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Welcome to PMI's GEMBAfication, the podcast where we explore real stories behind performance improvement and bringing improvements to where the work is really done, and of course the highs and lows that we experience making those improvements.
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I'm your host, Susannah Clarke, managing partner of PMI, and today I'm joined by Karen Winter, Chief Transformation Officer at Informa Tech Target.
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So, Karen, we're going to talk a bit about the problems that you saw, how you mobilised, what worked, what didn't.
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Most importantly, of course, what you've learned along the way.
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So, thank you very much for joining me today, Karen.
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How are you?
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I am great.
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Thank you, Suse.
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Thanks for inviting me uh to kind of speak on the GEMBAfication podcast.
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I'm looking forward to it.
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Thanks.
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Well, it's a pleasure to have you here.
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Um, I wondered if you could start by just giving our audience some context about Informa Tech Target and also what areas of transformation are your current priorities.
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Thank you.
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Yeah, so I'm I'm sure most of you will not have heard of Informa Tech Target, except for my colleagues who may be listening to this.
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So uh hi.
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Um we are a global Informa is a global business, uh FTSE 100 listed company that is mainly an events business.
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Uh the TechTarget part of that organisation is really media, marketing services, research.
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So we're kind of providing an end-to-end way of connecting people, whether that's buyers, sellers, researchers, uh, and pont end or you know, uh customers and and their buyers, right?
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So it's it's different ways of connecting people.
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Um, Informa Tech Target was formed from a combination of Informa Tech media and uh research businesses, uh, which was a division of Informa, and a company called Tech Target, which is a US Boston-based company.
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Um, so the transformation work has really been around preparing our business for that combination.
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So it was a very big uh MA mergers and acquisitions deal and sort of dividing up the business, uh, in ensuring that the systems and processes and people were separated in a way that could be then moved into its new homes and then continuing that kind of transformation post-the-deal closing.
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So it was a year in the development, um, and then we are now sort of well, uh 18 months plus into post-deal.
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And so it's a very large transformation program that has been around system consolidation in the main.
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Um, but I also have a operational excellence team, so a team of Lean Six Sigma experts who are there to establish kind of ways of working and build continuous improvement culture methodology across the organisation and into the different business units.
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Um, uh, and also I have an AI centre of excellence uh within my group, which has been running for the past sort of year to establish ways of working around AI.
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So it's quite broad, um uh and but all of those pieces work really well together.
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Yes, yes.
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Well, as you know, we're big fans of that understanding what the opportunities are really that AI can bring to speed up and make improvement more effective, um, without doubt.
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So, yeah, I get that um uh continuity between the link between the two.
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Thank you for setting that scene.
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Um, so let's talk about you know the the the process improvement, the transformation that's made a real difference to you.
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And if you can start off by just telling us a bit about what was the kind of problem you're seeing and that you're trying to solve.
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I think um one of the challenges we've had recently, which has uh been really led by our operational excellence team, uh, but has required a very broad sort of multidisciplinary team to come and solve it.
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Um if you can imagine we had two sales teams coming together.
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Uh, they had previously been in different organisations, so different structures of people, uh, but also in different CRM systems selling different products.
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The intent was to bring those teams together so that we can now offer our customers a single unified set of products and services.
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Now, the solution to that has taken probably um six to eight months for us to kind of get into a good state uh without actually finishing a kind of full system consolidation.
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So it's doing all of the other stuff around it rather than just the system consolidation.
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So it has involved uh working around our legal entities and ensuring we have agreements in place to be able to do that sale, consolidating the people, uh, consolidating products.
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So we ended up reducing our product lines considerably.
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I think 400 or so product lines were consolidated.
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So that work is led by our operational excellence team who are looking really at kind of what is the outcome we are trying to achieve here and what is the best way of doing it.
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So some of this may be process improvement, and there was a ton of process improvement, some automation delivery, uh, use of AI in the implementation of those solutions.
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Uh, but it's really holistic.
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I mean, including the change management, working with sales enablement teams to ensure people know what they're selling.
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So we have to take that really broad, holistic view.
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And that has been really successful in enabling us to transition off one of the systems, off some legacy ways of working.
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Um, so it saves us money, it saves us time, it kind of reduces a lot of complexity in the organisation so that we are then ready for when we are in a state where we can move on to a new CRM platform, right?
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So it's it's kind of transitioning in a gradual way from where we have been and the immediate customer and sales problem and finding solutions through uh all the tools that we have at our disposal and just drawing upon people in the organisation using those sort of Lean Six Sigma skills of facilitating workshops and enabling people to to sort of be own their own transformation and own their own solutions to the problem.
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So I think that's a really good example that we've had as part of this combination deal.
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Yeah, and and uh the the you mentioned the change management as part of that.
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I'm interested in you know what sort of things you've done to bring those two groups of people who are from completely different organisations and different ways of working and unifying them to have a common view on how they work together successfully.
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Yeah, I think it is um a sort of transparent way of working that we have and ensuring that we are bringing people who are representative of those different areas who are, you know, it's a so each group knows that they have somebody who's representing their views and that person is trusted.
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We have to be really clear, certainly, in in some of the sort of challenges we've had around this in in terms of governance.
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Like you you have you have given this person that role of making decisions on your behalf.
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Now you have to trust them to do it, right?
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I think there's certainly we have found uh in some of our other programs where you end up with um hundreds of different stakeholders on a call.
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You realize that's gone a little bit wrong, like that the people are no longer trusting the person that they've given that accountability to.
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So that there is sort of the human side of it for sure, in uh keeping people feeling optimistic, ensuring we're doing clear communication, involving the right people in our workshops and in our stakeholder meetings, but the the governance piece is also really important in terms of being clear about who makes decisions and who has input uh because I think it's the it's the clarity that gives people confidence.
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Yes, yes, definitely.
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So um how did you sort of get you know get going with all of this in terms of mobilising everybody?
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You talked about your operational excellence team, and obviously they've been key to to making that successful for you.
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Yes, uh I also have a transformation management office uh who are the people that kind of really do the working with our partners, third party suppliers, that kind of stuff.
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Uh at one point um uh the my head of uh transformation management team had 150 contractors working for him directly.
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I'm hoping he wasn't managing them all with hourly ones every week.
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But um that so we have we've had quite a large team working on this at various points.
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Um, also fortunate to have a change management and comms expert on the team and people that are thinking about the kind of behavioural aspects of how of change.
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So we have a really good range of skill sets across all of those things.
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And and and we also, lots of us have worked in Informa and in different parts of Informa for a while.
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So 10 plus years, I'm coming at I've just passed my 12th anniversary.
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Um, so we we can kind of mobilize a lot of people.
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We've got some shared history and understanding of how the business works.
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That means we can do that, but also experience of running large transformation programs, which is um sort of helps us to get people mobilized quickly.
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I I think it's kind of that working with groups that haven't had experience of a central transformation function has been a challenge, like shifting that gear and changing how we work with people a little bit has been harder, um, especially when there are kind of conflicts of priorities within the business, right?
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When when you're pulling businesses together, there are many, many things that need to be done.
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Yes, indeed, indeed.
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And you talked a bit about Lean Six Sigma.
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So I'm interested in something about you know those sorts of methods.
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Which ones have you found have been you know new to people, uh but also delivering the best results for you in combining that that workforce.
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Yeah, I I think the attention to data, uh tracking, understanding how processes work in current state, right?
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For some people that was really new to see a process map was like super exciting because it is really visual.
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And you know, I mean, it's when I first started, that was the thing that I got most interested in was kind of quite in-depth process mapping.
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Um and making that visual for people so they could see how complex what they were doing now gives that sort of the call to action, right?
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Okay, oh, I can actually see how broken this is right now.
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I do now I do now understand and I want to fix it too.
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Like providing people with that transparency about how they themselves work, um, helping people to build really sort of stronger KPIs for their area of the business so that we're actually tracking performance so you can see the benefits before, after during.
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I think all of those things have been really helpful for us.
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Um I mean, we've been able to sort of start training people too.
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So we have uh an internally developed sort of online learning white belt program, um, and we've done some yellow belt sessions and people that have never been exposed to Lean Six Sigma before, super enthusiastic and excited to learn how they can apply those tools to their own work.
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Um, I think, I mean, there are so many tools that are super helpful, stakeholder and understanding your stakeholders, whatever that might be, uh, whether you're using a Kano model or you know, just kind of stakeholder mapping and thinking about your communications as a base are based upon that.
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Um, and I think FMEA is very helpful for us.
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We do quite a lot of uh detailed risk analysis and understanding uh where things are kind of not perfect, right?
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Because if you're building interim workaround solutions, nothing is ever going to be perfect.
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So understanding where it could go wrong and mitigating against that, but having tools to do it has been really helpful.
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Yeah.
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And and when you, you know, you talked a bit about data and measuring and and therefore seeing performance.
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I do experience sometimes I've noticed that suddenly people they get so enthusiastic they just want to measure everything.
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You know, because they because suddenly everything seems important.
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How you manage that to make sure people really get, well, actually, you know, where you know, what's driving, what's driven, and yeah, what's the priority and and I guess the vital few, as it were.
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And I think that is um true even at the exec level, right?
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To sort of hold off that enthusiasm to want to measure everything that's in front of you.
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Um we go back to what matters to the customer, right?
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So uh there's one area that I've been working on with the team, in particular around fulfillment delivery of campaigns.
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What matters to the customer there is I've said to the salesperson that, yes, I want to go ahead with this deal.
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What is the day I get my first lead?
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So measuring that time period.
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So what we what we had been doing, teams have been doing previously was measuring the kind of time it took to fulfill from when they received the order, or they were measuring the time it took to issue the contract.
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And all of those things individually are important, but the thing that matters to the customer is the time from I've said go on this deal and now I've received the product I've asked for.
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So that became our kind of overarching KPI for that part of the business, and then measuring kind of defects and rework was another was was another thing that we wanted to to focus on because customers were finding that they were then having to go back and ask for something slightly different.
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So just being led by what what matters to the customer.
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Yeah, absolutely.
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And we've talked a bit, um you and I have talked about AI and and and and the um uh implementation of AI in order to help improve the ways in which you work.
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I wondered if you could just tell us a little bit about that and what you have been doing and how you've been you know governing that and and and identifying opportunities for improvement.
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Sure, yeah.
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Um so we, I think like a lot of people, uh a lot of businesses, established a sort of AI centre of excellence.
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I think because uh we have a transformation function which includes enterprise tech, it ended up with with me in in the transformation team rather than being technology-led, which I think is a really fortunate thing for us, and it's enabled us to look at it in a slightly different way than some other areas that I've seen where it's being implemented from a from a tech first, which I think um listening to uh Fraser Deere's uh podcast recently, I could see that kind of not tech first be kind of led by the problems you're trying to solve rather than I've got a nice tool and where can we use it, I think was the tagline there, right?
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And I completely agree with that.
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I think we we started off certainly by enabling people with some training and access to plenty of tools, like experiment, play, stop being scared of it, like have a go.
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Um, and I think that is the right approach to take, even though we've now we're now kind of looking at it and going, well, now we've got tons of tools in operation, right?
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And we need to consolidate that a bit.
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I do still think it's the right approach in order to reduce the fear that people have and to give them a little bit more, I guess, uh, control over their own use of it and their own experimentation.
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Um, but I think it was very clear to me quickly that it there are two different elements of AI use in our organisation.
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And one is very product focused.
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How are we going to use AI for our customers' benefit to improve our products?
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And the other is around operational efficiency, productivity gains, and so on.
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And we had two different cues.
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So we had people saying, I've got an idea for AI, I've got a use case that I want to try, we've always had our operational excellence, I've got a process problem.
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Can you help me fix it for them?
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Um very quickly, we kind of said, This needs to be a single cue, right?
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So um it needs to be a single cue that starts at operational excellence.
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This is my view.
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Uh starts at operational excellence.
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So you're looking at it from a process problem.
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What is the problem we're trying to solve?
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Is there a better way of doing this?
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Do we need to be doing it at all, especially in a place where you've combined, like, do we have duplicate processes here that we can we can actually reduce some way of working, improve the process, and then look at the solution.
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So AI becomes an option for the solution.
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It's not the leading leading star in this.
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It's not uh we want to use AI, here can we use it?
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But what are the business problems we need to solve?
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Which are the most critical, um, and what are the next steps we need to take?
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And AI, therefore, is like part of the solution set rather than rather than the an end of itself.
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Um I think that for us, that kind of moving AI to be an integral part of how business business units, uh how the operational excellence team are using AI to solve business problems rather than uh just sort of AI enabling everything we possibly can, because we've talked about work slop and things like that, right?
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It's just producing more crap faster.
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Which is not helpful.
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Um, so we need to fix the process first.
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So I think AI becomes a really key tool for lean practitioners to understand as part of their solution set, um, and not get carried away with just fixing everything.
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Yes, indeed.
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Indeed.
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And um so we talk about work slop, I guess.
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But you know, thinking about some of that, you know, in terms of perhaps things that ha that you've learned that didn't go as well as you'd hoped they would, are there any particular areas there that you look back on and think, oh, I would definitely approach that differently in the future?
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I think, I mean, for me at the sort of transformation macro level, uh thinking that we could deliver some really big technical transformation programs uh in a in a business that was just combining, like I think we ran too fast at that and we didn't look at the process problems first.
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Right.
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We we ended up falling into the trap that we knew was wrong, uh, of kind of we know we need to do some technology consolidation, so we'll do that, rather than sort of working with the teams a lot more to understand where they are, uh, you know, what what their process landscape looks like now, what it is that they're trying to achieve, what their what their pain points are right now, and kind of working with them a lot more.
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Um it, you know, that there's a sort of complex thing to do with with funding post-mergers that that sort of enabled us to get carried away with ourselves.
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But um I think not having done that well has in a has led us to take a lot more time in implementing those those uh solutions than we should have done.
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And time is an interesting um measure.
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Um I know that, and um you know, I'm sure you've experienced it too.
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There's a lot of um one it'd be like you talked about when the customer says go, I want my first lead and I want to know how quickly I'm gonna get that.
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When somebody says go on a transformation, you know, they want results, don't they?
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Yeah.
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So how have you found managing that expectation, um, particularly at the senior level, around how long this is really gonna take in order to get the right results out?
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I think it's about breaking it down into things where you can be confident that you could deliver uh, you know, part of the solution by a certain date.
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And I have to admit we've got that completely wrong in many cases, and we were way too optimistic about how long this would take.
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Uh so I didn't succeed in that, but um I still currently have a job, so that's good.
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I haven't completed.
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But I think again, it is that transparency again, right?
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Being transparent all along.
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Okay, look, we've just discovered this thing, and that means that it's now going to take us three months longer than we thought, or you know, the the data complexity means that we need to do two months of data cleansing that we didn't anticipate, right?
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I think it's all of that kind of the transparency and proactively managing with senior stakeholders uh is the only way to do it right.
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You uh it's a real mix of um, because we have a mix of waterfall and agile programs, it's really hard to predict, and that is a real conflict, actually, when you've got things that are dependencies, one is being run in an agile way, one is being run in a waterfall way.
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Uh actually managing those two programs is really challenging to do.
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Um, I think the team have done a phenomenal job of doing it as well as we have.
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So I I think, yeah, it is uh being optimistic because if you're not, you won't get the permission to go ahead.
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Uh, and then being realistic when you start to be faced with the challenges.
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Yes, yes.
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And and I like, you know, what you say about you know chunking it up into a set of deliverables along the way so that you can then, as you say, keep that sort of enthusiasm going by reporting success and results.
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Yeah, absolutely.
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And I think I mean having having sort of change in communications within my unit as well makes that really easy because I've got somebody who's always on the lookout for a success story that we can celebrate, um, and kind of doing that on a regular time uh time cadence so that we have have regular comms going out.
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And you know, when you look back on all of this experience that you've had bringing the teams together, the focus on, you know, ensuring that it's done from a problem perspective, prioritization of the problems.
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You know, what do you think is the biggest lessons that you and the team have learned about trying to lead change?
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I think there are uh a number of things that I think we knew we should or should not have done, and we didn't kind of stick to our guns or stick to our guts, as my daughter likes to say, um, on those things and and we should have done, right?
00:21:56.640 --> 00:22:09.279
So I think being ensuring that you are applying the Rigor that you know, like working to the principles, working in a way uh that is going to deliver the best results, even if it feels a bit like there's friction at the beginning.
00:22:09.279 --> 00:22:14.400
Um, one of the big lessons we had was around the maturity of the business itself.
00:22:14.400 --> 00:22:18.319
So bringing together different businesses.
00:22:18.319 --> 00:22:22.640
Uh one is quite a mature business, in fact, kind of quite bureaucratic.
00:22:22.640 --> 00:22:26.160
One was very start-up, um, one was kind of scale up.
00:22:26.160 --> 00:22:31.200
And those businesses at different points have different experiences of transformation and change.
00:22:31.200 --> 00:22:37.759
They have different um sort of informal networks, they have different ways of decision making.
00:22:37.759 --> 00:22:43.599
Uh, so it really tailoring your approach to where the business is.
00:22:43.599 --> 00:22:49.920
Like we talk about this as kind of where we find people where they are and and talk to them in the where where they are.
00:22:49.920 --> 00:22:54.640
But actually, the the business itself has a culture that we need to pay attention to.
00:22:54.640 --> 00:22:57.759
Um, and I think that was a thing that we should have paid more attention to.
00:22:57.759 --> 00:23:01.440
Like we we identified it and then didn't really come up with a plan to solve for it.
00:23:01.440 --> 00:23:03.519
So I think that that's my biggest lesson learned.
00:23:03.519 --> 00:23:05.359
I will make sure I do that properly next time.
00:23:05.599 --> 00:23:14.559
It would be a risk me not to mention your um you've been studying for your master black belt level six um improvement leader.
00:23:14.559 --> 00:23:20.400
I'm interested in that in terms of you know, you're a chief transformation officer.
00:23:20.400 --> 00:23:29.759
So I find it very interesting that there's still opportunity for learning, and that's um and we all know that that that actually that really does help in many ways.
00:23:29.759 --> 00:23:37.519
But is there anything in particular that you have really picked up on that you think has made a difference in your own practice?
00:23:38.000 --> 00:23:46.960
Yeah, I think I mean, uh yes, I I'm I realise I am of a seniority and age actually, that that lifelong learning is part of continuous improvement, right?
00:23:46.960 --> 00:23:52.720
It's really important and I'm really excited that I have the opportunity to be able to learn alongside my role, right?
00:23:52.720 --> 00:23:57.039
That's a it's a big thing for a company to allow, allow me that time and space.
00:23:57.039 --> 00:24:02.400
Um, I think learning, uh I it's it's a while since I did my black belt.
00:24:02.400 --> 00:24:20.480
So I kind of having a refresher and coming back to it, and think as I was just saying about kind of really sticking to what you know and applying that, coming back to learning it again or kind of refreshing on some things has made me more committed to doing things in the right way.
00:24:20.480 --> 00:24:24.960
I think that um has been a really positive experience for me.
00:24:24.960 --> 00:24:36.160
Um, I mean, a lot of the stuff that we talk about early on in the program around kind of change and working with teams and working with senior stakeholders has been super relevant.
00:24:36.160 --> 00:24:43.359
Um, and really I've had loads of work experience examples that I can bring in and lots of on-the-job opportunity.
00:24:43.359 --> 00:24:46.559
Um, the data stuff that we've just been doing, less so, right?
00:24:46.559 --> 00:24:54.480
I because I I have people for that now, and I I've needed to really kind of dig deep to find data that I can analyse myself and kind of work with that.
00:24:54.480 --> 00:25:05.119
But all has been really brilliant to kind of keep me feeling refreshed and like I can apply these tools genuinely to the next new challenge.
00:25:05.839 --> 00:25:06.880
Fantastic.
00:25:06.880 --> 00:25:09.200
Karen, thank you ever so much.
00:25:09.200 --> 00:25:14.799
I really appreciate you joining me for this and for sharing your learnings and being so honest.
00:25:14.799 --> 00:25:29.200
Um, all of this is is just such a key part of, as you say, you know, how we grow as individuals, how we grow within our roles um and how we help organisations improve.
00:25:29.200 --> 00:25:30.559
Uh, so thank you.
00:25:30.559 --> 00:25:30.960
Thank you.
00:25:30.960 --> 00:25:43.039
Um to our listeners, if you've enjoyed this episode, then uh please uh don't forget to subscribe, uh, share the episode with your colleagues, and obviously do leave us a review.
00:25:43.039 --> 00:25:52.319
The more we grow this podcast, um, everyone's uh work becomes better, um, and the more insights you can all make into your business and its operations.
00:25:52.319 --> 00:25:58.559
If you need any more information, you can find lots of resources for you at PMI.co.uk.
00:25:58.559 --> 00:26:01.119
And please do follow us on LinkedIn.
00:26:01.119 --> 00:26:05.519
Until next time, I look forward to seeing you, and thank you again, Karen.
00:26:06.240 --> 00:26:07.200
Thank you.
00:00:00.080 --> 00:00:16.160
Welcome to PMI's GEMBAfication, the podcast where we explore real stories behind performance improvement and bringing improvements to where the work is really done, and of course the highs and lows that we experience making those improvements.
00:00:16.160 --> 00:00:27.440
I'm your host, Susannah Clarke, managing partner of PMI, and today I'm joined by Karen Winter, Chief Transformation Officer at Informa Tech Target.
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So, Karen, we're going to talk a bit about the problems that you saw, how you mobilised, what worked, what didn't.
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Most importantly, of course, what you've learned along the way.
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So, thank you very much for joining me today, Karen.
00:00:39.600 --> 00:00:40.799
How are you?
00:00:41.280 --> 00:00:42.159
I am great.
00:00:42.159 --> 00:00:42.880
Thank you, Suse.
00:00:42.880 --> 00:00:47.280
Thanks for inviting me uh to kind of speak on the GEMBAfication podcast.
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I'm looking forward to it.
00:00:48.159 --> 00:00:48.399
Thanks.
00:00:48.640 --> 00:00:50.479
Well, it's a pleasure to have you here.
00:00:50.479 --> 00:01:02.719
Um, I wondered if you could start by just giving our audience some context about Informa Tech Target and also what areas of transformation are your current priorities.
00:01:03.280 --> 00:01:03.679
Thank you.
00:01:03.679 --> 00:01:09.280
Yeah, so I'm I'm sure most of you will not have heard of Informa Tech Target, except for my colleagues who may be listening to this.
00:01:09.280 --> 00:01:10.400
So uh hi.
00:01:10.400 --> 00:01:19.519
Um we are a global Informa is a global business, uh FTSE 100 listed company that is mainly an events business.
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Uh the TechTarget part of that organisation is really media, marketing services, research.
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So we're kind of providing an end-to-end way of connecting people, whether that's buyers, sellers, researchers, uh, and pont end or you know, uh customers and and their buyers, right?
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So it's it's different ways of connecting people.
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Um, Informa Tech Target was formed from a combination of Informa Tech media and uh research businesses, uh, which was a division of Informa, and a company called Tech Target, which is a US Boston-based company.
00:01:54.400 --> 00:02:00.560
Um, so the transformation work has really been around preparing our business for that combination.
00:02:00.560 --> 00:02:17.759
So it was a very big uh MA mergers and acquisitions deal and sort of dividing up the business, uh, in ensuring that the systems and processes and people were separated in a way that could be then moved into its new homes and then continuing that kind of transformation post-the-deal closing.
00:02:17.759 --> 00:02:25.360
So it was a year in the development, um, and then we are now sort of well, uh 18 months plus into post-deal.
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And so it's a very large transformation program that has been around system consolidation in the main.
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Um, but I also have a operational excellence team, so a team of Lean Six Sigma experts who are there to establish kind of ways of working and build continuous improvement culture methodology across the organisation and into the different business units.
00:02:49.759 --> 00:02:59.599
Um, uh, and also I have an AI centre of excellence uh within my group, which has been running for the past sort of year to establish ways of working around AI.
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So it's quite broad, um uh and but all of those pieces work really well together.
00:03:04.719 --> 00:03:05.520
Yes, yes.
00:03:05.520 --> 00:03:16.400
Well, as you know, we're big fans of that understanding what the opportunities are really that AI can bring to speed up and make improvement more effective, um, without doubt.
00:03:16.400 --> 00:03:21.360
So, yeah, I get that um uh continuity between the link between the two.
00:03:21.360 --> 00:03:23.520
Thank you for setting that scene.
00:03:23.520 --> 00:03:32.719
Um, so let's talk about you know the the the process improvement, the transformation that's made a real difference to you.
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And if you can start off by just telling us a bit about what was the kind of problem you're seeing and that you're trying to solve.
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I think um one of the challenges we've had recently, which has uh been really led by our operational excellence team, uh, but has required a very broad sort of multidisciplinary team to come and solve it.
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Um if you can imagine we had two sales teams coming together.
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Uh, they had previously been in different organisations, so different structures of people, uh, but also in different CRM systems selling different products.
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The intent was to bring those teams together so that we can now offer our customers a single unified set of products and services.
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Now, the solution to that has taken probably um six to eight months for us to kind of get into a good state uh without actually finishing a kind of full system consolidation.
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So it's doing all of the other stuff around it rather than just the system consolidation.
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So it has involved uh working around our legal entities and ensuring we have agreements in place to be able to do that sale, consolidating the people, uh, consolidating products.
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So we ended up reducing our product lines considerably.
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I think 400 or so product lines were consolidated.
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So that work is led by our operational excellence team who are looking really at kind of what is the outcome we are trying to achieve here and what is the best way of doing it.
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So some of this may be process improvement, and there was a ton of process improvement, some automation delivery, uh, use of AI in the implementation of those solutions.
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Uh, but it's really holistic.
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I mean, including the change management, working with sales enablement teams to ensure people know what they're selling.
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So we have to take that really broad, holistic view.
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And that has been really successful in enabling us to transition off one of the systems, off some legacy ways of working.
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Um, so it saves us money, it saves us time, it kind of reduces a lot of complexity in the organisation so that we are then ready for when we are in a state where we can move on to a new CRM platform, right?
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So it's it's kind of transitioning in a gradual way from where we have been and the immediate customer and sales problem and finding solutions through uh all the tools that we have at our disposal and just drawing upon people in the organisation using those sort of Lean Six Sigma skills of facilitating workshops and enabling people to to sort of be own their own transformation and own their own solutions to the problem.
00:06:07.120 --> 00:06:11.040
So I think that's a really good example that we've had as part of this combination deal.
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Yeah, and and uh the the you mentioned the change management as part of that.
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I'm interested in you know what sort of things you've done to bring those two groups of people who are from completely different organisations and different ways of working and unifying them to have a common view on how they work together successfully.
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Yeah, I think it is um a sort of transparent way of working that we have and ensuring that we are bringing people who are representative of those different areas who are, you know, it's a so each group knows that they have somebody who's representing their views and that person is trusted.
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We have to be really clear, certainly, in in some of the sort of challenges we've had around this in in terms of governance.
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Like you you have you have given this person that role of making decisions on your behalf.
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Now you have to trust them to do it, right?
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I think there's certainly we have found uh in some of our other programs where you end up with um hundreds of different stakeholders on a call.
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You realize that's gone a little bit wrong, like that the people are no longer trusting the person that they've given that accountability to.
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So that there is sort of the human side of it for sure, in uh keeping people feeling optimistic, ensuring we're doing clear communication, involving the right people in our workshops and in our stakeholder meetings, but the the governance piece is also really important in terms of being clear about who makes decisions and who has input uh because I think it's the it's the clarity that gives people confidence.
00:07:43.360 --> 00:07:45.439
Yes, yes, definitely.
00:07:45.439 --> 00:07:52.800
So um how did you sort of get you know get going with all of this in terms of mobilising everybody?
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You talked about your operational excellence team, and obviously they've been key to to making that successful for you.
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Yes, uh I also have a transformation management office uh who are the people that kind of really do the working with our partners, third party suppliers, that kind of stuff.
00:08:09.839 --> 00:08:16.560
Uh at one point um uh the my head of uh transformation management team had 150 contractors working for him directly.
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I'm hoping he wasn't managing them all with hourly ones every week.
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But um that so we have we've had quite a large team working on this at various points.
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Um, also fortunate to have a change management and comms expert on the team and people that are thinking about the kind of behavioural aspects of how of change.
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So we have a really good range of skill sets across all of those things.
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And and and we also, lots of us have worked in Informa and in different parts of Informa for a while.
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So 10 plus years, I'm coming at I've just passed my 12th anniversary.
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Um, so we we can kind of mobilize a lot of people.
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We've got some shared history and understanding of how the business works.
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That means we can do that, but also experience of running large transformation programs, which is um sort of helps us to get people mobilized quickly.
00:09:05.919 --> 00:09:22.559
I I think it's kind of that working with groups that haven't had experience of a central transformation function has been a challenge, like shifting that gear and changing how we work with people a little bit has been harder, um, especially when there are kind of conflicts of priorities within the business, right?
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When when you're pulling businesses together, there are many, many things that need to be done.
00:09:26.960 --> 00:09:28.720
Yes, indeed, indeed.
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And you talked a bit about Lean Six Sigma.
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So I'm interested in something about you know those sorts of methods.
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Which ones have you found have been you know new to people, uh but also delivering the best results for you in combining that that workforce.
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Yeah, I I think the attention to data, uh tracking, understanding how processes work in current state, right?
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For some people that was really new to see a process map was like super exciting because it is really visual.
00:10:01.679 --> 00:10:08.159
And you know, I mean, it's when I first started, that was the thing that I got most interested in was kind of quite in-depth process mapping.
00:10:08.159 --> 00:10:16.399
Um and making that visual for people so they could see how complex what they were doing now gives that sort of the call to action, right?
00:10:16.399 --> 00:10:19.120
Okay, oh, I can actually see how broken this is right now.
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I do now I do now understand and I want to fix it too.
00:10:22.559 --> 00:10:38.799
Like providing people with that transparency about how they themselves work, um, helping people to build really sort of stronger KPIs for their area of the business so that we're actually tracking performance so you can see the benefits before, after during.
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I think all of those things have been really helpful for us.
00:10:42.639 --> 00:10:47.039
Um I mean, we've been able to sort of start training people too.
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So we have uh an internally developed sort of online learning white belt program, um, and we've done some yellow belt sessions and people that have never been exposed to Lean Six Sigma before, super enthusiastic and excited to learn how they can apply those tools to their own work.
00:11:03.120 --> 00:11:20.320
Um, I think, I mean, there are so many tools that are super helpful, stakeholder and understanding your stakeholders, whatever that might be, uh, whether you're using a Kano model or you know, just kind of stakeholder mapping and thinking about your communications as a base are based upon that.
00:11:20.320 --> 00:11:24.000
Um, and I think FMEA is very helpful for us.
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We do quite a lot of uh detailed risk analysis and understanding uh where things are kind of not perfect, right?
00:11:31.200 --> 00:11:35.279
Because if you're building interim workaround solutions, nothing is ever going to be perfect.
00:11:35.279 --> 00:11:42.559
So understanding where it could go wrong and mitigating against that, but having tools to do it has been really helpful.
00:11:42.879 --> 00:11:43.519
Yeah.
00:11:43.519 --> 00:11:48.960
And and when you, you know, you talked a bit about data and measuring and and therefore seeing performance.
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I do experience sometimes I've noticed that suddenly people they get so enthusiastic they just want to measure everything.
00:11:56.879 --> 00:12:00.399
You know, because they because suddenly everything seems important.
00:12:00.399 --> 00:12:12.240
How you manage that to make sure people really get, well, actually, you know, where you know, what's driving, what's driven, and yeah, what's the priority and and I guess the vital few, as it were.
00:12:12.559 --> 00:12:16.799
And I think that is um true even at the exec level, right?
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To sort of hold off that enthusiasm to want to measure everything that's in front of you.
00:12:20.799 --> 00:12:23.279
Um we go back to what matters to the customer, right?
00:12:23.279 --> 00:12:31.600
So uh there's one area that I've been working on with the team, in particular around fulfillment delivery of campaigns.
00:12:31.600 --> 00:12:38.720
What matters to the customer there is I've said to the salesperson that, yes, I want to go ahead with this deal.
00:12:38.720 --> 00:12:40.639
What is the day I get my first lead?
00:12:40.639 --> 00:12:42.559
So measuring that time period.
00:12:42.559 --> 00:12:53.360
So what we what we had been doing, teams have been doing previously was measuring the kind of time it took to fulfill from when they received the order, or they were measuring the time it took to issue the contract.
00:12:53.360 --> 00:13:03.360
And all of those things individually are important, but the thing that matters to the customer is the time from I've said go on this deal and now I've received the product I've asked for.
00:13:03.360 --> 00:13:19.279
So that became our kind of overarching KPI for that part of the business, and then measuring kind of defects and rework was another was was another thing that we wanted to to focus on because customers were finding that they were then having to go back and ask for something slightly different.
00:13:19.279 --> 00:13:22.799
So just being led by what what matters to the customer.
00:13:23.360 --> 00:13:24.879
Yeah, absolutely.
00:13:24.879 --> 00:13:39.519
And we've talked a bit, um you and I have talked about AI and and and and the um uh implementation of AI in order to help improve the ways in which you work.
00:13:39.519 --> 00:13:49.360
I wondered if you could just tell us a little bit about that and what you have been doing and how you've been you know governing that and and and identifying opportunities for improvement.
00:13:50.000 --> 00:13:50.559
Sure, yeah.
00:13:50.559 --> 00:13:57.200
Um so we, I think like a lot of people, uh a lot of businesses, established a sort of AI centre of excellence.
00:13:57.200 --> 00:14:33.039
I think because uh we have a transformation function which includes enterprise tech, it ended up with with me in in the transformation team rather than being technology-led, which I think is a really fortunate thing for us, and it's enabled us to look at it in a slightly different way than some other areas that I've seen where it's being implemented from a from a tech first, which I think um listening to uh Fraser Deere's uh podcast recently, I could see that kind of not tech first be kind of led by the problems you're trying to solve rather than I've got a nice tool and where can we use it, I think was the tagline there, right?
00:14:33.039 --> 00:14:34.559
And I completely agree with that.
00:14:34.559 --> 00:14:46.639
I think we we started off certainly by enabling people with some training and access to plenty of tools, like experiment, play, stop being scared of it, like have a go.
00:14:46.639 --> 00:14:54.879
Um, and I think that is the right approach to take, even though we've now we're now kind of looking at it and going, well, now we've got tons of tools in operation, right?
00:14:54.879 --> 00:14:56.559
And we need to consolidate that a bit.
00:14:56.559 --> 00:15:09.039
I do still think it's the right approach in order to reduce the fear that people have and to give them a little bit more, I guess, uh, control over their own use of it and their own experimentation.
00:15:09.039 --> 00:15:16.240
Um, but I think it was very clear to me quickly that it there are two different elements of AI use in our organisation.
00:15:16.240 --> 00:15:17.759
And one is very product focused.
00:15:17.759 --> 00:15:22.799
How are we going to use AI for our customers' benefit to improve our products?
00:15:22.799 --> 00:15:27.919
And the other is around operational efficiency, productivity gains, and so on.
00:15:27.919 --> 00:15:30.799
And we had two different cues.
00:15:30.799 --> 00:15:40.159
So we had people saying, I've got an idea for AI, I've got a use case that I want to try, we've always had our operational excellence, I've got a process problem.
00:15:40.159 --> 00:15:41.919
Can you help me fix it for them?
00:15:41.919 --> 00:15:46.480
Um very quickly, we kind of said, This needs to be a single cue, right?
00:15:46.480 --> 00:15:52.159
So um it needs to be a single cue that starts at operational excellence.
00:15:52.159 --> 00:15:52.799
This is my view.
00:15:52.799 --> 00:15:54.720
Uh starts at operational excellence.
00:15:54.720 --> 00:15:56.720
So you're looking at it from a process problem.
00:15:56.720 --> 00:15:58.559
What is the problem we're trying to solve?
00:15:58.559 --> 00:16:00.960
Is there a better way of doing this?
00:16:00.960 --> 00:16:12.639
Do we need to be doing it at all, especially in a place where you've combined, like, do we have duplicate processes here that we can we can actually reduce some way of working, improve the process, and then look at the solution.
00:16:12.639 --> 00:16:15.840
So AI becomes an option for the solution.
00:16:15.840 --> 00:16:19.279
It's not the leading leading star in this.
00:16:19.279 --> 00:16:21.919
It's not uh we want to use AI, here can we use it?
00:16:21.919 --> 00:16:24.240
But what are the business problems we need to solve?
00:16:24.240 --> 00:16:29.279
Which are the most critical, um, and what are the next steps we need to take?
00:16:29.279 --> 00:16:36.480
And AI, therefore, is like part of the solution set rather than rather than the an end of itself.
00:16:36.480 --> 00:16:56.240
Um I think that for us, that kind of moving AI to be an integral part of how business business units, uh how the operational excellence team are using AI to solve business problems rather than uh just sort of AI enabling everything we possibly can, because we've talked about work slop and things like that, right?
00:16:56.240 --> 00:16:58.399
It's just producing more crap faster.
00:16:58.399 --> 00:17:00.799
Which is not helpful.
00:17:00.799 --> 00:17:02.879
Um, so we need to fix the process first.
00:17:02.879 --> 00:17:14.160
So I think AI becomes a really key tool for lean practitioners to understand as part of their solution set, um, and not get carried away with just fixing everything.
00:17:14.640 --> 00:17:15.599
Yes, indeed.
00:17:15.599 --> 00:17:16.640
Indeed.
00:17:16.640 --> 00:17:22.240
And um so we talk about work slop, I guess.
00:17:22.240 --> 00:17:38.240
But you know, thinking about some of that, you know, in terms of perhaps things that ha that you've learned that didn't go as well as you'd hoped they would, are there any particular areas there that you look back on and think, oh, I would definitely approach that differently in the future?
00:17:38.720 --> 00:17:58.799
I think, I mean, for me at the sort of transformation macro level, uh thinking that we could deliver some really big technical transformation programs uh in a in a business that was just combining, like I think we ran too fast at that and we didn't look at the process problems first.
00:17:58.799 --> 00:17:59.279
Right.
00:17:59.279 --> 00:18:22.559
We we ended up falling into the trap that we knew was wrong, uh, of kind of we know we need to do some technology consolidation, so we'll do that, rather than sort of working with the teams a lot more to understand where they are, uh, you know, what what their process landscape looks like now, what it is that they're trying to achieve, what their what their pain points are right now, and kind of working with them a lot more.
00:18:22.559 --> 00:18:31.119
Um it, you know, that there's a sort of complex thing to do with with funding post-mergers that that sort of enabled us to get carried away with ourselves.
00:18:31.119 --> 00:18:41.440
But um I think not having done that well has in a has led us to take a lot more time in implementing those those uh solutions than we should have done.
00:18:42.799 --> 00:18:46.480
And time is an interesting um measure.
00:18:46.480 --> 00:18:51.440
Um I know that, and um you know, I'm sure you've experienced it too.
00:18:51.440 --> 00:18:59.200
There's a lot of um one it'd be like you talked about when the customer says go, I want my first lead and I want to know how quickly I'm gonna get that.
00:18:59.200 --> 00:19:03.200
When somebody says go on a transformation, you know, they want results, don't they?
00:19:03.440 --> 00:19:03.599
Yeah.
00:19:03.839 --> 00:19:15.279
So how have you found managing that expectation, um, particularly at the senior level, around how long this is really gonna take in order to get the right results out?
00:19:15.759 --> 00:19:24.960
I think it's about breaking it down into things where you can be confident that you could deliver uh, you know, part of the solution by a certain date.
00:19:24.960 --> 00:19:31.039
And I have to admit we've got that completely wrong in many cases, and we were way too optimistic about how long this would take.
00:19:31.039 --> 00:19:35.359
Uh so I didn't succeed in that, but um I still currently have a job, so that's good.
00:19:35.359 --> 00:19:35.920
I haven't completed.
00:19:35.920 --> 00:19:40.559
But I think again, it is that transparency again, right?
00:19:40.559 --> 00:19:42.240
Being transparent all along.
00:19:42.240 --> 00:19:54.000
Okay, look, we've just discovered this thing, and that means that it's now going to take us three months longer than we thought, or you know, the the data complexity means that we need to do two months of data cleansing that we didn't anticipate, right?
00:19:54.000 --> 00:20:02.880
I think it's all of that kind of the transparency and proactively managing with senior stakeholders uh is the only way to do it right.
00:20:02.880 --> 00:20:21.680
You uh it's a real mix of um, because we have a mix of waterfall and agile programs, it's really hard to predict, and that is a real conflict, actually, when you've got things that are dependencies, one is being run in an agile way, one is being run in a waterfall way.
00:20:21.680 --> 00:20:26.720
Uh actually managing those two programs is really challenging to do.
00:20:26.720 --> 00:20:31.039
Um, I think the team have done a phenomenal job of doing it as well as we have.
00:20:31.039 --> 00:20:38.400
So I I think, yeah, it is uh being optimistic because if you're not, you won't get the permission to go ahead.
00:20:38.400 --> 00:20:41.839
Uh, and then being realistic when you start to be faced with the challenges.
00:20:42.240 --> 00:20:43.039
Yes, yes.
00:20:43.039 --> 00:20:56.960
And and I like, you know, what you say about you know chunking it up into a set of deliverables along the way so that you can then, as you say, keep that sort of enthusiasm going by reporting success and results.
00:20:57.359 --> 00:20:58.240
Yeah, absolutely.
00:20:58.240 --> 00:21:16.000
And I think I mean having having sort of change in communications within my unit as well makes that really easy because I've got somebody who's always on the lookout for a success story that we can celebrate, um, and kind of doing that on a regular time uh time cadence so that we have have regular comms going out.
00:21:17.279 --> 00:21:32.480
And you know, when you look back on all of this experience that you've had bringing the teams together, the focus on, you know, ensuring that it's done from a problem perspective, prioritization of the problems.
00:21:32.480 --> 00:21:40.960
You know, what do you think is the biggest lessons that you and the team have learned about trying to lead change?
00:21:42.240 --> 00:21:56.640
I think there are uh a number of things that I think we knew we should or should not have done, and we didn't kind of stick to our guns or stick to our guts, as my daughter likes to say, um, on those things and and we should have done, right?
00:21:56.640 --> 00:22:09.279
So I think being ensuring that you are applying the Rigor that you know, like working to the principles, working in a way uh that is going to deliver the best results, even if it feels a bit like there's friction at the beginning.
00:22:09.279 --> 00:22:14.400
Um, one of the big lessons we had was around the maturity of the business itself.
00:22:14.400 --> 00:22:18.319
So bringing together different businesses.
00:22:18.319 --> 00:22:22.640
Uh one is quite a mature business, in fact, kind of quite bureaucratic.
00:22:22.640 --> 00:22:26.160
One was very start-up, um, one was kind of scale up.
00:22:26.160 --> 00:22:31.200
And those businesses at different points have different experiences of transformation and change.
00:22:31.200 --> 00:22:37.759
They have different um sort of informal networks, they have different ways of decision making.
00:22:37.759 --> 00:22:43.599
Uh, so it really tailoring your approach to where the business is.
00:22:43.599 --> 00:22:49.920
Like we talk about this as kind of where we find people where they are and and talk to them in the where where they are.
00:22:49.920 --> 00:22:54.640
But actually, the the business itself has a culture that we need to pay attention to.
00:22:54.640 --> 00:22:57.759
Um, and I think that was a thing that we should have paid more attention to.
00:22:57.759 --> 00:23:01.440
Like we we identified it and then didn't really come up with a plan to solve for it.
00:23:01.440 --> 00:23:03.519
So I think that that's my biggest lesson learned.
00:23:03.519 --> 00:23:05.359
I will make sure I do that properly next time.
00:23:05.599 --> 00:23:14.559
It would be a risk me not to mention your um you've been studying for your master black belt level six um improvement leader.
00:23:14.559 --> 00:23:20.400
I'm interested in that in terms of you know, you're a chief transformation officer.
00:23:20.400 --> 00:23:29.759
So I find it very interesting that there's still opportunity for learning, and that's um and we all know that that that actually that really does help in many ways.
00:23:29.759 --> 00:23:37.519
But is there anything in particular that you have really picked up on that you think has made a difference in your own practice?
00:23:38.000 --> 00:23:46.960
Yeah, I think I mean, uh yes, I I'm I realise I am of a seniority and age actually, that that lifelong learning is part of continuous improvement, right?
00:23:46.960 --> 00:23:52.720
It's really important and I'm really excited that I have the opportunity to be able to learn alongside my role, right?
00:23:52.720 --> 00:23:57.039
That's a it's a big thing for a company to allow, allow me that time and space.
00:23:57.039 --> 00:24:02.400
Um, I think learning, uh I it's it's a while since I did my black belt.
00:24:02.400 --> 00:24:20.480
So I kind of having a refresher and coming back to it, and think as I was just saying about kind of really sticking to what you know and applying that, coming back to learning it again or kind of refreshing on some things has made me more committed to doing things in the right way.
00:24:20.480 --> 00:24:24.960
I think that um has been a really positive experience for me.
00:24:24.960 --> 00:24:36.160
Um, I mean, a lot of the stuff that we talk about early on in the program around kind of change and working with teams and working with senior stakeholders has been super relevant.
00:24:36.160 --> 00:24:43.359
Um, and really I've had loads of work experience examples that I can bring in and lots of on-the-job opportunity.
00:24:43.359 --> 00:24:46.559
Um, the data stuff that we've just been doing, less so, right?
00:24:46.559 --> 00:24:54.480
I because I I have people for that now, and I I've needed to really kind of dig deep to find data that I can analyse myself and kind of work with that.
00:24:54.480 --> 00:25:05.119
But all has been really brilliant to kind of keep me feeling refreshed and like I can apply these tools genuinely to the next new challenge.
00:25:05.839 --> 00:25:06.880
Fantastic.
00:25:06.880 --> 00:25:09.200
Karen, thank you ever so much.
00:25:09.200 --> 00:25:14.799
I really appreciate you joining me for this and for sharing your learnings and being so honest.
00:25:14.799 --> 00:25:29.200
Um, all of this is is just such a key part of, as you say, you know, how we grow as individuals, how we grow within our roles um and how we help organisations improve.
00:25:29.200 --> 00:25:30.559
Uh, so thank you.
00:25:30.559 --> 00:25:30.960
Thank you.
00:25:30.960 --> 00:25:43.039
Um to our listeners, if you've enjoyed this episode, then uh please uh don't forget to subscribe, uh, share the episode with your colleagues, and obviously do leave us a review.
00:25:43.039 --> 00:25:52.319
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00:25:52.319 --> 00:25:58.559
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00:25:58.559 --> 00:26:01.119
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00:26:01.119 --> 00:26:05.519
Until next time, I look forward to seeing you, and thank you again, Karen.
00:26:06.240 --> 00:26:07.200
Thank you.
