Iver Van de Zand 0:00:07.9:

Okey-dokey, good morning. This is Leigh Romeo, and my name is Iver Van de Zand welcoming you on an update where we are with platform and product. Leigh, my colleague, is talking you through the storyline that we have with AI, where we invest, where the big ticket items are. I'm going to cover a few other topics. My name is Iver Van de Zand. I joined not too long ago, six months. I'm the former CTO of SAP, also owned their planning products, so I know that area quite a bit. For Leigh and myself it's important to share with you where we are on product. If you follow Anaplan a little bit, if you read our messages and what have you, you cannot have missed the big announcement for an additional 500M$ million that we invest in product, so which little remind, that 500M$ is on top of the product budget that we have anyway. I think you can have a long debate about 500M$, but what it says is that the company is ridiculously serious in the product and scaling it up. You heard Adam Thier this morning, you heard Charlie, where we are with the product. Leigh and I are going to dive a little bit further in detail.

Iver Van de Zand 0:01:38.3:

If you look at the 500M$, and if you look at [?Ivo's 0:01:41.5] here as well, leading product, if you look where we place our cards with the 50M$ million, it's on four areas. We bet on four big areas. I'm going to call them out for you. Before I go there, one thing that you hopefully picked up this morning is that leading with application is a big ticket item. That is why you see it coming back in investment areas. Now before we talk the investment areas, I always think it's a good moment to just put a stick in the ground and look at what we delivered last year. I could use a zillion slides, I just took a few elements over here. If you look at what we delivered last year with product, pretty massive. Yes? Polaris is there, it's starting to get quite massively adopted, with over 80, 85 customers running it already today. We have Workflow over here. Do not underestimate Workflow. It is super-essential, Workflow. If you want to design for performance, Workflow guides you through that design. It's a very powerful element that is there. Geospatial is there. We have over 100K downloads, allows you to put your planning analysis from a geospatial perspective.

Iver Van de Zand 0:03:01.9:

I called out just two applications, just two. We launched more, but I just called out two, Territory and Quota, and Supply Chain, two very significant applications that have massive impact and super-successful. Of course, they're CIO essentials. CIO essentials is all our investments in the background: governance, access controls, what have you. Now coming back to where I started talking about the core investment areas, if I look where do we place the cards? That's what we need to remind, it is in four areas. Four. Yes? I'm going to talk you through in random order. Number one is leading with applications. You heard what Charlie said, you heard what Adam said, we already have been vocal on it. We are going to lead with applications, end of the line, discussion closed. Very important. It means from a product perspective, we massively bet on that one. Second one, natural dimensionality. I told you I'm ex-SAP. What is unique to our applications is that we, in one application, one, every type of planning, whether it's on a higher grain - financial planning, business planning. Whether it is on a way granular level - demand planning, supply chain planning. Whether it is somewhere in the middle - workforce planning. They all come together in one application. I don't have separate applications that I need to do together, like the competition. I have one. We want to strengthen that bat. We are massively increasing our investments in the Polaris and likes. I will talk you through.

Iver Van de Zand 0:04:45.3:

Number three, any planning project, whether you do it with Anaplan or another technology, any planning project, 65 per cent of your work is in data preparation. Check it yourself. I'm 100 per cent sure, it is above 60 per cent, 65 per cent that you put in the effort to prepare data, wrangle it, transform it, whatever, before you bring it into your application. We launched Data Orchestrator, and we will accelerate on that. On the last topic I don't say too much. If you listen to Leigh in a second, if you see where he is going with Anaplan Intelligence, you're going to be amazed. Let's start and let's talk through. I'm going to start with applications. I already told you a few things. Leading with applications, why are applications so interesting? Prebuilt everything. It is not just prebuilt content, models are there, connectors are there, content is there, Workflow is there, configurator is there, we put us there, the dashboard is there - everything is there. Super, super-powerful. You heard Charlie, we have ten today. We are investing in another, and we are going to end up with another 16 at the end of the year.

Iver Van de Zand 0:06:05.9:

Over here, I summarized a little bit why applications are so impactful. Is any application that we deliver going to cover 100 per cent of your needs? No. It is not. It is mostly likely going to cover 80 per cent of your needs. If I, on the contrary, put against that that you roll out an application in weeks - listen to what I say, weeks. Ivo and I and Leigh, we have a very long history in planning applications. I'm used to planning applications in the past that were rolled out multiple months, maybe even a year. We are rolling out in weeks with this technology. I don't need to fill in the lines for you what that means on time to value. You know yourself. The applications, the storyline that Adam told - and I'm going to repeat that a little bit because it's so important - is quite impressive. If you look at regular use cases, normally these can easily span four or five years. If you, like we are going to do, are going to put one code base below it, it means that we very soon - listen carefully to what I say - that we very soon are going to ship all our applications the moment you start utilizing Anaplan. So the moment you start using Anaplan, you get automatically all the applications. They are there. They are just there. You can do a sneak peak, you can play around with them, and you just decide, point and click, whether you want to utilize them. Whether you want to activate them. That is a massive change not happening in the market so far.

Iver Van de Zand 0:08:03.1:

The story is not done because we are going to make it stronger with an application framework, allowing all our partners, they are here today, building their applications and adding those to that. All glued together. The next step is, of course, that you can add your personal custom use cases that, for whatever reason, don't fit in one of the prebuilt applications we have, you can add them to that. All the applications - you saw it on one of the slides - are upgradable and customizable. Pretty unique. Customizable means that you decide, with the central configurator, my pulling dimension needs to be a hierarchy level of eight depth. You activate it over there. At the same time, when Leigh and I or Ivo and I are updating Polaris with new technology, it automatically comes into your application. Have a look at this.

Video plays 0:09:07.8:

Iver Van de Zand 0:09:16.1:

So what you see in the video is the way that we communicate with an application, updating dimensionality and [?IOR 0:09:23.1] keys. It is that simple, like it works over here. One central place for you to master and monitor all your dimensions, even across applications, through the configurator. That is very powerful and unique. I'm going to skip the video, I'm going to move on to respect the time a little bit. If you look at the portfolio that we have today, there are ten applications. You see them on the screen. These are the ten that we have ready to plan for the moment. We are going to very soon launch an additional 5, and by the end of the year, we're going to close down with 26 applications in total. Next year wouldn't surprise me that we have double that. The message I leave with you is we lead with applications. Going to be a very big and important theme. Remember, we had four investment areas. I talked about connected applications.

Iver Van de Zand 0:10:30.6:

The second one is - something went wrong with the clicker - second one is natural dimensionality. I already mentioned we have extremely powerful calculation engines. That calculation engine is so powerful for a reason. What it can do, it can cover any planning use case. If I want to do financial planning, or I want to combine that, or let that drive, for example, demand planning or supply chain planning, complete all the data [unclear word 0:11:06.3], we can do it in one application. We can have the insights end to end, one application. We can do AI through the whole line. Unique, very powerful. That is why we also want to further double-down on that. The decision taken within Anaplan, when it comes, for example, to applications, is that every application that we newly develop, as of now, is mandatory on Polaris, is mandatory on ADO. Polaris and ADO will be everywhere. I think that is a very powerful statement. Also if you look into Polaris, I can talk a week about Polaris and all the cool and powerful things that are in there. If you see that that application can do half a quadrillion cell and still responds within a matter of seconds, that is ridiculous. Ridiculously powerful.

Iver Van de Zand 0:12:03.9:

I have a data warehouse background. For me, the [?white 0:12:06.3] number is even more powerful. I don't know if the data warehouse designers over here, but ever try to model a dimension that can run half a million numbers? It is really impressive. That is what we can do with Polaris. That is what's happening. These numbers come from a customer. That is what's happening day in, day out. Now moving forwards, if you look at the evolution of Polaris a little bit, we even launched recently the on-demand calc functionality. We signed up, I just called out a number of quite impactful customers, you see them over here. We are super-successful with Polaris. On the next slide I made a comparison. We did a test. If we develop, if we apply a supply chain application in both Classic and on Polaris, and compare that, look at the difference, look at the difference in model size. Even when the number of products and the number of customers was way higher in Polaris, the size of the model is just a fraction of what it is in Classic. That makes it so powerful. Also the way that we move from Classic to Polaris, if you will be interested utilizing that, it's pretty strong.

Iver Van de Zand 0:13:30.3:

Now recently, I don't know if you follow me on LinkedIn or you'll have a little bit on the messages, what we've also done as a product organization, we provided even more clarity to you by launching a statement of direction. What that statement of direction says is that the innovations, as of now, that we develop for the calculation engines are done in Polaris. Does that mean if you're using Classic you're in trouble? No, you're not in trouble. Innovations though we start developing permanently in Polaris. We are very happy to guide you, if you will be interested, to help you moving to Polaris. Now looking in a bit more detail, it's a touch techy, but if you look where we roadmap-wise invest in Polaris, I'm not going to call out all the lines, but there's loads of additional functionality constantly flowing into the product. Very interesting, I really like that is that we are going to bring in performance monitoring in the product very soon. Very cool. You can exactly see what's happening where, you know the performance of the interactive modeling and what have you. We are working on a number of UX-related features that were massively asked by you. This is high level, the things, the themes that we have on the short-term for Polaris. Yes, we are working also helping you with even better clarity when it comes to migrating from Classic to Polaris.

Iver Van de Zand 0:15:08.4:

Out of the four, we talked about planning applications. We talked about natural dimensionality. The third area of investment is data orchestration. Again, I repeat, 65 per cent - listen to me - 65 per cent of the work of any planning application is done in data prep. Why not think a little bit on can we make progress over there? Yes, we can. Ever studied the performance of companies like Service Now and Salesforce? If you really look at their history, how they moved up, have you seen where their acceleration came? I did. It came exactly when they brought data orchestration into their portfolio. We are also going there. I already mentioned, repeating one more time, is that ADO is going to be the de facto standout in applications as well. If you look where ADO plays, this is a high-level, logical architecture on how Anaplan fits in a planning set-up. If you look at the orange-colored font types, that is where data orchestration plays. Finding the data I want to connect to, connecting to that, blending the data, joining it, transforming it, wrangling it, that it's exactly in the form that you want - and then now it comes, the magic word, pushing - pushing it into your models or even into a data lake. That is where data orchestration plays.

Iver Van de Zand 0:16:51.9:

The technology that we already had for a long while is DataHub, which in itself, a DataHub is basically a model that can create that connection. Data orchestration is the next level model to simplify your end-to-end data sweeps. What is unique to it is that if you work with Data Orchestrator, which is a point-and-click solution, so you don't script, it's widgets that you glue together, is that you have full transparency in the full data flow. It also requires way less of technical knowledge and resources to build something. So I built my data pipelines quicker, better, with more insight. Fully transparent. Do you know what data lineage is? You all know that? Very quickly, data lineage, I have a planning application of 15 data sources, and I have 45 models. One table in one data source breaks. How do I quickly know what model is affected, what reports are used by that model, and what users I need to send an email that the data is not correct? That insight we call data lineage. That is what Data Orchestrator provides. That is why we go from - one moment, it's a bit sensitive to - let me see, where are we? So we go from DataHub, which looks like that, which is a point-to-point solution, to an orchestrated solution with Data Orchestrator. Repeat it for you, we go from DataHub, that looks like this, and works perfect, but complex, requires a lot of knowledge, to this, fully transparent, with impact analysis. That is Data Orchestrator.

Iver Van de Zand 0:19:03.8:

So Data Orchestrator does a little bit more. You probably heard and have seen that we also have consolidation technology available in the product. We even have integrated that. Guess how we did that integration. We are doing that with ADO. You see on top what we can do currently today already is that when you use consolidation, you want to integrate that to provide one-stop shop for your CFO, with planning, with consolidation, with everything. We can have ADO pick up the data of consolidation, wrangle it, and through a Workflow we bring it back to the consolidation area. So massive progress made over there. I already touched most of the elements why I think your attention should be with Data Orchestrator. It's about lowering the cost. Things are way quicker too, and way easier, with less resources to develop. The qualitative element, the full transparency is over there, but most important, you develop your data pipeline way quicker. Don't underestimate 65 per cent of your time is in Data Orchestrator.

Iver Van de Zand 0:20:19.9:

If you look where we invest in the product, that is here. The key elements that we have in the short term, if you look to the next two, three months, what is on my agenda, what is in my emails? We are even [?bettering 0:20:31.9] the performance of the product. It's already super-strong, we're even bettering it. We're working write back, so we're going to enable you to write back your data [unclear words 0:20:43.2] S3, and we're also bettering the authentication times. A very interesting one is that we are going to bring data spaces to ADO. That's super-cool. I can have my development environment. I can have my testing environment. Production. You build in an automatic life cycle management. I brought a video to show you Data Orchestrator. I quickly am going to show you that, to just give you an idea. What you see behind me is Data Orchestrator, and I told you the way that you work in Data Orchestrator is that you, one, connect to data, you see that happening on the screen. I can connect to data in three ways. There's a whole list of prebuilt connectors, and the connectors that we have is the typically [unclear word 0:21:39.8] ones the most commonly used, Salesforce, Workday, what have you. Is it starting early? No. There you go. We can connect to models. We can connect to CSV files.

Iver Van de Zand 0:21:56.8:

The moment you connect to data you bring it in, the data physically comes into Data Orchestrator, and over there we go into a next step where we go into a transformation view, which allows you to wrangle the data. I can join multiple data sources together. I can schedule them. I can use widgets to aggregate the data. I can use widgets to split/connect columns. I can add formulas. You see a little bit happening on the screen today. Quite interesting, on the right-hand side of the screen is that whatever I do, the full literacy is there. I always know what I build. What are the details? Where's the data coming from? That transparency we maintain, we carry with us through the whole cycle. Over here you see the transformation element where I can start working with prebuilt transformation widgets. You just crack and open them on the screen, and this is how you gradually build up. At a certain moment when I have my transformations ready, ADO's unique that it's made to populate models. I can directly, in parallel, populate all my hierarchies. I can directly, in parallel, populate all my lists, or even my models. I just wanted to give you a glimpse on where we are with Data Orchestrator, and I encourage you to follow us. Data Orchestrator is very massive. We are super-successful with it.

Iver Van de Zand 0:23:28.6:

I'm going to close now with a last message, which I hope you like as well. I'm going to come back a little bit on the start-up of the applications. You probably remember that in the start of my talk I talked about all the applications that we manage [?well 0:23:46.4]. If you look at, imagine that you use multiple applications, like I indicate on the screen, you could imagine that some of those applications have commonly-used dimensionality. Your product set or your SKU set could apply in multiple applications. Currencies could apply in the same way to multiple applications. Your cost center set-up could apply in multiple applications. That commonality of those dimensions, in other words, the master data of all those planning applications, guess where we are managing those? In ADO. I'd like to welcome my colleague, Leigh Romeo. He's leading and driving the AI topic. Leigh, I know you have a fantastic story.

Leigh Romeo 0:24:46.0:

Thank you, Iver.

Iver Van de Zand 0:24:47.1:

Good luck with the clicker.

Leigh Romeo 0:24:49.7:

Two things. I don't know whether I'm ever going to have a following as big as you on LinkedIn. Two, who'd have thought PowerPoint is more complex than data management? Let's have a look. It worked first time, amazing. Let's talk about Anaplan Intelligence. We're going to continue on the story that Adam and Charlie spoke about this morning. We're going to go into a little bit more detail. We're going to talk about Gen AI, CoPlanner, but not only just CoPlanner, how Gen AI is across the platform. We're going to talk about modeling capabilities within CoPlanner. Any master Anaplanners in the room? Anyone from a [?COE 0:25:38.2]? There's a couple there. Yes. We're going to make your lives a whole lot easier. We're going to make you happier turning up Monday morning. Then we're also going to go into a bit of our vision. Where are we going with this? We're going to talk about Anaplan agents. Exciting stuff. We'll kick off and we'll remind you all around how we're approaching AI at Anaplan. This is our platform stack. We are infusing AI across the platform where it makes sense. There's a whole lot of things that we can do, but we need to do the right things.

Leigh Romeo 0:26:28.9:

We're not just a point solution at Anaplan, we're a platform. You'll probably recognize that there's an AI for sales in the market, there's an AI for workforce, there's an AI for finance. Anaplan is a single platform, and we have one connected AI. Why is that important? Well, that's because we can connect all of our lines of business together. Thinking about the scenario where you can ask a question about your highest gross margin products, but not only that, but how does that affect your supply chain? What kind of workforce needs do you need to be able to handle that kind of growth? That's what's really unique about Anaplan. I'd like to talk about CoPlanner. We've heard a lot about applications today already. It's only 11:30. CoPlanner is turbo-charging applications. Now, we promised you, our customers, that we would deliver CoPlanner on all lines of business, and we're doing that. You've seen supply chain. We've got finance coming out soon, T & Q, we're doing that. Two, we're connecting them, and that's what's so powerful.

Leigh Romeo 0:27:55.8:

CoPlanner. We're delivering more capabilities on CoPlanner. What's that doing for you, what problem is it solving for our users? Well, CoPlanner gives you instant insights to the most common business questions. It's giving you those answers instantly. Why is that important? Well, I don't want Ivo having to go into his application trying to find the dashboard and trying to find that data to his answer. It's going to take time. He may not know the application at all. So it's giving your users those instant insights and those instant answers. It's also giving you recommendations, suggestions. It's leading you in the right direction. It's also creating, it's the generative element as well. Think of the visualizations that you can create off the back of the answers that come out with just a click of a button. Save that card, push it to a new report. We're really moving forward with this. What's the next step? Where are we going beyond CoPlanner on applications?

Leigh Romeo 0:29:13.8:

You can see demand planning. We're live now with supply chain, IFP right round the corner, launching in April. T & Q, the team is hard at work right now with T & Q, and then we've got Workforce. What's next? We've had this question many times. Can we connect CoPlanner with our own data? The answer is yes. We're developing a console so that you can take control. You can select your data that you want your users to have access to. Not only that, you can create synonyms, and glossary of terms that matter to your organization, that are specific to your organization. You can create those. You connect the data, and then you create the questions as well. Now, why are the questions so important? Adam was mentioning this earlier. Well, there's a few things to consider here, governance, compliance, security. You need to add guardrails. You don't want your users asking some pretty random questions, some silly stuff. We had a question the other day - what happens when someone's got the IFP application, and they ask it, who are the last five presidents? It won't answer that question because it knows that it's only related to the data that we've specified within that application. So this is a big move. This is coming out later this year, the console for any use case, with CoPlanner.

R1: 0:30:54.0:

Leigh, we're actually lucky enough to have Adam. Adam will ask the craziest questions, so you can handle that, you can handle…

Leigh Romeo 0:31:01.4:

That's exactly right. Yesterday we had what's called our PTAB, our Product Technology Advisory Board. We had some very special, select customers in the room. We spoke about the console. We had CoPlanner up there, we were testing CoPlanner, asking some crazy stuff. Then looking at how we can make our console even better with the input from our customers. All right, let's move on. Something else that everyone's been asking about, modeling capabilities within CoPlanner. Well, the good news is we're doing this as well. We're starting out with guiding our model-builders. We're talking about connecting our AI technologies to sources like Anapedia, and the Planual, to give you best practices and recommendations around, for example, formulas, or if you've got questions about Polaris or the format of a particular formula. We're starting out with guidance, connecting up to Anapedia in a conversational interface. Then we're looking at optimization. So think about performance issues or bottlenecks within your model, your formulas may not be to best practice, but they just kind of work. Then after a while your model's scaled up and it's getting a bit sluggish. Wouldn't it be great if you could just optimize? We're doing that as well.

Leigh Romeo 0:32:42.5:

Then thirdly is auto-build. Being able to generate models, generate modules and applications. We're really going from that shift of no code, using these agents to create these models for you. Think about that. We're guiding, we're recommending, we're fine-tuning, we're also building. All right? You can see here, tap on button optimize, CoModeler comes back, gives you some suggestions, accept that suggestion. We even had some feedback yesterday - what if you accept a new formula that's written for you with a back test? Great idea. Let's think about that as well. So here's where it becomes really interesting. We spoke about CoPlanner, but not this is about how CoPlanner works with all of our other AI capabilities. I'd like to take you through a few of those. Now, let's imagine this. Think of a scenario, you're an analyst, you're hard at work, the middle of New York. The markets are moving, they're pretty volatile, but it's the end of the day. Now, you need to keep track of these markets. There's a couple of things you can do. You can try and do that manually. It seems like a lot of hard work. You could come back in the morning and then see what happened overnight. That's not going to fly.

Leigh Romeo 0:34:17.3:

Now the good thing is that you've got CoPlanner. You strike up a conversation with CoPlanner, and then you activate detector, anomaly detection, that's going to detect anomalies real-time in the data. You instruct it to look at this market analysis. Now you've left for the day, and guess what happens while you sleep? Detector is detecting anomalies, patterns, outliers, and then what it's doing is it's triggering forecaster to then forecast different scenarios for you, so that you can get the optimal output. Then it triggers optimizer to then look at your top-down strategic goals, and then figure out the best path. Now you come to work in the morning, CoPlanner has put all of this together in a clear, actionable summary. Decision points. Then all you have to do is one click, off to the Workflow agent, which then sends the [?EC 0:35:21.3], your exec team, a pre-read before the next meeting. It's not even 8:30 in the morning. How easy is that? So let's just think about what are the alternatives here? We could wait days or even weeks to try and synthesize all of this data together. What you're doing is combining Anaplan agents with the scale of our models - think of Polaris. You really are doing this at a massive scale, so more scenarios, more predictions. You really do have that competitive edge, that massive scale with Anaplan agents.

Leigh Romeo 0:36:08.7:

Now I do like to do one last thing, so I will do that today for you. Something a little bit special. We like to call this AI-driven workflows. This is all about automating your business processes. We know we can do that with Workflow. What makes this special is that it's doing all of the hard work for you. Imagine that you have a diagram of your business process. Imagine being able to put that into the Workflow agent and it creates that for you, or you've got a sketch of the diagram, put that in, it will generate natural language as well, or even off an existing Anaplan application. This is really saving you a lot of time, energy. It's also increasing adoption as well, so you're really bringing the workflows into your organization and automating those business processes. Let's take a look.

Video plays 0:37:18.9:

Leigh Romeo 0:39:32.5:

So there you have it. AI-driven workflows. That does conclude our presentation. I hope you all enjoyed what you saw and where we're going. We'll be around today if you have any questions, so thank you very much everybody.