The Consulting Growth Podcast
Joe O'Mahoney is Professor of Consulting at Cardiff University and a growth & exit advisor to boutique consultancies. Joe researches, teaches, publishes and consults about the consulting industry.
In the CONSULTING GROWTH PODCAST he interviews founders that have successfully grown or sold their firms, acquirers who have bought firms, and a host of growth experts to help you avoid the mistakes, and learn the insights of others who have been there and done that.
Find out more at www.joeomahoney.com
The Consulting Growth Podcast
Transforming Consultancy with Productisation and Automation: Tim Redgate of Axioned
Imagine if you could transform your consultancy's repetitive tasks into a unique service offering or automate more of your back-office? That's precisely what our guest, Tim Redgate Strategy Director of Axioned, discusses in this fascinating episode of Consulting Growth. We dive deep into the concept of productisation and how it can be a game-changer for consultancies and professional service firms.
I kick off the conversation with Tim by exploring the role of tech investments for decision-makers and the potential benefits and pitfalls of productising people services. We share essential strategies, including the significance of having a passionate product owner, a dedicated team, clear goals, and budget constraints. We also highlight why it's crucial to start with a feasibility study or proof of concept before jumping into the deep end.
Later, we venture into the exciting realm of automated workflows and productisation. Imagine having a tool that could streamline your consultancy's repetitive tasks – that's the power of automation. We also discuss AI's potential across various industries and its possible impact on the consulting industry. Tim also shares his experience with low-code and no-code solutions and how they can help to supercharge the first stages of product development. Join us on this fascinating journey, where we explore the cutting-edge intersection of technology and consulting.
Prof. Joe O'Mahoney helps boutique consultancies scale and exit. Joe's research, writing, speaking and insights can be found at www.joeomahoney.com
Welcome to the Consulting Growth podcast. I'm Professor Joe Omani, a professor of consulting at Cardiff University and an advisor to consultancies that want to grow. If you'd like to find more out about me and access some free resources to help your consultancy grow, do please visit joomanicom. That's J-O-E-O-M-A-H-O-N-E-Ycom, right. Welcome back to the Consulting Growth podcast. I am very pleased to be hosting the Tim Redgate in this session Now. Tim, we've known each other for 20 over 20 years now, but very occasionally got in contact and I believe we both had more hair and it was a slightly different colour back in those days.
Speaker 2:It would mirror the image today actually.
Speaker 1:Yes, some time ago. Welcome, tim, nice, to see you again.
Speaker 2:Good to see you as well, joe. Yeah, obviously, yeah, it is, it must be. I think it was around 2001 when we worked together. Since then, apart from losing lots of hair and getting grey beards, we've both gone on our separate journeys, starting our own businesses as well, and things like that.
Speaker 1:Yeah. So, tim, I've got you on especially to talk about productisation and developing software for boutiques, consulting firms, professional service firms. But before we jump to that, could you tell our listeners a little bit about your background and how you got to where you are today?
Speaker 2:Sure, so after working together as we did at 3 before it was 3, the mobile company, immediately after that I founded a digital agency, so in the days when it was building Flash websites and that sort of thing, and then that very much moved on to business that built lots of apps for mobile when that was the thing that everybody did and then increasingly became very tech-focused through that business. So building a lot of what I'd call some custom tech products, custom software for large enterprises, some startups and things like that. And really for the last four years, so post that business that was about 15 years of that business and then post that I've been working as an advisor, stroke, fractional strategic lead for tech services businesses and tech product companies. So typically working with the end clients of those businesses tend to be often startups or businesses within businesses where they're trying to do something a little bit different. That the shelf isn't cookie cutter, so they require that degree of customisation and custom engineering. Really.
Speaker 1:Great, thank you, and I guess the firm that you're most heavily involved with now is Actioned. Could you tell us a little bit about what they do and what you do for them?
Speaker 2:Yeah, so Actioned is a tech services business, so we're about 90 people, largely engineering focused. So of the 90 people, 50 of those are engineers, software engineers, so very technically focused. And the reason I spend most of my time on that business really is that it very much is the delivery side of the strategy. So if we're talking to an end client about how they might take an idea to market and either create a new business or create a new business, actioned is very much about hence the name. Actioned it's about putting that into action and creating the thing.
Speaker 1:So, beyond the strategy, Okay, let's dive in a little bit to, I guess, what the listeners are going to be most interested in, which is around the sort of productisation of people services. You know people, knowledge and that side of things. Now, before we get into how and what and why, I'd like to think a little bit strategically about it and get your view on this, because a lot of consultancy or boutique owners, agency owners, look at with great envy the margins and the valuations of SaaS companies and they think, well, you know I should be doing SaaS Now. I also know a lot of SaaS owners who look at consultancies and think I could do with that predictable cash, heavy revenue coming in, and I could do without these big investors jumping on my back every time I want to make a decision.
Speaker 1:So consultancies and other firms are thinking and there's been a lot of this in the last 10 years of the price of software development and no code locos has happened. But it's a very difficult balance to get right strategically sometimes, you know, unless you're doing just sort of a, because software is a very different thing to people, I'm guessing. Strategically, the question I'd like to ask is strategically, how should the senior decision makers, who are primarily focused on people and client relationships and trust and all the people things that make consultancies work. How should they think about tech as a potential investment that they might make, alongside all the other potential investments that they might make, including hiring more people?
Speaker 2:There's obviously a few different lenses. So I've personally been in that situation where had a very people led business they were engineers, but effectively you're selling their time and as a client, and had that similar dilemma of it was a boutique business. So we were 20 people, you know, had some big clients and it was a nice predictable in lots of ways, but we knew that the multinevue going to be exciting as a sort of service-based business. So had it in our heads that we would spin out and we wanted to create a tech product. So that was a strategic decision based on exit. If that's the end goal and that's the sort of bet that you're going to make, then that's the lens through which you view it and therefore you look at more as tech investment, as a potential exit vehicle. But I think ultimately the thing that I see obviously in consultancies we see it in agents, specialist agencies there's subject matter expertise that exists within those businesses. Usually the start point of the product idea is like I do this, I know this subject intimately and know it to great level of detail and can spot an opportunity to productize. So that's one obvious space where the strategy would say well, do we have enough knowledge? Have we got enough of a gauge of the market and enough of a gauge Whether this thing that we know is needed widely, then clearly an opportunity.
Speaker 2:But there's also, I think again in a people-led business and I've worked on this with an HR consultancy actually over the last couple of years where they had a process and a product in terms of it was a methodology and a framework through which they had to go and consult on company culture basically, and in that situation the initial driver for productizing was really labor intensive. They were going out and having to do face-to-face interviews across large businesses. They were gathered together through a range of survey, monkey surveys, pulling it all into spreadsheets, number crunching what they were finding and then putting together these big, long, power point driven reports to go and then back to the client. And so there was just an obvious advantage to productizing aspects of that and automating aspects. Well, we don't need to go and have all those face-to-face interviews. We'll have the ones that are and we'll align our consultants with the high value strategic thinking. But all of that number crunching, all of that data gathering, all of that visualization of data is the stuff that can be done instantly using tech.
Speaker 2:So there's, I think you can view it through both lenses and in terms of one is do more with less, more number of people, and therefore it's just an efficiency.
Speaker 2:And then there is potential for a product that will have a life of its own or will have its own value. And then sort of in between that, I suppose, with the extreme being okay, we spin it out as a separate business, which, interestingly that HR consultancy did. Do you go that to the full extent of okay, this is a SaaS platform, we're going to sell it to companies and hopefully one day exit versus the sort of the efficiency end. And then in the middle of that I guess you've got, yes, efficiency and technology, but then the proprietary nature of the technology you might build is also about going does it make us more sticky with our clients? So, by having cool in that system, is it just another value add on top of our traditional business that says, actually, this makes us sticky? It means that they're not going to necessarily go to another consultancy because, on top of the knowledge and the people that work with day to day, we've got this added value through the tech.
Speaker 1:Yes, yeah, I mean it's. I'm putting myself in the position of a, say, a booty owner 50 to 100 people and we're doing okay. We've got 22% margin, got reasonable growth, but I'm looking at these opportunities. One thing I have seen a lot in an advisory position is decision or seniors leaders will start up a IT project or a SaaS project or some form of productization project, but they won't give it to attention or investment it deserves and so it's kind of just done as another thing alongside their day to day work, and they will get a lot of their internal people working on it sometimes and it won't be a priority, it's not driven.
Speaker 1:And my advice on this and I'd love to know what you think, what your view would be, but my advice on this has always been to treat it as almost a separate investment. So, whatever money, whatever profit you take as leaders in the firm, almost treat it as if someone had come up to you in the street and said look, I've got this really sound investment idea, I've got a lot of internal knowledge, how about putting some money into this? And so you've almost got a separation, both sometimes physically, where the work is occurring, but also psychologically. It's an investment project that needs to be run with specialists and thought about as something separate rather than something that's done alongside day work, because I've just certainly I've seen it go wrong a lot of times. What are your insights or feelings on how to think about these types of projects?
Speaker 2:Yeah, I think absolutely having a separate investment, seen as a separate investment, is the right thing to do. I think even more important than that is to have a product owner OK, yeah, business who it's their baby, and I think I've seen that work with clients. I saw it work in our own. In our own instance, we had somebody that had come up with the idea and we effectively backed it. So then you've got the investment, you carve out a team, ideally, and you make a priority and you make that their day job. And then you've got this product owner that's got not only the time and the investment but passion and the fire in their belly to do it. So it's not seen as a peripheral, secondary thing. It's like you run with this.
Speaker 2:I would say that's what I've seen work. And also it doesn't have to be a massive investment. That first stage it could be OK, we're going to try and get to this point and we've got three months to do it. And you set those limits and you know that it's not going to be perfect, know that it's going to be creaky under the hood from the tech standpoint, but you want to get to a proof point and then make further investments. But I think if you set those guardrails and go right, this is your budget, this is the team that are allocated to it At least a good chunk of their time. This is the product owner gives it the best chance of being a success.
Speaker 1:I think those are really good points and it's obviously or maybe not obviously to some of the listeners, but what I have seen happen a few times is that founder or leader will go out to you know they'll find a code on Upwork and say, look, this is my idea. They'll get them to build it. And then they realize they haven't really thought through the idea and perhaps the person they've got isn't necessarily as dedicated to they would like. And it's a very easy way to burn through a lot of money. If you're trying to get the perfect product initially and I really like your point about going for a beta or an alpha before you launch anything I think that sort of that.
Speaker 2:Build it and they will come approach. Is is expensive, yes, and it's risky much higher risk. We tried to launch. So from within my own agency, we tried to launch a few products over the years because we've got it in our heads that we were going to do this. I was talking to someone about this the other day.
Speaker 2:So what started out as just being right? We need some ideas from within the business and we wanted to find that owner or we just knew that. You know, within our team there'd be more knowledge than just as the sort of directors going strategically think about it. So we had a few false starts with things that we built that we thought would get tracked. And the thing that ultimately did work and we took it out to market and it was very successful when it went to market was it was a video personalization platform, and we effectively built very early alpha version of this technology, almost to the point where we called it more of a feasibility study. It was a technical feasibility can we do this thing that we couldn't see being done anywhere else? We just put an engineer on it with a product owner driving what the functionality should be.
Speaker 2:But it was a case of going. You've got a really short space of time. We maybe gave him four weeks. We got to the point where we had this feasible thing. We said. And it was a case of we know it works because we've got it working. It's hanging together with all these different bits of technology. It's not massively scalable. I don't know how it will work at scale, but we know it works. The first thing we did was we just put together a beautiful deck and went out to see some clients and said we presented it like it was ready. The interest and the clamour that we got from showing this really early proof of concept convinced us to invest further. We effectively closed our first deal with a major film studio before it was built.
Speaker 1:Yeah, I think that's a wonderful lesson to. So many times, especially when things have gone wrong, I have seen leaders say I've got this great idea and started to plow money into it. Then you ask the question well, who have you spoken to? Who's going to sell this? What do the clients think? And they'll say well, hold on, hold on, I'll get a prototype first. You can end up spending 50 grand on getting to prototype stage and then realize that not only is no one interested, but you don't have a mechanism necessarily for selling it to the clients. I think that's a really important point. Okay, let's get down to a bit more practical stuff. If I'm a founder of a again, 50 to 70 person firm, primarily people-based, I've got my CRM system, I've perhaps even got some software for managing projects and my finances are all on zero or free agent. What are the obvious things that I should be looking at in this day and age, especially since there's been so many developments over the last five years? What should I be looking at in terms of either automation or software?
Speaker 2:Automation. Obviously there's loads of options out there that you can use from an enterprise level. Obviously, you've got things like ServiceNow, which is like automated workflows. If you're working more with SaaS products within a boutique scenario, then you can use things like Zapier to make systems talk to each other, to maybe streamline some of those processes and automate those. I see that as dipping your toe in the water before you then go and get them.
Speaker 1:Tim, let me just pause you there for a second because you've mentioned a couple of things there that I realized you're very familiar with. Some of our listeners may not be at the stage where they know what ServiceNow is or even know what an automated workflow is, so could you just talk a little bit around how that might work? I've got this company. We do fairly standard projects. They're not necessarily standardized, but we're at the stage now where we've got seven or eight services that we typically offer clients and our back office is all relatively standardized, not necessarily as polished as it might be. What might automated workflows offer?
Speaker 2:If we think about the simplest level, it's tools like Zapier or Zapier, which effectively is a sort of if this then that coding. So it's a no-code platform but with some business logic you can say, well, if a really simple version of if we hit this date, then we trigger this email out to a client for a reminder or a payment or something like that. So it's very simple, if this then that. Or it might be that you're taking data out of one system and putting it into a spreadsheet, sort of do the number crunching. So those type of simple if this then that type of statements. I think there's lots of systems out there that would allow you to do that. So automating just parts of the workflow in certain elements will be ripe for automation. Certain elements will be well, it's so nuanced that it's not right to do that or it'd be much more complex to do that.
Speaker 2:And also simplest, lowest hanging fruit, the stuff that we do day in, day out, that I know I can automate because it's a repetitive task. That's always the first place we start, and it's also the first place we start when we're building out a product for a client. What's the simplest stuff? I mean you can focus the engineering on the complex.
Speaker 1:Let's take an example. Like I see a bid, I'm sorry. I saw a C and RFP that I like to look of and there's a loose process that I've noticed over the years. It tends to be that I'll send it to Claire, who's a partner, and say, should we go for this? Claire sends it back and says yes. So I dig up some previous bid that I've sent in, draft it out and then send it to a junior to finish, and then it might go two ways we might get send it to the budgeting and resourcing person to look at pricing and people, and then we might send it to some form of review process, that type of document flow. It's not the type of thing that would work quite well with workflow automation.
Speaker 2:Yeah, exactly, and I think if you think about project management tools, they're very much built for that. So even things like Basecamp, which obviously is very well used in the sort of small software engineering environment and usually in smaller agency environments, those will have you can effectively create templates, so what you're saying. So if I'm going to start up a new project, which an RFP response would be one of those, they will hear of the templates that happen around that, and so there'll be a template based on these are the tasks that need to be fulfilled, these are the people who need those requirements, fulfill those tasks, and so that's just a going. Yeah, it's repeatable and we know it's slightly different each time. So you go in and you have to tweak it, but you start with the. You know you start with that. This is our process, and if, on this occasion, we're not going to send it to Claire, we're going to send it to John. Then just go in and tweak that. Okay, in the automated process.
Speaker 1:Okay, let's go a little bit further, then and start talking about some productization of what we're doing. So they might be quite a few six or seven services that I say offer to clients, and, if I think about the typical consultancy life cycle, there might be a bit of research, it takes place, perhaps some interviews, and then those interviews get analyzed and then perhaps I might have some form of draft design, which might be a process map or a workflow or a business case or whatever, and then there might be some form of presentation that comes out of that to the senior people. How do I go about thinking? And I might have some data that comes off the back of that, and I might have data that perhaps goes across many clients that I haven't ever thought about looking at as a whole. Where do I start, as a business owner, thinking about productization when I have, perhaps, all these opportunities? Perhaps don't know about them because I'm just used to dealing with people and people-based services.
Speaker 2:Yeah, I guess there's those things that are some things that are repeatable, so common and across all consultancies that productizing almost doesn't make sense, because it's like, well, everybody's doing it, they've all got their own way of doing it and they're probably all automated, or many will be automating to a certain extent, because it's so known. So then it's a case of, well, I would potentially productizing into an already crowded space.
Speaker 1:Okay, yeah.
Speaker 2:So I think that's something to so doing that due diligence of. Is anybody else doing this?
Speaker 1:Could I buy this?
Speaker 2:off the shelf, or could I buy off the shelf with three or four different platforms? Sure, yep, that's always the first place to look, and even when you're productizing because sometimes it could be a case that the product itself could be the way in which you pull together multiple services Sure, yep. So, yeah, you almost kind of have to break it down into its atomic parts. Okay, it's a multi-stage process, some of which is data gathering, some of which is data presentation, some of which is recommendations, and so, yeah, I think it's a case of can I automate part of that journey? Yep, at worst makes me more efficient. Best, gives me an angle for a product.
Speaker 2:I'm trying to think of a good example, because we've worked with a media agency in creating a platform that was very much based on predictions. So it's, if you're about to go and spend money on a media campaign, it's like, how do we predict where that campaign's going? And it'll be based on what happened historically. We'll give you a sense of which direction it's going. Things going off track, on track, are we doing better? And that is a. The data that you get historically is all there. It's in different places, so you're maybe looking in different places for that yeah, as a human going in and actually looking at that.
Speaker 2:By spending some time doing that you can get a sense of okay, I can see this is going off track because cost per acquisition is going up. But then where that's gonna go and how you predict that with any degree of confidence will come down to some sort of algorithmic analysis. So say, okay, most likely to stay in this. The further out it goes, the less likelihood it's gonna happen. But so from that scenario again, you can imagine how, using multiple systems, you could get to that point of finding out how a campaign is doing. And in that particular scenario, the advice that we gave to that client when they first came to us with the idea was go away and do this on a spreadsheet and you could piece together different systems.
Speaker 2:There was a way to get data out in a sort of aggregated fashion through a third party service provider. It was relatively expensive, but not as expensive as building something yourself. So it's like to pay them three months worth of license fees to learn. Then it's only cost you $1,000 versus tens of thousands of dollars. You can start to see how a product would develop out of that, because you're still doing the heavy lifting, you're still having to interact with it. It's not automated it's not truly automated, but it is. Elements of the journey are automated, so your data gathering becomes automated. So, yeah, I think that's the first place to look is what things can we do now, today?
Speaker 1:As you were talking. A lot of what you were saying made me think about reporting. So obviously in a large professional service firm, you find to have a cadence of reporting and there's data coming from lots of different sources. But if you're in a boutique and I've seen, I see this very, very often, it's a lot of boutiques I'll have a spreadsheet here, they'll have a PDF coming from somewhere else. They'll have a semi-automated system that's generating some form of data and the seniors spend a lot of time getting this data together, putting it in the right format and then presenting it to the board, and the board might come back and say well, actually I want a bit more detail on this. What types of solutions are available there for the busy partner that has, or CEO that has responsibility for getting all this data from different places and presenting it relatively coherently to a board?
Speaker 2:Well, obviously you've got data visualization platforms like Microsoft Power BI or Tableau and things like that, which obviously are well used, especially in enterprise, well used to create those sort of data dashboards. I would say, kind of underneath that you've also got the likes of Airtable, which is again for a boutique SaaS platform. It's effectively like an online spreadsheet but got some elements of database, so you've got this central repository. Because I think that's the problem you have with the more traditional flow is that data's coming in from all different places, probably crunching it somewhere in a spreadsheet, and then they're creating a PowerPoint and so everything is. It's very linear, and then it's like, okay, you'll get another report in a month's time, but if that actually midway through the month, I wanna know how things are tracking, having that sort of always on the discipline of doing that in an online system versus doing it offline, sort of end user spreadsheet.
Speaker 2:I think that's the other thing it comes down to really is the discipline to use those tools versus and we see, I think spreadsheets are classic for that, even in massive businesses, and one of the businesses I've worked with over the last couple of years was exactly that. It was a sort of spreadsheet killer, if you like, within enterprises. So trying to remove large, complex, critical, business critical processes off of spreadsheets because it's obviously inherently fraught with issues, both in terms of somebody puts in the wrong calculation. There's been plenty horror stories of that.
Speaker 1:Yes, I have been responsible for one myself, tim, if ever you want a market to expand into, I can highly recommend universities. They are typically 20 years behind on their use of data. I'm sure all my university might be saying this, but I was sent a spreadsheet which, to be fair to me, the people that had sent it to me had hidden the data on it. I didn't see it and I gave it to my assistant to send out to students. The students very quickly worked out that there was hidden data on it and revealed it. It created tricky times for us, especially me. I see that I'm externally examined at many universities, aside from consultancy. There's a huge market there for you. Yes.
Speaker 2:This is it, that particular business that I've been working with, largely focused on the financial sector. Even in large international banking environments, you've still got a lot of things being done on spreadsheet. I think that's that discipline to do things online, do things through a system and make it as easy as possible. I think that's the other side of it. So the big part of any adoption, if you're going to roll out any system, it's about adoption, isn't it? Because you can build a beautiful product in the world.
Speaker 2:Again, that's why getting a beta version out as early as possible, testing with this, was the angle that we took with that media agency in terms of do it in a spreadsheet, do it for yourself. If it improves your management of those campaigns just by following this process, that's one win. Then share that spreadsheet with two other people in your business, come back and say, great, this has improved my campaign. Then you're just getting those proof points and it's in a very low cost, low risk way and it just gives you that I can now make the next investment.
Speaker 2:The worst thing is going away creating something and then nobody really uses it because everybody's like well, I kind of do it slightly differently and I don't want to be forced down this route, and that's why people end up going back to spreadsheets and saying, well, I know all the data is there in this system that you've created. I'm just going to download a CSV and go and go somewhere else offline, because that's what I'm used to working with. So it's yeah. How do you make it as easy as possible for people to adopt and valuable enough for people to adopt?
Speaker 1:Talking of simplicity, I don't know if it was you that did it, but it might have been someone you worked with. But I remember at three, when we were designing you know, never seen before applications from the third generation of mobile phones and they were planning on spending an absolute fortune on various bits of software to mock things up, and some bright sparks said, well, we can do this in PowerPoint and effectively, effectively just mocked up the UX, or CX as it would be called now on PowerPoint. Everything was hyperlinked and it saved hundreds of thousands. I'm guessing that's you're doing things. I don't mean via PowerPoint, but rather than paying coders hundreds of thousands of pounds, there's cheaper and quicker ways to do things sometimes.
Speaker 2:Yeah, I think. Yeah, there was lots of that. I wasn't involved in that particular one, but I remember we did some stuff at three. That was a similar thing where we saved them a lot of money by using a different process for a recommendation engine. Actually that was it. But yeah, I think.
Speaker 2:Yes, powerpoint's not going to be, or any of those sort of end user applications, those sort of personal applications. They're never going to be scalable To a certain extent. You're also you have that with no code as well. So I think you know a lot of enterprises. Obviously you're adopting no code, but what they're effectively doing is saying, well, let's use this no code solution versus using a spreadsheet or versus using, you know you go back even for people using like Lotus Notes to build. So you know that you're effectively giving them better tools ideally have been, you know, it approved and easier to manage from that point of view, but you still end up with you give them all the freedom in the world.
Speaker 2:You know, if you can give these sort of citizen developers all the freedom to create, then you'll end up with quite a lot of disparate solutions. I think that's still there's a scaling issue with. But it's great for doing that initial proof point, let's see if we can piece together a process using some no code solutions that just prove that that it's going to be valuable. And then low code is that nice sort of in between stage where you get some engineering by but you also get the engineering discipline, which is a case of you know, you can't get every citizen developer in there that can go and change things, like the spreadsheet example of unhiding cells or whatever it might be. It's like okay, if there's certain data that we want to lock down, we can do that because we've got engineering process around the implementation of a low code solution but obviously allows you to shortcut a lot of other areas.
Speaker 1:The no code, low code thing is I've not used. I've in the past I've gone straight to coders because I didn't. Why is that? I was, I guess, a bit scared that the no code or low code wouldn't provide me with what I wanted. That was based on ignorance rather than knowledge. It all fear rather than knowledge. How capable are low code and no code solutions at creating relatively quick, relatively effective solutions for common challenges that a business owner might have?
Speaker 2:I think, absolutely I think, a no code solution in the hands of somebody that is knows how to use it and it's confidential. We often talk about the spreadsheet jockey and it's the same process really, in terms of oftentimes and when we're working in those sort of banking environments and you go in and you find some spreadsheet, that was effectively. It was a system. Spreadsheet is a system. It'd been created, typically by an external consultant, because they'd come in with all the knowledge, knew how to create all the macros and create this kind of amazing spreadsheet, but then they exit the building and nobody knows how to change it. Yes, they had to change it because they're going.
Speaker 2:Well, this crucial process over here hangs off it. I see no code. In a similar vein in terms of the right person with the right understands the business process, understands how to use the tools to create that and automate that to a certain extent, can do that, but again, the knowledge tends to be held within quite small singular. I think it's the same with things like you see it, with AI, that ultimately, the best use of AI is when the person that's prompting it knows what they're doing. I think the same sort of applies really for no code that, yeah, you really need somebody in there that knows how it works, how to get the most out of it. But they don't have to be technical, don't have to get into the code.
Speaker 1:Yeah, I guess I've seen the whole range. I've seen companies that started off as consultancies and are now SaaS firms. They realized halfway through the process they've got their real asset with their data and so they flipped completely to, in effect, offering data initially with them as the interface between the clients, but eventually as self-serve so kind of flipped the company. That to me seems quite rare. I've seen two instances of it over the last five years. What I see more common is, as you started off with, is consultancies seeing they're doing the same things again and looking for a solution for that. I think a lot of consultancies are looking over their shoulder competitors who are productizing what they're doing and thereby saving costs and sometimes improving quality, sometimes offering clients capabilities that they might not have.
Speaker 1:But I think part of this mix is AI and you bought it up. I'm obviously very interested in it at the moment. How does AI fit into this mix? Because it seems from my perspective I'm seeing a lot of firms using it for tasks, not strategically, not systemically, but to be a consultant who's doing a workshop. They'll think what can AI come up with? Or finish this blog post, or finish this report. I haven't seen many use cases, or I have seen two or three, but I haven't seen many use cases where it's sort of more of a strategic investment by the firm. What are you seeing on your side?
Speaker 2:I think that sort of parallel pathing with AI is. I'm seeing a lot, as you say, helping with tasks. I'm doing this thing anyway. It's going to work faster if I've got AI doing elements of it. We use it within our teams at Action. The engineering team have been using it for a long time. So completing some of the coding or suggesting what the code should be for a certain interaction and things like that Senior engineer gets it, uses it, knows when it's made a mistake and fixes it. Junior engineers it's a dangerous thing because they don't spot the, they're not experienced enough to spot Things like testing and QA. That obviously is setting up automated tests of websites and apps and things like that. Then it's really good at writing test scripts and AI is great at that because it's fairly repeatable stuff. I think that's I think everybody should be using it.
Speaker 2:I'm saying to my kids at school doing GCSEs and A-levels. You've got to do it, you've got to use it, you've got to get left behind and, although it's sort of frowned upon, obviously from the point of view of education, you need to know your subject, you need to learn what you're supposed to be doing, but get it to write your first draft If you're revising. Get it to write your flashcards, things like that, because it's just a time saver In terms of more. A lot of the businesses that we work with and I work with are very much it's process driven. You know building out systems to support a process. So, ai again, because everybody wants to know. It's the question. Everybody's asking and saying, yes, I'll speak to someone, just as he. It's like the fan. Finally question on every call I go on to, it's like you know the final story around you know.
Speaker 2:And, finally, what are you doing with AI? You come to be into a potential client and I would say that you need to be looking at it from the point of view of, yes, if you're working with lots of data, then start looking at how AI Interprets that and but run it in parallel. You don't necessarily need to integrate it fully into the system yet, and we're doing that with a couple of clients at the moment where we are Taking data sets that they're working with, running them through some language models to maybe analyze some analyzed text for context and information, and we might create something like a what you call like an AI workbench, so it's an area where they can go in and actually analyze what's happening and spot where it's gone wrong and maybe Tell it where it's gone wrong. So that's like saying, well, you can expose your data to these systems, and I think that's going to become even more prevalent, because there's been obviously a concern about exposing data to them because of the privacy, but that's now being solid, open AI have now announced this sort of they're called gpt's private versions of chat gpt, so they can have it in-house, which I think is really the right thing to do because you can be in banking and pharmaceuticals and well, anything where you you know you've got secretive, secret content and or highly sensitive content. So I think you are going to see it being used more and more. So I would just say, to get anybody that's in any industry quite frankly, yeah, yes, I agree, should be running it in parallel and seeing how it how it performs and how it can improve your own Workflows and all your own productivity. Yeah, I think it's incredibly powerful.
Speaker 2:I, as a sort of anecdotally a good friend who's a child psychologist, quite high up in what she does and often speaks at conferences and things like that about the subject matter that she's expert in. And we're at a dinner party recently and and she was sort of asking about AI and chat, gpt and mentioned that she'd got a big conference coming up and she'd got to write 30 minute presentation. She said, you know so she's always the hardest thing is sitting down and getting that first draft, because I just need to, you know, be disciplined and clear a Sunday afternoon and I'll go and lock myself in my study and do it. And we flippantly over the dinner table said, you know why don't you what's the subject? And she sort of read out this log and set out this long, complicated subject.
Speaker 2:Plugged into chat gpt and she was just blown away. You know, and this is very top of her game Was blown away by the first draft that it came back with and she was like that's probably saved me four hours. It's incredibly whether it's quiet, the Elon Musk sort of state of killing us all, often chasing us up trees and things.
Speaker 2:I think you know that's probably more on the side of it should make us more efficient, more effective and hopefully give us more time for doing the things we enjoy, versus Doing the things that take up time that don't necessarily need to. Yeah, I think that's my only. My main advice is yeah, just you've got to work with it and see how it applies.
Speaker 1:Yeah, I think there's a lot to be said, for experimentation Isn't there, and I know experimentation takes time. But there's a lot that can be done with AI, just simply by practicing prompts. You know, put one prompt in. If that doesn't work, add something, take something out, keep playing with it till you're happy, and especially now the context windows are so huge.
Speaker 1:You can actually, you can provide very detailed prompts and lots of resources, especially with these GPT's which is an awful name, by the way but these personal bots that we can create now, I'm guessing it's going to controls as well, that the interesting thing about that is the control of the data set that goes in.
Speaker 2:So, if you, I'm supposed to be into another business, actually in the education space, so this will be interesting from a university point of view. So, as an assistant to students, it could be that actually there's yes, there's a vast array of information that they could draw upon, whether it's about things to do locally, access to certain things through the university, things to do with their subjects. You could control the data set that informs that bot. That means that you know they can ask it anything. It reduce, it means they don't have to go trawling through document after document to find out.
Speaker 2:I think that's the thing that, again, is really powerful, that you can say, well, actually, within this context, need to know this information, and I don't want to be, because the problem with it being totally open Is the hallucinations, things that didn't happen, and because it's sort of you know, creates a story based on information it's found here and saying, well, this is the most likely outcome or I'll tell you that, but actually that isn't the real truth.
Speaker 2:So I think you know the the control that that will come with it in terms of you know, both in terms of how it needs to be controlled and needs to from a governmental and just societal point of view, but also from the point of view going actually, and I need to know that, in this context, what I'm getting back is based on you know, based on information that I trust and rely on, and I see it as being very you know, very powerful for that and it's not really the focus of the podcast, but you're a right guy that's immersed in this area, so I'd love to know your view on it.
Speaker 1:One thing that worries me is that at the moment, chat gpt for plus or turbo, whichever version you've got access to with very little training will provide an answer to Most business questions that a, an analyst or junior consultant would. I have no doubt in a year or two that it will get to the consultant, perhaps even senior consultant level, especially if you have put some of your own data and some of your own content into either vector bases, vector databases or have fine-tuned the software. This also applies to students. I'm encouraging my students to use it.
Speaker 1:But what happens to that critical thinking that allows you to know whether or not something is wrong or could be improved or it's got the wrong end of the stick? I'm thinking you know it would be so easy now for a junior consultant to save themselves a day a week by plugging stuff in. Content comes out great. Present it as chat gpt4 becomes gpt5, 6, 7, whatever. It gets better and better and in five years time perhaps you've got a senior consultant or even a principal consultant who? Or a student at the university who has produced very good stuff and the clients are reasonably happy with it, but hasn't ever had to write a report themselves or never had to write an essay from beginning to end and therefore Maybe I'm just sounding old, therefore Can't spot weaknesses and haven't got that level of critical thinking. I don't know.
Speaker 2:Yeah, it's um, because part of me, I think you know, for those sort of junior level roles and and certainly you look at junior lawyers, you know that's, I think you know it's been widely reported. You know, when you look at the sort of jobs that are most at threat, lawyers is pretty close to the top of the list on research and finding precedence and that can be done by AI in seconds. So, yeah, again going back to my kids, you know you worry about what the future is for them and how they form their careers. Whichever way they go.
Speaker 2:I'm trying to encourage them to go into the creative industries for that recent but I think, consultancies and, and you know, similar to the work that I do. Maybe I'm just being blinkered to it and trying to sort of convince myself that I'm going to be useful in five years time, but I think it's still a people business, still about there's the nuance of Session that happens between humans. I was again. I was speaking to an education business yesterday who works with they do like careers advice Within schools and and as part of what they do, but you know, they were saying obviously somebody can go and plug in Information.
Speaker 2:You know child can go to chat gpc and get careers advice. I said, yeah, but it's not about the advice really. It's about the ability of the advisor to extract the information from that child is going to give them a sense of actually, what do you really want to?
Speaker 2:do so, it's a gig up to the prompt. It's like if you don't know how to prompt it, and sometimes you need somebody there to be coaching you really to get the information out of you. And I think you know consultancies are in a similar position, whereby it's the end client. It's really, how do you coach the information out of this to make sure that what you then deliver meets their needs but also meets their kind of, meets the needs of the business but also meets the needs of them as a person? In the same way as we talk about adoption, you know, if we talk about adoption of technology, it's you've got to understand the human side of that Because, yes, you can put together the most perfect system in the world. Adopt it because they'd rather do it the way they've always done it. You know there's other, they won't change. But it's only through the coaching and the human side, where you understand what those things are, you can find those pain points.
Speaker 1:Yes, I think that's a very good insight and I think there's lessons there for business schools, consultancies, your friend the child psychologist, that actually this I guess it's going back to the old consultancy thing, that the skills really matter, the interpersonal skills, communication, persuasion, the stuff that AI is going to be. You know, technically I'm sure there's no reason why can't do it, but emotionally engaging with the person is still, fortunately, our default preference, isn't it? Yeah?
Speaker 2:yeah, well, that's it and I think I guess, bringing it back to that sort of software development, we started talking about really product development and a lot of the work that I do personally and a lot of the way that I try to encourage our technical team in particular. It's more of the human side of you know, if a client asks you a question or asks for a certain piece of functionality, it's a really understanding the why behind that Is that really what you're asking for.
Speaker 2:If you're making a technical decision or you're making a request around a certain piece of functionality, you've got to understand the motivation for that, because it might be that they don't have enough knowledge about the technology to ask for the rest, and it might be that actually, when you boil it down and get to the root cause of why they've asked for it, it could be something totally different. And so there's yeah, the human side is, I think you know it is right for everybody. You know, and software engineers are probably that classic of being they'll deal with what's in front of them, they can deal with a problem and they'll work in the code and maybe not so much on the human side. And when you find the ones that can span that, then they typically are the ones that rise to the sort of CTO levels.
Speaker 1:Yeah, thank you, tim. How can listeners find out more about you and Actioned?
Speaker 2:Well, actioned is yeah, actioned is spelled with an X, so it's A-X-I-O-N-E-D. So yeah, obviously there's a website and me, linkedin. I'm not a massive social media user, so I'm not going to an active Twitter feed or anything like that X feed, should I say. And but yeah, find me on LinkedIn, tim Redgate. There's not many Tim Redgate in the world, so I'm quite easy.
Speaker 1:I'll put all the links in the show notes, and also to the Zapier, servicenow, basecamp and AirTable systems that you've mentioned, so I'll put them in as well.
Speaker 2:Yes, yeah, absolutely. I mean just yeah, there's loads more, but they were the ones that sort of off the top of my head. But yeah, happy to follow up and if anybody's got questions, absolutely.
Speaker 1:Brilliant. Thanks for your time, Tim.
Speaker 2:Thanks, joe, good to speak, good to see you, take care.
Speaker 1:As ever, thank you for listening to the Consultancy Growth Podcast. This is Professor Joe Omani at wwwjoamanicom.
