Podcast with Pip Part 2
Pip shared her views on the importance of developing an ethics, data and technology charter for organizations to start digital transformation in the workplace. Weida says leaders should focus on communicating data, using data communication as a strategy. Having a charter of ethics for how companies use data and technology will be good for the company's long-term well-being. It's over and above the legalities. An ethics charter is not necessarily governance. In fact, in the absence of higher purpose, that's where corporate governance get very heavy. She does not find that heavy governance is a good replacement or doesn't necessarily improve privacy. Digital transformation is not a one and done, it must be both continuous adaptation and evolution as technology changes and evolves. Technology is an enabler, not an end in itself. Leaders need to be willing to experiment with new technology and be open to uncertain returns. The future will belong to the bold, those who are willing to be brave with their digital transformation agenda. Andrew shared a story to reveal the upskilling puzzle. Pip believed that leaders got a problem of people not knowing what they need to learn and subsequently, HR struggling to figure out what do our people need to know for a future that is uncertain when we don't actually know what our strategy is, how will we ever understand the skills that they need.
[00:00:00] Andrew Liew Weida: Hi, everyone. Welcome to the AI of mankind show where I share anything interesting about mankind. I'm your host for this season. My name is Andrew Liew. I work across four Continents and 12 international cities. Also, I work in tech startups across a range of roles from selling products, making customer happy, figuring out fundraising, making finance tick, building teams and developing sticky product. Apart from building startups. I've also worked in fortune 500 companies as a chief data scientist or technologist or people leader. You can call me Jack of all trades or master of learning. I hope to make this podcast show a great learning experience for us In each season, there is a series of interesting things where invite guests to share their views about their life and interests.
[00:01:09] Andrew Liew Weida: Now let the show begin.
[00:01:26] Andrew Liew Weida: In the previous episode, Pip talk about his backstory. Along the way, she shared her views on how covid19 get people thinking about how people interact with technology to do their work in their workplace be it online or offline. She also mentioned this actually lead to the rise of VR, metaverse and extended reality over time. This episode continue the part 2 conversation with Pip and Pip shared her views on the use of data impact trust, the purpose of developing an ethics, data and technology charter as well as the importance of having skill inventory in organizations to start digital transformation.
[00:01:56] Pip: we must discuss and agree upon the use and application. What are the the analytics that come outta, what are we building on top of that? What is our approach to our people? That's where things start get getting really sticky. And that's why a lot of the people who asked me about monitoring, they were looking at punitive measures in ways of using this data and that to me is just a one way track downhill. It's not just the trust. They won't trust the collection of data. They won't trust the application of technology. It's more than the relationship between manager employee that is affected by a lack of trust. In fact, I believe it could undermine the overall digital transformation strategy because if an employee is not gonna trust how their company uses data or collects data and how they use it. Then it doesn't matter what you do with technology. Employees will undermine the efforts.
[00:02:46] Andrew Liew Weida: It sounds like we need to encourage leaders to have a town hall on a regular basis on what is the data that we collected? How is the data being used to help you guys without, going down the slippery store of being a punitive measure so that there's trust and people are willing to give more data, knowing that it's helping them for their wellbeing and maybe their bonuses kind of stuff.
[00:03:10] Pip: I'd go one step further than that. One thing that I often encourage people to do is to develop an ethics charter or a data, and technology charter in their workplace. HR did this decades ago with the development of values. Once upon a time there were no values and HR ran sessions and focus groups, and you name it to develop the values for companies. That was my sort of early career focus. But today the issue is around data and technology to develop, to have the conversations, to be able to develop a charter or a set of principles within an organization about how data is used. How technology is selected and some high principles around that. I think that will go a long way to airing the conversation rather than on tool by tool basis or a case by case basis as an overarching approach. And companies can even apply this to how they treat their customers and treat their customers data. It's over and above the legalities. It's the very philosophy of how that company believes we should use data and technology in the interest of people.
[00:04:14] Andrew Liew Weida: I like the way that you think along that line, cuz I was thinking along the line of two parts, one part is definitely along what you mentioned is leaders should really focus on communicating data, using data communication or communication of data as a strategy, whether it is a marketing, whether it's a HR of course the other side is there's having a charter of ethics will be good. But having said that, I think we want to be focusing on the benefits and the use of that and not too ring-fencing it whereby it stifle innovation because I mean, I used to work in big companies and innovative companies and they caution on the side of people doing bad. So obviously not being the punitive slippery slope of people are bad, but they are worried like people will abuse the data. I give you two story. One was a bank . To get data science work, where I have to fill out what they call the DAR form means data access request form. Just to get one column of data, I have to talk to six, seven people and then by the time I'm done with this form, that form, it is three months. Hey, my boss is like, what have you been doing with data saying, oh, I'm just collecting data because of the safety ring fences .
[00:05:25] Pip: Yeah. Now it's crazy. I think when, and that's why a higher purpose. An ethics charter is not necessarily governance. I see them quite differently. In fact, in the absence of higher purpose, if you will, that's where governance get starts getting very heavy. And governance often is left to individual people's judgment. So when you were getting it signed off, you were leaving it to someone in a C suite to understand A, what you were doing, B the true nature of that data and see if the way you're going to use it is appropriate. And with all respect to them, I doubt that they were all skilled enough to actually do that. They just got it. They didn't see any red flags flying, so they just signed it off. Rather than having the strength of purpose to say, or from a charter perspective, say, " what do we do? How do I make these decisions? And if they have to make it, or is it just automatic? So, yeah, I do not find that heavy governance is a good replacement , or doesn't necessarily improve privacy and let's say nefarious use of data and technology in the workplace. I've seen some companies with very heavy governance. I'm thinking the banking industry just generally doesn't improve the purpose of why they do what they do data or otherwise.
[00:06:38] Andrew Liew Weida: Now let's say a leader or Csuite comes to you and say, "PIP I really like you and I wanna do digital transformation. I wanna do this ethical charter. What do I need to take note in order to really digitally transform instead of just lip service? "
[00:06:51] Pip: The first thing that's offered overlooked is they need skills. They need their people to have skills often they'll say we just hire them. And you, and I [00:07:00] know that those skills don't exist anywhere else. But really the best people to transform at any organization are the people who are already in it. So unless they start by understanding the skills as needed for that digital transformation and to build it in their workforce, they're not gonna be able to continuously transform. Digital transformation is not a one and done. It must be both continuous adaptation and evolution as technology changes and evolves. And this education of course includes them. Gone are the days when CEOs had to have their emails printed for them, they couldn't use the computer. That was it in my day. I used to have to print them for the HR director long time ago. So the skills is number one. The number two is not being blinded by the bright, shiny lights and fabulous promises of cool technology. They have to start with a problem what are they trying to accomplish as a business? Where is the opportunity that is presented to them through technology? Technology is, a tool. [00:08:00] Technological tool is an enabler. It's not a means or an end in itself. So unless they understand the problem of what they're trying to accomplish as a business very deeply and be able to match it with the unique value that a technology may be able to offer and putting that at the center of their strategy, then they're going to be a bit like equals chickens. You've got to come back to the business, got to come back to the problem. I see a lot of companies, chase, bright, shiny things and it really is they burn so much money and effort and wonder why it doesn't yield results. And then the final one for me is , I do believe the future will belong to the bold, those who are willing to experiment with technology. If a leader has a culture that is featured with risk aversion or time consuming decision making , or if there's hesitancy to allocate funds, to programs with unclear return on investments they will find experimentation and agility, very difficult. If you're trying something new you can try as Many technology projects as you like to put a clear ROI. We don't know. So they need to be comfortable with unclear returns of investment. If they don't have those three things, they will find experimentation and agility, very difficult. Subsequently they won't be able to be brave in their approach to an ongoing digital transformation agenda.
[00:09:19] Andrew Liew Weida: Let's talk about the skills, because I think this is a common thing that both of us, really like to talk about. For C-suite our leaders out there, they will always be thinking, yeah, we all know that we need to upskill or re-skill our people but how do we really know that the individual is really learning and most importantly, convert the learning to try something or to apply something. I give you a quick example. One of the big company that deals with transport and the S VP of learning development. "Okay. The problem is very simple. Let's gonna get LinkedIn. Everybody, blast out emails and go chase to all your line managers, make sure a line manager, chase all the juniors making sure that everybody goes through this like 15 minutes click of like LinkedIn learning for almost like three months." I call it the learning festival and so like what happened was that people was just, okay, I just sit down there, click it on and do cooking or call my friends, play computer game and that's digital training. At the end of the three months the CEO or some big heads, like, okay. So they randomly call upon these juniors. " what have you learn?" "Digital marketing. Okay. Come you go to this department and do digital marketing." Sorry I don't know how", like "what you mean, you don't know". How do we solve this kind of problem?
[00:10:31] Pip: Yeah, look, it's a really difficult one and I don't pretend to be an L & D expert. It was not my sort of specialty throughout my career and I really do think that today we need those expertise, the educational. The Pedago people who specialize in pedagogy and understanding. The biggest issue we've got is that I see is in some ways the problem that I experience personally, it's not a matter of learning a completely new skill on top of the builds on what I've got. It's building a new skill or knowledge base beside what I've got. Now, when I said, it's another string to my bow, it's compliments, but it wasn't deeper hR. I, wasn't going to learning more about human resources to be able to do digital transformation. I had to learn something different. Now, when we are looking at those sort of parallel, all those adjacent type of skills, it is much harder to map than it is to map a skill that will build. It, would've been very easy to say in HR, you are missing this and this at a high level of competency, you can go and do blah, blah, blah, . So the rationale is pretty specific. L and D so you know it's learning on these experience, in these fields. So that is easy to map, but my technical skills, I didn't even know what I didn't know. I didn't even know how to, and if we magnify that across workforces, that's what we've got. We've got a problem of people not knowing what they need to learn and subsequently, and HR struggling to figure out what do our people need to know for a future that is uncertain when we don't actually know what our strategy is, how will we ever understand the skills that they need to learn? I wish I could answer this question. It's a really difficult one to answer in my personal experience. My personal view is that no learning is wasted. You never know what is going to be useful. You really don't from either experience or something you read in a newspaper. For me, the most important thing is time needs to be spent learning personally for every individual. It's not just HR agenda or company's agenda. We all have to be interested in learning and helping find it ourselves. I found mine. Mine didn't come about because anyone in HR or except for me or anyone in the company said, this is what you need to learn. Now I discovered my own path and I built it myself. A lot of the time we outsource that discovery process to HR, or to business who are struggling. So yeah, wish I had a clear answer.
[00:13:03] Andrew Liew Weida: I had a interesting view that because you mentioning about discovery, individuals need to set a path and through that path, they discover, oh, this i actually need to solve this problem, but I dunno how, and that's where they, oh, I realize that this is the skill that I need to learn. So that could be one angle. Like enable learning discovery through taking on a specific pathway or specific mission. And that's where managers or leaders can work with agile or scrum master for tech stuff. We should also have a skill analyst or skill data scientist, or skill manager to annotate the skills or knowledge that is missing to solve that specific problem .
[00:13:42] Pip: I don't think we've been doing it long enough to generate the data yet. So could we curate personalized work learning journeys that are embedded in their work? So what they need to learn is in their hands. The data doesn't exist yet. It's certainly not in a form that we can harness that data to be able to work. I'll give you another example of something that I've been working on recently. I work in a voluntary basis to the AI APAC Institute. And one thing I've been helping them do is develop a capability framework. So we had a discussion at the beginning and I decided that we needed a capability framework rather than a competency framework. Our friends in HR will understand a difference. Okay. For everybody else, it really doesn't matter. But when we through our discussions around what capabilities do we cover, it became very clear that we need to provide training or education to people who work with AI, not in AI, and it's a subtle, but a significant difference. If you are working with AI, you are not an engineer, you might be a risk specialist, you might be an HR specialist. You might be a finance specialist. You might be a marketing specialist, but everyone works with AI differently as a tool in the course of their work, rather than deep in the tool, as people who work in AI and the more we looked at this, the more, we realize that actually all these technologies, the training focuses on people who work in the tool or in the technology, not with the technology. As an augmentation to what they are doing today in their skill. So still working in their specialty area. But not necessarily and just for the tool of AI,
[00:15:20] Andrew Liew Weida: For the analogy, let me help the audience out there. I like to use like the vitamin pill that I'm looking at, like this vitamin C. So everybody wants to be healthy. Everybody wants to be fit. Doctors say do more exercise, take supplements. So when with AI means I'm using this with the vitamin C, I'm growing up with the vitamin C, I'm getting healthy with the vitamin C. So it's about consuming. How do I interact and consume with this vitamin C whereas, you mentioned about in AI means like the guys who's making the vitamin C the guys that's making the doses of vitamin C making the bottles of vitamin C. Am I gonna say that? Is that the good analogy?
[00:15:59] Pip: Yeah. That, that's close enough. Yeah, absolutely.
[00:16:01] Andrew Liew Weida: Right now, we are facing an explosion of what I call a TMI too much information age. When you wanna solve a HR problem, let's say recruiting, or let's say onboarding, and we have about two, 300 onboarding software. And then the HR manager be like, oh my God, what should I do? Like, okay. All the HR software, all the onboarding HR software, these days all have this flavor called the AI . Yes. What is the advice to help a HR manager to work with AI to solve his problem or her problem?
[00:16:30] Andrew Liew Weida: Hi everyone, thanks for tuning into this episode. We have come to the end of part 2 with Pip . In the next episode, we will continue with Pip on part 3 which she explain the reason why people don't know where to look for the right tools to kickstart digital transformation . On top of that, this episode talks about the importance of problem identification over solutioning. She will also share how AI integration with other technologies is important to enable digital transformation She shared her observations about how the tools can be choosen to serve companies at the expense of people. [00:17:00] Finally she share an observation that AI leads to the rise of algorithm management and how that impact autonomy, tasks significance and job complexity.
[00:17:07] Andrew Liew Weida: If this is the first time you are tuning in. Remember to subscribe to this show. If you have subscribed to this show and love this. Please share it with your friends, family, and acquaintances. See you later and see you soon.