Rewriting the Rules: CS Leadership Myths in the Age of AI

[Speaker 1]
We're going to start the session now. So in terms of the session, we're going to cover off CS leaderships and some of the myths we hear now around AI. In terms of the session, it is interactive.

So there is a Q&A section inside the app if you want to go in there and ask any questions during. We'll get them on screen towards the end and try and go through them. So I'll introduce our speakers.

So Dom, I'll start with you.

[Speaker 4]
Hi, Dominique Duquenois, very complicated French name, often called Dom, it's easier to remind. Heading customer success for SSNC Blue Prism. We are an AI, sorry, automation software company acquired by SSNC Group, a financial services group, three years ago.

[Speaker 2]
My name is Laura Linick, based in Germany, and I'm leading customer success for Germany and Switzerland for SIS, 50 years in the software industry, big data analytics company. My name is Christina Fischer.

[Speaker 3]
I'm from SAP, part of our strategy and operations team and responsible for my team for everything regarding the adoption and consumption platform and the program. So we're running a big, big game site installation since we are more than a year in the meanwhile. And AI is definitely a hot topic, as you heard from Alex earlier today.

[Speaker 1]
I'm Liam Gillaran. I'm regional vice president of customer success and solution consulting here. So I think if we go to the first question, which is game site fashion is always an icebreaker.

The question is, what did you want to be when you were a child?

[Speaker 4]
My initial answer was firefighter, and after I thought it was a bit too standard, and in the train this morning, I was thinking about it and archaeologists came up because I was a big fan of Indiana Jones when I was a kid, and after this morning plenary session, it feels a bit too standard to me now.

[Speaker 2]
So as a child, I wanted to work in the hospitality industry because I thought, oh, that is great, working in a hotel and making breakfast and talking to the people and everything like this. And then in school, I made in German, it's called a practicum. And then I liked, yeah, okay, maybe not.

[Speaker 3]
I was always looking after my mom. She was a teacher and I would become a teacher as well. And I also studied mathematics and sports in my former life and ended up at SAP.

A little bit different route in my CV, but nevertheless, everything that I learned there is definitely helpful for my daily life and my job as well.

[Speaker 1]
Nice. I actually wanted to be a firefighter, but now it feels a bit boring after Dom said that was a very normal answer to go with. Cool.

So let's get into the session. I think in terms of some of the questions that we see most, I think the big one that we look at is what have you had to unlearn recently? So from a CS leadership myth unlearned and what have you replaced that with?

So Dom, I'll let you lead on that one.

[Speaker 4]
Yeah. I think the myth of we will adopt AI quickly is something we really worked a lot in the last months. I think that to adopt AI in a scaled way across an organization, you need to, someone this morning was talking about change management.

It's more than change management. You need obviously to manage the change, but also govern the change to make sure it will scale. And what we've observed, and I think we would redo differently, is not only go through the governed route, but help the people to understand what AI will deliver in terms of impact.

And it's a balance in terms of personal productivity and individual initiatives in terms of adopting AI and the governed way where you will be able to scale and deliver impact.

[Speaker 2]
Yeah. So for me, the myth is customer success scales through headcount. And this is not only a myth I came to realize over the last couple of years, but I think it's true since a long term or since a long time.

It's not about the headcount, it's really about the expertise and it's about what the people can bring to the table. And it's about how to scale our business, how to work with our customers in a more, let me say, intelligent way and in a more scalable way. So adding more people to something doesn't necessarily help because most of our customers, they don't want to have yet another QBR and another interaction and another meeting.

What they really want to have is answers to their questions. They want to have results and answers to their questions in the moments that matters. And so I think we need to rethink how we bring the expertise to our customers and how we can scale it internally in our organizations to multiply the knowledge of one person to the knowledge of 100 outcomes for our customers.

[Speaker 1]
You were right in terms of people just want the answer faster now and not have to go around so many different groups of people.

[Speaker 3]
Yes, from an internal perspective, we are serving 2,500 CSMs. We have more people working on post-sales activities so the contribution of all the people across SAP is huge and AI is not solving the problem. So we really need to understand how and who is contributing to the outcomes the customer expects from us. So how we can really change a little bit the AI in regarding to what's the context we need to provide constantly, what is the content we need to provide constantly, as you said, at the moment that matters for the customer.

So how we really can ensure that we have the right point in time, the right information and the right format available. So nothing that is pretty new. But with AI, people expect that it's getting like this, but it's not the way.

So we really need to do a lot of foundational work. We really need to work on data foundation across the company to ensure that we have everything at hand and can really drive the outcomes that matter.

[Speaker 1]
In terms of those questions you're getting from the C-suite, are you getting many questions around using AI retention or is it more around workforce efficiency?

[Speaker 3]
I would say it's everything. So AI should solve all problems we have, driving the KPIs, driving the outcomes, driving headcount efficiency targets. AI is the answer to everything at the moment, but we really need to convince and also manage expectations in a way that AI is not solving everything and not helping in every sense.

It's also not the answer to everything. So we really have a huge initiative at SAP regarding how we can drive AI internally, what are our own tools we can use and give our people at hand, what we're doing with all the technology we have internally and externally available and how can we really use it in a way that it's governed, that it's right because AI also creates, I would say, a different version of the truth. So we really need to find a way to have a framework available that helps but also do the right things.

[Speaker 1]
Tom, what about from your perspective?

[Speaker 4]
I think you were talking about data and I think when it comes to AI and retention it's all about how you explore the data differently and also just to echo what you were saying, AI can give so many different answers to the same question, but sometimes it's going back to the basic AI techniques, machine learning or equivalent and going in deeper data dumps in terms of really exploring this data and making sure to have a 360 view of all the low signals of risk, of expansion, of events or maturity of our customers across their journey.

[Speaker 1]
In terms of how AI is changing the customer success teams and functions that you've got at the moment, how have they adapted to that change and how do they make peace with some of those things that AI is replacing inside their role?

[Speaker 4]
It's easy for them to make peace because I think that bringing AI in the first layer of productivity gains is helping them all the boring activities of a CSM Yeah, boring activities of a CSM of meeting summaries which are key in terms of customer relationships building these relationships on the long term but that's helping them to free their time on boring stuff so they can focus on more strategic activities with our customers.

[Speaker 1]
And are you seeing much from an SAP side of trying to change jobs to be done I guess?

[Speaker 3]
It's the same, everything that we can automate we should automate, everything where we really need to have a human in the loop we should keep because I think at the end of the day the context is always what makes the difference and AI is helping as you said, it's not boring it's maybe repeatable, things where we really have standardised activities always supported by AI, meeting notes signal identification, early risk detection, there's so many things where we really can use AI for what helps and drives a little bit the time sensitive topics a little bit faster than we maybe done in the past where we had to dig manually or we really need to bring data from different systems together so that's definitely a thing where AI can help so we're getting faster but it's not helping in every sense because sometimes a number is just a number and it's just a report but you need to understand what's behind. So I think this is a little bit where we need to get more the sense of what people think and what customers think with all the sentiment analysers we're doing with other signals we're using where we have not just data, also kind of contextual information or anything else to have a better picture regarding the 360 not just numbers, regarding KPI related also what drives the customer what issues, what challenges, we see this in the global world. Every day something new at the moment coming up and AI is helping us to getting these things faster together.

[Speaker 1]
Yeah I think probably it's quite good actually when you think about AI is accelerating a lot those processes and there's a big push from a lot of boards to have more AI embedded in processes inside the organisation. How are you making that judgement call of what stays human and kind of protecting that I guess than just saying hey let's just put an agent on everything which is now

[Speaker 3]
I think it's not an easy answer where you can say hey these are the five activities you can easily move to an agent, really that's a kind of evaluation with the different people, with the different activities, always driven by the outcome we expect and then we really need to understand and analyse where we can see okay this can be really delivered by an agent this can be delivered by a semi-automated agent where we still need people to make the final approval like we have seen in the demo earlier.

So I would say that's not a real guideline at the moment we're evaluating and analysing all processes we have and really checking with the different teams and people there and move what we can automate and we really see we can drive productivity with that.

[Speaker 2]
I think AI is absolutely fantastic in providing answers however it's up to us, to us humans and to leadership to decide okay great answer but did the question matter? So for us it's really like what was the question? So I personally think that one of the biggest misconceptions is that AI will replace human judgement I don't think this will happen and we heard it this morning also in the session so it's brilliant at analysing context and bringing you signals, frameworks and everything but at the end of the day it's the human who will determine what does success look like for our customers, for our teams for our businesses. So let me give you an example from FSI so we are serving large enterprise customers which are complex multi-layered multi-relationship and if I can have only AI signals I get a dashboard which is great, yeah dashboard looks good but the dashboard as to your point it does not give me the context, it doesn't maybe give me the context of the one department my CSMs or I'm working with but what is with the other 15 departments or the other locations so I think the humans still need to be in the loop to provide the judgement because dashboard is green projects looking good engagement scores up but there is a change in sponsorship there is a political discussion ongoing with the leadership team. There are so many signals I only can understand if I have the context and I need to have the context from all the buying departments or users or using departments so for me the human judgement still is relevant and will be.

[Speaker 4]
Human judgement and human decision.

[Speaker 2]
Yes.

[Speaker 4]
You can't replace a human decision at the end of the day. I think it's a question of segmentation so your height of customers you may want to have more tailored human engagements with them but I think the key elements we need to go to is the person we are addressing. We're talking about different business functions but we, our main contacts within our customer base is what we call centre of excellences where we have different type of people from a developer to a head of a programme and depending on these different type of contacts you want to engage in a different way you want to also to develop different type of activities if you want to develop workshops with your head of programmes which are your key economic buyers at the end of the renewal cycle you would need to have these human interactions and decision making. Yes.

[Speaker 1]
I guess the roles and head count and team structures how are you seeing as AI does take over some more of those jobs with inside the role how are you being challenged or what do you see that role look like and role changes now you're embedding more AI in the business.

[Speaker 4]
Your shop was talking about soft skills at the end of your session this morning and I think that that's a key one to do well just to continue on my last comment the CSMs will be more pushed to have strategic engagements with more senior stakeholders within organisations they need to be prepared to that we need to train them to coach them and that's a lot about soft skills and that's the key element we are currently working on already.

[Speaker 1]
And what are you seeing in SAP what's the structure look like?

[Speaker 3]
At the end of the day it's the same we really need to drive more human skills in our organisation to focus at the moment really what is really the knowledge and the skills people need to really make the difference and drive the conversation with the customer to really focus the outcomes what is really beneficial for the customers in the conversation not just showing some numbers we're always driving QBRs where we're really trying to put the right context and content together but what is really important that the person understands what are the conversations should be about what are the questions you need to ask so this is something you cannot learn just really listening to an AI agent or have a kind of AI driven training out there so you really need to get an understanding of the situation you're really trained and you're getting conversation, communication so I think that's getting much more important in the future because talking to an agent we all see this on a daily basis when you have an issue with one of the global platforms buying something the first 10 messages are always an agent and then you need to type in some buzzwords and then get a real human into it this is how it works as of today you're trained to these things this is exactly what it needs to be to get an understanding what makes the difference and what is the value you need to provide as a company like SAP

[Speaker 2]
To comment on both your points it's also if we're thinking of the evolving being customer success manager over the last couple of years I hate to say this word but it was like the happiness department when I was starting it was in this job then we moved into relationship and now all of a sudden okay now you need to be strategic for say what do you mean with strategic, what is strategic how can you learn to be strategic you need to have enablement us as leadership team and the companies need to have a program enablement programs to really help CSM's having these conversations to your point AI can provide the information and the talking points and the facts and figures but how you translate and transform this into having the strategic conversation with your customers is a completely different story similar to oh you have a revenue number okay now you need to be more commercial what is more commercial meaning who of our CSM's can have a conversation with a CFO or are unable to have that and can provide the business so the role is shifting and I like the shift because as you say the leg work the more boring work this is can be done and facilitated by the AI agents so that we can have more time to train our teams and enable our teams to have the meaningful and the value conversations

[Speaker 4]
sorry just to add on training and I would add continuous training and adapt prepare the team for continuous change yes because what we see also is where technology is evolving everything is evolving and you need to be facing this continuous change on a day to day also and that's a new mindset also we need to enable our teams

[Speaker 1]
yeah I think I mean that's a really good topic to go into Tom I think thinking about new ways of working change slightly different changes to role like you said strategic or commercial how are you leading the people on the ground through that change right now so it's

[Speaker 4]
well first of all not be afraid of failing I think everyone can experiment as an individual team member and that's I would tend to say the easy part the most complicated one is aligning the team in terms of practices because you want obviously to innovate fast and fail fast if it doesn't work on an individual level but if it's a success you want to scale it and for that you need to have to put in place a really strong team collaboration because you as a leader you will not be enough to enable and coach your team it's a team effort at the end of the day for me

[Speaker 1]
what enablement kind of changes working for you

[Speaker 2]
so I have to say the hardest part is not learning the new technology or learning to work with the AI agents for me that's I say for the team it's easy it's new technology okay you get it that's fine the processes but for the CSMs and for the teams I think what we need to work on in the future is redefining their value because AI is changing the way how CSMs are working and can work and it also has to deal with the human factor as in how they identify themselves so in most professions the role and the people are defined on I know something I'm an expert in a specific area but AI is changing that fundamentally so knowledge and expertise is becoming let me say a commodity so what we need to do is to really help the CSM to not giving up you all know fear of missing out and I would like to introduce fear of being irrelevant and this is happening to a lot of our customer success managers because they are asking wait it is a threat so they are asking okay if I can do this will I be replaced will I become irrelevant and this is so not true what is happening and this is something we need to help and we need to shift the conversation from what task can AI do towards now that AI is available and is helping me with all the information and facts what can I do with this what can I do with my free time what kind of meaningful work can I do right now and I think that is the fundamental change we are in as an industry.

[Speaker 3]
And I think in addition it changes also the management skills you need for this so you need to be more coach you need to drive them to get a kind of picture what is their individual USP internally externally how they really can shape their profile what are the benefits they can bring to the table to the conversation and also when I'm leading a global team spread across the world so you really need to have a different communication a different conversation you always need to ask them questions what is the benefit what is your contribution what is the outcome you are looking for and this implies in a way that you need to ask different kind of questions you need to get an understanding of the vision you need so leadership was on the business side to help you to go that route and also I think what's at the moment a little bit tricky because we don't have a clear target so we have a vision we have an idea we don't know how the work looks like in two weeks four weeks six months I don't know so we need to work with assumptions we need to really get an idea does this stuff have the right path and people ask me always why make this decision left or right I say I have an intuition this could be right and I think if we can provide value if we can provide something what helps the people on the ground on a daily basis then we have done a good job and this is the question I'm asking myself every day and this is what I also give to my team members they need to ask the same questions themselves every day

[Speaker 1]
I think when you think about two years ago the things we're doing now with agents are we weren't in our mind in terms of what we could do I think it's going so quickly I guess what decisions have you has changed for you as a manager now of individuals are you thinking about either buying new software or building it in house or even just how you go to hire the talent within the team how has that changed

[Speaker 3]
that's a good question when I receive a CV I'm looking mostly if the person has analytical skills because this gives the kind of signal that they can understand and have a kind of idea how things are coming together so and technology it's given it's changing so fast I need to make decisions for MCPs and stuff like that I haven't thought before I don't know beginning of the year so things are changing for us as well but I think what's really important is to get an understanding can people solve a problem can really a person understand what is maybe the reason why this is happening like this so this is where you need to think a little bit more what are the human skills and for sure what are maybe some kind of professional skills as well but I think at the moment they're not that important because we don't have that silos as you said it's also evolving so what is a CSM as of today?

It's a strategic partner for post sales or we say post closing activities because we are running a huge services organisation as well they also have a contribution on post closing so we have enterprise architects they're helping our customers solution architect putting together so it's not a classical CSM task they're doing. There's so many skills needed to really understand the complexity of our customer and we need to help them and this is also where we need maybe different skills in the future to understand how you can coach also the customers in the best way.

[Speaker 2]
To your point and I come into this again it's like hiring for expertise really for domain expertise specifically when you're in Europe in FSI so bank in France runs on completely different laws like a bank in Germany or in Switzerland so it's completely different so you also need to have this domain expertise AI can again provide you with the fundamental knowledge and information about this but you need to have someone who can hold a conversation with your customer ideally in the same language.

[Speaker 4]
And in the same culture.

[Speaker 2]
And in the same culture.

[Speaker 4]
I would add because I think to take your example France, Germany, Spain there's so different cultures you need to be able to adapt. I'm not saying you need to buy to recruit someone in Germany someone in France, someone in Spain but someone adaptable to these cultures that's key and the terms of adaptability I think is a key one and also adaptability to the team that will join. I think that when you, it's more and more important to make sure that the persons you are adding to a team will adapt and integrate to the team because we are creating this human workforce.

Yes.

[Speaker 1]
In terms of when you think about the hiring sides obviously you're changing the skill set you're looking for. You mentioned around curiosity and analytic skills. When you're trying to solve a problem inside the business how has that changed in terms of now you've got the ability to build your own first.

Is that the approach you go or is it hey we'll look and see what our vendors that are already existing have in place before we go to buy. Has that changed much in two years for you?

[Speaker 4]
I would tend to say that we go and look at our vendors because especially in the CS space on the Gain side you have the domain expertise around CS. We are also building agents for our own customers so we look at this and we have a program in terms of customer zero and we look at this also for our customers in terms of agents so we go to build in a second step but the first one is not only looking at the technology our vendors, our partners can provide but the expertise, the experience they have in implementing, scaling the technology.

[Speaker 1]
Perfect. I think the last one that I've got on the list for you guys is probably more of an honest of what do you wish you know now around AI and the changes that you would have loved to know when you started in this field?

[Speaker 4]
Not put AI everywhere. I think that's an obvious one. I think that first we talked a lot about human in this conversation.

I think that leaving the human in the center of the relationships is key but also looking, having a clearer view in terms of where AI can deliver impact. That's something key.

[Speaker 2]
Completely agree. A couple of years ago, oh we need to be AI. We need to be AI driven, AI everywhere but few people really understood at that point in time what does it mean and what do we actually want to achieve with AI.

If you build an AI tool or work with an AI tool, have the outcome in mind. What is the result? What do you want to achieve with AI?

Also for a couple of customers and companies, it's like okay, everybody gets a license. 500 people are doing exactly the same thing. Is it scalable?

No. Maybe I'm not saying be prescriptive but be a bit more outcome driven. What you want to achieve and that has to do with what is the AI strategy for your own company and how do you think it will evolve in your company that you can make it workable for your customers or on behalf of your customers or in favor of your customers.

Not do AI just to do AI and put it on a paper.

[Speaker 3]
To add to this, the people around us expect that AI is happening immediately. To get really value out of AI, you need to do so many things first. You need to check the data.

You need to check the processes. You need to check the governance. At SAP you can imagine we have data security, workers council, all the fun stuff.

It's not that easy. It just can turn on AI and it's working. Then also to manage the expectation on the other side that AI is super cool and everybody can do something, but we identify unfortunately a lot of things that are not allowed and data are not right and we need to really shut things down.

It also creates frustration as well. I would say when we look back at the last six months, be patient. I think this is something and AI, it's cool, but the way to really be AI ready for everything takes so many steps and I have an analytical background.

We have done with projection, predictive, prescriptive, machine learning. All needs to be done that we really can enable AI completely and this is what people sometimes forget.

[Speaker 1]
Yeah, I definitely think like you said earlier, having all of the context available when you're going through it is super important. So getting that data layer right, the connected systems, otherwise you're just creating more chaos inside the organisation. I think the one thing my CFO definitely would have liked to know from the start is probably how much token spend goes up.

[Speaker 3]
We have.

[Speaker 1]
That's been the shocker that's got everyone out this last, at least last 18 months, is token spend. In terms of the main question you want to run through, I think it'd be great if anyone wants to go to Q&A. We can go into the app and you can add in there and Georgia, take over some Q&A for me.

[Speaker 5]
All right. I might look at the screen and look at you at the same time. I think we do have a few questions via the app.

I might just prioritise that. And if you think that question is interesting, please upvote so we're going to address it first. If you don't know in the app, if you go on the homepage and you scroll down, there are all the tracks in bubbles and that's where Q&A is and you can plug your questions or upvote questions there.

Right. First one for our panellists. Can you give us one concrete example of an initiative or an action, even a small one, which helped your organisation leveraging AI better?

[Speaker 3]
Turn on our own AI application where we can easily add skills and connections and to be able in a governed environment to pull out I would say a lot of insights and activities and also we are exploring how we can use this in the game side environment to really get more CS related activities in and out of our platform.

[Speaker 2]
I can give a quite boring example but it's so powerful AI as in meeting summaries or enterprise account summaries. So I asked my CSMs and my team, okay, I want to run a QBR with you on your accounts and we leveraged AI to facilitate this conversation and we recorded this conversation and we facilitated AI again to turn this conversation into a blueprint we could also use for the broader account team, for the sales team to really help them understand where are we at the moment and then I challenged them to put it into a success plan.

So there are various options and possibilities how you can do the mundane work via easy things like meeting summaries or note summaries.

[Speaker 4]
I totally agree with you and that's what we have done but making sure all our CS teams have their own AI features for personal productivity enabled is a very quick decision to have, makes you the impact is really on the CSM so they can adopt the technology and as you were saying in the second phase you are able to use this technology again to make sure that you are creating playbooks.

[Speaker 1]
I think the one around small examples, there are some ones that actually make the biggest difference, especially to a CSM doing the visual role, I think EBRs can take a long time to put together, some of that is you've got to read data and tell a story from the data, you've got to be good at formatting your presentations and meet your company guidelines and they're all things that could make something take a couple of days before you go into that session.

I think just small things about enablement and things like sharing all of these skills that we produce for our customers out there in the marketplace but cutting down those EBRs from a couple of days to a day or half a day is a massive impact on the workload of that CSM because while they're prepping for that EBR the other work doesn't go away so how do we make sure we maximise that time so those small quick wins are the things that we're seeing have a massive impact.

[Speaker 5]
Alright, there's a very upvoted question which I find very interesting. In one word in this new AI world what's the number one skill a CSM should have?

[Speaker 2]
Curiosity. Definitely.

[Speaker 4]
Can I add a second one? Sorry, empathy. Awesome.

[Speaker 6]
Alright.

[Speaker 5]
For the leaders in the room who are just starting this shift and this new AI world where would you tell them to begin? I think we heard some before. I think Laura you said like just get a framework in the company on how AI works and drive by objectives, right?

[Speaker 2]
So as a new leader it really depends it depends on your book of business it depends on the segment, it depends where you are but first of all, all the time what I would do and AI wouldn't work without the data foundation so if you're, I'm sorry but if your data is crap, the outcome is crap. The best AI tool cannot help and similar if you have a book of business make sure that you have all the necessary data that you have access, as a leader it is so crucial that you understand your customer's book of business or the book of business from your CSMs are the risks there? Are the patterns there?

Do you understand where the customer, what is the customer objective? Do you have all the basics the basic foundation? Once this is done you can get creative, okay what are my objectives and what are my company objectives?

This year, next year, long term strategy where do I want to grow? What do I need to drive? And based on that you build your strategy for your book of business.

[Speaker 3]
And take maybe simple things at the beginning don't really try to boil the ocean, quick wins really, look at what are repeatable tasks you need to do everyday what is maybe you need to have meeting summaries for example or filling input for EBR documents, QBR documents pretty simple things where you can easily show the value and also the data already available so where we need to define a complex infrastructure get data from different systems then it takes too long that people understand wow AI is helping me on a daily basis so really focus on the simple things look at what you can automate what people are doing everyday, every week, whatever and help them and really be smart

[Speaker 1]
I think the two that I would add from my perspective is firstly the curiosity piece don't just take the answer it's not stupid, don't take the answer back ask a follow up so you can double check that you've got it right and that you're not going to go and say something and get it wrong I think that's when you're starting out in this and then the second piece is as a leader don't assume everyone is at the same level of competency or knowledge or education around AI because they won't be in your team so do a foundational level of enablement of like AI and how to start using it because if people are more fearful they don't really understand, that will be a barrier to get them to start using it sometimes as soon as you start that ball rolling, you start to see them going for it but the barrier can just be the fear of I don't know where to start I don't know what task to do there first so try and bring that to a baseline level for the organisation is critical

[Speaker 4]
I think it comes back to the quick wins I think it's operationalise your strategy and making sure that you show what you are delivering and go step by step, I think that's the key one

[Speaker 5]
You're leading into our next question We've discussed a lot about internal synchronicity and enabling the CS org but how are you measuring the customer experience of increasing adoption of AI agents outside of the classic lagging indicators of GRR and NRR

[Speaker 4]
You can measure token consumption to come back to your point If I was ever happy with that but I think it's more a question of making sure you identify with your customers what are the outcomes they want to drive with that AI and you are able to measure against them where they are in their journey to achieve these outcomes

[Speaker 3]
If you look internally you need to define this first and regarding building an NIH and then thinking about what I want to achieve, what I want to measure it's not the right way, so really think about first what you want to change and what are the KPIs you can look into it and really seeing something is improving because I think that's one of the biggest failures we see as well, that our AI should be built but nobody knows what it should be helpful

[Speaker 1]
I think on that one as well thinking about some of the metrics obviously you have very new metrics just in terms of are my teams finding things easier to do like ENPS is a really good one if you've got a large book of business and you ask them to do EBRs and actually they are time consuming and tough if you start to improve that and make that more efficient you'll start to see things like ENPS increase across the team and obviously that should also feed back into your external satisfaction programs as well so a really easy one I know we've mentioned EBRs but it's a great way of being able to help put a new process in place with AI help that generate some of the content some of the stories, some of the actual content for those meetings and then actually get that feedback as a leader post an EBR just to get the temperature check based on these new ways of working it's really fast feedback I think as we mentioned failing fast is really important so getting that feedback immediately after you know you've just changed the process either internally or externally allows you to quickly do it without it being too big

[Speaker 2]
and also I mean we're in a completely new era and it might be also the case, and I'm just asking does the old success metrics still work in the new area of AI, so is NPS very controversial I know, is NPS still working or is CSAT still working in the context of AI, in the context of how I work with my customers and I think we as leaders should be empowered to also say okay, in my book of business, in my company we have different metrics or we have additional metrics on how we use, sorry, on how we measure success, and success comes in different formats, it can be the amount of use cases it can be the amount of use cases applied to other customers and to other industries, it can be so many different things, it can be not only you might know this, reference leads converted but how many times did this customer speak at a conference with whom and why and what does it move, AI can now measure this, so this is a different measurement than a static lagging indicator it is forward looking, so you actually can already try to project into the future with the measures you're pulling in right now.

[Speaker 4]
To say it differently, it's not only financial indicators or...

[Speaker 6]
Say it differently.

[Speaker 4]
But it's coming back to the engagements what are the new dimensions in terms of engagements you were talking about advocacy in other words, I think it's important to really invest on advocacy more and more because that's where you see that your customers are investing on you and that's a lagging indicator in some way.

[Speaker 2]
Don't get me start talking on customer advocacy.

[Speaker 5]
Come and find them afterwards they have a lot to say on this There's one for you, Liam. Since you're responsible for both solution consulting and CS, where do you see the value in having both teams interacting?

[Speaker 1]
Yeah, I think for me, there's a couple... Both inward and outward. So outward from a customer perspective, when I go to a meeting and they've got one person they can look at and say, okay the sales team and the pre-sales team are going out there and explaining the outcomes of what your software should deliver, and I ultimately own the delivery of that with the post-sales teams as well.

It can put a lot more confidence in the client that they're buying it because it's not a handout that was a pre-sale motion and we were promised things and then we didn't get that delivered in the post-sale motion because ultimately I'm responsible for all of that. That gives clients a lot of confidence when you go into it. It also creates a lot of accountability between the solution consulting team and the CS team.

They're actually one broader team. It's not a case of we need to do anything to win a deal, it's we need to make sure we win the right deals that we can make successful and that my colleague in my same team is going to be successful at delivering. That's a really good place to be.

As you think about going through the actual life cycle of applying for an award, you can really start to blend that onboarding experience with the right team members that are coming in. For example, it's not a case of sales have sold something, pre-sales are finished, onboarding team come in, then CS team come in later and it's kind of fragmented and all of that data and context gets lost in each of those handover points. The benefit is actually your pre-sales person can stay longer in the sales cycle because we're not measuring them just on going out and doing a business.

Your CSM can come in earlier than they would naturally normally start. It creates that really seamless, almost like handover of the pattern in a relay team between those two professionals. On the other end of the scale, when it comes to things like renewals, solution consultants have a different kind of mindset and technical background of the products and the different products.

Gainesville's got five different product clients so they can go into a lot of depth, which I wouldn't expect the CSM to naturally get into that same level of depth. Sometimes clients just need, in an earlier to a renewal, is actually a refresher. What are the new and exciting things that have come out that I might not be taking advantage of now?

A solution consultant can come and paint that story slightly differently to a CSM who's had an established relationship for a long time with a client, knows the ups and downs they might have gone through during that period of time. It's a nice way of bringing a new voice. Sometimes it's that whole thing of same message, different voice actually land differently.

Actually being able to blend them all together without someone turning around to you and saying, well, is there an upsell? Not at all. If there's no upsell, you're not getting an SE resource.

We're all working towards the same goal of GRR to the point where I actually put GRR in the pre-sales team's comp plan. They aren't just on new business deals and ARR. They're actually compensated on GRR as well.

[Speaker 6]
I'm going to change the word comp plan.

[Speaker 5]
That's a whole different section. It's here. It's coming.

I think we have just a couple of more minutes. Let's maybe take this and see how long it takes us. For decades, we looked at the CS ratios of ARR per CSMs. AI breaks that ratio. If coverage is no longer the constraint, what replaces it when you're presenting internally in the board deck and so on, NRR, expansion per head, something else. We're looking for any sort of examples or ideas that have been looked after for a CSM comp plan with the new AI component.

[Speaker 1]
One of the ones you mentioned earlier is average revenue per employee. That's getting more and more important in terms of getting obviously as high as possible with traditional models of how we have CSM ratios. How much time do we have in terms of hours?

What are the jobs to be done? How long do we expect those jobs to be done? Roughly the amount of accounts that CSM can manage.

That's how we used to break it down. Without AI replacing that, I'm definitely seeing a lot more shift in terms of revenue management. We need to target X million of revenue per CSM and the AI is there to help them manage that level.

It's less about the volume, it's about the actual value of the book of business they're seeing. I think the other side is CSMs are getting pushed more commercially. NRR is not something you're doing already.

It's going to be something that's going to be more in the CSM field. We're seeing more CS teams moving to cheaper revenue offices for a shift in reason. It kind of breaks that whole, it's a cost centre type approach that still gets bloated out there.

I expect to see more of that NRR in there. That can be really simple. I work for a lot of different organisations where actually licence up sales can go to account managers quite easily.

It's like, hey, the CSM's doing a really good job, now they want to buy more seats and then the account team's getting compensated on those increasing in licences. Actually, in my world, that's where the CSM should start to get a comp on them. It's like, they're driving the adoption, they're driving the value.

The reason why we're selling more seats is because the CSM has done such a good job, so let's make that compensation fairer than just the normal CSQL. If this is a whole, we're selling into a different business unit or we're selling an additional product that they don't have already, then that's where I think it goes back into the normal traditional selling. I think renewal and light expansions are going to come more and more in the CS space, and they should be rewarding comps in the same way.

[Speaker 5]
Any last take from any of you? Well, we can give one last round of applause for our panellists. Thank you so much.

Thank you.