Preparing Your Organization for the Future of the Workforce

Ian Bester, General Manager @ Brainstation; Falon Fatemi, Founder & CEO @ Node; Benjamin Powers, Freelance Tech Journalist

Ascent Conference 2019

Benjamin Powers [00:00:06] I think let’s just dove right into it, and I’d be curious to hear kind of because there’s such a wide array of backgrounds that people have that bring them tech, if you could talk a little bit about what brought you all into this field and then also just give a bit of background on a Node and brain station.

Falon Fatemi [00:00:22] All in one shot. So my name is Falon Fatemi, I am the founder and CEO of Node, which is an A.I. company based in San Francisco. Before going into what Node is. I was born and raised in Silicon Valley. So it was sort of born into the tech world. Started working at Google at 19 years old. I was the youngest employee there and spent six years there, six years in the startup world, and then ended up starting my company node at Node. We have invented artificial intuition, which is a proprietary deep learning platform that analyzes people and company data and turns it into use case specific predictions that enable organizations to understand which prospects will become customers, which customers are likely to churn before they turn in, which key talent is likely to leave before they leave. Our customers use our technology as a piece of prediction infrastructure within their applications to accelerate their time to market for turning their application data into prediction about features. And then we also worked directly with Fortune five hundreds and mid-market, fast growing companies to help them with their talent and customer turn.

Ian Bester [00:01:30] Hi there, guys. My name’s Ian Bester and the general manager BrainStation, based here in New York before I get into BrainStation. My background in technology doesn’t go too far back. I come from a retail consulting background and I work for a company called Barrows that was forging the way ahead in terms of blended retail experiences. And for a company that worked in retail for 30 years historically and the physical spaces, it rapidly needed to evolve itself into the digital world. And so I was given the opportunity to lead that initiative at the company. And so I had to rapidly upscale myself in technology and also hire a team around me to be able to go and develop the products that we were building in this digital physical world that we’re moving into. And so I, in that period, learned a lot in a short period of time around technology and how to build products, both digital and physical products that worked together throughout the customer journey and and also how to empower people with the right skills needed for the future of the business. So that’s where I started to really get interested in technology for Brain Station. Brain Station is the global leader in digital skills training, supporting businesses and professionals with workforce transformation training and professionals with the skills they need to future proof themselves in the future economy. And there is no time like the present for everyone in this room as an example to start thinking about what skills they need to be able to be relevant and to add value back into their own team and into their future career. So Brain Station provides in-person online learning and online live learning, which democratizes learning for the future of work. And that is our ultimate goal. We have an aim of educating a million people by 2025 and we’re well on the way thanks to online live learning and on demand.

Benjamin Powers [00:03:19] And Falon, so talk to us a little bit about the really the business opportunity of integrating A.I. and artificial intuition into these workforce’s and workspaces more generally, what are companies kind of missing and what does it bring to the table that we really need to be thinking about in the next five years, the next 10 years?

Falon Fatemi [00:03:37] At the end of the day, I is really hard and I read an article in the paper this morning that actually stated that I was going to add 13 trillion to the global economy. But the rate of adoption is is very slow. And the reason for that is there is a ton of organizational and cultural barriers, especially in the Fortune 500, where they have legacy solutions on top of legacy solution that actually prevent them from being able to adopt these types of cutting edge technologies. And the reality is that the next wave of transformation has to come from the enterprise because we are in a situation where, you know, really these organizations have to innovate or they’re going to die. And we’re seeing that in just general stats over the last 20 years were over 50 percent of the Fortune 500 have disappeared and life expectancy has decreased even more dramatically from 75 years in 1950, five to 15 years in 2015. And we’re not even talking about A.I. playing a part in that. So I will be a wrecking ball to the enterprises that don’t adopt it. And so to your question around, what’s the potential benefit for these organizations? Well, it’s basically helping them get a real understanding of the core aspects of their business internally and be able to make better decisions as a result. So, for example, if you knew which next markets of opportunity you should tap into for, say, a new product that you release and that’s going to accelerate your time to success and revenue and profitability and competitiveness, I mean, who wouldn’t want that if, you know, which key talent or executives are going to leave before they leave, before they even know that they’re disengaged, you can actually step in and do something about that and save on four to five more costs that you’re going to spend in trying to replace that person, retrain them, and that doesn’t even count any of the cultural impact. So what we’re talking about here is leveraging this type of technology internally within organization, analyzing the data that they have all over the place in whatever shape or form it’s in, and turning that into basically a crystal ball for them to be able to make the right decisions for their business.

Benjamin Powers [00:05:39] No, thank you. And then uhm Ian in kind of zooming in on the employee workforce itself, what are some of the things that brainstation is working on to really help them engage with the feature that Fallon’s talking about and kind of these necessary changes, you know, just even kind of understand the vocabulary of some of these systems having a certain comfort level. Can you speak a bit to how you all are trying to shape workforces towards that future and get them prepared for it?

Ian Bester [00:06:01] Absolutely. So I guess let’s get a let’s get a take in this room. Who feels comfortable with the understanding of machine learning as an example? Hands up. OK, yeah, it seems like about 30, 40 percent of the room maybe, and there is no question and I don’t want to use the C word, there is a threat to our economy in the future. And I don’t think people are realizing it right now because it’s a slow burn. It’s it’s the burnout of skills that people have learned in college and traditional education that they believe is going to take them through their career. The average now in the recent Lillington study says that millennial will great recent graduates are going through one and a half jobs in their first five years of work just in the last three years. That’s doubled. Not only that, there is a workforce across the globe of one hundred and twenty million that have to be retrained in the next three years. And the undergraduate students subscribed to undergraduates in the US is only 20 million, and only half of those end up working in the field that they studied and their major. So there is a huge skills gap in the global economy that we have to tackle and as individuals we have to tackle. Companies can only do so much. They can they can invest in learning platforms and and providing their staff with development budgets. But it’s also up to the individuals to recognize this need and recognize this gap. At Brain Station, we are committed to helping businesses tackle that transformation and tackle that skills gap by helping to up skill and retrain and retool staff so that they don’t have to spend millions and restructuring people out of a business. And in addition to that, supporting professionals with taking their career into their own hands and helping them with the skills they need. We do that through a number of means. We help them in person through the five key pillars of the digital product lifecycle, data design, development, marketing and product management. And we provide them with hands on learning through expert instructors who we’ve solicited through the industry that we vet vigorously before getting them up in front of all our learners. In addition to that, we democratized learning by providing an online learning platform through Synapse, our custom-built online learning management system where they can dial into any of these courses. There are about twenty five across these five pillars that they can dial into in the evening and learn these, learn these specific disciplines that’s helping them individually and for workforces. We’re helping train teams through this transition that we’re seeing in the industry right now.

Benjamin Powers [00:08:43] And I think in conversations previously we were talking about some of the cultural barriers just within institutions to try and move these things forward and really get organizations future facing. What are some of the ones that in each of your instances you run into most commonly? And what are some people should be looking out that might seem comfortable right now, but real obstacles to really embracing the sort of future?

Falon Fatemi [00:09:02] So I’m a big believer in digital transformation has to come from the leadership. And I think the CEO hostile, not frankly, if it doesn’t come from the top and it’s not a corporate strategy imperative, it will not be successful within an organization period. End of story. And we’ve seen this time and time again, because what ends up happening is without understanding the greater picture of the greater impact and how it’s having more holistic strategy around how it’s going to be a layer within the organization internally or be integrated into the product that you’re then selling to your customers, you end up with solutions that end up maybe costing you millions and years in risky experiments, maybe providing a 10 percent kind of nominal sort of increase or improvement or whatever metric you’re trying to drive it around. And it ends up largely failing as a result. So there’s a lot of other layers as well as you start to peel back the onion in terms of why it doesn’t work. And that also includes, like a lot of these companies that do have analytics, people are data scientists within those organizations. And I’m really talking like more, you know, larger companies here. They they’re very much comfortable with the way that they have been doing things and the way that they have been evaluating things in a way that they have been analyzing things. So changing that and disrupting that is a threat in a lot of ways, especially when we’re talking about bringing in new technology that might take away some of the sexy stuff that they like doing, like building algorithms, when the reality is they’re not really building algorithms, they’re doing fancy data analysis. And, you know, cutting edge deep learning is really the right tool for the job for a lot of complex business problems. But there’s not a lot of understanding of that kind of technology proficiency with it, comfort with it, because they can’t explain it, which is just a temporal thing. And so what you basically end up with is, frankly, a lot of pushback, a lot of politics and a lot of it’s coming from fear. So the way that it needs to be positioned at a leadership level is that this is an existential threat. We need to advance and change the way that we do things. So that it leads to market domination and profitability and success, and that has to start from the top.

Ian Bester [00:11:19] Yeah, and sort of just reiterating the point, it is a huge threat ahead of us and the economy. The other thing that’s interesting about workforce transformation is that I think everyone in this room, in this conference is pretty, pretty savvy when it comes to technology. But I guarantee many of you are going to be very successful in your respective businesses. And in the next 10 years, you’re going to be looking at trying to find the talent you need to take your business from them into the next chapter. And that’s where you’re going to face that threat in terms of how you’re helping your staff actually become fluid in their intelligence. And that’s another term we need to be comfortable with. It’s fluid intelligence that we need to start leveraging in our businesses. And we can do that by providing teams with the support they need at the very, very top. And we read about it. About 50 percent of CEOs say that upskilling or retooling their staff is their number one priority. A lot of that you can read through because action, you know, you need to see the action to see the proof in that. But the challenge is actually individuals and the individuals themselves taking that leap of faith into their own hands and taking that step into the right direction. Yeah, you might not know what machine learning is now, but tonight you can go and read about it. You can sign up for a course. You can actually study it and become proficient in it within the space of three to six months. And it’s just getting off your ass and going and doing it.

Benjamin Powers [00:12:42] And I think you were telling me that you see as recently spent going to spend a lot of money educating their workforce and they likened it to something as essential as health care. You know, what sort of incentives can companies take to get their employees to go and do that extra reading? You know, people have busy lives. We only have so much time. So what are the ways that companies can really be a channel for that rather than being an outside thing that individuals have to take up on their own for fear of getting out of the future of the workforce?

Ian Bester [00:13:06] Yeah, actually, the numbers are quite staggering. I read it this morning. It was three billion dollars into retooling and reskilling their workforce globally. That was the biggest number I’ve read in recent in recent weeks. And every week, every day, there’s another article about another CEO investing into their workforce. So it’s prolific. The question itself is really important because what they can do is, is multifaceted. There’s two parts you can look at a digital transformation and look at restructuring entire business. You can you need to find a blended workforce mixed with adaptable individuals and hard skilled individuals and believing in your in your high performers and investing into them and giving them the time they need in the workday. Because, as you say, we’re busy individuals to go and invest into that skill because the payback in the in the few months after they’ve done, of course, will be immediate. They’ll be actually able to apply those skills immediately into the workforce like data. As an example, you’ll be able to understand what questions to ask in terms of trying to infer the insights you need from an incredibly large dataset and how to present that back to your stakeholders within the business, which will make you more valuable and which will put you into more interesting roles and interesting jobs going into the future.

Falon Fatemi [00:14:24] I look at that question a little bit differently, and I agree with what you’re saying, I think also, though, there is this element of organizations really, you know, looking themselves in the mirror and understanding where are their strengths and where are their weaknesses. So a lot of companies and a lot of analytics teams and smart data scientists, they want to build everything from scratch. And that’s cool. But is that your core competency as an organization? Is that really where you should be investing your time? Does it make sense for a payments company to become an A.I. and data company? I don’t think so. I don’t think that’s the right answer. And absolutely, you will need to skill your workers so they understand, you know, the latest and greatest technologies and can architect the right systems and solve the right problems. But building everything from scratch is not the answer. And that’s why that’s part of the problem that we solve in terms of coming in and helping accelerate the ability for organizations to leverage their existing resources with their existing talents to be able to solve these complex problems.

Benjamin Powers [00:15:20] Yeah, because you’re a bit more about how artificial intuition can can the portability of that and how that can really come in to an organization and help them leverage some of these skills. What are some of the techniques it uses in how is that, you know, make it work for each company differently, but in a really kind of individual way?

Falon Fatemi [00:15:36] So what we’ve done is we packaged up our technology into a rest API, meaning any developer that can make for API calls can basically create models and do machine learning at scale. And obviously that took multimillions and years in engineering and unicorn’s of talent on our team to make that a possibility. But the secret sauce underneath that simplicity is data in combination with use, case specific and proven models. So we’ve spent the millions. And so so actually, before I even go into like how it works, I think the really important piece here is the the dirty little secret in artificial intelligence. And that field in general is everyone thinks that the aizer, the algorithms are sexy. It’s not about the algorithms, it’s about the data. And most organizations lack a deep understanding about the entities, the people, the organizations, whether they are in their product or that they’re interacting with or a client or talent perspective that is actually required in combination with their own, you know, core IP in terms of data to really generate these times. If you use case specific predictions, and that’s part of a product value chain that we own. So we’ve spent the millions and years in acquiring a data layer of half a billion profiles of people and organizations. This is used to basically retrain our A.I. system to in some ways comprehend and uncover. Got it. Uh, implicit attributes which drive more precise models and require less training data so that in combination with cutting edge, deep learning packaged up in a way that any developer can plug and play without needing to be a data scientist and without needing to spend millions and years. And that entire process being reduced to a matter of seconds is how we solve that problem.

Ian Bester [00:17:24] I just want to build on that in terms of this this idea that automation and machine learning and AI is going to usurp a lot of roles going into the future. It absolutely is. And there will still be enough work for everyone out there. The only problem is the transition for people to get into that space is going to be incredibly hard. Think about the end of the industrial revolution or the agricultural revolution. It’s we’re in for a tough 20 years. And I do believe that just by putting the effort in as an individual and as a business, you will reap the rewards.

Benjamin Powers [00:18:00] And so as we start to wind down, you know, this panel in this session, I’d be really curious to hear about what are maybe the top three kind of way points that companies should be looking at in the next 20 years to both make sure that the systems they’re using get to where they need to be and they can leverage the tech that’s out there in a really productive way and not just kind of stay stuck in the current times and then also for their workforces generally and bring them into the future with them. What are what are maybe three takeaways or other areas that they really need to keep an eye on to ensure that they’re going to be there even in 20 years.

Ian Bester [00:18:33] Give that one one second to think about that one, because there’s three yeah, I would say we’ve mentioned it already. It’s it’s take your your workforce seriously, take the development seriously, invest in them and don’t look at your bottom line and think it’s all going to go to waste. I promise you, it won’t find a partner you can trust and believe in and build out a roadmap for the transformation of your workforce, no matter how small your team is or how big your team is. We work with a lot of Fortune 500 companies all the way down to teams of of 10, 20, 30. And so you’ve got to make that commitment into your workforce and find a partner you trust. And then as an individual, I’d suggest you need to take your career into your own hands. I couldn’t be more clear on that one.

Falon Fatemi [00:19:21] I’ll give it one or two things. Only build and house, it is central to your core competency is No. One. If not, then partner for that type of technology. And then my second piece of advice is make sure you bring in the right talent and are really understanding the impact of the technology from an ROIC perspective. So hiring tons of bodies that are really expensive and that taking millions in years, a longer time horizon to then get to an ROIC increase of 10 percent, not worth it. So really, really understand what’s the right tool for the job and how long it will take to get you there. And if you’re spending more more money on the actual bodies versus the technology, then that’s one answer.

Benjamin Powers [00:20:15] Well, great, thank you all so much for joining us and thank you so much for sharing your insights. And I’m going to hand it off.