Episode 8: Dave Griffin

Dave Kemble  0:23  

Hello, and welcome to the next in our digital transformation Podcast. Today we are joined by Dave Griffin. With a background of global-scale manufacturing as well as innovative start-ups, Dave’s recent career has combined his practitioner experience with academia, learning about next generation technology and business science. Through his spin out company, Surrey Innovations, Dave now works intuitively with companies and their people, utilising both practical experience and academic research to make the best decisions possible when considering their future fortunes. Dave, welcome to the show. And as always, first question, what does digital mean to you?

Dave Griffin  1:02  

I knew you’d start with easy one day thanks very much. The ‘D’ word. I almost actually liken it to Cloud in the fact that we didn’t really understand what Cloud was until everyone started using it. Digital is the same I think, and perhaps contentious for a digital transformation series of podcasts, but I do find the ‘D’ word quite sort of distractive, almost in so much that if you look at it in the dictionary, it basically talks about digits and ones and zeros and measuring things. And that doesn’t really come across as a business scenario. And so my idea of digital transformation is, is literally to reset it to the point where instead you say, ‘Well, okay, let’s talk about the business’. And let’s use the fact that digital is trying to establish the use of technology to change your business, but come at it from the business point of view. So my, what does digital mean to me, it’s a segue into talking about enterprise and business functions and people and skills and capabilities, I don’t typically go down the tech and the digital route as far as my approach is concerned.

Lawrence Hill  2:10  

So when you’re supporting or advising a client that is interested in innovation or automation, where do you begin?

Dave Griffin  2:21  

I immediately ask, ‘why?’ Lawrence. I mean, you know, if you go back to things like business model canvases, and the ‘what’ and the ‘why’, and the push and the pull and goodness knows what else you’re trying to do as an organisation. So I kind of take technology out the room straightaway. And I said, Well, okay, do you understand why your enterprise has got to where it is today? Do you understand fully why you’ve got these skills and capabilities and what they’re capable of? And how you have you got a really cognizant understanding of where you want to go to? And is that a reasonable step forward? An example would be the fact that there was a leadership team that were very highly motivated in bringing in ideation and change and what they were doing for the enterprise. But all the ideas were at the board level, not coming up through the organisation. So they got me involved to try and get people to use the word interstitially… to start thinking about how they can improve the business. And my view would be that you can get everyone thinking innovatively, then the whys and the whats of what you’re doing – either at your individual workstation or at a more functional level – begin to fill up a jigsaw puzzle of what you’re trying to achieve. So I will walk into room and I’ll say, Well, okay, why am I here? What are we trying to achieve? What’s the fundamental outcome? Is it achievable? How do we deliver it? I don’t even go down the digital tech route in the initial approach. 

Dave Kemble  3:42  

Interesting. And that’s quite… again… innovation is a very, very broad term and I can imagine when you  are getting people to think innovatively must be quite hard initially. But once you get a few ideas on the table, I should imagine things start opening up and there’s a lot of people build on other ideas. How do you even start that process with people to get them to think innovatively? 

Dave Griffin  4:09  

I think so. The first thing that comes to mind there, David is trust. And it’s a weird way to answer your question. If you walk into a room you typically find, okay, people don’t necessarily accept you warmly, because there’s going to be change, there will be more work to do over and above your business as usual, there will be perhaps even risk to your own work because if you go down the route of we need to optimise we need to automate or whatever. You could be talking to individuals that say, ‘Well, why would I get involved in that process? Because I might be losing my job. I could be talking myself out of out of a job here.’ So I tend to get the the idea going that the reason I’ve walked you into a room is because this particular enterprise, whoever it is, wants to expand and expand rapidly and do different things. So it’s about building capability rather than streaming things down. So the first thing I do is is get people to trust the process that this is not about trying to automate and do you out of a job type scenario. It’s actually about expanding, automating the stuff that might not be so interesting for you, but get you thinking more creatively about how you can do your job and add more into the process. And once you get… once you get across that threshold, you’re absolutely right. It’s staggering to know where the millennials where the experience people come from, by way of what they think they can add to the process and how they can contribute. And almost without exception, holistically fantastic ideas. And whether it’s top down or bottom up, people are impressed and see where the talent comes from. And generating that sort of symbiotic environment is totally rewarding. It’s fascinating. I’ve never seen it not work if you like in that regard. 

Dave Kemble  5:51  

Brilliant. That’s really interesting. You talked about the millennials there, and that, I think sometimes there’s no such thing as a stupid question. I think we touched on one of these with, with Sharon Prior in a previous podcast where one of the millennials asked, Why do you send emails? And to us, we think, Well, why wouldn’t you send emails? But the question remains well, but Yeah, but why? So well, to communicate? But why email? Yeah, oh, that’s a good point, actually. Because with WhatsApp or something like that, you can see when that’s been delivered, you can see when it’s been read, there’s, there’s more benefits to it, they felt they could do it quicker. So it’s really interesting that  innovative thought process and any, as you say, allowing people to have that forum, to feel they can ask, what might they might be internally thinking, cool, this is going to be a silly question. But actually will allow you to then look back and go, Well, hold-on that makes perfect sense. Why, why are we doing that? And what can we do instead? 

Dave Griffin  6:52  

The absolute minimum you get out of that scenario, Dave, is the fact that someone’s actually wanting to contribute, and they’re actually engaged. They’re on the bus. And yeah, at a behavioral level, that’s already great. You know, to be fair, it could be I mean, I’ve done it all the time. Every day, you know, I ask dumb questions. You know, I was, I was with my in-laws the other day. And they said, ‘Could you replace this bulb?’ I cannot believe I’m sharing this with you. But it’s an indication of how free I am in, in sharing knowledge, which isn’t knowledge. I said, Well, could you turn the lights on so I can judge the wattage of the bulb? And they said, it doesn’t work, Dave, and I can’t believe I’m trying to help my in-laws have a bulb that needs replacing, because they couldn’t reach it. I said, Well, can you switch it on? So I know roughly what the wattage is. I mean, that’s, you know, it’s ridiculous. But if nothing else, it’s an indicator of the fact that I was trying to show interest in promise. And I think that’s where there is no bad question that you can ask, because there’s always a context from where it was asked, the greatest threat of getting involved in innovation when you percolate down into the organisation. And this is, you know, that that example, where a lot of the ideas come from a small bunch of people, but how do you, how do you get it interstitially coming up through the organisation, the biggest challenge there that you have to grapple is the fact that people come up with great ideas, you have to give feedback, you’ve got to have the loop back to say, great idea, Dave, putting the light on would have been brilliant. But it didn’t quite fit in that environment because the bulb was broken. But you’re thinking it right, because you were trying to judge how to specify what the solution looked like. And I’ve just made that off the top of my head. And who knows how that sounds. But But I think the so my experience is the fact that when you get people thinking in an ideal ative way innovative, not with any fear, you know, they’re trustful of the fact that the reason they’re engaged in this process is to build a business to grow it to do the stuff that’s actually more interesting and more creative, rather than the more repetitive stuff that you can automate. Once you get across that trust, and you begin to have the process that does start to reward that. It’s almost like you then get a tiger by the tail. And it’s a question of well, okay, how do you then go from ideation to selection to scale? And it’s that process of intuitive decision making when you don’t really know what’s going on, but you can actually get the, the multiple to the masses to scenario plan, and you get a, you know, a pretty good picture of what’s going on.

Lawrence Hill  9:17  

How do you ensure that the right questions are being asked right at the start of that journey?

Dave Griffin  9:25  

Absolutely. And that’s why I come from a business aspect Lawrence, because you, you can bring in tech, you can automate, you can use intelligence and automatic artificial intelligence to look at data and we’ll come on to that perhaps a bit later on, and all these fantastic things that can process the information but data isn’t knowledge. You know, that there’s a famous Einstein phrase or statement, you know, you can have as much data and information as you want, but it’s not knowledge. It doesn’t help you make decisions. So, the the essence of of trying to get people to, to be more intuitive as to how they plug into the business model is priceless. And I think as I say, I think leadership teams benefit from it, they get then start to identify the the main movers and shakers within their organisation. And they can build on sort of business models that they otherwise wouldn’t have thought of it. So it is an ambiguous and the VUCA environment, if you like VUCA, being sort of volatility, uncertainty, complexity, ambiguity, and it’s probably the first time I’ve managed to remember all four of those in one sentence, but the decision processes that you need to go to have to be intuitive, there has to be a sandpit that’s governed, that means you don’t break anything when you fall out of the sandpit, but you’ve got this fantastically sort of wealth of activity going on, that people can really absorb themselves into, but, but it becomes a knowledge pool as opposed to a data pool. 

Dave Kemble  10:48  

Interesting. Yeah. Thank you for that. And with regards to that, what we’re seeing a lot at the moment, I don’t know, this is the digital transformation podcast. But digital was the buzzword for the last couple of years. Right. And everyone had to do digital. What we’re seeing now is automation. AI is very much at the front of people’s minds. And I know that’s an area that you’ve looked at Dave, fairly extensively, in terms of the benefit realisation of automation, and how to measure that. Have you seen that change from sector to sector? I guess the question I’m asking here is, is there a, are there certain sectors that benefit more from going through automation than others?

Dave Griffin  11:42  

Absolutely, I think so coming at that question from a slightly different angle, you know, studies that we may be familiar with, you know, in future of work, you know, that they talk about the fact that the wealth creation that’s come out of automation is astonishing, and the last sort of 20 years and hundreds of billions of pounds worth of greater revenues for people earning greater salaries, because the the skills and capabilities of what they’re doing are more valued, etc. And an automation has undoubtedly, taken away the more mundane repetitive tasks. I mean, that’s… that’s in the sort of ages, to say it’s a little bit like using Cloud as a recent statement in a cloud or local clouds or private clouds have been around for decades, almost with regard to how you manage your, your infrastructure, as has automation and innovation, obviously, it’s the internal combustion engine was an automatic version of a horse. That’s why it’s horsepower. Yeah. You know, where would we be if we hadn’t automated or, you know, people hadn’t sort of, uh, you know, trying to think was it been? Ferdinand Ben’s, I don’t know, who came up with that sort of idea early on. But, you know, automation has been going on all the time. And it is about trying to identify areas where things can be safer, things can be more productive or less cost, there can be a better quality of whatever you’re trying to produce. And I think so in that regard, automation, does fit into certain areas that at a sort of guttural level, it’s more to do with manufacturing and repetitive pieces and, and sort of scale. So a lot of automation into service centers and support centers, voice, voice systems, if you like and call centers, etc. I think the other end of the the the wedge, if you like with regards to automation, and you’re moving into artificial intelligence now is where you begin to go to the bleeding edge where massive progress in medical science in sort of biometrics of people well being those sorts of areas, I mean, that there are astonishing areas of security as well, we were, we were doing work on on biometrics of people going through airport terminals, trying to determine whether these people had terrorist intent or not purely by the fact that you could give them a device, they could have a wearable, you could be watching them. And you can learn about how people react and coping situations and begin to almost sort of triage scenarios where people can be be determined in that regard. Health Sciences is phenomenal with regards to AI, you know, the idea now that they can do virtual clinical trials, in some areas that they’re creating disease and conditions. That means that medical trials and radiation therapists and, and putting people through that process can be avoided. But also, the trials process can be massively accelerated. So you know, from from the early days of automation, where you might do something because it was going to be damaging, it would hurt to the point where actually we can begin to save lives and make massive societal impact on some of the benefits of AI. It’s kind of everywhere, really, and I don’t think in many cases where it fails, I think it’s more of a cultural thing might come on to that later. But failure typically is about does the business model work or, or, or culturally does it not accept to where the data lives sort of thing and that there’s more so little softer issues as to why things aren’t taken forward. 

Dave Kemble  15:02  

Interesting, thank you for that…

Dave Griffin  15:04  

…I sometimes have an analogy of trying to explain something and I go off on one. And we can’t work out how on earth we got there. But it’s, um, but I’m trying to get the message across and I, I started making up a story about the Forth Road Bridge. And it was about the fact that well, you know, paint technology back in the day, it only ever lasted about five years. So they had to repaint the bridge every five years. But wouldn’t it be silly if you actually you’ve got new paints coming through that it was more resistant to corrosion, and it’s stuck better, and it stopped the rust, and all that sort of stuff. And it lasted 20 years, and you paid a lot more money for this fabulous paint, it might even still be red. But actually, you still paint you still repainted every five years because you didn’t bother changing the process. And it was it was it was a completely different sort of conversation I was having, but it was along the lines of the fact that it’s not just about changing the processes. Sorry, problem. It’s not just about changing the technology and how you can do things and how things can be better. If you don’t change the process. And what people do to take the benefit from it, it’s a waste of time, all you’re doing is spending more money for pain and, and recoating it when you don’t need to. And that meant that as a metaphor, that was something which which is quite prevalent to what Lawrence hadn’t mentioned earlier, is that it’s about digging into the processes as well. And making sure that it’s not just about tech, it’s about bringing the people with you, and fundamentally changing everyone’s world for the better so that they enjoy the work better. 

Dave Kemble  16:24  

Yeah, I love that. I think that’s a really good anecdote. 

Dave Griffin  16:28  

I suspect I suspect it’s not factually correct. And let’s be fair. I don’t know how long the paint does last on the Forth Road Bridge, but the essence is there. 

Dave Kemble  16:36  

Well, I learned that I was that was the Humber Bridge, but it’s probably they probably do on both. 

Dave Griffin  16:41  

So now I think I think the fourth row, actually, it’s not the road. I mean, it’s a technical point. It’s actually the Forth Rail Bridge, isn’t it? 

Dave Kemble  16:50  

It’s the one that’s Yes. You’re quite right. They famously used to they finish painting it and then draw it we go down the other end and start again. And start…

Dave Griffin  17:03  

Exactly, yeah, what a contract. Yeah. But behavioral science is a whole new area. You know, that comes back to that point. Behavioral Science is fascinating. I mean, that’s whole new subject. But how do you? How do you motivate, I mean, some anecdotal stories about people getting into a lift, and they did some studies that everyone was facing away from the door and people that went into the lift, turned round and face the back wall sort of thing. Why would you do that? Because everyone looks at the door or the buttons? Don’t know. Yeah. But if everyone else is staring at the wall, behavioral science suggests that you go with the flow. It’s like slight sort of herding. Yeah. And you can get into that space with regards to things that are cognitive and automatic. With regards to change management. It’s fascinating. The whole bag of worms, of course, but but it’s a… it’s a phenomenal area with regards to how you comes back to that, you know, what role would you like to have, you’d like to have a role where you optimise people’s fun and ability to do things brilliantly as best they can, because then your jigsaw puzzle will be absolutely in tune sort of thing. But if you’re trying to do get people to change and do things differently, and fundamentally, they’re not hardwired that way. It’s a devil’s task to achieve that. So behavioral science in project management is phenomenal. Fascinating. 

Dave Kemble  18:13  

Yeah, it’s interesting. I used to work at the airport many, many moons ago back in the 90s. And that used to regularly change signage in the airport, just to see how the general public reacted to certain things. And even simple things like putting a bollard in the middle of a concourse, which you’d think why the hell would you do that would make such a difference, because to your point there, everyone suddenly go, Well, we all want to walk on the left hand side, and actually, or everyone was spread out, for example, but actually, by putting that ball out there, people’s mindset would go, Well, hold on, we’re all gonna go like we do with roads, and then we’ll all walk and then anyone coming this way is going to go that you’re not going to get that mass of people walking together. And it’s literally just by putting a simple bollard in in a way. But still, the people coming up to you when you’d have a huge ‘gate four’ sign above you and they come up to you and say, Where’s gate four? Well done. Yeah. 

Dave Griffin  19:14  

Yeah. Well, I mean, we didn’t, you know, we didn’t talk about it. I mean, it’s alI related in so much that it’s digital twins. I mean, you talk about sort of habitual habits of drivers. We will, we did some work with Kier, the key highways on road safety, and combed off areas, and the intrusions on cones. And we were looking at using sound based technology to hear anomalies that gives you an advanced warning that actually there might be a vehicle coming down the motorway at high speed that actually is either in the wrong lane or in the wrong place. Or that cones have been hit because actually a lot of workers get injured not by the vehicle but by the fact that a big truck will clip a cone. The cone… the cone travels through the air at 30 miles an hour and it weighs about 15 kilos. So that there’s, you know, there’s things like that. So road worker safety and using digital twins of what the background noise of a safe site sounds like. And if there’s an anomaly that went through wearables as well that you can look at, you know, what site works better than others? And how can you improve safety of people? So, that’s another example where an AI and road safety and all that sort of area is just percolating through to fantastic opportunities that you just can’t… You can’t grapple into one 30 minute conversation, I guess. But yeah, yeah. That’s fascinating as well. Yeah. Okay. Highways, were always saying we put the matrix signs up, slow down, you know, roadwork, is in the in the in the road. 40 miles an hour. And you know, and I’m one of them. Yeah, I’m thinking, why 40 miles an hour, you know, it’s not raining, I can’t see another car, there’s nothing down the carriageway. I don’t slow to 40. But that and they say, but there’s a reason why you’re trying to manage expectations, and you’re trying to deal with people’s behavior when they’re in the car. And that’s a little bit like project management, people stick with what they know.

Lawrence Hill  21:10  

Are there parts of the globe where innovation in some of these areas is likely to proceed faster than others?

Dave Griffin  21:19  

Lawrence, it’s, it’s mind boggling to be honest with you. Because, you know, we, we struggle with technology today to deal with the amount of data that’s generated and how to process it. And you know, in a few years time there’s going to be 50 billion connected devices machine to machine devices. I do hope because it’s one of my passions is that we get ubiquitous 5g You know, even if it was ubiquitous 4g, to be honest with you the that we did some work a few years ago now where we were we were polling major global organizations about well, okay, what’s your priority to have inverted commas a bigger pipe with great bait with bigger data bundles coming down it called 5g type thing, I’m being very simplistic about this, or would you like a smaller pipe that goes to the middle of the Sahara Desert sort of thing, and you can plant plant trees there and irrigate and get data from there. And the reality was that we would take any, you know, there’s still almost half a planet is outside of broadband and internet connections. And when you consider the the shifts geologically with regards to climate controls, and, and how things are being irrigated, and goodness knows what the, I think the idea of a ubiquitous connectivity around the planet, whatever the generation is, is a massive enabler. And, and it’s fascinating with regards to where that will take us because the intelligence that will have to do the right thing in the right place the the opportunity to grow the right crops to put the planet in a better place with regards to its balance on on net zero on the the opportunity to mitigate some of the toxic toxic toxicity that we have around the planet that’s more gaseous rather than anything else. And I think the AI, and as I said, into machines, to machines, etc, is just generating far too much data. So the we will need to go down AI routes almost indefinitely to try and process the amount of data to get some meaningful comes back to Einstein statement. You know, information isn’t really much until you turn it into knowledge. And I think the the major generational step will be the ability for enterprises to fundamentally understand how they can take their data and interpret it and synthesize it into something that’s meaningful. And that’s a moment I still see that as a major barrier. Because you either rely on technology companies that can either over inflate what the art of the possible might be. Or if you look at your own enterprise, how on earth do you have the skills or capabilities to deliver change that’s so impactful. So there is a gap there. And it’s a quantum leap that you need to take internally to get skills and capabilities, or externally with regard to what your outsourcing and your technology partners look like. So that whole, that whole thing needs to be processed and percolate down into something. And I think the the genesis of that may well be how you start to engage in how you start to innovate and how you have your discovery led processes on what what your horizon looks like, and how you how you begin to create scenarios and build business plans on something that is fundamentally unknown. But it’s trying to predict the future with the trends that you’ve got available to you. And that will begin to align your thought processes, how you how you select your partners, what infrastructure you put in place, how you train your people, because you won’t be able to employ them all in, and how you then sort of then program manage that to a to an outcome if you like.

Dave Kemble  24:37  

Fascinating, it’s interesting, isn’t it? As you say, you’re gonna get more and more data available, then you’re gonna have to constantly update how you’re interpreting that data and using it and improving the AI to make sure that the data that’s coming in is interpreted correctly for the needs of your business. So with that in mind, you talked about that ‘where do you begin?’ element when we were speaking earlier? What’s the starting point when you’re working with your clients talking about innovation, automation, etc? How do you go about ensuring that the right questions are being asked to the right people at the beginning of that journey? 

Dave Griffin  25:16  

It’s a it’s a lovely moment. And again, a little anecdotal story, we were doing a workshop program where we were looking at sort of AI versus AI as in emotional intelligence, because you know, at the end of that, I do believe as a subject as a sort of adjunct to what you just asked there, Davis, the fact that, will machines think and be able to make sort of value based decisions? Or are we going to genetically engineer people bit like The Matrix and sort of, you know, engineer people down to be able to make make decisions down? Or that sounds a bit McCobb? Or are we going to make machines come up to the way we can think, and I don’t know what that solution looks like. But when you’re making decisions, we have what we call the project dilemma. You’re trying to make very impactful decisions at a point in the program design, if you like, the discovery phase, where the impact and the direction of the decision you’re making is massive. The amount of information you’ve got around you that is substantive, and perhaps reliable is very low. So how do you fill the gap basically? So to answer your question, we, we tend to do a lot of scenario planning, we tend to look at bleeding edge research, we tend to try and amalgamate different sources and triage various in how can you add into content to get people thinking in the right way, a little bit like the innovation piece of getting everyone thinking the same way? Never a bad question to ask. And my experience is that you run multiple in parallel, sort of what we call innovation sprints, and they’re basically just sandpit, we’re playing with ideas. We’re putting nodes of thought processes in there that have a have a nexus of trying to pull together a whole idea of what a business model might look if it’s something that’s particularly bleeding edge. And you’re trying to build a jigsaw and generate those images and what that looks like from unknowns, you know, the good old Donald Rumsfeld, you know, there’s loads of unknowns that you know, that you don’t know about yet. How do you How on earth do you predict those So play around with innovation Sprint’s you play around, you’re getting everyone’s thought processes in everyone that collective knowledge, if you like, comes together, and you’re trying to plow a field and a little furrow there that says, well, actually, with everything that we’ve now understood, at that point, that date stamp, that’s the best decision we can possibly make. And then you go Agile, you move, you move along that line, you make it that, okay, let’s align behind that. That’s our decision. That’s our selection, how do we scale that you’re forever adding more data into that process, you stop, you do more innovation, sprint should do more scenario planning. And you just basically refine your thoughts as you go along, because it gives you an opportunity to then plug in developments and journey learnings as you go along. And it’s the best possible way. So it’s a highly discovery-led intuitive process about how you make the best decision, when does it when actual information intelligence is low.

Dave Kemble  27:57  

Fantastic. 

Dave Griffin  27:58  

And just to dive into that, sorry, that’s not just the senior management team that are doing that you, you get that, that that sort of interstitial competence and, and granularity for like, because you fundamentally are engaging the whole company that has an opportunity to, you know, add the the will of everyone, if you like in that regard. So it burns off the edges of some of the erroneous pieces that you might have early on.

Lawrence Hill  28:25  

It sounds like it’s really easy to get bogged down in that sort of art of the possible. So how do you do you need to self regulate progression in order to avoid drowning in experiments?

Dave Griffin  28:41  

I think well, there’s there’s two questions there, Lawrence. The governance and the self regulation piece does worry me, we already have those problems in social media, the metaverse online abuse, etc. How, you know, crypto currencies that are perhaps a little bit more out of shape than they should be with regards to governance and the it’s almost like policy cannot keep up with innovation and change. And that’s a fundamental worrying. But I think you have to, you have to take that on board as far as getting everyone to new over process and can you over enthuse people to try and change enterprise? How do you manage that that’s the tiger by the tail piece if you like. That’s where I think you need to have sort of strong processes that say that there’s this you need to manage this with business as usual, you still need to run the business, you still need to do your day job. But actually, there’s an element of if we can automate some areas if we can buy some more time if we can generate more time in your calendar, to start to tap to start morphing more innovative and ideated thinking into your agenda as a normal systematic approach rather than a well let’s have a pizza and innovate at three o’clock on Friday afternoon, then I think you’ll find that it becomes more manageable at a personal level. It’s almost like you break it down into an individual level at an enterprise scale sort of thing. So how you, in my experience, how you manage that is you put top level management saying, We will feed back, we will, we will reward we will have the communication in place, we will give feedback of the alignment as to where we’re going and it gets everyone on board.