this is ubiquitous. 95%. Of companies will have some level of technical debt someplace, in their organization. Whether, that's customer, facing or shared services, or operations.

There. Is going to be a reckoning, at some point you if you will lack, of alignment maybe, business leaders are moving, too, fast compared. To what the CIO can deliver or maybe they don't have a good enough relationship to. Actually, push things forward together, lack, of alignment is often a problem when, you're trying to make, these initiatives happen, making, bad bets an organization. That, goes out on a limb and does a project in. A certain area well. It, didn't work out now the organization, takes a step back and says oh we. Can't have another failure like that we lost, money on the last one that's. Problematic, because in the new world you actually have to encourage failure at times this is part of the agile, development method, you may have heard about you, have to be able to fail in some circumstances. But, sometimes, it sets a bad precedent. Finding. A path, out of this conundrum between, sort. Of the leading edge companies, and those who are kind of real companies. Means. That you have to be balanced, in the way that you approach this and you have to have organizational. Structures in place to help you overcome these problems, for. Example you, may want to make some kind of balance between projects. That will drive revenue and those that will cut cost cutting. Costs as I mentioned is is, a is a good thing but you're not going to grow your. Company necessarily. By cutting costs alone so, investing, in revenue generating, tech as a, balance, to cutting cost is often very, very helpful there's. Also risk versus repurposing. I may, say gosh I want to go all-in on VR I think it's big for my company, well. Early, indicators, are that would be a really bad idea right we're not seeing a whole heck, of a lot how many people here are using VR ooh. We. Have one two three okay we have a few but that's I mean this is at Dartmouth, for goodness sakes I mean that's leading edge adopters, most of us are not doing that so if we were to bet. On the risky, new, tech instead. Of repurposing, mature tech to solve the business problem, that, is a trade-off we have to make we. Also need to make sure that we have the right skills and talent and people to execute, or we, have to go to outside, entities. Who will help us to make these projects, happen and. As I mentioned freedom to fail you, cannot become good at almost anything, as an organization. Unless, you are allowed to learn for mistakes and all too often people, work in organizations where failure means I'm out the door so, you have to build a structure like an Innovation, Center or an Innovation, Lab where, failure.

Is Sort. Of curated, and understood. As part, of the process, make. Sense okay. I, want. To talk now a bit about who. You're going to be employing, in the future because. Many, of you have read a lot about the, future of jobs being robots. I, so. There's a very famous academic study, about this it's by fray, and Osborn, Oxford. 2013. And. It was an analysis of, all the jobs in America using. A particular, data set called the O net database, which. Is a government source that looks at every job in America and. Statistically. Figures out what are the components skills required. To do those tasks, they gather this data by, going and doing depth interviews, with people in every job in America it's such a powerful resource it is it is unparalleled, in any other country which is why to, British, academics, use that data set and their, conclusion of, that of that study, that 47%. Of, jobs are at, risk of computerization, or cannibalization, by, computers. At some. Indeterminate, time, in the future. So, you will often hear people say half, the jobs are going away people, are going to be out of work whatever I have. A little bit different perspective, I have built off of the, same data set actually so I will introduce you to that but my thesis is that in the next ten years let's say actually, nine let's my forecast. Goes to 2027. The. More typical case will be that we will be working side-by-side with robots. Rather, than being, replaced, by robots so. Let me see if I can convince you of that I'll start with a little history you may have heard of the wonderful film hidden, figures and. In that film Catherine, Johnson Dorothy, Vaughan and Mary Jackson worked at NASA they, were mathematicians, and. They were their, title, their job title was computer. Because, they actually did the computations. That sent, people into, outer space they, played a key role in this the interesting thing here is that their title was computers. Because, over the last hundred years we. Have essentially. Asked people to. Become. Like computers, right we've, asked, people to, follow, business, processes, that are very well defined and business. Processes, are a set of rules they're very much like an algorithm in computer, science right an algorithm, is essentially a set of rules as well so we've asked people to follow. Algorithmic.

Logic, When, they complete their test this this is at every level by the way I mean if you are a, housekeeper. At an airport I've interviewed the Cincinnati, Northern Kentucky Airport, about, they were using a wearable, tech they're using smartwatches, from Samsung to, tell the janitorial. Staff when to clean the bathroom, using AI it's. A very interesting situation, but. They are following, computational. Logic so for a hundred years we've asked people to be more like computers so it's no surprise if. We start passing some of those tasks, off to computers because we have the logic in place so. In the next 10 years what we're gonna see is that almost. Any business process, down to the level of the janitorial staff will. Be run at its core by some kind of software, automation. And, intelligence. Of various, I don't want to call it a I will. Become common, but over time, but. In many cases. Escalations. And, improving. Those systems will always, accrue, to human beings almost always in that in, other words I may. Be doing a job today maybe. 70%, of my job tasks. Let's divide the job from the tasks, could go off - let's. Take a very simple example you, are all of all of us when, we're in professional, life have to set up meetings on our calendar, and, we have to email back and forth and we have to say oh are you free this time are, you free this time and I mean this is what this is how I still live sometimes and I'm you know it's morphing that. Is a task that is much better done by a computer. There, are companies like zoom day I X, dot I and. They and it's funny a very small anecdote X dot ai is a company, who's doing this you you work with Amy, Ingram, may I Amy Ingram, so it hunt like you get an email from Amy, Ingram, and it'll, say okay well what time do you want to set up this meeting and I, had a research assistant. Who was setting, up a meeting with the CEO of this company and, he was doing all this back and forth with Amy Ingram, and he didn't know it was a bot and it. Turns out it was actually not, a person, it was a it was a software system so, there's tasks, like that that we're gonna take off human plates right we're gonna move it off and we're gonna say this, task is best done by a, computer, okay, so that's the argument for, you, know cannibalization, but, really the, future of work is really following two vectors, in my view of course, we've always had human labor for thousands, of years. The. IT revolution. Opened. Up the opportunity. For. What is effectively, outsourcing. To, countries other than the United States for labor arbitrage, right, so you have people, in the Philippines, answering. The phone or whatever doing, tasks people in India doing your programming, that, is that. Is a existing. And now, almost defunct revolution, because what, we're seeing today and in the future are two things an Augmented. Digital workforce, where, I have tools at my disposal some, of them could be intelligences. Some of them could be devices. Some. Of them could be visualizations, whatever. They are that. Helped me to be more effective, in the work that I'm doing down. To the level of people, working in warehouses. Who I'll show you some examples later I can, augment, a worker with. Technology, and raise their productivity the. Other side of this is robots AI in automation and that's the part I just talked about where you're, literally saying okay there are certain tasks, that can just go off to these BOTS these, are interconnected, it's, very important, that you understand, that what, is not happening today in. On mass at the companies I work with is. A lot of total, replacement. Behavior. Even. Amazon if you think about their warehouses they're, using lots of Robotics physical robotics, those. Physical. Robots which were part of a company called Kiva which, was purchased by Amazon, in 2012. Are working, in an intimate dance with the human beings in those in those spaces they.

Are Actually, choreographed, to work side by side with people so. These are the two vectors and let's, start off with this augmented digital, work force I want to give you an example of how, this works at its best there's. A startup called Doxil AI and what, they've done. Is they've recognized, that in the construction. Industry, 98, percent of construction, projects, run on average, 80 percent, over budget and are delivered 20 months behind schedule it's, a pitiful record isn't it I mean and we, know that this is the case what. They are doing to, solve this problem is they are employing, computer. Vision technology, as deployed. By robots and drones who, go around a construction. Site every single day they. Photograph, and video every. Single thing that has been done on that construction site they, feed it into a computer, vision system that can interpret progress. Against goals so, on a daily basis, if one set of pipes has not been installed. That's. Going to cascade right it's going to Domino, other contractors. On that project they, want to know in real time how, can I avert, this disastrous. Delay now, I'm not going to make any claims that Doxil has solved this but, but the concept. That they're doing is exactly right it's using. These technologies, to help a construction. Manager, stay, on time it, also they also do deliverables, to the CFO so, the CFO understands, what the financial, implications. Would, be if this project falls behind or where they are so. What, this is doing is it's augmenting. The. Decision-makers, using AI make. Sense okay. Clinicians. Are increasingly. Using technology, not, at every hospital but they are increasingly, using technologies. The. Simplest case and I know that this is happening in a lot of hospitals is something, like you, have a barcode, or a QR code on your on your patient. Armband. And every. Time medicine is distributed, to you it must accord, with the CRM.

System They, scan your badge, the software. Says yes this is the right patient, the right, medication. Here's the amount there are so many medical errors as we know this, is powerful, it takes a cognitive. Load off of the mind of the nurse or other clinician. Who may be distributing, this medicine to you and it lowers the rate of errors. It increases their productivity, it is a win win and as, a patient I'm looking forward to that as well. Augmented. Reality gets, a lot of hype in the b2b space there are real scenarios. Where it is used one of them is this, one if you were in retail if, you've ever worked retail in any context, you know that like, stacking, shelves is, actually a really time-consuming you, know job I mean it's it takes a lot so imagine, if you could you could just visually, lay it out before, you actually stack, the shelves maybe you could even bring in a focus group and ask customers, like would this work for you right, so you're actually saving time again this is augmenting. The power of the worker using. Augmented reality it's not replacing anybody, it's, super, charging that workers capabilities. Ok. Vector to robots, AI and automation they. Generate fears as I mentioned, most people, who are technologists. That we survey say. That you know negative attitudes around this or a problem I cited fray, and Osborne previously. My, view is that job losses are real and you can talk, to elevator. Operators, who don't exist anymore or telephone. Operators, or many call center jobs if, you don't believe me they do go away but they're not the biggest part of the story, one thing Fran Osborne did is they focus on loss they didn't look at the new jobs that were created out of the automation economy. And I have a lot of research I've been doing for four years on this topic that, suggests there are real jobs coming out of this world but, more importantly most of us our jobs are just changing in. Accordance with the augmentation, point, I my. Job is different because I work with Salesforce, you know as a CRM, system it, changes the way that I interact with my customers, it changes the kind of tasks that I as an analyst have to do every, day, so. My forecast, says that 17%. Of today's jobs will be lost to automation, by 2027. I used the same data set as Frei and Osbourne but, I put parameters around it they say someday, and, I say 10 years and I used a very specific, set of assumptions.

So, Actually, I talked to them and they were really nice but. You know I disagree with the conclusion but, what I'm finding is that there are these new jobs whenever, you think of it this way whenever you have a robot, think. Of a physical robot you, need a robot repairman and that person that job did not exist before there, are many new jobs of that sort that we are seeing the, green shoots of so that's, the little forecast, there in the future what we're gonna see is that yeah there's certain jobs that are going away, office. And administrative roles as I mentioned you're setting up meetings you're not you're not gonna have a lot of future call, center you know which has already been hit by the outsourcing. Revolution. There's going to be further hurt by really. Good interactive. Voice response not, the the bad stuff that we see but, we're gonna need more people actually with technology. Savvy and management, roles you're going to have to design the next generation of, business processes. That take into account a I for, example rather. Than human resources, we may have something like human machine resources where if, you have a digital colleague. That you're working with how. Do I do that where's, the learning and development how do I train my workers to actually learn how to work with digital employees, and. And and so on in the interest of time I shall, move on but, upskilling. Is the key here when. You hire people you're, going to be the burden is a little bit higher if you're employing some of these technologies, you have to have in place really. Good training programs and let me tell you most companies, do not have good Learning and Development functions, this is an unfortunate fact but, the change management the Learning and Development these are critical success, factors if you do not do these things the. Technology, will fail. As. The. Job scare shows AI is kind of the pinnacle of the hype curve right now you, have your you, know Elon, Musk and even Stephen Hawking saying like AI is gonna destroy the world this is a, bit, vague you know kind of prognostication. And back, in the real world what we're finding is there is a backlash, brewing, because, hospital. M md anderson spent sixty, million dollars, working over years with IBM, watson to try to cure cancer that's, a very ambitious ask but. They didn't see results so they they pulled the plug on the project and started with a different approach. Because the software was not working and you find bloomberg, has the story what happens if AI doesn't live up to the hype, ai is not as, one of your professors was telling me earlier it's, not a magic, you know wand I mean there's a lot of hard work that goes into these things technology, is a tool so, we're gonna see a big backlash so what is real in AI is solving, narrow, focused. Business problems, well-defined, problems, with clear parameters and, clear, results, that's what's working today that's, what's going to work over the next few years I'll, give you a few examples, Salesforce. Has in. Their CRM system if you're familiar with Salesforce, they, have this tool called Einstein, and although, Einstein sounds, like you could ask it anything and it would know anything that's, not what it does what. It does is it helps to sort. Of sort through opportunities for. Salespeople. Basically, I'm a salesperson I have this list of contacts. And prospects, how, do I predict. Which one of them is likely to convert and buy my product obviously.

I Want to start at the top of the most probability. Right I want to work on the ones that are most likely to win and that is effectively, what what, Salesforce Einstein does it takes different, parameters. It uses machine learning in there to to help learn from the past but it's using particular, parameters, to help score, the opportunity, for a salesperson. To actually, be able to go after a deal, that's, a well-defined, problem though this is not the same thing as a sign, Stein anything, about the future of relativity, but. Branding comes into play. Zooom a I uses, chat and AI to help employees, generate. Contracts, so let's say you decide, that you want to have. A new job offer you're, hiring someone, this, is often, I can tell you from experience not, the most fun part of one's job because it's very manual, you have to get all the stuff you're not a lawyer you're, like you know it's ugly what, they are doing is they are automating. That process using. Scripts, and what, they do is they present, you with a standardized. Form you, put in parameters it will adapt and, it'll help save you probably, eighty percent of the time right. A narrow, focus problem, that, uses intelligence, and lots, of data but is, tailored. To a business, problem not boiling, the ocean. Robotic. Vision technologies, uses computer, vision and robotics to. Turbocharge various. Production, I interviewed these folks saw their their robot and basically. It is using computer, vision to assemble. Complex, machines, this used to be done only, by hand by human operators who frankly get inured, to what they're seeing full go by on this you. Know all these parts, they actually start making mistakes what. They can do with computer vision is recognize. A part pick it up put it in the right place and move on and it can work 24/7, so, disruptive, right I mean disruptive, but it's a narrow and focused problem it's practical. InterContinental. Hotels Group. Is using, natural, language user, chatbot, called amelia which, is again maybe a little bit overhyped, in terms of its branding, but amelia, does, a couple things really well amelia can understand, natural, language in, certain languages very effectively, and so, complex requests. That come into the the. Hotel dashboard. You know it can actually understand, what those things are it can quickly determine, if it can execute against, the problem, or if it needs to escalate, to a human being and just doing that well is incredibly. Incredibly hard again, very, narrow set of problems here, but you. Know yielding, a lot of business value oh and I mentioned know Cincinnati. Northern Kentucky you, know they had this situation where their bathrooms were dirty all the time they kept hiring more people this was not working so, what they did was they worked with smart. Watches. They gave them to all the janitorial staff they. Instrumented. The bathroom with a little so every time someone goes in the bathroom it, registers, as a person, rather. Than sending people in every hour which, doesn't take into account the vagaries, of flight, changes, and all that they, went in after 50, people used the bathroom so, guess what they actually didn't need as many janitors, because it was so well optimized, they could actually lower, the number of janitorial, staff but. Actually get much better results and better customer experience. So. It's a cool example, so. The verdict on AI on automation you, know is that the hyped world or the leading edge that maybe only Google or Amazon can, do is a general. Artificial, intelligence that can solve multiple problems and, that. Is a wonderful vision it will come true at some point we are not there most. Business, people at most organizations. Even leading-edge, ones are focusing, on narrow. Well specified problems, to which they can apply AI to. Solve a business problem and, generate. Value for customers or operations, that's. Where we are today that's where I predict, and Forrester, predicts we will be for the next five years when you guys are out there leading the charge that doesn't, mean that you should give away all of the creativity, you know and ideas it just means that be realistic, about the. Maturity of this technology as you apply to problems. So. Augmented. Virtual and mixed reality a spectrum. Of technologies, that are similar virtual. Is occluded meaning you have no vision you it's a totally, virtual world augmented. Means I'm adding. Digital information to, my natural view if these were smart glasses that would be the case mixed. Is usually, 3d. Anchored, objects. I could see a hologram, with hololens for example, these. Are very powerful tools under certain circumstances. However again they are often overhyped. We. Often think if, you remember Pokemon though I'm sure everybody played you.

Know You could imagine a world where there's, a world of anchored objects I just pull my phone out and if I have a certain subscription, to something like there'll be an object that only I see and because you don't have that subscription you don't see it you, know that one will get there maybe someday but that's, a that's a bit of a you. Know a hype perspective. Or you, know there's this kind, of government Airport security where they're scanning every face and, superimposing. Over, the faces who is who you know and actually some of this is happening in China but, it's not mature and it's it's actually there was a study in Heathrow. Airport in London and they found that uh that, it was wrong more than it was right about getting. Getting this information. And. Then there's also things like rendering imagine, if you're making a movie and instead, of like, shooting all the scenes and doing the CGI later. Imagine. You could render the CGI on the spot, you had the compute to do that this, is actually what's happening at the leading edge of like, Marvel, movies and things like that they're using engines, that allow them to at least see what the CGI could look like and then refine, it later so all of that is really cool or digital twins as well you, may have heard of this this is where you make, a digital copy of something in the real world or some process in the real world that is feeding data in real time and maybe, you can look at that and say okay this is the operation of my oil platform. Or whatever it's a full digital, twin, that gives me information all. Of these things matter and they are starting to happen but. What is really, possible today, what, we're seeing is that market. Inhibitors, are there to be overcome the technology, is not very, mature, we, are not at the iPhone stage of the augmented, and virtual reality market, by which I mean before. Then I was talking to Patrick about this before the earlier, before, the iPhone there were 10 years of smartphones that didn't quite take off they were from, Nokia Symbian and they were blackberry, and that sort of thing we, haven't found our iPhone, moment where everyone, says I need VR, for example. So. We need to overcome some problems, for, using, these technologies limits. On things like battery life on use. Outdoors some of the really, best devices, like microsoft's, hololens actually. Can't be used outdoors because, of the light and the way it refract. Some. Of these devices don't have safety glass hard hats, they're not equipped, for the jobs that people want to use them for just yet so. We have to keep that in mind but. Early successes, can. Show us the direction forward. Ford. For example is using microsoft. Hololens and mixed reality in this case to, design. Vehicles, right so in, the old days believe, it or not and this still happens you're designing a car you work with all these different people, you build a clay car out, of clay and like, walk around it and you you, know chip off of it like that's that's. How you design a car I mean a chassis you, know it's a little bit more complicated than that but it's a physical, object with, this you can actually just create render something, in virtual, space and you, can change it at will and it also means that if I am in Tokyo, and and, somebody else is in you, know Dubai we can work together simultaneously. On the same model in space, at the same time so there's a lot of sci-fi to that but this is a real scenario that a real thing that you can do today and what are the outcomes here it means that you can get better collaboration, from more people it means you're gonna have more creativity because you can do more cycles, of design. That's. A real scenario. I interviewed. A company called AG Co they make tractors, tractors. Are actually very high-tech devices today. When. You assemble a tractor. There are 2,000, steps plus and you're. A very skilled laborer, who is doing this assembly unfortunately. In the old world you would have to go and type a few things on a computer for step.

1612. Turn. Over here do that and then you you sort of forget so you go back and then you go and fit finalize that and then you go to step. 1613. Right so with with Google, glass they, are able to actually get all. Of the sort. Of steps and and, schematics. Right, in front of them they can they can sort of glance up and they don't have to interrupt their workflow this, is a real pragmatic. Focused, kind of scenario, that creates. Value training. Is very interesting, I think it's the killer app for virtual, reality right, now this. Is a corporate kind, of scenario where UPS, Walmart, other companies, have moved a significant. Amount of their. Training to VR why, because your experience 'el if if. It's black friday and you've never been through one you can experience, that in walmart here. UPS, is using a steering wheel with the VR to, simulate different, safety parameters like. I don't know a a dog runs out in front of your mailbox I don't know I don't know much about it but I mean it's a cool scenario, because what it can do is it's very measurable. It's very experiential. And at the end of the day what they're finding is their, drivers are better trained. That's. A real scenario. Augmented. Reality is, by the way still happening largely, on tablet. Devices not smart, glasses you, know all of us kind of want smart glasses but they're they're not ready for primetime. Engineers, at Bosch are using augmented reality where, you can see it's over an engine, it's superimposes, and tells you what is going on with the engine some, of you I don't know if anyone has used this Hyundai, has, done this for their owners. Manual, for cars if you own a Hyundai you, can actually download the. Entire, map. Essentially, rather, than like who actually reads those books right no one does so, you actually just hold your tablet up and it tells you well this is this and this is this and you know it's a it's a wonderful scenario, so these, kinds, of practical scenarios. Lead. You away from hype and toward, real results, so. The verdict here is that the hype and the leading edge or head-mounted displays. You, know all of this I tracking, and. Trust me I'm really into this technology like I'm a big fan of it but it's just not happening yet and and it needs more time before, it happens, what is really happening and, what is creating value with this emerging tech is narrow focus. Scenarios, mostly, done on smartphones, and tablets. So. Between, hype and, reality. Finally. I want to talk about what. You guys will do as business, leaders as, you. Go into organizations, and you say ok JP. You know I'm gonna prove you wrong we're gonna do this emerging tech and we're gonna make it work but. How are you gonna sell that vision, internally, that's the big key issue because, a lot of Champions. Fail because. They can't get buy-in they can't get budget they can't get people to execute around, that strategy and so what we talk about a Forrester, is a business. Case lifecycle, that I developed, which, is to, say I'm. Gonna drive by in too often those, has anyone here actually, built a business case in the past like at a real company, ok. Yeah I figured some of you would or at least participated, in it oftentimes. Companies think about business, cases as before. And after, before. We need a business case to sell this internally, ok. We'll go and do some numbers after we. Have our business case that's the end, it's it's powerful unfortunately. This doesn't work often, there's. A socialization. Process, that needs to be followed and there's a lot of storytelling, it's not just numbers it is a vision of how this is a technology, is going to impact your business so the, business case lifecycle, suggests that you have to do iterations, these. Iterations are not just numerical, they involve a lot of socializing. And buy-in step, one is to establish with.

An Initial ROI model, or traditional, business case using, external numbers, right so maybe the vendor says here's some customers, that we've served here's some numbers maybe Forrester gives some numbers somebody, gives numbers of others, who have attempted to use this technology in the, past and you build an initial business case but guess what that's not your business case you, need to go through the cycle you need to elevate that use, that initial ROI calculus. To, start having conversations across. Barriers if you are a business, leader this means going and doing a deep dive with, the technologists. And operations, people to, make sure that this technology fits into the infrastructure, if you are you, know a more of a leading-edge technology, type leader, you, need to work with other business, people to get on board right and it depends on what vertical but no matter what vertical, you are in you need to start having these conversations as, you, build those coalition's, hopefully. A vision. And a strategy for. How this, investment, will change your business will, begin to emerge the, creativity, of the group comes into play this is not just a purchase, of some off-the-shelf, technology. It is a systemic, change so. You have to build that through a lot of hard work and if you are championing, this investment you're in charge of doing that okay. Hopefully you have gotten that buy-in then. You do a pilot a pilot. Is a limited, but, real test, of how this technology will operate you, will pay money to do this pilot you will invest to, make this happen but you will collect data on customer. And, and financial, outcomes that, will help you down the line to, determine if this is the right move for you strategically. Because, what you'll do is you'll plug that data into another. Version, of the, business. Case that is much, more representative of, reality, because, it is based on your organization. Your verdict your experience, rather, than promises. Coming from some vague vendor, you, know saying oh we can make we can make magic happen does, that make sense this, is a process, and and, and you know one of the things when I was like, your age that I didn't really understand was this whole issue of buy-in. And and and sort of internal. How. Organizations. Actually work that's, why you know it's a great idea to get an MBA because. I think you'll get you know you'll get a lot more exposure to that than, I did. Sometimes. In order to make this happen radical, storytelling, is required, what, I am showing you is a real comic.

Book Strip that was used by Lowe's when, their, Innovation Lab wanted, to do the, Lobot which is a customer, service robot that, wanders around and, you can speak to it if, I've used it you can say Lobot, I want the Black and Decker such-and-such. Lobot. Is connected, to the inventory management system, and Lobot. Can say okay we have the black and decker such-and-such would. You like me to take you to it and then Lobot, will start move in and, you'll walk actually, the number one complaint right now is that it moves too slowly, it's. True like people don't want to wait for this thing because it's like I don't want to kill children but. You know what they did was they in order to do this I mean like this is a radical, vision like not everybody's, gonna be able to get you know an investment in a robot, in their store they hired, professional. Science fiction authors to write stories about the future of retail particularly. Hardware they really did this they, took the best of these stories and they distilled them into a comic, book that, was used to tell the story of what the endpoint would look like and by, describing, the endpoint, what they were able to do is to get everyone to say of, course we want to try to do this everyone, got excited rather, than when, you show a PowerPoint and you sort of go slide, by slide sometimes, it says people in the audience say oh that's gonna take away from my budget, oh that's gonna be a problem for my people rather, than that get everyone to agree on the endpoint and then, decide how you're gonna do it later so that's what worked for Lowe's it may not you know your mileage may vary but, radical, storytelling, doesn't mean you've, got to do comic books it means you, have to think outside the box figure, out what works culturally. At your company, for, storytelling, and then take it to the next level and find, a way to do that. Like I say you don't really need all these things you. Need to have it's. A it's a buy-in technique, so, that's. Sort of the intro I wanted to make sure we got to some Q&A because I think conversation. Is really important, I feel an awful lot at you but I'm curious to hear what questions, you have about emerging. Tech yes. Please. There. Will be a tremendous amount of national variance of the performance, and the. Execution, of these things data, privacy, is a really good example because. It impacts AI in a great way, anyone. Who's ever worked in Germany will tell you that they have the strictest privacy rules, in the world in Germany this, is just a reality you have incredible. Limits on the, type of data that you can collect it. Goes beyond what if you've heard of GDP are the the new. European, privacy law it goes well beyond that China, on the other hand has an awful lot of latitude right I mean they are scoring people, based, on sort, of their performative, nacinda social, context, and they're using that data so you're going to see very big, fork between a country like Germany in, a country like China in, terms of how they use that data because, they have different levels of it and what, they can do with it so, national. On a national, level it can matter a lot I think it can also matter a lot within a country we. Have a current administration, that is not focused, on regulatory, action, to. Put it mildly right so, I think that you know in this environment for this country, we're gonna find that there's going to be a lot more experimentation. When, regulation, comes in which you know just candidly, like I'm a regulatory, type, guy I'm like let's regulate but there are dangers to that - you could squelch, the, power of, new, movements, that are going on Patrick. And I were having a conversation about driverless.

Vehicles, You know and I think you. Know on the one hand the United States is kind of the Wild West right now for this because, it's. Basically, down to the level of the municipality. If Pittsburgh, you know a San Francisco famously, said no more wham-o cars which is Google's self-driving, car, effort because, someone was was hit by a car. Basically. Though you can find a town somewhere, in the United States to trial the stuff out including Boston where I live you have new tana me running around the Seaport District right now but. Other other areas, you know you're not having it because they say that it's a safety danger, bottom line is this is a very big area to navigate both. On a national level on a you know I think on an administration, by administration, level and very much locally as well, yes. Please. Labs. In, addition labs and older playing this can you talk about giving. Forces prototypes a lot of different companies how. Our companies incorporating. This labs concept, well in, terms of investing. So. The. First thing to know about innovation, labs is most of them fail they. Become cost centers or perceived, as cost centers very, famous failure was Nordstrom, Nordstrom, actually. Made a big PR campaign out of this they said we, have 50, people this was a couple years ago 50 people and innovation, and they're working on augmented, reality and, data science, and customer, experience they had ten different roles in that in that lab and you, know sort of quietly about a year and a half later even though Nordstrom's. Growth at that point was very high their financial returns in general very high, mysteriously. They stopped talking about the lab and all those people were redeployed right so, the best-case scenario is to have a small focused team of people no, more than 20 employees who. Have a mix, of business. Operations, and IT experience. Who, can come together and, understand, how to apply these. Things to problems, they also must be allowed to fail as our reference this is a great place, to do that in, science, as we probably all know failure. Is a very big, teacher in. Business, too often failure is not a teacher because you lose your job in. An Innovation, Lab you need to have a setup that is pragmatic, enough to, drive actual, results, while, also recognizing that you learn from failures, and you have to have a portfolio earlier. I talked about how you're gonna have different, levels of risk for different technologies, doing, a project with a mature, existing, technology. That has just never been applied to your vertical, and your business is a great idea because you know parameters. About that tech but, in your portfolio, you should also have riskier, more emerging, things that could be leapfrog, that could be disruptive, you know that against my very pragmatic, wisdom today may actually out of the blue change your business so, it is definitely there are there. Are definitely, some. Organizational. Structures, that can be placed you, know in on an Innovation Lab that, will. Help it last thing I'll say is very interesting, there's a whole debate in your. Professors could tell you more probably about this than I can but you know there's been this debate since Bell. Labs which, was sixty years 70 years ago about. Where to locate an Innovation, Center do you want it close to your business do you want it far away and I've seen companies that do both things if, you are Viacom, you, feel. Like innovation needs to be seen by executives, every day so you put your lab in the middle of Times Square at the headquarters so, that every time that the the executives. Walk through you can show them the current project, if you're Nestle, and your your your existing. In a small, town in Switzerland where, everyone lives in the same town everybody, is Swiss or whatever you, know it's all very insular. They, decided, to put one of their outposts. For innovation, in San Francisco, they said we need to be closer to, the disruption that's, going on in Silicon Valley and, they send people on the six-month tours from from, Switzerland, so this is a big area I think the thing is there's, a wave every, few years it's like innovation labs oh they don't work Innovation Lab so this, is um this is a procedure. Because. Often, times these things don't work I have, done a lot of work in this area happy. To chat about it at lunch if you come. Yes. It's. An excellent question and right now we're at an early enough stage that, this is not often.

A Problem so if you're in a law firm and you implement, ediscovery. Software, there are enough people around who, have done this job manually, that they understand, how this works, and they can still tutor people and and all of that we, do have in different verticals though where, maybe there's less like. Let's say you have people. Who have a high turnover rate, in your company, you're, gonna have very, little of that an organizational. Wisdom you're, gonna have to rely, very heavily on learning and development to create curricula to, train people on how this works, it is not insuperable by the way the auto industry, has done this for you. Know 40 years right I mean using, there. Are certain tasks that are simply never done manually, in on a car line, except. Under duress circumstances. So, what you wind up getting are people who understand. How to manage the bots they, understand, how to manage the technology stack, in a waiting to change the parameters and by the way you're gonna find that machine learning over time really, helps them it augments their decision-making because you, learn and you learn and you learn and the system is always learning so, the input the outputs get better I would, say your question is powerful because there will be a skills gap it requires new kinds of training but on the other hand as we automate, certain things the, very, skill, set of managing the bots maybe, all that's needed you, had a question. Our. Knowledge. Is leading companies also me. How. What. Strategies. Yeah. I mean this is uh this, is a huge problem and sometimes you should talk to Patrick about this he used to do this work and Deloitte. But um the. One. Thing I would say is it depends, on the kind of business you are in but, the technical, debt that we're seeing today are things like we haven't moved to the cloud at all or we. Have we're using there we talk to companies not. All the time but pretty, regularly they'll say I have a software system that was running since the 70s. Really. It's. True it happens in healthcare for regulatory, reasons it happens in even. In telecom I talked to a company that was using a really old mechanism, and and by the way in those cases often, the people who program, that or long-dead so, sometimes, you need to actually go, to, the, level of the Board of Directors to.

Do A digital transformation you hear a lot about digital transformation, digital. Transformation, is essentially, a set of building blocks that is to say we have these we have these very fundamental systems. And sometimes you have to rip them out you, need to be able to build enough, of a overarching. Business, case to, be able to say we need to invest in this forward-looking. Leaders will recognize, that that agility everything, else up that stack is predicated, on the bottom line infrastructure. But what often happens, is, quarterly. Performance. We. Don't have the money the, reality, is your company will go out of business if you do not address these things you will not be able to compete even on the basic level of email marketing which, by the way is a basically, a defunct category. Of marketing now so I guess what I would say is there are no easy answers believe, me I have, these conversations with clients and I'm like I don't know what you're gonna do you're gonna have to try again because you you don't have the fundamentals in place but, what I have seen is that there. Are certain leaders, who are able to say look we have this one problem, but it's interconnected. To your problem, you can get other managers, on board, with this and then there's there's change I talked to this CIO, who came in from the outside and didn't, know what she was getting into very, recently and she said wow, I I like, a turnaround, story but this is like we. We need to start from scratch and, so, her approach. Was to, build, mini. Business cases with different leaders and sort, of form a coalition, within, that organization, to put the pressure on upper management, so, yes. To. Stop the car surrenders. To, dynamic. We need to my movie, day I people, kind of complain, a lot of things yeah there's also a big waiting machine learning and then you can think of augmented. Intelligent funny things like do you think that matters for people to think about yeah. Oh. It's a really good question I mean I for, for reason of time I didn't include our like, what is AI slides but you know AI. Is being thrown around as if it were some unitary, phenomenon, when it's really not AI, is, a broad, set, of Technology tools that, mimic, how, human. Beings are able to sense think. And act. Everything. From I want to sense the world through computer, vision and, I need to be able to identify what objects, are using, broad, databases. Lots, of machine learning goes into that lots, of deep learning increasingly, goes into that machine. Learning and deep learning or building, blocks that are part of AI but they are not all. Of AI there are other tools as well natural. Language understanding and. Natural language generation, flip. Sides of the same coin related. There, so essentially, what we're dealing with are a number, of discrete. Tools that need to be woven together to. Make a solution. This is hard to do it. Is something that often if you're at a non technology, firm you often are gonna work with outside vendors. To. Help you to do this because weaving. Those things together or you may go and buy the IP, soft Emilia and sort of live, within the limits of what they can do right, now the well. We predict in fact I'll give you a sneak peek because this is um right, now is when we start to do our predictions. For 2019 the, one I had one of the ones that I've submitted to our editorial. Board is that. AI washing. You know you've heard of green washing where.

You're You're not really environmental. But you say you are AI, washing, will become a huge topic by the end of next year because so. Many organizations, are purchasing, AI solution. That are not yielding the expected, or anticipated benefits. Because, they do not understand, what they're trying to do they're boiling the ocean like MD Anderson, they are the. Vendors are over-promising. And under-delivering. They're, just a host of problems so understanding. What AI is in, your context, I think is crucial time, for one more. Really. Quick question last question otherwise. I will say. Well. Yeah I mean the first success, thing is very powerful actually my research shows that as well if you can engineer, an initial success which I realize is kind of chicken-and-egg, right if you can't then you're in trouble but being, able to then be very good as an evangelist, as a PR, person as an internal, marketer, these, are important, skills and if a lot of times technologists, do not have those skills business people sometimes have the skills but don't have the technology chops, too so as MBA, students I guess my last recommendation, is whatever, vertical. Industry, or area of business you're going to be in technology, will touch it be digitally, literate and very good luck to all of you thank, you.

2018-10-16 16:35

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