Leading Change with Data
Hello everybody. Dr. Jen Frahm here with another Conversations of Change. It is the year 2021. This is our first podcast coming back to you, and I really, really hope that it has been a lovely, restful, recuperative time that you have been through over the break.
As I signalled towards the end of last year, this year, I'm coming out with a new book which is very much around what leaders have to do, what they have to change to be able to better lead change into what is unarguably going to be a pretty radically tumultuous future for us, at least in the short term. I don't think that's going away.
So, I am bringing a few guests to you who I'm really curious about their fields and how that will contribute to this book. One of the areas that, I've been saying for a while, in terms of navigating uncertainty, is really the importance of data in your organization. And from a leadership perspective, to lead change, you need to be really all over data. And what we talk about as data informed decision making.
For those of you who have got the Agile Change Playbook, you will know that we have data informed decision making as one of the core capabilities of how do you deliver change? But in this interview, we're going to talk about it from a leadership perspective and say, look, how do you lead in organizations from a data perspective?
I am absolutely delighted to welcome to the podcast Stewart Bird, Digital Futures Leader from Aurecon. Stewart, welcome to the conversation.
Stewart Bird:
Thank you very much for having me, Jen.
Dr. Jen Frahm:
Listeners, I've done work with Aurecon in the past and that's where Stewart and I first crossed paths, when I was working on digital transformation there. They’re, hands down, you know, I think you've just, what, AFR's top 100 innovative companies. You've just won. Well done, kudos.
Stewart Bird:
Yes. We've won first prize in that one, which was fantastic.
Dr. Jen Frahm:
Yeah. Absolutely. So, I couldn't have a better person to be chatting to about this. Stewart, I kind of feel like I'm going to do a bit of Googling with you, and tell me what this means, and tell me what that means.
Stewart Bird:
No problem.
Dr. Jen Frahm:
But let's start with, you recently, it was in November of last year, published an article on LinkedIn which was about navigating uncertainty. I loved it, because it had so much of the stuff that I talk about, but I felt like you did it much better than me.
Stewart Bird:
Not sure that's true, but thank you very much.
Dr. Jen Frahm:
I want to start with that article. You had a paragraph in it, and I'll actually read it, because it was very good.
"When the signals of change are clear, for example, Bill Gates and Barack Obama warned of pandemics, climate science is widely accepted, and the digital revolution has been underway for 20 years, why is it still so difficult for organizations to adapt effectively?"
Why, indeed, Stewart? Tell me.
Stewart Bird:
Well, I think there's a lot to that paragraph, obviously. But I think one of the main sort of things is, obviously, we know change is happening. We live in a time where the world we live in is fast paced, it's changing rapidly. Obviously, we've gone just through the pandemic which has thrown a lot of things on its head. So, we all know change is sort of inevitable.
But I think what organizations struggle with is to really be able to have the processes and the tools to really break down what that change actually means for them. To be able to put themselves in a wider context, into a wider economic context, societal context, so they can really understand what that change means for them. What the implications of that are. What risks they're going to face in light of that change. What are the opportunities that that change presents them?
So, I really do think that it's the tools that these organizations are lacking. And I think part of that is that the way that we traditionally run organizations is looking at how we can drive as much efficiency, productivity, optimization into our processes as possible. But what we tend to neglect is to cast the net a little bit wider. We're looking at sort of narrowing down exactly what we do so we get very good at it, rather than actually building in some slack, building in some redundancy, actually casting a net a bit wider so that we have more context. We're more illuminated about the context in which we work so that we actually sort of better understand the change that's coming towards us. I think that's where organizations get stuck, really.
Dr. Jen Frahm:
Terrific. So, there's a few things there to unpack, but I'm think I probably should take it a step back further. You are a digital futures leader in the organization. Tell us how you got to that role. What is the pathway for someone who is working in this space as a leader in organizations?
Stewart Bird:
Yeah. I think my sort of path is probably a little bit unconventional. I didn't come from a tech background at all. My education has been in banking and finance, and project management. But I worked for a similar company to Aurecon when I started my career. Engineering consulting company. International one.
I ended up finding a role in the digital innovation team. And from there, that's sort of grown into more pure sort of innovation. Starting to grow now into more sort of futures research, strategic foresight type work. So, it's been a little bit of a unconventional sort of path. But I think the background that I have had, not being from a tech background, has actually really helped. It's given me a little bit more broader context to look at, rather than getting sort of stuck in the technical side of things. I tend to see the business or economic implications of technological change rather than focusing on the tech development itself.
Dr. Jen Frahm:
I imagine that that's something that comes up for a lot of leaders around, I guess, in some cases, self doubt. Am I positioned to do this if I do not have a strong tech background with that? If you look across the clients that you work with, do you find the mix, do they need to have a strong tech background? Are you an anomaly, an outlier? Or, are you representative of leadership in this space?
Stewart Bird:
I definitely don't think that you need a tech background. I think you do need, obviously, an understanding about what technologies are likely to reshape your industry. You have to have a vague understanding about the implications of those. But I think, you know, a lot of organizational leaders will naturally have a business mind. They'll understand how businesses operate. What they need to be able to pick apart in technological developments is not necessarily what technical skills do you need, or how do you need to code, or can you crunch data, can you design algorithms? You need to know what the implications of those things are.
So, for example, with, AI (Artificial Intelligence) is going to impact your industry in some form. Rather than knowing exactly how to create a neural network or something like that, you need to know, what sort of work is that likely to affect that we do? Is it likely to be codifying, digitizing knowledge that normally a person would be performing more manually? What does that mean for your potential business model? Do you charge out that person's time? But now that it's digitized, how are you going to capture value from that? How are you going to make money from it? Are you moving into a product space? Are you charging subscriptions? All of that type of stuff.
So, being able to sort of look at the implications, the second, the third order sort of implications of these things is what's really important, I think.
Dr. Jen Frahm:
You mentioned before the term redundancy. Typically, in change, redundancy has a fairly loaded meaning. But I know that you're talking about it a little bit differently. Can you talk to me about redundancy and resilience in the space of digital and data? What are we talking about there?
Stewart Bird:
Yeah. I think, in that context, the way I'm sort of describing redundancy is more along the lines of having slack in the organization. Actually having activities or investment that are going towards things that aren't core business.
So, having just come through the pandemic, there will be lots of organizations that are in survival mode, or they're looking at, how do they streamline exactly what they do? Cut all unnecessary costs out of the business. Optimize focus. But that can also be a dangerous thing to do, in the long run, because if there is a change, as we've already described, we live in a time of enormous change and it's constant. So, inevitably, there will be changes. You might actually get caught off guard if something was to change, if you had narrowed your focus a little bit too much.
So, really, what I'm describing with the redundancy is having a broader range of activities that are actually giving you insights into your broader context, or giving you experience in new ways of working. New business models. New markets. New types of product and service developments. So that, should change come, it isn't a shock to the system. You're well aware of it. You've got some experience in it, and change is easier in that regard. So, that's what I mean by redundancy in that situation.
Dr. Jen Frahm:
So, now, what I'm wondering is, I guess there's an assumption behind this wondering, is that your use of data, data, data. Being mindful now of global audience here, and I'll probably annoy everybody, because I keep swapping them up.
But your use of data is informing where do you develop redundancy, or how much do you keep redundant? Do you know what I mean?
Stewart Bird: Yeah.
Dr. Jen Frahm:
I imagine there's a real juggle there between what is surplus? What is sufficient redundancy? And it's data that tells you that. Is that right?
Stewart Bird:
Yeah. I suppose there's two parts to this. There's sort of the operational part. The exploitation side of it. And then, there's the exploration side of it. Data in the exploitation side of things, that is obviously going to be used to drive efficiency into the business. Data is what's going to drive automation of processes which, and as described before, if we're talking about data being the fuel for AI, that is codifying, digitizing, productizing knowledge from within that organization. Taking people away from having to do repeat tasks again and again.
In that regard, that is also creating, that sort of redundancy is creating slack. It's freeing up people from things that were once repetitive, that they had to do again, and again, and again. So, it frees them up to be able to learn new things. Actually innovate on the work that they do in their day to day so that they can create new value, rather than just having to repeat what they do.
So, data really can drive that side of things. That can really play a key role on the exploitation side. But in the exploration side, as well, data is really important. Data, what we can use it for is we can, as I said before, we can cast that net wide. We can actually look for those signals of change through data that we can collect.
So, this could be pure sort of data. It could be looking at the financial markets. Where is money being redistributed to? Is that telling us something about changing consumption patents or investment patents? Is that telling us something about changes in the wider economic landscape? Or, it could be more sort of information artifacts. It could be news articles. It could be blog posts, journal articles that, researching or exploring particular topics, and that's where we're seeing that there's interest that's potential signals that something might be changing. There's developments in different technologies.
And by using that data, we can actually start to identify where there might be trends that might be growing. Might be just early weak signals of change. And from there, we can do the sort of implications analysis. If that was to take off, if that was to accelerate, what would that mean for our business? What would that mean for our clients' businesses? What would that mean for our end users, or customers, or the communities that we live in? And start to do that break down. What do these things mean and what sort of actions do we really need to take today to make sure that we're not exposed to risks that might be throw up? Or, we're really positioning ourselves for opportunities that that's going to present to us, that change.
Dr. Jen Frahm:
You're bringing up for me a couple of connections where I'm sort of connecting the dots from my side here. One of the areas that typically, I work with leaders on the qualities that enable them to navigate uncertainty. And so, curiosity and courage, two of the strong ones.
What I was just thinking then, on, as you explained that, if we think about redundancy in context of operational change, as you described it, the efficiency and the freeing up people. It actually takes a lot of courage of leaders to stay that course and free people up, as opposed to then laying them off, really making them redundant, right? Because that's the easy thing to do at that point.
And I think the other thing is that exploration piece, that's really where you're drawing on curiosity. To be open minded and curious around what is potential here. And I like what you're saying about weak signals. Can you talk a little bit more about that? What that means in your world.
Stewart Bird:
Sure. Yeah. It's a big part of what we do in digital futures. A big part of our group is to bring sort of strategic foresight, futures research methodologies to the organization. And hence, the digital word in the title. We do that from a digital perspective with a sort of technological lens.
But a big part of our role is to actually go out and do what we call horizon scanning. We're looking at a broad range of different inputs, sources, information sources to try and figure out where there are early, early signals of change. Can we see that there is research that is starting to grow in a particular area of technological development, for example? Or, can we see that there are a few early movers in a particular market that are starting to exploit a new business model that has the potential to really upend the traditional players in a particular market?
So, we're looking for all those little sorts of artifacts, wherever they sort of come from. As I said before, we could be looking at where money is being invested. We could look at where patents are being filed. We could look at early, early academic research. That type of thing.
Dr. Jen Frahm:
I think, I'm going to ask you to go back just a little bit more. Strategic foresight feels very jargony. Can you break that one down?
Stewart Bird:
Yeah. I mean, essentially, what we mean by strategic foresight, it could be referred to as futures research or futures studies. Essentially, in simple terms, it's really a systematic way of exploring the possibilities that lie ahead, if you like.
Again, what we're looking for is patterns of change. Those early signals of change that might suggest there's some sort of shift in the works. And then, what we do is we analyze what those changes might mean. We look at the flow on effects of that change, should it occur. And we look at what sort of actions we really need to take now.
So, it's not necessarily about, a lot of people will think it's sort of crystal ball type stuff. It's sci-fi storytelling, or what have you. But what we're really trying to do is to understand systems. We want to understand how systems interact with one another. We want to know if there was a change in one of those systems, how that is going to cascade through a whole range of other systems that it interacts with. And, of course, in today's world, we're far more interconnected than ever before. We live in very complex environments. We operate in very complex environments where changes in one part of the world will cascade, or have the potential to really cascade throughout all facets of our economies and our work.
So, what we're trying to do is to look at where those changes are likely to occur and what those flow on effects are going to be. And then, work with stakeholders around the business, leaders around the business to design actions, design initiatives, design projects that are going to put us in a good position should those things start to affect our business. Allow us to profit from them, more in anticipation rather than being super reactive to them.
Dr. Jen Frahm:
Reactive. Sounds very fun.
Stewart Bird:
It is fun. We're in a very lucky, a lucky position. We're always exploring something new, which is great.
Dr. Jen Frahm:
So, it does raise a question for me, though. If we think about how we're navigating uncertainty, leaders in organizations, the question is, how accessible is that capability to them? Obviously, you're presenting one model, which is the buy model, that they engage consultants who have teams who do this for them.
Is this becoming an area that, in the future, we'll see organizations having embedded futures people? Or, are they already there and I'm just a bit ignorant about it?
Stewart Bird:
I definitely think that it's something that is growing. It's not overly common to see futures people in organizations just yet. But I think this is an area that strategy functions are really starting to latch on to, and start to invest more in. I think sort of the stigma around the futures or the foresight is starting to fade away, and people are actually seeing there is a lot of value in these methodologies for organizations. So, I definitely think it's a growing area. Definitely.
Dr. Jen Frahm:
Interesting. Interesting. So, recently, Aurecon published the third of a three wave series of digital futures, and this one was about data informed decision making. And I'll put it in the show notes for people so that they can access that.
Couple of things came up for me when reading that. Back in the day, when I used to do qualitative data research, we were always seeking avoid what, it was Professor Andrew Pettigrew described as data asphyxiation. The risk as a qualitative research is that you will suffocate in your data. How real is that for organizations and what do you do about that? Tell me about too much data in organizations.
Stewart Bird:
I think it's definitely a risk. I think many organizations grapple with having a huge amount of data, trying to capture absolutely everything, and then, just sort of drowning in it. Not knowing what to do.
So, I think the, from my perspective, I don't think the right thing to do is to necessarily just capture absolutely everything. I would suggest that organizations actually start to think about where data can really enhance what they do in an operational context or really how it can actually sort of contribute to their strategic planning, their strategic thinking. And then, actually be very deliberate in capturing the right data. Because, obviously, the quality of the data that you're capturing, as well, is going to be key.
Obviously, there are a whole lot of new techniques that are coming through. A whole lot of new technologies that are actually helping organizations better manage and analyze huge data sets that are quite messy and unstructured. Aurecon has built up a great capability in things like that computer vision, image processing, natural language processing, so that we can actually go back through and actually analyze huge amounts of unstructured data. Images, video, documents. All of that type of thing. So, there are a lot of technologies that will help in that regard. But where possible, I do think organizational leaders should actually think about, strategically and operationally, what value they're actually trying to achieve and be a little bit more deliberate in the data that they capture, and how it's managed, and shared, and presented around their organization.
Dr. Jen Frahm:
I remember, when I was finishing up my Ph.D, they were just starting to launch technology platforms which could take great volumes of text. And the analysis was getting pretty close to what you would do inductively, as a human being, with your sorting and stuff, which had me very curious about the future of that as a domain.
It does raise for me the question, though, of ethics in use of data and decision making. Is this a space that you tend to work in, or do you find, are there ethical challenges that leaders need to be thinking about when it comes to, how do they use data to inform their decision making?
Stewart Bird:
Yeah. Of course, yeah. I think, always, ethics should be front of mind whenever we are working with data and analyzing data. I think the space that we play in, as Aurecon, we're sort of less exposed to some of the challenges in that space because we are dealing with things like physical asset data. We're dealing with data from buildings, from machinery, from transportation systems. That type of thing. We're not necessarily dealing with people's sort of personal data, which is obviously where a lot of these issues, ethical concerns arise.
But I think it definitely should be something that we constantly think about. And one thing that we definitely thing about in that regard is, yeah, how do we actually work, when we're developing these systems, these algorithms, these models that are analyzing data, they're automating a particular process. How are we really working closely with the subject matter experts, the domain experts, rather than thinking the technology can do it all and the black box solution will solve everything?
I think working very closely with stakeholders who have intimate understanding with the data, the systems, the area that you're trying to tackle, is critically important. So, I think, from our perspective, we're lucky. We don't actually have all the sort of the same challenges that, say, some of the social media companies, for example, will be grappling with. But it's certainly something that we need to take into account. Even though we are looking at, say, building data, is there occupant data that we're actually looking at? Are we looking at visitor patterns to a shopping center, for example? What form is that data coming in? Is it anonymized effectively? Are there any issues if that data was to be leaked or hacked?So, it's something that's always front of mind for us, as well.
Dr. Jen Frahm:
It's interesting, isn't it? Out of the latest report, and this is always, your reports are always research driven in those reports. I'm curious, were there any particular industries that had a really high maturity of data informed decision making from their leaders? That, clearly leaders are on top of this, as opposed to maybe industries that struggle, that there's real opportunities to improve.
Stewart Bird:
Yeah. I certainly think, I think the obviously answer to that one is that a lot of the tech companies, obviously, right on top of this. They have purposefully set up and innovated on their business models so that it is a closed loop. They are constantly using data to improve the services and the products for their end users.
So, if you look at, say, Amazon or Uber, they really employ what are known as fly wheel business models or virtuous cycle business models, where they're constantly basically transferring data from one area of their business to enhance the next. And in that regard, it's constantly growing. It's virtuous rather than vicious. And I think, in many organizations, a lot of the business models that organizations employ are still very linear. Still very transactional. They're looking at engaging a client or a customer, selling some to them, producing something to them, delivering, handing it off, shaking hands and saying, "Thank you very much. Hopefully, you buy from us again next time."
And then, basically, they have to win that customer or client back over every single time. There isn't a closed loop. It's very linear. But with organizations that really are on top of this, they are establishing these virtuous cycle models that are more closed loop. They're establishing, they're using digital technologies, digital interfaces, digital tools to have sort of continuous engagement with their end users, their customers. And through those digital platforms, they're actually being able to extract data insights. They're able to feed that back into their improvement processes or the development of products and services that would add value to that end user on a continuous basis.
So, this is really, and it's speeding up the nature of competition in many ways, as well. In this digital age, we expect organizations to be constantly improving their services. It's just sort of-
Dr. Jen Frahm: We do.
Stewart Bird:
Because we know that they understand how we're using it. They've got analytics on how it's running. If it crashes, we expect them to have to crashalytics on that and understand when that's happening, and why it's happening, and then, fix it straight away. As customers, we're expecting quick improvements. Constant improvements.
I think organizations, if they're not looking to set up those, more of a virtuous cycle model and maintaining those sort of linear, transactional models, there's going to be a widening gap between those organizations and those that actually have those sort of continuous engagements. Those data driven relationships with their clients, customers, and users.
Dr. Jen Frahm:
It puts some pressure on them. Because you're so right. As a consumer, we do. We start to expect whatever we see happening on the iPhone as, or your smartphone as normal practice, not best practice. And it changes our expectations completely. But I like what you've shared there. I think, from a leadership perspective, this notion of interrogating our business for, to what extent are we taking part in a virtuous cycle or starting to build and plan for it is a pretty important change, organizational ch-, looking at.
Stewart Bird:
Yes. Definitely. It's a big change for how many traditional organizations work. Being at Aurecon in professional services, this is something that's not traditionally done by these sort of firms. And what we're sort of seeing with some consulting firms is they're moving to sort of what they call an asset based model.
So, rather than it being just about a project with set start and end dates, someone comes in and offers you some advice in the form of a report or a presentation at the end of the project, and they go, "Thank you very much." They're actually productizing a lot of the solutions that they use, and sort of embedding those within client organizations in the form of digital tools. And then, plugging in data sources from that client organization into those digital tools. And that is actually analyzing them, just as, say, a consultant might do on a spreadsheet or an Excel model in the past. So, they're actually getting sort of constant, real time advice, essentially, that they can act on very quickly. And it's a continuous engagement.
In return, obviously, these consulting firms, advisory firms will be getting more continuous insights from their clients, as well. So, we are sort of starting to see this shift, and it's a really fundamental shift in business model in some of these more tradtional industries. Which puts all sorts of challenges in front of organizational leaders around workforce challenges. Do we actually need a whole range of new skills to be able to build and productize these digital tools? Takes a whole lot of new entrepreneurial creativity to be able to actually get these business models up and running, and scaled effectively. So, it is a huge challenge for leaders.
Dr. Jen Frahm:
Yeah. And I really think that's part of the structure of resilient organizations going forward, is the startup model within. To what extent have you got, it's almost like a two speed organizational economy, that you have your BA, but you also, you have these startups within that are continuing to innovate, and introduce the new, and produce.
Stewart Bird:
A term that's sort of starting to gain a bit more traction, Janusian strategy.
Dr. Jen Frahm:
Sorry. Say that again
Stewart Bird:
I think it's pronounced Janusian strategy. Essentially, Janus is, I think, a Roman god.
Dr. Jen Frahm:
Roman god of change?
Stewart Bird:
Yes. Of change. Double face looking in opposite directions. It sort of builds on that. That you've actually got that sort of two speed portal. You're actually going after things that are potentially in conflict with one another simultaneously. And to hold that kind of balance, for leaders, is obviously challenging. But in the organizational structure, the way that people are rewarded and the metrics that are built around that, that needs to be factored in to be able to allow that.
Dr. Jen Frahm:
That's fantastic. A Janusian strategy.
Stewart Bird:
Janusian strategy. Yes.
Dr. Jen Frahm: God. I love my podcast. I learn. I learn. I do appreciate that. And, yes, I do know Janus. Yes. Of course. The report that came out, what surprised you out of it? Were there any, gee whiz, didn't expect that?
Stewart Bird:
I'm not sure whether there were any huge surprises, but what I am sort of continually surprised by is that there is still a huge inward focus for many organizations. Given the world we live in, the pace of change, I would expect that organizations would be doing more external exploration, essentially. Not necessarily focusing on purely efficiency, and productivity, and optimization within their own organization.
To me, that still comes as a surprise. We still obviously see a lot of people defining digital, in inverted commas, as doing things just more efficiently. Doing the same thing but just more efficiently and more productively, rather than it being a driver of really holistic change, as we've just discussed. Going into business model transformation, workforce transformation. Digital is a catalyst for a huge amount of fundamental, very complex change. And to see that a lot of people were sort, I don't know, not aware of it, or ignoring it, or it's too hard to grapple, always does come as a surprise.
Dr. Jen Frahm:
Yes. I know that well, and I think that's, where I come from, with navigating uncertainty, there's a really high, I place a high value on your relationship with mindfulness. Your ability to tame your brain. That much of what you've talked about creates, that creates a heightened limbic system response. It's fight, flight, freeze. This is potentially a threat.
And if we, personally, as leaders, don't have the capability to calm ourselves, we don't see the opportunities in digital. We only see what is safe to us, which is what is known. What is Taylorism, what is efficiency, all that kind of stuff. But is that relationship between brain health and science to be able to be open to future, in an opportunistic way, which I think is really, really interesting space to be in.
Stewart Bird:
Yeah. Definitely.
Dr. Jen Frahm:
Stewart, you have provided an A+ education for us today and created lots of stuff for us to be thinking about, which I'm very, very grateful. What can our listeners offer to you? What would you like of them?
Stewart Bird:
You've obviously mentioned that we're producing these reports and these publications that we're putting out into the market, to the public. We're continuing to produce those. We're actually taking deeper dives into a lot of the topics that we have talked about. We have one that is just being released around workforce for a digital future. How we need to evolve our work forces for the changes that we have just discussed, and what are going to be the critical skills that are going to come up?
We've also got one that will follow that around using data and learning as a key competitive advantage for organizations. Looking at how all of this really does change the economic conditions that organizations work in. If listeners are interested in learning more, then, please Google Aurecon digital futures and you'll find all of our publications. And we're always open to discussing these further. So, if anyone wants to just continue this sort of conversation, then, reach out and we're happy to do that.
Dr. Jen Frahm:
Connect with you on LinkedIn.
Stewart Bird:
Exactly.
Dr. Jen Frahm:
Terrific. Aurecon does have exceptionally strong social media presence. So, I'll make sure that I put all that in the show notes as well. But, for now, Stewart Bird, thank you so much for joining us on this Conversation of Change.
Stewart Bird:
Thank you very much, Jen. Pleasure.
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