CAREER STRATEGY

Hi, this is Peter Clayton, host of the TotalPicture Podcast. I focus on Innovation in HR Tech, TA Tech, Recruiting, Talent Acquisition, and career strategies. Today, I’m joined again by Paul  Leonardi,  the Duca Family professor of technology management at the University of California, Santa Barbara.  Paul’s Co-authorTsedal Neeley is the Naylor FitzHugh professor of business administration at Harvard Business School — an award-winning scholar, teacher, and expert on virtual and global work.

Welcome to Part 2 of my interview with Paul Leonardi, Co-Author of  The Digital Mindset – What it really takes to Thrive in the Age of Data, Algorithms, and Artificial Intelligence— Published by Harvard Business Review Press. If you’ve not done so, I encourage you to watch Part One of our interview first.

CHAPTERS:

  • 00:00 Interview Preview
  • 54:29 Introduction to Part 2
  • 1:18:12. 11 Trends that Will Shape Work
  • 2:02:16 Guest Introduction
  • 2:34:13 Collaboration, Computation, Change
  • 3:34:07 Approach to Collaboration
  •  6:45:05 About Computation
  •  8:55:18  Change
  • 10:22:21 Cybersecurity and Privacy 
  • 11:20:00 Leading Cultural Change
  • 11:48:27 Hybrid work arrangements
  • 15:15:23 Explain The Blockchain and How it Works
  • 17:40:10, Alvin Toffler Quote from 1970
  • 18:37:06 Continuous Learning
  • 20:23:03 30% Concept
  • 20:50:25 Connect with Paul
  • 21:17:28  Closing Comments

Now, consider this: According to an HBR article titled  “11 Trends that Will Shape Work in 2022 and Beyond:”  one Trend highlighted is this: “Managerial tasks will be automated away, creating space for managers to build more human relationships with their employees.” 

“The next generation of technology will start to replace additional managerial tasks, such as providing performance feedback and supporting employees in building new peer-to-peer connections. Our research shows that up to 65% of the tasks that a manager currently does has the potential to be automated by 2025.” 

The authors of The Digital Mindset focus on the following questions that many people have today regarding how to interact in a digital world question such as:

  • How much technical capability do I need?
  • Do I need to learn how to code?
  • What do I need to know about algorithms?
  • What do I need to understand about big data?
  • How do I use digital tools effectively?
  • What exactly is AI?
  • Do I need to prepare to have a bot or robot on my team?
  • How do I collaborate successfully when people are working remotely?
  • What are the best ways to make sure my data and systems are secure?
  • How do I develop skills to compete in a digital economy?
  • Is digital transformation different from other transformations?
  • How do I build a digital-first culture?
  • Where do I start?

TALKING POINTS:

Paul, as I mentioned I’m my intro, I’d like to return to the three major approaches to the Digital Mindset used in your book: Collaboration, Computation, and Change. Can you briefly describe each of these and why they work together to create a Digital Mindset?

One chapter – titled Drunks and Lampposts I think will resonate with this audience: It’s time to become conversant in statistics. Can you give us an overview?

I’d like you to touch on the blockchain. A lot of people just relate it to cryptocurrency. What do I need to know about the blockchain for my career and my job?

I’d like to finish up our interview with this: There’s a fabulous 5-star review of your book on Amazon written by Robert Miller, a “Hall of Fame” reviewer. His review starts with this: Here is a prediction from Alvin Toffler in 1970: “The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.” To me, that sums up what it really takes to adopt a Digital Mindset.  Do you agree?

How can our listeners and views connect with you and your work?

LINKS:

  • The Digital Mindset: https://amzn.to/3lqoy5h (Amazon Affiliate link)
  • Paul Leonardi’s Website:  https://paulleonardi.com/
  • 11 Trends that Will Shape Work in 2022 and Beyond:   https://hbr.org/2022/01/11-trends-that-will-shape-work-in-2022-and-beyond
  • Part 1 of this Interview: https://youtu.be/NMCZzqoUC-c

#DigitalMindset #careerstrategy #futureofwork

Full Transcript:

Paul Leonardi: [00:00:00] What are the censors doing when they’re collecting or sort of turning inputs from the environment into data? How are those data being put through models that are segmenting and categorizing those data in certain ways and some transparency into what that looks like and asking the right questions, understanding what data we’re collecting and what data we’re leaving out. Understanding how to present those data to various audiences that have differing levels of sophistication about how to make sense out of the phenomena that we’re interested in. And then some kind of rudimentary understanding of statistics, because statistics are being increasingly deployed by data scientists to make recommendations about courses of action. And if we don’t understand how those statistics are being constructed, we’re going to have problems.

Peter Clayton: [00:00:55] Welcome to part two of my interview with Paul Leonardi, co-author of The Digital Mindset What It Really Takes to Thrive in the Age of Data, Algorithms and Artificial Intelligence, published by Harvard Business Review Press. If you’ve not done so, I encourage you to watch Part One of our interview first and you’ll find the link up here. Now consider this: according to an article called 11 Trends that will shape work in 2022. One trend highlighted is this. Managerial tasks will be automated away, creating space for managers to build more human relationships with their employees. The next generation of technology will start to replace additional managerial tasks, such as providing performance feedback and supporting employees and building new peer-to-peer connections. Our research shows that up to 65% of the tasks that a manager currently does has the potential to be automated by 2025. And I’ll put a link to this article in the show notes. Hi, this is Peter Clayton, host of the Total Picture Podcast. I focus on HR technology to tech recruiting, talent acquisition and career strategies. Today I’m joined again by Paul Leonardi, the Duka family professor of technology management at the University of California, Santa Barbara. Paul’s co-author is Adele Neeley. She’s the NAYLOR Fitzhugh Professor of Business Administration at Harvard Business School, an award-winning scholar, teacher, and expert on virtual and global work. Paul, welcome back. As I mentioned in my intro, I’d like to return to the three major approaches to the digital mindset used in your book one collaboration, two computation, and three change. Can you briefly describe each of these and why they work together to create a digital mindset?

Paul Leonardi: [00:02:54] Sure. So if you recall, when we define earlier what a digital mindset is, I said a mindset is a set of approaches we use to make sense out of an act in the world. And we really took that definition to heart and said, okay, well then what are the approaches to the world that you need to operate from in order to be successful in the digital age and collaboration, computation and change are the three approaches that really emerged from our analysis and our work with all these these people that we really identified as having really strong and well developed digital mindsets and an approach to collaboration I think makes sense to most people. They’re like, Yeah, I’ve got I’ve got an approach to collaboration, right? There’s ways that I know how to interact and like to interact with other people. I think often strategically about who I’m going to work with, how I’m going to work with them. So people are comfortable and often familiar with an approach to collaboration. And our suggestion perhaps argument is that we need to shift our approach to collaboration a bit in the digital age on a couple of key dimensions. One relates to the conversation that we just had about chatbots and AI powered agents, and that is that we are increasingly seeing these kinds of technologies, not just be tools that we use, but tools that we interact with as though they were teammates or people. This is happening often in manufacturing contexts.

Paul Leonardi: [00:04:26] We’re seeing it happen in the military. We’re starting to see it happen within decision-making groups and task forces in large organizations that these kinds of tools act as decision aids in kind of real-world, live decision-making contexts. And so you have to kind of think I know when I say collaboration, usually collaborating with a technology doesn’t jump to mind. We think that technology is the medium through which we are collaborating with people. But the shift that we need is in thinking about how do we actually bring a machine into our collaboration and as a partner. And so we give a number of tips and ways of thinking about that. We also discuss how now in the digital era, our work, our relationships, our interactions are much more likely to be distributed across time and space. And this is a pattern that’s been growing for some time that really escalated during the pandemic with this wholesale shift to remote work. And now we’re in this flux of like, well, what is what does work look like now people in different geographies and different time zones. And what that means is that the kinds of activities that we do to collaborate with other people need to change. In some ways, no longer. We can take for granted that people see us and they know what we’re doing and they see us working hard. That just doesn’t happen because they talk to us on Zoom every so often, right? Or they see the outputs of our work.

Paul Leonardi: [00:05:56] But because we’re geographically or physically distributed, they don’t necessarily see what we’re doing every day. And so we argue that we need to develop an approach to collaboration that allows us to really build and enhance and establish our own digital presence so that we’re present to other people, our collaborators, even when we’re not physically co-located, and that we kind of recalibrate how we make attributions about other people’s behavior when we are not co-located and we’re not able to sort of resolve the ambiguities in their response by quickly asking them a question or seeing some seeing that traffic was there’s a lot of traffic on the way to the office today. And so that’s, of course, why that person would be late. So developing and kind of changing our approach to collaboration is the first major approach that we talk about. The second is computation. And when we talk to really technical folks and companies, they’re like, Oh, I know a computation, totally get it. When we talk to people that are not necessarily really technically sophisticated or don’t work in technical roles, they’re like, What do you mean? I have to approach computation in a certain way. I don’t even get what that means. And our argument here is pretty simple, and that is that we really need to understand the production of data, the way the data are presented, and we need to understand how to have confidence in interpreting results that are being presented, predictions that are being made based on the analysis of those data.

Paul Leonardi: [00:07:28] And that involves developing some rudimentary skills and areas that we talked about a little bit before, including understanding what are the what are the sensors doing when they’re collecting sort of turning inputs from the environment into data? How are those data being put through models that are segmenting and categorizing those data in certain ways and some transparency into what that looks like and asking the right questions, understanding what data we’re collecting and what data we’re leaving out, understanding how to present those data to various audiences that have different levels of sophistication about how to make sense out of the phenomena that we’re interested in. And then some kind of rudimentary understanding of statistics, because statistics are being increasingly deployed by data scientists to make recommendations about courses of action. And if we don’t understand how those statistics are being constructed, we’re going to have problems. Danny Kahneman won the Nobel Prize for something called Prospect Theory in the 1990s. And the basic insight was that humans are really bad at probabilistic reasoning. It’s really difficult for us to understand probabilities and statistics are all about probabilities, so we need to develop some kind of fluency in that and we try to give a bit of a primer on on what you need to know, even if you’re not a data scientist. And then the third and final approach is about change. And the way that I like to categorize it is as follows that we, we typically think of change as something that happens occasionally, right? That we have long kind of periods of harmony and stasis and things are staying the same. And then there’s a moment that comes right, a series of events and a big change happens. And then things are relatively calm for a certain period of time. And then another change event occurs. That may have been a useful way of thinking about the world. Pre-digital, but today it’s kind of an outdated approach. And that’s because everything that we do right in our the information environment and the technologies that we use and the decisions we need to make and customer preferences and the demands of our employees are just in a constant process of change. You know, there aren’t these periods of stasis anymore. It’s like once we finally think we can put our head above the water and take a deep breath, the waves start to splash us in the face again. So we really say sort of urge that your approach to change needs to recognize that we’re always sort of transitioning from one technology to another, from one data set to another, from one strategic initiative to another, and that don’t ever expect to be able to pull up a chair and put your feet up for a while, because change is always happening. But if you reorient to change in that way, you can start to see new possibilities for action.

Paul Leonardi: [00:10:20] And we talk about this in three key areas. One is about cybersecurity and privacy. So if you recognize that the tools that we’re using are embedded in an ecosystem of other tools that are themselves changing, you recognize that there’s going to be a security breach, there’s going to be a problem at some point because you just can’t manage all of the interfaces and keep everything steady. And if you recognize that, then you can develop a new approach for how you deal with privacy issues and security issues. We talk about this in terms of experimentation, that one way to deal with this constant process of change that’s occurring is to rather than make big decisions and hope, they stick to really try much smaller experiments. And we talk about how do you develop an ethos of experimentation within your organization? How do you make sure that depart mentalization doesn’t kill experimentation at the fringes, and how do you democratize the idea of experimentation so that anybody can do it? And then finally, we talk about the importance of leading cultural change and developing a culture that is resilient to this constant transition that’s happening. And how do you upskill people and how do you implement new tools in ways that get them to see the utility of them? And so this approach to change as this constant process of transitioning is really important. So we give lots of examples and stories from great individuals and organizations that have managed to do this well.

Peter Clayton: [00:11:49] Yeah, I think that is so important. I mean, an example right now obviously is the struggle many companies are going through with hybrid work arrangements or bringing people back to the office. People don’t want to go back to the office. They like working from home, you know. So how do you approach all of this and find an equilibrium where you can keep your best employees, which they all want to do and and yet, you know, achieve what you’re trying to accomplish as a business.

Paul Leonardi: [00:12:24] Right. And it surprises me when I read about all of these major decisions that companies are making around the return to work or hybrid work, how they’re presented as though we’ve come up with the answer. Right. You know, it’s going to be two days in the office, right? Pick your days. It’s going to be Monday through Wednesday and Thursday, Friday in our office. You don’t have to come in or whatever the thing is. Right.

Peter Clayton: [00:12:48] Look at Apple trying to get everybody back to the spaceship. Right?

Paul Leonardi: [00:12:52] Right, exactly. And I think those kinds of broad prognoses. Right. Or these big statements about this is what we’re going to do don’t really reflect an evolved digital mindset around this idea of experimentation. Because look look at the the quick evolution of tools that have happened just in the last two years. I mean, the ability to have these kinds of video conferences at this high level of fidelity, the way that we can share files and co work on those files and real time, I mean, capabilities and the technologies themselves have been exploding. The. The needs right of our employees have been shifting pretty rapidly. And there’s there’s no reason to believe that those transitions, either in technology or in worker preference, are likely to slow down. And so it makes little sense to say, here’s our approach to hybrid work. I think what would make better sense is to have more of this experimentation mindset and to say, we’re going to try this approach right? Or we’re going to try these couple of different approaches and we’re going to see which ones help us to sort of maximize productivity, but also employee well-being, which ones make help us to create and maintain a strong culture, yet still giving people enough individual freedoms that they can kind of manage their own lives around their work. I think that is the better move in this. But the way the world is now, right, is to say we’re trying a series of experiments. We’re going to see what works and what doesn’t work. We’re going to learn from them. And then we can start developing policies that are adaptive to future change rather than come out and say, our policy is X and everyone’s going to.

Peter Clayton: [00:14:42] Do it right. Yeah. I mean, when I launched Zoom this morning, there’s a thing we now have a whiteboard implementation in Zoom, you know, so it’s that kind of thing. It’s just constantly changing and evolving and what you can do and and how you can use tools like Zoom. And it’s been wonderful for me because everybody is upgraded their system and they’re now, you know, they all have nice cameras now they have mikes and, you know, so for what I do, it’s it’s fantastic. Right. One thing I’d like you to address, Paul, because you did speak about this in your book, and that is I’d like you to touch on The blockchain because a lot of people just relate it to cryptocurrency. And what do you need to know about blockchain for our careers and our jobs?

Paul Leonardi: [00:15:35] Yeah, that’s a good question. So we give kind of a primer on what is blockchain, because I think like you, most people say they hear blockchain crypto, they think those are related. Not quite sure how. And what we want to do is give people a good framework for understanding what that is. And blockchain is really a distributed ledger system and it allows for entries into a kind of centralized well, it’s decentralized, but think of it as like a public database, right? Where everybody can see what entries you’re making and know that those entries are being watched by others so that you can’t fudge them in any particular way. And so there’s an increasing fidelity to data that are possible and potential reliability to transactions that are occurring via blockchain. And we give some examples in the book about how this works. In particular, the diamond market has really benefited from from the use of blockchain. How is blockchain exactly being embedded in business in a way that everybody should understand? We don’t really know exactly yet, right? We’re still really in the infancy of blockchain, but we thought that what made sense was if we could give kind of an overarching preview of like, well, what is blockchain and what are some potential ways in which it can be useful? We can help people begin to appreciate the opportunities that exist for enhanced security and reliability in their ledgers and in their transactions, so that we might be able to start imagining new and better ways that blockchain can be useful in our businesses. So I think the exciting thing is that we’re kind of in the Wild West, right, in terms of where where could blockchain go? But it does really represent a fundamental shift in core technological capabilities that has the potential to reshape many of the ways that we record keep and we conduct our transactions and organizations.

Peter Clayton: [00:17:40]  Paul, I really appreciate your your time today. I’d like to finish up our interview with this. There’s a really a fabulous five-star review of your book on Amazon, written by a guy whose name is Robert Miller, who is in the Hall of Fame, whatever that is. And his review starts with this. Here’s a prediction from Alvin Toffler in 1970, quote, The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn and relearn and unquote. And so to me, that sums up what really takes to adopt the digital mindset that you’re writing about, right?

Paul Leonardi: [00:18:26] It does. And one of the key elements that we discussed throughout the book and really, really. Double down on the second to last chapter. The one on transitioning is about the importance of continuous learning. Right? That. Gone are the days when, you know, you went to high school, you went to college, you learned some stuff. You then applied throughout the rest of your career. Now that doesn’t happen, right? We need to be in a continuous state of learning and we provide in the book that foundation. I think to get you to 30% in the various areas that we cover. And you can think of that as building a foundation, but the structure on top of that foundation is going to continue to change. And so we need to continuously learn about advances in new technologies. We need to learn about advances in computer program. We need to learn about advances in how we collaborate with people that are distributed. We need to learn about how we continually upskill our employee workforce. And we end the book with some case studies from both high tech and frankly, not very high tech organizations that have done a really good job of helping to develop programs by which their employees can learn digital skills continuously. But I think that the biggest, biggest thing that’s important about this is humility, recognizing that I don’t know everything, that things are going to change and I’m going to have to be a lifelong learner. And I know that was really important for me to help get me to the 30% or beyond in some cases, is to say, even though I’ve got a PhD from a college of engineering right at the top Research University, I that was 20 years ago now, right? Like, I don’t know everything and I’ve had to take more classes and refresher courses online and in person to continually build and rebuild my skills. And that takes a certain amount of humility to do. But I think if we can recognize that, we’re going to be in really good shape to be good learners.

Peter Clayton: [00:20:25] Yeah, I really love the 30% concept because that just tells you, well, I don’t have to know everything about everything. I can just know if I know this much, I will be competent enough to converse with people who know a lot more and learn something. That’s right. I think it’s brilliant.

Paul Leonardi: [00:20:45] Great.

Peter Clayton: [00:20:45] Thank you. Thank you. So how can our listeners and viewers connect with you and your work?

Paul Leonardi: [00:20:50] Yeah, well, getting a copy of the book hopefully is a great first start to start getting that 30%. You know, you can follow me on Twitter at P and 31. I’m also on LinkedIn and I’d love to connect there. And I’m pretty engaged and like to respond to comments and interact with folks. And you can find me at a poly and dot com also for lots of other articles and teasers and things that hopefully help you to develop and keep developing your digital mindset.

Peter Clayton: [00:21:16] Well, great. Thanks again, Paul. The book is The Digital Mindset Where It Really Takes to Thrive in the Age of Data, Algorithms and AI, and it’s published by Harvard Business Review Press. And here it is. And I really encourage everyone to pick up a copy of the book. There’ll be a link to my Amazon affiliate account down in the show notes. So thanks for watching. Thanks for listening. And till next time. Have a good day.

Paul Leonardi: [00:21:43] Great conversation today.

Peter Clayton: [00:21:45] Thank you for tuning in to part two of my interview with Paul Leonardi. If you enjoyed this content, I’d appreciate your subscribing to the channel. It’ll really help to attract new viewers. My name is Peter Clayton and stay tuned to the TotalPicture podcast by hitting the bell icon. Hope to see you soon.