644: How to Sharpen Your Skills for Jobs That Don’t Exist Yet with Michelle Weise

Pete Mockaitis
Michelle, thanks for joining us here on the How to be Awesome at Your Job podcast.

Michelle Weise
Great to be with you, Pete.

Pete Mockaitis
Well, as I was reading all about you, one thing that I found, I guess, touching or moving or wanting to touch up on for a moment was we’ve spoken with some people who have worked and written books with Stephen R. Covey, and it was just sort of beautiful to hear some memories of that great man and teacher who’ve lived on, and, likewise, I wanted to hear a bit from you, to start us off, about working with Clayton Christensen. What’s something folks should know about him and who he was when you were collaborating with him?

Michelle Weise
He was one of the most generous people. He would always kind of make you feel like you were the most important person talking to him at that moment. And, it’s funny, I had a lot of folks who would see him speak at large events and they could sense his sort of folksy tone from him and his kindness, and he would say these beautiful things, and people would turn to me and say, “Is he really that nice? Is this for show?” and it really wasn’t.

He was sort of rooted in that way. He was driven by a really intense faith. He was a Mormon. At his funeral, it was kind of amazing to hear the incredible amount of service he did on the sidelines. And that just sort of…that feeling of just kindness and generosity that was emanating from him, I think it just showed through every action.

And, for me, it was life-changing to work with him directly and to write with him and to learn from him, and to go very deep into the theories of disruptive innovation and sort of see where he would get frustrated with kind of the misuse of his theories. And everything I learned about storytelling, I learned from him.

Pete Mockaitis
Well, that’s beautiful. Thank you for sharing. And so, oh, yeah, we’re going to be doing a little bit of storytelling, I suppose, here about your insights associated with long life learning. I keep almost saying life-long learning every time, it probably happens to you a lot with your collaborators here. So, well, hey, let’s go meta for a second. Michelle, tell me, how can we tell this story most effectively?

Michelle Weise
Yes, so the reason why we’re getting tripped up on long life learning is we’re so much more familiar with this concept of life-long learning that we should be constantly learning how to learn throughout our lives. What I tried to do in this book was to move us into action. I was just noticing a lot of inertia around this concept because we know we need to reskill throughout our longer more turbulent work lives. But where is the actual infrastructure to sort of take these on and off ramps, in and out of learning and work, or do both at the same time and not have it feel so painful?

And so, for me, this mental shift comes through this concept of a longer life. If we extend our life spans, which we know since 1840, we’ve tacking on three months of life to every single year since 1840, so our life spans are just definitely extending but so are our work lives. When you look at early Baby Boomers and how long they’re staying in the workforce and how many job changes they go through by the time they retire, it just helps us kind of snap us into attention, and to say, “We have to start building a better functioning ecosystem in which we can access the education and training we need in order to thrive in the labor market.”

Pete Mockaitis
Okay. And that thesis seems to just make sense as a natural implication of living longer and such. So, could you maybe share with us something that’s surprising or counterintuitive as a discovery that you’ve made along the way as you’re putting this together?

Michelle Weise
Yes. So, I have been doing a lot of research on the future or work, and what I noticed in a lot of the literature and the analyses out there by chief economists as they’re trying to sort of forecast all the different kinds of ways in which jobs are going to become obsolete or this industry will become decimated by these technologies, what I realized was this kind of intense focus on the “it”, or the things or the jobs, or the tasks and numbers.

And so, what I realized is if we actually kind of move away from thinking about the future of work to the future of workers, and all of us having to somehow kind of move through this learn-earn, learn-earn cycle, to me it kind of helped surface some of the most intractable issues and barriers that we need to solve for today.

So, what my book does is it really actually elevates the voices of people who only have a high school degree, who are constantly being overlooked for work they could actually perform, and noticing where the barriers kind of coalesce. So, these concepts that I come up with around better career navigation, or better wrap-around support services, or more targeted educational pathways, or more integrated learning and earning, and more fair and transparent skills-based hiring practices, those aren’t just coming from me thinking what we need to do. It’s really kind of trying to gather all this qualitative data.

We did over a hundred hour-long in-depth interviews with folks to sort of sass out, “Where do people keep kind of bumping up against pain points?” And if we designed this future system better, then all of us are going to actually end up benefiting. It’s the same idea of the curve cuts that we did when we kind of created the Americans With Disabilities Act.

When you’re cutting into the curve and you’re making a sloping curve, you’re not only helping folks who are disabled who need to use a wheelchair, but you’re helping mothers pushing strollers, or FedEx delivery folks with their dolleys, you’re helping runners, cyclists, skateboarders. It’s this idea of universal design. But when we want to target our focus, because it just seems like this huge, expansive challenge, we focus on the people, the future of workers.

Pete Mockaitis
Lovely. Okay. Well, so then, as we got a lot of workers listening right now, can you sort of frame things up for us a little bit in terms of…? So, you make a point that the old model of, hey, there’s education, then there’s work, then there’s retirement isn’t what we should be relying upon going forward. Can you expand upon that?

Michelle Weise
Yes. So, just the notion that we could have one or a handful of jobs and retire in comfort, that’s already become sort of a quaint notion. And when you look at the amount of job changes that people are experiencing by the time they retire, folks are already going through, on average, 12 job changes by the time they retire.

And so, as we think about that longer more turbulent work life that is shaped by rapid advancements in technology, we can only extrapolate from there, “Wow, we may have to somehow entertain 20 or 30 job changes by the time we retire. And so, how in the world are we going to navigate that when one is just so difficult to navigate?”

Pete Mockaitis
Yeah. Well, lay it on us, how should we navigate these optimally?

Michelle Weise
Yes. So, I think the perfect illustration of what’s not working today is when we look at what the pandemic has shown us, which is when retail and hospitality were just completely decimated as industries, we had no way for people who were in those customer service roles or those frontline worker roles to actually transfer their skills from retail or from hospitality into something totally different but to identify their kind of transferable skills.

And I think, all of us, we believe that we have really important kinds of skills. Those transferable skills that can help us port our assets from one specific area to another. But, in general, when you think about the job market, we think about it in such a linear format. We kind of, if we start off in retail, or if we start off in office admin, when we think about advancement, we think within that line of work. It’s harder for us to sort of think about moving beyond that industry that we started in.

And the reason why we feel that way is because that’s what employers tell us, right? The employers want to see exact work experience in hospitality to move you up to a manager role. We don’t have ways of validating other kinds of experiences. So, one of the key solutions for us that are exciting for us to anticipate, and we already see these different kinds of AI-powered platforms.

What they’re doing is they’re helping us surface maybe some of our hidden skills. The skills that aren’t necessarily recognized by a formal credential, like a degree or a certificate or a certification. And what they’re doing is, as we’re typing in, I used to be a barista, that signal of the barista helps the platform actually surface, “Oh, did you know that folks who were baristas they have these specific competencies and skills.”

So, there are ways in which these platforms can not only help us surface our own skills but then help us envision pathways where we might actually be 75% of the way there towards something in human resources, or 85% of the way there towards something in advertising and marketing. We just didn’t know it; we couldn’t envision it for ourselves.

So, these kinds of tech-enabled platforms are interesting kinds of seeds of innovation to look at that might help us not only kind of validate our own skills whether we’ve acquired them through taking care of our own families or through work experience, and also understand the kinds of gaps we might have to fill in order to move into these other opportunities.

Pete Mockaitis
Well, that’s really interesting when you mentioned that if you’re a barista, you can very well have under the surface like all of these skills that you’re applying there. And that reminds me of a previous guest we had, Todd Rose, talking about dark horses and how what might seem like completely different skills are actually, if you zoom way in, super similar in terms of, “Oh, actually, well, you’re using your hands to shape these things into other things so that they fit. Those are similar.” Much like, “Oh, you are optimizing a manufacturing production schedule is sort of like solving a puzzle over in the realm of math or physics or something that, who would’ve known, those are quite common or quite complementary.”

Michelle Weise
Yeah.

Pete Mockaitis
Well, these platforms you speak of, how do we get our hands on one? So, can I go to some website right now and it’s going to tell me all my hidden skills?

Michelle Weise
So, that’s one of the challenges. There is like a free one off of Emsi called Skills Match where you can start to surface and kind of build a resume using these technologies. But this is one of the challenges and this is what I’m trying to point out in my book is that there are hundreds of thousands of innovations and solutions out there. The problem is for any normal person to understand where to go, like if we’re suddenly laid off, we don’t know who to call, where to go, who to talk to.

There are so many of these solutions out there but they’re not knit together in a way that’s easily understandable and navigable for any person. It’s not that we need a whole slew of new innovations. We need these things to become just more accessible so we can understand and comprehend how to navigate this who to go to for, “How do I know that when I pick this learning experience, a future employer is going to validate it and understand what it means? And how do I know precisely which skills I need to acquire? And which school actually offers those three competencies? I don’t need a degree, maybe. Maybe I already have a degree. I don’t want to go back to school full time. How do I get just what I need in order to move on?” And that’s one of the challenges.

But there’s a bunch of these groups, like Skyhigh, FutureFit. And what they’re doing right now is they’re more B2B, they’re more working with enterprises and trying to help them get a better understanding of who’s in their workforce. Because a lot of companies, and it’s very odd to think about it this way, but most companies don’t actually know what their people can do.

They know job titles, they know names. They don’t have a real granular sense of the skillsets, the competencies, all those hidden talents that folks have. So, that’s where these innovations are starting is trying to help employers be less wasteful, not always recruit externally, but look at the talent that they have right in front of them, and think, “Maybe I could actually take 30% of these folks and build their skills in X, Y, or Z technique or strategic goals for the future.”

Pete Mockaitis
Yeah, that’s exciting, and, indeed, it just seems like a huge opportunity that’s just waiting to be plucked. A great manager would know a lot of what their team is capable of. Yet, how is that information captured, collected, and transmitted elsewhere? And one of the incentives for doing so, you’re like, “No, Michelle is a rock star. She’s working for me. Get your hands off. I don’t want you to snag and do a completely different function.”

Michelle Weise
That is a real challenge within the companies. Yeah, this kind of like zero-sum game of, “Oh, if you take my person, you’re hurting me versus helping the company.” It’s hard to get out of that mindset.

Pete Mockaitis
Totally, unless you have sort of a widespread culture and reciprocity and such so that you say, “Hey, you know what, there’s give and take, I might lose Michelle for a couple months, but I’m going to get Phil who’s amazing and fills another role that we really need,” so there’s that trust there that can be handy.

Well, now, you just got me dreaming big, Michelle. I remember I once, I don’t know if I’m going to do this or not, but I hope someone is doing this. But when you talked about the high school folks who did not have diplomas and yet are capable of doing so much but it’s hard for them to sort of prove that. I kind of imagine just like forming this whole business where we just sort of like assess the crap out of people in terms of like all of these batteries of things because I come from strategy consulting and we did case interviews, and I found that that was a pretty excellent means of identifying if some folks have a particular set of skills. And so, that’s one kind of a test for one set of skills.

Likewise, there’s many tests for many other skills. Wouldn’t it be cool if folks could go to some sort of facility for a week or something and get a rundown on all their skills in a language that firms could read and understand, and then open up opportunity for people as well as savings for the companies? It seems like someone should have invented that. Maybe it needs to be me or maybe that’s in the works. But, Michelle, give us your take on to what extent does that exists, a means of identifying and appreciating hidden skills so that companies can save money and not have to hire the Harvard grad, and professionals who don’t have the degree can see some cool opportunities?

Michelle Weise
Yeah. So, what you’re identifying when you’re talking about seeing how someone responds to a case study is you’re testing their problem-solving capabilities, you’re trying to see, “What kind of systems-thinking, critical-thinking capabilities do they have?” I was just talking to a colleague who used to work at Arthur Andersen and they had this very open-question format where they would do the same things where they’d be trying to assess out someone’s sense of initiative and collaboration and these more fuzzy things, but trying to see how they talk about this in the context of solving a problem.

The good news is that there are these innovators who are working on new kinds of ways of assessing curiosity, problem-solving, all these really important kinds of skills that we know are going to be deeply valuable in the future of work. Because as we think about the rapid advancements of AI and how intelligent these AI are, where it’s not only able to read, drive, see, but it’s also able to write poetry, it can paint Picassos. It’s getting scary how far these technologies are sort of infiltrating our lives. What is our human advantage? What is our competitive advantage when we compare ourselves to these machines who can usually do some of this work far more flawlessly than we can? And it comes in these human skills.

So, places Imbellis and Mursion and all these different groups are trying to figure out ways to test out someone’s problem-solving capabilities where you’re on a computer and you’re thrust into this setting where you’re in this natural environment in the mountains and something is dead in front of you, and you need to kind of poke it and look at it, sort of see what is going on, and you’re trying to figure out what happened.

And so, on the backend you have psychometricians kind of figuring out what all those clicks mean, what are you doing when you’re putting these two datasets together. So, there’s really interesting ways in which groups are trying to democratize the process, and say, “We’re looking for the best problem-solvers in the world. If you can kind of solve this problem, this is really exciting.” And it makes me think of what you’re talking about with Todd Rose’s concept of the dark horse.

One of the most valuable assets that we will bring to the table is our ability to take concepts from seemingly unrelated domains and make them make sense in the context of the problem we’re trying to solve. So, InnoCentive, as an example, this was a platform that was created partly because at Eli Lilly, these chemists and scientists couldn’t figure out a problem so they posted it online and they found out that a lawyer could actually solve the problem using his sort of different kinds of contextualized expertise to help them figure out a way forward. Or, when they tried to figure out how to create more efficient ways of solving for oil spills in oceans, it was actually a pastry chef who talked about the process of making chocolate mousse and how that might actually help us think through how you remove oil from water.

And this is all, I’m totally stealing this from David Epstein’s book Range, but it’s this idea of, “How are we going to cultivate not only problem-solvers but people who can display that sense of range?” And it doesn’t always come from a four-year college degree. We don’t always get that real intensive interdisciplinary learning that we probably should. And, for me, for the next steps for higher education, that is a real opportunity for them to kind of break down silos across disciplines and departments. But, as we think about those skills that are going to make us most valuable, it’s going to be those kinds of hidden ways of thinking about problems.

Pete Mockaitis
So, let’s hit that for a minute there. So, AI can do a lot, and right now we’re very much evaluating humans being able to draw from different disciplines and putting them together. So, What are the fundamental kinds of principles or distinctions that…? Like, we think human brains are going to be able to do this better than machines even 20 years from now. What are those things? It’s not playing chess or Jeopardy, but what is it?

Michelle Weise
I think probably the most helpful way of thinking about it is when I talked to an executive from Apple who, he actually went to Stanford for a mechanical engineering degree, but as part of his general curriculum he took a class on ethics. And he mentioned that that class is probably one of the most valuable classes he had while he was an undergraduate, because when they’re producing technology, new technologies, new products, the thing they have to think about is, he called it sort of volume impact repercussions, where they have to think of second-, third-order effects of what they’re building, because, in an instant, millions of people are going to be leveraging whatever it is they are producing. And so, they really have to kind of anticipate forward and think, “What are all the ways in which this can go wrong?”

And if we think about where we are today with social media, we didn’t do enough of that. We didn’t extrapolate enough far forward. And when you hear the co-founders of a bunch of these different social media companies, you hear them say, “I didn’t think that this is the way that it was going to be used.” But this is what humans do bring to the table when we sort of bring ethics and judgment and values, and try to think forward.

And this also has implications on the kinds of people you bring around the table to do that sort of analyses. It has to be a diverse group. It cannot just be young white male undergrads kind of thinking about this problem. It has to be a diverse group of folks kind of thinking about those volume impact repercussions. So, I think those real skills in exercising judgment are going to be critical, that we can’t rely on the AI to do.

Pete Mockaitis
Okay. So, second-, third-order things. And I guess that makes sense to me in terms of like as I think about things that are like playing chess or Jeopardy or even like composing or painting, it’s sort of like they’re all kind of bounded in a way in terms of find the right answer, or the right move, or apply a principle of color or sound.

Michelle Weise
Right, they’re finite. Yeah.

Pete Mockaitis
Versus saying, speculating as to what social media and how it will impact us with widespread adoption. That does seem harder to stick inside code. Anything else that we humans do great?

Michelle Weise
So, a couple of years ago, Amazon had tried to leverage AI to diversity their hiring processes, and they thought maybe AI could do a better job than humans. And so, they kind of built out this new system, the AI started kind of going through the diverse set of applications. And then it was the humans kind of watching and seeing the output to sort of identify, “Huh, kind of strange that so many of these folks are named Jarod. Or, a lot of them played lacrosse.”

And they started to realize, “Oh, my gosh, we’ve trained the AI on flawed data.” They kind of looked at their existing talent pool. They tried to sort of say, “These are the senior leaders at our company that do great work.” But what they did was they trained the AI to search for people that looked and sounded exactly like their existing leadership, and that is not a way that you diversify your talent pool.

And so, it took humans to kind of notice and sort of exercise some judgment to say, “Wait, something is wrong. Interrogate it. Look deeply, look into the data,” and sort of say, “Oh, okay. We’ve got a problem here.” Because the AI will only just kind of repeatedly get smarter and smarter with the data that it is trained on. And we see this also happening, unfortunately, in the legal system where we’re developing sentencing structures based on deeply inequitable past data of how we’ve punished people.

So, we need this kind of deep-thinking humans for the future who have enough domain expertise to be able to question the AI because we cannot just let it…the crazy thing is that most companies…

Pete Mockaitis
Right. Jarod is in here. Whatever you say, robot.

Michelle Weise
Yeah, most companies like don’t know if they can trust their AI right now. I have a statistic in the book where they are not comfortable auditing the sort of their existing AI.

Pete Mockaitis
Not comfortable auditing it?

Michelle Weise
Yes, so this is from an Accenture study that basically fewer than a third of companies surveyed have a high degree of confidence in the fairness and auditability of their AI systems, and less than half have similar confidence in the safety of those systems. So, we’re so reliant on these technologies and yet we don’t fully trust the algorithms that undergird them.

Pete Mockaitis
Well, I buy that even in a very easy example. I think about machine-generated transcription, which, I mean, that’s existed for 20, 30, 40 years and yet it’s still not great. I don’t know. If you have 98% accuracy, okay, that sounds really impressive, but that’s really still like three errors every minute. And so, in this conversation we’d have a hundred or two, and so I wouldn’t call that good.

And so, anyway, I just find that, I don’t know, not to be quite grouchy, but I’m a little skeptical myself in terms of maybe eventually it will be awesome but right now I’m not super impressed, and maybe I just haven’t been looking at the right places to blow me away.

Michelle Weise
No, what you are pointing out is what this MIT economist named Daron Acemoglu calls so-so automation. So, like when we think about just the rise of ATMs in the last few decades, what’s interesting about an ATM is that it is far better than a so-so technology because it actually completely made obsolete the role of a person counting money because it could do it really well.

And we don’t actually have a lot of technologies that we’re building today, the transcription one is a perfect example, or the robots that we use in warehouses where we have to depend on people as pick-and-packers to be able to sort of get the thing out of the robot’s sort of treasure trove and put it into a box.

So, we’re creating technologies that are just so-so. They’re not great enough to completely obviate a certain task. And, as a result, we’re not creating enough forms of truly creative labor. Because when ATMs kind of took over, what was fascinating to see is the sort of burgeoning of the services industry in banking. It wasn’t that people just became useless, it’s that they actually transferred their skills into different domains.

Here, what we’re having is a lot of kind of unfulfilling what researchers called ghost work. It’s this kind of interstitial stuff that we have to do on the backend even when we’re training AI. You have tons of people, these mechanical turkers who are working for cents on the dollar, who are identifying all the photos that are coming up from the AI to say, “That’s a face. That’s the same face as that one. That’s a body part. Ooh, that’s not a body part we want to show.”

Pete Mockaitis
“That’s a cat. That’s not a cat.” Right?

Michelle Weise
Exactly. And, “Not a hotdog. A hotdog.”

Pete Mockaitis
Silicon Valley.

Michelle Weise
But we have a lot of terrible work that’s emerging because of that not-great-enough technology. Right now, we’re in this awkward phase where we’re not creating enough forms of creative labor.

Pete Mockaitis
Well, Michelle, these are a lot of interesting ideas. I’d love it if we could sort of zoom in here now for the professional who are maybe in their 30s or 40s who got a lot of work left in their career before retirement, likely. So, what’s our game plan in terms of learning the right stuff effectively and well and keeping our careers moving in a great trajectory?

Michelle Weise
Yes. So, I think one way forward is, unfortunately, for us as job seekers, a lot of the burden rests on us, and a lot of the financial risks also rests on us to make these decisions on our own. But moving into the future, what we really need to see and what, I think, will signify the kind of company that we want to work for are the ones who stop this kind of dis-investment in training their existing workforce and start to realize, “I have all this talent within. How do I help them acquire the skills they need to be successful?”

And I think the most powerful indicator of a company that is truly invested in us as job seekers are the ones that tell us, “You don’t have to do this on your own. We’re not going to just dangle tuition assistance or tuition reimbursement dollars and say, ‘Hey, we’re glad that you would like to advance your education. Go do it on your own time on top of everything else you’ve got going on in your lives.’”

The most competitive forward-thinking companies are going to realize that the workplace is really the classroom of the future. And I’m not talking about on-the-job compliance training, risk mitigation work, like sexual harassment training. I am talking about real new skills-building activities. So, it’s critical that the company not only identifies really transparent internal mobility pathways for you and for us, but it also has to be very explicit about carving out time in the flow of the workday for you to acquire those skills because it’s not fair for us to have to somehow squeeze it in on top of stitching together multiple part-time jobs, or all our caregiving activities. It’s too hard to just kind of stack that on top of everything else.

So, I think the things that we need to look out for the future are the companies that are truly invested in our reskilling and upskilling who kind of figure out ways to make that learning bite-sized, or for an hour a day, or an hour a week where we can be doing this in the flow of work. And, also, for educational institutions and providers to be able to modularized their learning in ways that’s more accessible where we’re not always bending to the sort of linear structure, the college or the university, but that it’s much more flexible and easily consumable.

Pete Mockaitis
And that’s a beautiful world that I’d love for us to live in. And I guess part of why this podcast exists is that we’re not there, and it is a little bit of a do-it-yourself proposition for a lot of folks these days, and fair or not, pleasant or not, stressful. So, let’s talk to the professional who’s in an environment that’s not so enlightened with regard to offering some great learning opportunity, and let’s say even, hey, they’re a little mercenary, they’re just going to go take it, “At 11:00 a.m., when there’s no other meeting on the calendar, I’m just going to do me some learning.” What are some of the top resources you’d recommend to them? I’m a huge fan of LinkedIn Learning myself, but what else would you say in terms of, “All right, you got an hour. You’re going to do some learning,” what are some of your favorite places to go?

Michelle Weise
So, one that I talk about in the book is called GLEAC. And what they do is they make this kind of mobile-friendly learning apps where they just take minutes and they have folks, for instance, who are customer service or retail folks in Prada stores, as an example, where they’re building up their reflection and communication of this kind of human skills that they’re developing where they’re exercising their judgment. And they are these bite-sized learning applications that a worker can kind of leverage while they’re working.

Another one would be Mursion that I’m kind of really interested in.

So, we tend to think of executive coaching as reserved for people kind of mid-level managers and up. What Mursion enables us to do is practice those really important human skills in a low-stakes environment. So, giving feedback, receiving feedback, these really critical skills for success in the workforce but we generally only practice them in a high-stakes environment, when we actually have to give someone really tough feedback or when we’re receiving it from our bosses.

And, generally, I know whenever I do this, I leave the conversation sort of thinking about all the different ways in which I could’ve done it better. And this environment actually has avatars in front of you, and the quality of the imagery is good enough where you can notice different people’s nonverbal cues, and you hear their voices change, and so you have to be responsive in that moment.

And it’s actually this kind of interesting AI-powered platform that’s puppeteer-ed by one human also in the background, where the human can play the role of like six or seven different people with different voices and different characteristics. And so, it gives you that chance to practice negotiation, all these different kinds of skills that we need to get better at because the fascinating thing, just in general, with human skills is even though we’re human, we’re not very sophisticated at them. We actually have to practice these skills. And just because we take a LinkedIn Learning class on empathy, we’re not somehow going to become more emotionally intelligent just from taking that one class. We have to figure out ways to practice this. So, those are the kinds of innovations that I’m excited about.

Pete Mockaitis
All right. Thank you. Well, then, tell me, anything else you want to make sure to mention before we shift gears and hear about some of your favorite things?

Michelle Weise
One thing that might be important for job seekers to know about is the existence of different kinds of alternative learning providers kind of outside the traditional realm of colleges and universities. I think most people have heard of these things called coding bootcamps where you go and you get pretty savvy in web development or frontend development and you do this for 6 to 12 weeks, you pay $20,000 out of pocket, and maybe you get this great job.

Those have typically kind of been more geared to folks who already have a degree, sort of more affluent who can actually afford to pay out of pocket. But there are these interesting other set of providers that I call on-ramps where they do this kind of really important human skills-building work but they also help learners get skills in healthcare, advanced manufacturing, cybersecurity, data science, enough to get hired by.

There are amazing stories of a US Postal Service worker becoming a quality assurance engineer for Facebook through this data science immersive program. And what they’re doing is that they’re actually stitching together that kind of career navigation with a very precise educational pathway with a direct connection to an employer.

And so, there are these kinds of opportunities available. It’s a matter of trying to, again, it’s back to us as the individual job seekers, the burden is on us to kind of find some of these. But a really interesting example of another one is one called Climb Hire we know that Salesforce administrators, they are a job that are in demand, that are in high demand. And so, what they’re doing is they’re building these skills but they’re also embedding social capital building into the learning process where they’re helping folks, who may not have the best professional networks, learn how important it is to build relationships, build professional networks.

And when a person actually gets a job at a company, as a Salesforce administrator, the onus is on them to refer and bring someone else into the company from Climb Hire because the CEO realized from LinkedIn data, as an example, that people are nine times more likely to get a job through a referral so they’re helping job seekers and learners really build this skill because it is something that you kind of have to learn how to do unless you’re sort of born into an incredible network.

Pete Mockaitis
All right. Thank you. Well, now, could you share with us a favorite quote, something you find inspiring?

Michelle Weise
So, you heard me talk about David Epstein who wrote Range, and he talks about deep learning, but he says, “The most effective learning looks inefficient. It looks like falling behind.” And I love this quote just because I think when we think about all the ways in which we are kind of channeled and incentivized to achieve, we’re always measuring through this kind of testing that is actually not measuring what matters.

And if we were actually to sort of really understand what kind of learners and that kind of deep learning in folks, it would actually look like failing. And I think that’s, I don’t know, that’s important for us to know.

Pete Mockaitis
And how about a favorite book?

Michelle Weise
Probably Beloved by Toni Morrison.

Pete Mockaitis
And a favorite tool, something you use to be awesome at your job?

Michelle Weise
I have one of those keyboards that are split into two and kind of at an angle.

Pete Mockaitis
Oh, me too.

Michelle Weise
I have some tendonitis, so.

Pete Mockaitis
That’s good. I’ve got the Freestyle2 from Kinesis.

Michelle Weise
That’s what I have.

Pete Mockaitis
But you got the tents going. I didn’t get the tents. I just got the split because I’ve got, I guess, some wider shoulders and so I always found that I was…Yeah, so I like being able to stretch out and be me without having to crunch them in.

Michelle Weise
Yeah. I have the same exact one, the Freestyle2. Underneath you can flip out the thingies.

Pete Mockaitis
Oh, that’s right.

Michelle Weise
You know what I realized, I think I pressed the delete button so much that I actually really kind of hurt my wrist and needed to re-shift my posture.

Pete Mockaitis
Well, I think that there’s something beautiful hiding in that. Perhaps it’s revision, commitment to excellence, iterating, learning, that meta stuff there.

Michelle Weise
Yeah, nothing you write is golden.

Pete Mockaitis
Not at first anyway. And how about a favorite habit?

Michelle Weise
Oh, walking.

Pete Mockaitis
And is there a particular nugget you share that you’re kind of known for, people quote back to you a lot?

Michelle Weise
Oh, I think maybe because I learned this from Clayton Christensen, one of the most powerful parts of the theories is when you see something that looks less than, our immediate kind of reflexes is to sort of scorn or disparage it or to dismiss it as, “Ah, it’s not an important innovation to pay attention to,” but Clay always said it could be just good enough. And that is something that I try to convey to folks. When we have that very human reflex, when we perceive newness as danger, that might be actually the precise time where we need to take a beat and look at the thing more carefully.

Pete Mockaitis
All right. And if folks want to learn more or get in touch, where would you point them?

Michelle Weise
I’m always available through Twitter and LinkedIn @rwmichelle or I have a website called RiseAndDesign.io.

Pete Mockaitis
And do you have a final challenge or call to action for folks looking to be awesome at their jobs?

Michelle Weise
I think, in general, it’s still this concept of collaboration. I think we, generally, just because of the way we trained from K-12 on through college, it’s so often kind of this notion that things are a zero-sum game, where if you’re winning, I’m losing. But in this concept of kind of long life learning, there’s no winning list. And so, how do we actually change our behavior instead of always sort of trying to be the leader? How do we actually make sure we’re collaborating in truly distinctive ways? I think that’s something that I think about a lot. It’s a hard behavior to turn to given the way that we’re trained.

Pete Mockaitis
Well, Michelle, thank you. This has been a treat. I wish you lots of luck in your long life learning.

Michelle Weise
Thank you. You, too.