R1 0:00:07.5: 

Hey business genius, you've got decisions to make. Not to mention changing consumer demand, hiring freezes and supply chain disruptions. Problem is one wrong decision and, boom, share price faceplants. That's where Anaplan Intelligence comes in. It's built different, with AI at the core, to process massive amounts of data with unlimited calculations and dimensions that uncover insights no human eye could see, and your finance team already sees a lot. 

R2 0:00:35.5: 

We see a lot.  

R1 0:00:36.6: 

Anaplan runs more scenarios than you can count, so you can decide in real time, with confidence.  

R3 0:00:42.6: 

Predicting the future.  

R1 0:00:43.8: 

If we were legally allowed to say that, which we're not.  

R4 0:00:47.8: 

No. 

R1: 0:00:48.7: 

You still make the call, but now it's informed by AI that's trained on over a decade of planning best practices. So Bob here can deal with that pesky supply chain disruption like a boss. Might want to dial that confidence down a hair, Bob. Anaplan, right decisions, right now. 

Unknown Speaker: 0:01:07.6: 

Please welcome to the stage senior vice president of global marketing, Kerri Vogel. 

Kerri Vogel 0:01:15.3: 

Hello. Good morning. How is everyone? Yes, all right, that's great. Well, welcome to Anaplan Connect, we are absolutely thrilled that you're here today. Anaplan Connect started three years ago and just this year we will be at 26 different cities across the world. Last week we were in Milan, did not get to go to that one. Yesterday we were in Stockholm, in addition to kicking things off here with our technical training. So again, welcome, and I can't fully see you, but I'm interested. Has anybody attended all three Connects here in New York? All right, that's awesome, incredible. Well, welcome, thank you for being here, we're excited. Now, Anaplan Connect, it's actually about you. So one of the reasons we do these events and we bring them locally is so that you get the opportunity to connect, to engage, to learn from your peers. So I want to take a quick minute and just look at who's in the room today. So we today have 356 companies represented across 15 different industries, and we have 1000 registered attendees. I will say some may have slept in for this first part, but we're excited for them to join after. Who else is in the room? It's our partner sponsors, and we are very grateful for them. If they are in the room, I would love if you can just stand up for a quick second, because, yes, thank you, thank you very much. We appreciate you. These are also the people we would love for you to connect and engage with during the break, so please definitely meet with them. Let's talk about this morning. So this morning at 8:00 am Anaplan launched a press release, which is exciting, and we are talking about all of our AI and our application innovations.  

Kerri Vogel 0:03:11.5: So the good news, you do not have to go to Anaplan.com, although you are welcome to do that after. Because you're going to get a front row seat into that innovation this morning. We have Anaplan CoModeler, that's live. Anaplan Custom Analyst and Agent Studio, and 12 new applications, and you get to hear all about that this morning. All right, so what is the agenda? So you are going to be here for about - until about 11:40-ish, I say ish, because we'll see. We're going to talk about the company strategy first. So I have been at Anaplan for four years now, and I will say the company I joined versus the company that it is today is very different. So we want to make sure you understand that. We're going to go right into that product innovation and then we're going to talk about applications. Now, a question some of you may have had in the room is why am I sitting on a ring pop? Did anybody wonder? That's random, right? So we have Bazooka here, so thank you. Thank you to Bazooka for the ring pops. So Bazooka will be here. Then we have an incredible panel from Deloitte. We then take a ten-minute break. Now, those are hard in these things, but we can do hard things, I will coach you through it. We will come back into the room and we're going to talk all about AI. We also are very excited to have two customers, so Nasdaq and Brookfield Properties will be on stage, as well.  

Kerri Vogel 0:04:39.2:  

So as you can imagine, it's an incredible morning and I'm super excited to be here and I hope you are, as well. So without any further delay, I would love to bring onto the stage Anaplan's president and chief revenue officer, Greg Raldolph. 

Greg Raldoph 0:04:59.8: 

Hello everybody. Good morning. I like the front row here. Hey everyone, it's great to be with you, thank you for coming. I am super excited about the agenda we have today. As Kerri said, it's a power-packed morning and I couldn't be more energized. I know many of you were here yesterday, I believe, and you got to engage with our product leaders, attend some technical sessions and even gets hands-on experience in our labs. Which I missed that part, maybe next year. Look, today is about one thing, it's about the future of planning and decision making, yes? Regardless of what industry you serve, or what role you're in, every single one of you is navigating more complexity and more uncertainty than ever before. The speed of change is more challenging than I've ever experienced in my career and I trust the same for you. Yet we're being tasked with analyzing what feels like an infinite amount of data to generate faster, smarter decisions. The challenge is turning that massive amount of information into clear insights, so that we can create a viewpoint to be able to optimize our resources, to protect our margins and to drive top-line revenue growth. That's really what today is all about and where we're going to focus. 

Greg Raldoph 0:06:39.2: 

So there are three things that I hope you walk away with the session today. Number one, I hope that you recognize that you're partnered with a strong company, that has an incredibly bright AI future, yes? You'll see that throughout the day. Number two, I hope that you recognize today that you're partnered with a company that has practical AI solutions that solve problems today. I was at dinner with a customer last night and she said, 'The thing I love about -' she's tired of AI slideware, yes? I'm sure you all see a lot of that, right? What she said that she loves about Anaplan is the AI capabilities that she gets today, she can use and solve problems today, okay? The third and maybe the most important is the fact that I want you to walk away today with the recognition that Anaplan is aggressively investing in the future of AI, is that fair? Those three things, okay? Let's see if we're successful. So look, what I plan to do in 12 minutes and 20 seconds is bring you up to speed with Anaplan. The evolution that we've gone through as a company, I'll give you a quick snapshot of our market position and why we have confidence in our position to compete in the market of AI. Then I'll highlight the innovation that Kerri touched on. Adam, EJ and Joe will go into a lot more depth, thank goodness, on the capabilities that we're talking about today. So Anaplan, 2026 marks the 20th anniversary of Anaplan, did you know that? What an incredible story, yes?  

Greg Raldoph 0:08:21.5: 

This company has done amazing things over 20 years, it's been impressive to see. In 2022 the company reached a plateau, a growth plateau. They were at $600 million of ARR, they weren't profitable, publicly traded company, not a very good combination, yes? So Thoma Bravo took the company private, brought on Charlie Gottdiener. Did I get that right? Yes? Gottdiener. My boss isn't here, so I'm okay, I can mispronounce his last name. They brought in Charlie in 2022 to lead the company as CEO, also brought in Adam Thier, who you'll hear from in a minute, to deliver product strategy. They developed a new strategy, a three-phase strategy called Roadmap for Profitable Growth. This was in 2022, yes? Roadmap for Profitable Growth had, really, two foundational principles. Number one is they knew they needed to drive product innovation to capture the market opportunity that existed, yes? Let me tell you, I've been part of private equity companies, it's not normal for them to want to innovate in product. They want to just drive revenue and cashflow. Charlie and Adam did an incredible job leading the strategy to focus on product innovation. Number two, a maniacal focus on disciplined execution, yes? They recognized in order to scale the company, we can't operate like a startup anymore, okay? So those were the two primary principles of the strategy. 

Greg Raldoph 0:09:57.7: 

Fast forward to today, the strategy is working, people. We're at $1.2 billion of ARR, which is a massive improvement in that timeframe. We're a rule of 51 company, which if you don't understand that principle, it means that your growth rate and your EBITDA margin exceeds the rule of 50. If you add 113 per cent net retention rate to that, you're literally in unicorn category, yes? So as a company we're in a very strong position, yes? We're in a strong position, but we believe the best is yet to come, yes? Anaplan is uniquely positioned to take advantage of the massive unlock coming from AI, yes? We enable decision making that is faster and smarter and more efficient than the traditional transactional systems, yes? Those systems are great, I've used them my entire 30-year career in tech, I'm sure you have, as well. Maybe not 30 year, but however long you've been in the business. They've been capable at their particular function, but they operate in silos. They're backward looking, they're historical systems, yes? We sit on top of it to help you think about and make decisions on where you need to go in the future, yes? Companies operate today in a fundamentally different way. Decision cycles are compressed, the market signals now shift literally continuously. Executives are demanding answers to decisions in real time. What should we produce? Where should we allocate capital? Where do we deploy talent? 

Greg Raldoph 0:11:49.0: 

As a company, you've got to be able to replan when reality changes, am I right? You guys know that better than anyone. The AI winners of the future are not those companies that manage a massive amount of data, although that's important. It's the companies that are able to translate that into faster, smarter decisions. So the elephant in the room is why do we have so much confidence about our position in the world of AI? It's a great question, that's a question that every company, whether you're software or you're an industry, should be asking themselves. There's a massive amount of change, we all experience it and see it every day. I think the thing that - first and foremost, if you think about the world of AI, and the most successful companies in the marketplace, they plan with Anaplan, yes? We also have very tight go to market and product innovation partnerships with many of these companies. In fact, we were in the Bay Area last week with Google and Nvidia, talking about not only what they're doing with our products, but what we can do together. So many of you may have seen Jensen's video, his interview from Davos, where he talked about the five-layer cake of AI. Did you see this? Pretty interesting. 

Greg Raldoph 0:13:10.7: 

The main foundational layer is power, the second layer is chips, which is what they care about, the third layer is compute capacity, yes, the hyperscalers. The fourth is LLMs, right? Those four layers form the foundation of AI, but what Jensen went on to say is that the top layer is where the value lies, that's the application layer. That's where the value unlock happens, and he specifically said those companies that are able to provide specific domain expertise will be the companies that win in that marketplace. The four areas that we believe that we're unique is, first and foremost, our domain expertise, and added with business context, allows you to act on AI. Secondly, and you'll hear a lot about this today from Adam, is if you think about - you take the probabilistic nature of LLMs, of AI, you add it to the deterministic capabilities of our calculation engine, which is incredibly powerful. Together offers you the ability to make precise, accurate decisions, that LLMs on a standalone basis just aren't able to do. The third component of why we believe we're in such a strong position, which is a benefit to you, we connect enterprise data with workflows. That allow you to centralize decision making and distribute across the entire business enterprise, which is incredibly powerful. Lastly, our platform turns real decisions into unique data insights that are unique to you. That give you a competitive advantage in your marketplace.  

Greg Raldoph 0:14:58.8: 

So now the fun part. I'm fortunate enough, I joined the company six months ago and you come into a software company that has already made significant progress and innovation. Two years ago there was a commitment to spend $500 million, a multi-year commitment to spend $500 million on R&D. Again, that is unheard of in private equity, but it set the foundation for what we have today and why we're in such a strong position to capitalize on the momentum around AI. Again, Adam will talk in more detail about that. Last year we came out with more innovation and more opportunities, both with our application strategy, AI-enabled application strategy, and capabilities to provide domain expertise through Analyst. Today you hear Kerri talk about the fact that we're announcing - we have announced two new AI products that are super compelling and we'll talk about them. Then, also 12 new applications. So our first product is CoModeler. Has everyone heard of CoModeler? Has anyone heard of CoModeler? Some of you purchased CoModeler in the audience, so thank you for that, by the way. We had a limited release in Q4, we started offering it to clients in January and we've had significant momentum around this. For all of you model builders in the room, architects, this allows you to build and to extend and to optimize your models. 

Greg Raldoph 0:16:30.8: 

It allows you to get four times productivity from the current model builder capabilities today. The future is bright, so if you haven't seen it, you should get your hands on it. The second component is our custom analyst capabilities. When we announced the domain-specific analyst we got a lot of feedback from clients saying, 'Look, we want that same capability to be able to get access to our existing models.' So the team, Adam and his team went to work and delivered this capability that now we have available to you today. So we're excited to talk about that. EJ is going to go into a lot of detail around our application strategy. 12 new applications in four core domain areas. This has been a phenomenal lever for growth and momentum for us in the marketplace. So I would encourage you to dig into the details there. So finally, before we hear from Adam, our north star as a company has always been connected planning, right? We want to give you visibility across your enterprise to make fast decisions. We recognize in the past it's been challenging to accomplish that. We've given you the opportunity, but it's taken a lot of complexity and heavy lifting to do the integration. What Adam and EJ and the product organization have been able to do is build out a unified data model and data ontology that connects those applications together with pre-built integrations across the applications, to give you inherent connectivity across each of those business functions. To allow you to make decisions across the enterprise in a super compelling way. 

Greg Raldoph 0:18:19.5: 

We call it the Platform Network Effect, and the more you add applications to the network, the more you get the effect of being able to collaborate and make wise decisions across the enterprise. So we have a video that we'd like to show you that reflects that very point, so let's run the video, please.  

R5 0:18:55.6: 

I remember looking at the alert and just thinking, this isn't happening. Not tonight.  

R6 0:19:13.9: 

The math just didn't add up. We were looking at the total collapse of the quarter in a single night. 

R7 0:19:22.5: 

At 2:00 am you're not looking for a report, you're looking for a miracle. 

R5 0:19:38.2: 

We had promised them, to everyone, but 40 containers of our entire line were sitting at the bottom of the specific. 

R6 0:19:48.2: 

Nikki rang at 2:00 am and when your phone rings at that hour nothing good follows. My first question was, 'Which products?' When she said, 'Premium,' I knew we had a problem. 

R5 0:20:00.4:  

I remember looking at the alert from the Anaplan Supply Chain Analyst and thinking, this can't be real. 

R6 0:20:07.9: 

I told Nikki I didn't need a report in the morning, I needed to see the full impact right now. 

R5 0:20:14.1: 

I asked the analyst for an impact assessment and immediately got what I needed. If we prioritized our strategic accounts, we could still service nine of our most important customers, but the analyst also flagged our penalty exposure. Our three biggest contracts were fixed, no wiggle room. If we failed them we were staring at $900,000 in penalties alone. 

R6 0:20:39.9: 

Saving some customers is one thing, but a near $1 million penalty is a nonstarter. So my next question was, 'Well, what else can we do?' 

R5 0:20:48.5: 

Before I even finished typing, the analyst had already surfaced a recommendation. An alternative with an eight per cent lower margin. 

R6 0:20:58.0: 

A moment like this usually triggers a month of panic, of teams scrambling, leaders drowning in noise, but we had something that could actually see. The resolution saved us $5.1 million in revenue at 2:00 am. The bad news was I knew it was only a matter of time before our friends in finance would start asking questions.  

R7 0:21:22.5: 

I didn't get the 2:00 am call. I got an alert directly from the Anaplan Finance Analyst. Our cash forecast was bleeding red because of this supply shift. Honestly, my first thought was, why is it always a supply chain issue? My second thought was, what are our other options? We modelled the tradeoffs instantly. It gave us confidence to align ourselves with the supply chain decision, but we still had to balance our books at the corporate level. To protect the bottom line our AI analyst recommended we defer to a lower priority R&D project. The plan went back to green. 

R8 0:22:03.9: 

Here's the thing that people always seem to forget. Changes like this have a direct impact on our hiring plan. So prior to having Anaplan that would have meant a week of meetings and I wouldn't have let Raphael live that down. The moment Raphael's plan was updated, our workforce plan responded, no time wasted. The Anaplan Workforce Analyst identified the open requisitions, paused them and redirected the investment dollars in minutes, not weeks. 

R6 0:22:36.0: 

We averted crisis, saved millions in revenue, while the rest of the world was still asleep. Supply chain talked to finance, finance to HR. 

R8 0:22:44.5: 

We were all looking at the same reality, right as it was happening. A single source of truth, AI at our fingertips. 

R6 0:22:52.9: 

Usually teams are just trying to survive the chaos, but we were able to ask the what ifs and respond with confidence. 

Inderdeep Brar 0:23:16.0: 

Please welcome to the stage chief product officer, Adam Thier.  

Adam Thier 0:23:24.7: 

That doesn't look like me anymore. I've been here three years, guys. We've been on this journey for three years, and I remember the first year. It was all about cost of ownership, time to value, and we introduced ADL, right? Now what we're talking about. What we're talking about now is planning in real life, right? How much of our time planning is spent reacting to 40 containers going off a ship, a truck not getting there, materials cost skyrocketing? Planning in real life is not what planning was ten years ago. Ten years ago, Anaplan introduced Connected Planning, which was great, right? It built this company to immeasurable levels, it made this company incredibly powerful in the market. The problem with Connected Planning ten years ago was you did the connecting, right? You built the models, you put it all together, you maintained it. Over the past three years we've worked really hard on doing Connected Planning where we do the Connected Planning and you take advantage, not you do the Connected Planning. So we didn't talk about 26 - I can't keep track of them anymore. 26 apps three years ago. In fact, two years ago we first started talking about apps, and now, wow, I'm tired. I'm going to sit down. 

Adam Thier 0:25:07.2: 

That's a lot of apps, but that was the point. The point was I can't take down time to value, I can't do planning in real life, I can't give you the ability to react in seconds or minutes if I don't give you the foundation. So we have our incredible platform, we have our incredible calculation engines, the ones that you use and love every day. Now we've built the apps using that same technology, using that same platform. So then you can take them, you can upgrade them, you can extend them, you can modify them, but, most importantly, they bring all the data together. None of this works if you don't have access to all the data. When those containers go off the ship, you need to know about it as soon as possible, and it has to work its way through all the plans at the same time, because planning in real life is really planning in real time, right? Because you guys all heard of Albert Einstein? He has this theory of general relativity. Well, we have a theory, it's called the relative value of time. Because when a container goes off a ship, every second matters a whole lot more than when everything's going normally, right? So the ability for those people in that video to react and solve that problem, by the time the sun came up, is where the world is headed. That's where we're taking the world, right? 

Adam Thier 0:26:48.0: 

It's not just as simple as all of a sudden we know we have a problem, right? That you have a supply risk for your premium tires. It's what are you going to do about it, right? Well, first of all, you need to know, what are the impacts, right? So again, in our applications your customers are in there, your customer contracts are in there, right? Your penalties are in there, all the things you need to operate, to figure out what to do next, right? We give you all the analyses, right? We give you not just the planning, we give you the ML, we give you the replenishment forecasting, we give you all the views of the data you need to make the decision. Click, there we go. Right, we use AI, we're not just - Greg said it, AI vaporware, right? In our world we have a technology today that does recommendations, that does nearest equivalent, that's available today. So when you go and say, 'What do I do?' You can take a picture with this product and say, 'Find me the nearest equivalent,' and it will find that. So the system is doing the work for you, the system accelerating the time to value, the system is accelerating that relative value of time. So that then you can then decide, how am I going to deal with this, right? More importantly, everybody's operating off the same data, at the same time. All those apps are talking to each other, right? 

Adam Thier 0:28:25.8: 

Remember, you did the connectivity, you did the Connected Planning, now we do the Connected Planning. So you can immediately figure out everybody on the same page, right? If 40 containers went off a ship five years ago, it was days, right? In those days it included my boss yelling at me, a lot, but you get it. There's a sense of urgency trying to figure out what we're going to do. When you have it all connected together, when supply chain's talking to finance. So supply chain's got a problem with customers, it's got a problem with customers' deliveries. You can't just solve the customer delivery problem, you can't just say, 'We'll spend a fortunate.' No, finance has to look at it and go, 'Can we afford that solution? What is the most effective solution?' Then we bring in AI again, because AI isn't just about solving your problem for you. AI is a stimulus mechanism, right? I assume everyone's using AI. I love AI, Claude is my friend. I've never had a friend before. When you think about the way you interact with AI, it's a back and forth, right? It's not like tell me this or tell me that, it's a back-and-forth conversation, and that's how we've incorporated it into our analyst products. To be that back-and-forth conversation. Because we all know that when something bad happens, when 40 containers go off a ship and then we all get in a meeting room, after we find a meeting room, and we send out the Zoom and the Slack and we all get in that room together. We go, 'What are we going to do?' We all stare at each other for a second. 

Adam Thier 0:30:11.4: 

Wasn't it nice when AI can just provide the stimulus to, well, here's some options? Right? That's how we look at AI, right? That agent, my friend Claude, it's there to facilitate that conversation, right? To help you find that and because it has access to so much more information, both within Anaplan through the MCP, but also outside, you can really have really thoughtful, exploratory conversations about what you should do, how do we solve this problem, right? So Trent - Trent, are you here? Trent's a real person. It says you've got a $700,000 penalty. Five years ago we might have forgotten about penalties while we were doing this, or the finance team might not have been aware that there were penalty clauses in those contracts, as we're making it. It's all there, it's all exposed. So this is the journey we've been on and three years ago, when I stood up here in front of you the first time, brand new and Charlie and I had done all the math and science and figured out that Anaplan took 46 weeks, on average, to implement. The failure rate of the initial implementation, getting off on the left foot, if you will, wasn't great, and the ongoing costs were not great. People were like, 'I can only afford this much Anaplan because I have to have this many people to take care of it.' Our journey was to solve that. 

Adam Thier 0:31:45.3: 

In solving that we are now - we have 2.3 million customer models. Think about that. We have 2,600 customers. What are we at, 2,600? 2,700? 2,700 customers, 2,800 tomorrow. With 2.3 million models. Think about that. That's an enormous amount. That runs on 500,000 CPUs and 9.6 petabytes of RAM. At any given moment around the world. We do 6,000 software deployments a year, so we are issuing new releases of our code multiple times a day. Like 20 times a day we're pushing code. Over the past year, three years ago, people that were here in the room three years ago, did we have stability problems? Yes, we weren't up as much as we needed to. We're at 99.96 now, headed for four nines. Our system is much more robust, much more reliable, and we are all over the world. We're in 24 locations around the world, be it our own data centers, be it Amazon, be it Google. We are all over the world, running real time. Four years ago we had Classic, we had what we called the Classic engine. We'll talk about that in a minute. Last year we saw 2,200 per cent - yes, 2,250 per cent growth on Polaris, because it's so much more scalable. I want to make a point here, we love Classic. Classic is never going anywhere, right? I joke that it's on my calendar for 2035 to discuss what to do with Classic. What people don't understand is that the calc engines sit in the middle of a much bigger platform called Core. 

Adam Thier 0:33:47.2: 

Classic is one of a number of calc engines that we have on the horizon. It's not going anywhere, that essence of Anaplan that many of you bought into a decade ago, which is a person can sit down at their computer and build a really sophisticated plan in a number of hours is never going away. That is our core essence, right? We have enhanced it by adding apps, we've enhanced it by adding data management, but the ability for you to sit down and go, 'I need to build a plan real fast,' is never going away. Classic is never going away because of that. Two years ago I stood up here and talked about apps for the first time. We've sold over 300 of them. I think I need to sit down again. Right, and now we're in the world of AI. What was the first thing we did in AI? We created a tool for our most valuable customers. Our Anaplanners, our Anaplan architects, our Anaplan master Anaplanners. The most important people in the world to us are the people that build and use our models, right? The first thing we built was an AI tool to help you build more, to manage more. We'll hear about this in a few minutes, but people are doing really interesting things with CoModeler. Mapping out their existing estates, understanding what their models are doing, going back and documenting their models. So it's really a tool for that master Anaplanner or that Anaplan architect to really be able to be that much more valuable, to really take what they know about planning and express it in a way where you can build these plans much more quickly. Where you can iterate on them much more quickly.  

Adam Thier 0:35:40.8: 

So this is Anaplan today. Anaplan three years ago was this. We had the Classic engine, we had PlanIQ, now Forecaster, which we rebuilt entirely the past two years. We had Optimizer, which is our library of linear algorithms. We have an API now, a really good API, so you can use your own Python, and now we have Syrup, which is the replenishment AI engine we built. We are going to be adding more MLs, we're going to be adding a lot more MLs along the bottom to do different kinds of things. MLs for workforce planning and analysis, we're going to be adding MLs for across the supply chain. Because this iteration between plan and ML ends up with an analyst that gives you way more options. That gives you that stimulus on what you can do. So three years ago I stood up and talked about lower cost of ownership, right? We have 500 customers on Polaris out of the 2,700. That's a lot, right? That engine scales to 19 quintillion cells. You can have million-member plus dimension lists in Polaris, and many people have adopted it, there's a lot to do, but out of the box, generally speaking, it's 97 per cent compatible. So if you just move your model from classic to Polaris, it's going to be a 97 per cent fit. With CoModeler this year, as we improve it, it's going to be able to do that migration almost entirely by itself. So what we have seen is we have seen customers now with up to 8,000 models. Think about that, that's an insane amount of Anaplan models, but they're running their entire businesses, just like that shipping example. Three years ago I talked about data management, right? 150 customers using ADO now. 70 per cent documented cost reduction using ADO versus data hubs, versus all that manual stuff. Seamless integration, right? Databricks, Snowflake, SAP, ad infinitum, right?  

Adam Thier 0:38:29.4: 

More importantly, there was no way we could have done AI at scale if we hadn't done the data wrangling that ADO does. We just couldn't, because AI's all about data, right? It's all about huge breadths of data and managing it and orchestrating it. That's why we call it Anaplan Data Orchestrator, because we have to orchestrate it all together. This is the first layer in the platform that has allowed us to not only do the TCO and the ongoing cost of ownership and the time to value. So 46 weeks became 20 weeks with ADO. With apps we're seeing 8 to 12 weeks. Now, apps aren't just about apps, we talk about apps, but really the point of apps is the pre-connectedness of apps, right? So they all share a universal data model, and we understand the hypothesis of context, right? When supply chain talks about inventory they think units, locations. When finance thinks about supply chain they think about costs and working capital, right? We've built that context into the system so that when it's over here in supply chain and it's units, it's working capital and finance. You don't have to build that connection, you don't have to think about that logic, how do I turn units into working capital? The system's already doing that, right? We have that across. You look at headcount in particular, you've got a position, you've got headcount, you've got members of a sales team, you've got skills, right? Does this person have these skills? That's what we're seeing in the world of workforce, it's about the skills. 

Adam Thier 0:40:21.5: 

We're seeing the same thing in AI. Does that agent have the skills? Can it do a close, right? Can it be a financial analyst? Does it have the skills that a human has, but in silicon form, to do the work of that human? To assist that person, to be their friend? So this is the point of applications. The point of applications isn't just buy this, it's out of the box, it's easier, it's quicker. Yes, it's a lot quicker, it's 8 to 12 weeks and it's configurable. We've seen customers with this sit down with an application, with IFP in particular, and ran 26 configurations in three days. So it wasn't sit down, build the requirements, figure out what I want to do and start building. They ran the configurator 26 times in three days until they picked the one they like. They're like, well, we like this part of this one, and this part of this one, and then they had something out of the box in under a week that they could really work with. That's great if I want to solve this problem, but if I want to do planning in real life, where it's connected across the enterprise, it's the connectivity. It's that universal data modelling. It's what we call the planning flows. How does the planning information flow across the enterprise? Right? So every application is much faster time to value, 8 to 12 weeks. Much lower cost of ownership, generally about half. Then these are built for the future. We didn't just build templates, these are not templates, these are not starter packs. We rewrote an entire layer of our software so they're upgradeable. So as we add features to the application, you get those new features, right? 

Adam Thier 0:42:11.7: 

We give you the guidelines and guard rails and with CoModeler now you can take that model and extend it and when we push the upgrade it doesn't break, right? You test it, you put it into prod. So it's a huge differentiator for us and it's a huge differentiator for you because you can get that end-to-end Anaplan now, right? So this is all part of the platform and, again, going all the way back to what I said, nothing in here is something that's different or special than what you could do out of the box with Classic ten years ago. We've just built upon that, at the core of all these apps, at the core of CoModeler, at the core of ADO, at the core of everything we do is our old friend, Classic. The ability to sit down and build a model. That's never going to go away. So our ontology is foundational for this planning network, right? So it's not just the apps, it's the fact that they all share a common data model, a common ontology, and they all understand the contexts it crosses, and it's all unified. So you don't have to do anything. You can extend it, you can happily extend it. Then we get to the layer of AI, right? So we have today CoModeler and the analysts, right? CoModeler is build Anaplan, analysts dramatically expand the usage of Anaplan to new people, right? We want those people to be able to understand what's going on in the business. So your atypical Anaplan user. Somebody that can go in there and say, 'What was my best-performing product last quarter?' Well, in their mind they best meant something, to an AI it's like, well, I better come back and tell them what my most profitable product was, what my highest-selling product was, right? Again, have that conversation. 

Adam Thier 0:44:16.3: 

For the regular person out there, it's huge. You're talking about somebody - a guy getting off a truck in front of a gas station, about to load the shelves, right? What's the most - the best-selling product at this gas station this week, right? Were they in a position to do that before? No, they might have been driven some information about that, but being able - that regular person, employee, being able to have that conversation with Anaplan about what's going on at this customer, what's going on with this spend, what's going on with these materials, what's going on with this inventory? It's dramatically expanding it. So CoModeler and analysts. Then we're building in agentic platforms, which these are built on. So then you can have - with Agent Studio you can build whatever analysts you want. You can build whatever works for your business, and you can mix and match it with all the other data, right? You want your SAP data, you want to talk - get me the actuals from SAP and the plan from Anaplan, go ahead. That's what ADO's underneath there for. So we're really getting into this world of planning in real life, right? These agents will be out there giving you the stimulus to run your business. Not sitting there and going, 'What do I do?' Because there's some mornings I wake up and I don't know what the hell to do. The AI is there to give you that stimulus, to give you that advice on how to run your business, based on what's going on, and doing it in real time, right? We've always talked about real-time planning and we are here now, right? 

Adam Thier 0:46:09.1: 

With the applications we are here. With that, I'm going to bring up EJ. So EJ runs the apps group at Anaplan, he's the reason I'm so tired. He built all this stuff, so EJ, come on out, buddy. 

EJ Tavella 0:46:31.3: 

Man, I've got to back that up. Adam, phenomenal. So excited to be part of the team. What the platform team is doing is amazing, the technology we're building out has been, I think, just fundamentally changing how we do business with our customers over the last couple of years. I've been here two years, joined two years ago. The second day on the job I had to stand up and give a speech, so count it like three years in, third time doing the speech, and I'm just super excited to be here. I came on board to run the supply chain business, we've grown that business now about 10X over the last two years and now I'm taking over and running the overall applications business. It's really my pleasure to work with the four different COEs. We've got a finance team of experts, we've got a workforce team of experts, sales planning, performance management, revenue planning, and, of course, supply chain. We're bringing the teams together to really deliver, as Adam said, on this vision of how do we truly have connected applications, right? We've got this phenomenal platform that we can scale, we can build on, we know what our customers build. So thank you for being great customers, thank you for the creativity that you brought to the platform and us getting a better understanding of, really, what can we do with the solution? With the inventive applications, right, our goal is not to replace building, our goal is to augment it. Our goal is to give you something as a starting point. How do they give you a springboard that can really scale? What's that foundation, and then how do you take that foundation with the platform, with ADO, with Polaris, with all the new technology and then extend that to really spend your time and focus on how do I add the most value to my business? Where am I really unique? Where do I really need to have those unique connections to my end-to-end process? I think what we're seeing in the real world, as Adam said, is amazing time to value, right? We're seeing 25 to 30 per cent faster time to delivery, and then lower total cost of ownership through the fact that you can automatically upgrade the solutions. You build in better solutions. 

EJ Tavella 0:48:32.7: 

Frankly, we're tying in the analytics. So as we get into this and we talk about what is an application, we'll spend more on this. Hopefully you guys have seen this, if you haven't then we're going to give you a quick peak in the box today. Applications are much more than just accelerators, as people talk about, right? Applications really are building in best-in-class solutions. We work with partners on almost all of these applications, as well as institutions and industry experts. We've a team of over 200 people that are actually helping us to define and build out these applications. So we're bringing a user experience, really a role-based specific user experience. How do I think about how do the individual users want to run their day-to-day job? How do I make it easy for them? How do I make it easy for them to use analytics to make better decisions and how do I make it seamless for them to then connect the dots across that overall process? These applications are AI driven. Adam was talking about it, AI at the core. We've got AI integrated in across the end-to-end process. So that means we're bringing to life our tools like Forecaster or Optimizer, our integration with Syrup now. So how do we take those tools, instead of giving you a solution that you can craft where you want? We're really thinking about how do I tie that into my forecasting cycle? How do I use the demand planning process to drive integration into trade promotion planning and give you better predictions of what your spend is going to look like? 

EJ Tavella 0:49:52.1: 

How do I integrate optimization into my workforce planning processes, so I can actually optimize what my workforce needs are based on my capacity, based on my resources? It's prebuilt to work for you and your business, right? So this is trying to really bring together best-in-class analytics, and then tie on top of that, as Adam was talking about, all of the analyst agents, right? So now you have analysts and agents connects to the applications, pre-connected with hundreds of questions, so you can ask interesting questions that give you insight into your business. You can start to make decisions and, shortly, you'll be able to actually drive actions with those agents, as well. So actually have it drive decisions as part of that process and automation across that cycle. The last piece is the scalability that Adam talked about, right? So we work with customers that have tens of users and we work with customers that have tens of thousands of users, right? So we're talking about massive scalability. When we look at some of the supply chain use cases, we're doing store-level replenishment for thousands of stores, for hundreds of thousands of products, on a daily basis, right? So we're talking massive amounts of data and we've built these solutions on this technology in a way that truly is going to scale. We spend a ton of time testing the performance, running tons of data through them and making sure that these truly scale out to deliver the solutions that you guys need as customers. 

EJ Tavella 0:51:10.7: 

So at the bottom we'll hit a couple of points here. They're configurable, we don't expect that we know exactly what your business looks like, but we know generally how a demand-planning process should work, right? So we've got configurations that helps you to find what do your hierarchies need to look like? What are the different attributions that you guys want to drive against? What are the right metrics for your overall business? You guys set the thresholds, you guys can add in additional hierarchies, you guys can then extend these applications, right? So applications are not meant to be 100 per cent out of the box, turnkey, you never use anything else. We have the power of the platform, so we want you to be able to extend them. Almost all customers do, right? It's not customer. This is very different than traditional enterprise software where you've got an out-of-the-box solution. If you want to change anything outside of the configurations, now you're talking custom. You're talking custom for other software, now things aren't upgradable, now things are hard to manage, now things are using specialists to be able to make those changes. In Anaplan extensions are just additional modelling, so the stuff that you guys know and love, you can extend applications with. You can also connect them to custom models. So we have - we've sold a lot of applications, we've sold hundreds of applications over the last year. We have hundreds of customers that are alive on applications.  

EJ Tavella 0:52:26.9: 

What we've found, which is interesting, when we first went out we said, 'Hey, look, we've sold to a lot of the early adopters, a lot of the customers that really want to build things themselves.' What we've found is, actually, 50 per cent of our customers buying applications are existing customers. These are customers that have - maybe they've bought finance and they've built their finance solutions, they've got a phenomenal COE that's building our finance. Now they're moving to the supply chain or workforce planning, and they don't have a COE that has that knowledge or that expertise. So instead of going out and trying to figure that out themselves, they're saying, 'Great, I can use an application to accelerate this process.' So we're seeing a ton of that kind of work in place. We're also seeing, again, for existing - for net new customers, about 50 per cent are going to net new customers. Net new customers these days are coming in and they want a solution, right? They love the flexibility and the scalability of the platform, but they also want to have something that can kick them off and [?strong about it 0:53:17.6]. I've got to a guest speaker today from Bazooka, you guys all have your candy and your chair here. We'll talk a little bit about that, like why they decided to use applications to accelerate that process. Okay, so let's jump in and let's make it a little bit real here. So we're looking in an application. I want people to understand, what do these things look like? 

EJ Tavella 0:53:36.3: 

We spend a lot of time on what the look and feel looks like, right? So I'm inventory planning, I can understand the changes in the process. Is it running? There we go, okay. I can drill down, I can check exceptions, I can identify where I've got outliers and then I can go in and I can kick off analyst, right? So I can kick off my supply chain analyst. I can start to ask intelligent questions. An analyst is connected to the applications, and we understand the details of the applications, the attribution, again, all the metrics. I can go in and I can understand, great, where do I have the most product for product three, week four, in what DC? It's going to give me answers, right? It's going to think about it, it's going to go back to the model, it's going to be tied to specifically that information that you've asked for. We're going to be able to give you accurate answers that define that goal and result. I can access this through my phone, my mobile phone, I can access this through the application. We find that if - for executives, especially, for people maybe that are not in Anaplan all the time, it's a great way to get questions answered. Once I'm in it and I get the answers, by the way, it tells me where to go if I want to drill down. So I can drill down and see that information in the application, I can understand what's happening there, and then I can also kick off workflow and other activities across those pieces. So we really think this is a great new way to just think about reducing the friction when it comes to how do I make decisions, how do I get access to data? 

EJ Tavella 0:55:02.2: 

Really democratize that process. So this is going to continue to evolve and we're spending, as Adam said, a ton of time on how do we really integrate AI at the core of these applications? Okay, so Adam talked about this a lot, I'm not going to spend a ton of time on it, because we talked about the integrations with data hub and that layer that really allows us to extend the applications across the unified data model, right? So connecting these applications. When you buy one, it can be connected to the next one, it's networked automatically. You don't have to load data more than once, it's in that overall process. So I want to get into the meat. The team has been working super hard, we actually have 28 applications, Adam, not 26. So we had 16 before today, we're launching 12 now. So on the foundation we're adding - and I'll jump in here quickly and give you some of the details. For the finance side we've got five new applications, right? This is really extending that suite in really our focus area, right? So we've got consensus margin planning, subscription revenue planning, profitability analysis, cost planning. We've also got our first IT application, so focused on the office of the CIO, which is software spend planning. We're going to extend a few more into that COE, as well. So let's drill down a little bit on profitability analysis.  

EJ Tavella 0:56:23.0: 

For us, this is really taking the financial planning process and getting into true profitability, right? So what's working, how do we make sure we understand the right scenarios across our process and focus on driving margin into the overall business? We'll get into supply chain. I'm going a little quickly because I'm hitting on time. We've got four new applications, so we're going to continue to extend on our retail footprint. So we're adding in assortment planning, we're adding in replenishment planning, which integrates Syrup for really deep dive analytics all the way down to the store skew transactional level details. We've got our first procurement application in spend analysis, so direct material spend analysis. Then trade promotion planning, which is one of those use cases, I'm not sure it necessarily fits in supply chain, but it's supply chain meets commercial planning meets revenue generation, right? How do I optimize my trade promotion planning and connect trade spend back with the demand signal, and understand what that means from a closed-loop perspective. So if we drill down in assortment, right, assortment is extending for merch financial planning into what is the mix going to look like? So what's my targets with MFP? Assortment is what is my mix? How do I make sure to have the right products at the right time, and how do I know if I need to have 15 different skews for this category, or if I need to have 50 different skews for this category, which one's going to be number one? Which one's going to be number 50?  

EJ Tavella 0:57:40.2: 

We're driving in analytics across this overall process, as well. Then we get into workforce planning and workforce planning is actually our fastest-growing line of business. We're super excited about this and we've done some huge deals with massive customers that are doing workforce planning for tens of thousands of employees. There's a major investment in this space. I'm super excited about these. Project planning allows us to understand how do I make sure I have the right resources for projects as I'm kicking them off. How do I understand the profitability? How do I make sure they're coming on board, on time, and that we hit the project planning on time? It actually ties back to one of the financial applications, which is project cost planning, as well. Then we've got cost center planning, which is - sorry, call center planning, which is really focused on how do I manage the staff across a specific discrete unit of planning and understand the capacity around the resources that drive those overall processes. So HR is a big one, if you haven't seen the HR applications they are very sexy and we should drill down more. Then sales planning is an area that we continue to invest in and sales planning, if you think about it, it's all things for the office of the CRO, right? The head of sales ops, right?  

EJ Tavella 0:58:53.7: 

So how do I do my territory quota planning? How do I set up and do my overall capacity planning for the workforce of the sales organization? As well as now sales forecasting. So with sales forecasting we can really start to do opportunity planning and actually get into understanding what is our probability of hitting these targets and getting to that overall bookings forecast? Again, these are connected now into demand planning, as well as into revenue planning. So I can convert from a bookings forecast, to a demand signal, to a revenue signal across that overall process. So very excited about these new applications and we're seeing a ton of traction. If you're interested in those more, go out to the tech booths. We're going to have people that can demo these for you today, you can get in and see all of them in detail. Any of the ones that we already had, that are existing, as well as all of the new applications. So these are absolutely ready to go and we are excited about sharing them with you. I will end with very quick highlight on what's coming. So we've got more to come. This is, frankly, just the tip of the iceberg, there's a few that aren't even on here yet, but we are now launching partner applications. So you're going to see one here listed, which is the biotech partner application, for example, with one of our partners, Bluecrux, to build out a very specific biotech planning application. We've got a lot of exciting applications. Our goal here is to really build out a portfolio that lets us, all said, capture 70 or 80 per cent of our customers' major use cases, right?  

EJ Tavella 1:00:20.3: 

There's always going to be things that we want you guys to build yourselves and that partners are going to bring, and we think partners will help us accelerate that and go from the 60 per cent to the 80 per cent here over the next couple of years. So very excited. Again, thank you all for the huge adoption that we've seen for applications. So with that I'd like to invite Sankar Karuppasamy on stage. He is a customer with Bazooka. 

Sankar Karuppasamy 1:00:55.8: 

EJ. 

EJ Tavella 1:00:56.0: 

The perfect song.  

Sankar Karuppasamy 1:00:59.2: 

Almost got my last name. 

EJ Tavella 1:01:00.6: 

Almost. I almost got it. Karuppasamy. 

Sankar Karuppasamy 1:01:02.7: 

Karuppasamy. 

EJ Tavella 1:01:03.6: 

Karuppasamy. Here we go. All right, well, thank you for joining us. The CIO at Bazooka. You've got a lot of responsibilities. Tell us a little bit about Bazooka. I think everybody knows the brand, it's iconic. I've been eating Bazooka gum since I was probably seven or eight years old, at baseball. 

Sankar Karuppasamy 1:01:21.7: 

Absolutely, and thanks for your team getting this ring pop made in Pennsylvania. So excited about it. So Bazooka, company's an iconic confectionary brand and we have a portfolio of brands. Ring Pop, Baby [?Partner Pop 1:01:37.5], Push Pop, and all that. We are a global company, operate out of New York, which is our headquarters, and we're also in the UK, servicing a lot of other markets across the globe. 

EJ Tavella 1:01:52.4: 

Excellent. So as you looked at this, and I know you guys are growing quite fast, and obviously that global footprint, what were the compelling events that caused you guys to decide to go through this transformation, right? I think it truly is a transformation. 

Sankar Karuppasamy 1:02:06.4: 

Absolutely, it's a great question. So we used to be part of a parent company called the Topps Company. So around 2022 we were sold out to another firm, we are owned by PE companies, like you are. That is a pivotal moment for us. The reason is we're not part of a parent company anymore, but now we're an independent unit, our own company. So we started asking hard questions and said, 'Hey, do we have the right infrastructure, right systems in place to be able to meet our ambition, right?' That's where the whole thing started. For example, our sales has more complexity because we have more products and we want to expand into different channels, and our operations is a global supply chain, very complex network. Our finance, because of the new owners, Apax Partners, there is a need for a robust P&L, right? The team was doing an amazing job, even with the complexity, but there is a lack of integrated decision making at speed, that lack of that integration costs us, right? So that's where all this transformation effort started for us, from a planning point of view. 

EJ Tavella 1:03:33.1: 

So the board and the exec team and you guys aligned, okay, we need to have this? 

Sankar Karuppasamy 1:03:36.7: 

Absolutely, those are some of the critical things that we had to do to get board buy in. Then, from the board buy in, you have executives aligned, which makes the whole transformation and change much more easier, right, than otherwise. 

EJ Tavella 1:03:50.4: 

I was going to say, I know we're talking about change later, but I think just that foundation of having truly the executive team on board with this is why we're doing this, this is important, always helps that. 

Sankar Karuppasamy 1:04:00.2: 

Absolutely, and it is, to me, the ambition we had from a growth perspective, right? So it's completely having alignment at board level is absolutely critical. 

EJ Tavella 1:04:12.1: 

Yes, perfect. So as you guys started to look at the market, and I know you guys had some legacy tools, we'll talk about that in a minute, what steer was the guideline to get you to Anaplan and why applications versus customer build? Walk us through your logic. 

Sankar Karuppasamy 1:04:27.2: 

Great question. So we did our due diligence, right? We looked at a lot of different platforms, to come to a conclusion of Anaplan. I think there are a couple of things that we used to make a decision. Number one, we didn't want to be in the business of building applications. We're not a software company, we're a candy company, right? So we want to spend our effort innovating products and get the product to our market and customers. So we didn't want to build software ourselves, and that's one of the key things that we went towards Anaplan, because you had pre-built applications. Even if it works 80 per cent of the time, that time is saved for us where we can configure or extend your application to do that. So that's one. The second thing is really to have an integrated business planning, right? Our transformation goal is to really have an S&OP process which touches sales, operation and finance, right? Because prior to that we have had individual teams working their own systems and they're all doing an excellent job, but because of the lack of integration we couldn't make the decision. So that's another reason since Anaplan offered an integrated planning system, that's another factor to decide towards Anaplan. 

EJ Tavella 1:05:49.5: 

Yes, no, I love it. I think we're seeing that more and more, where the siloed decision making of, great, I'm going to go and buy a supply chain planning tool and then I'm going to go and buy a different tool for financial planning or a different tool for sales planning. I think a lot of CIOs in your position are thinking about how do I consolidate, right? How do I simplify? 

Sankar Karuppasamy 1:06:06.2: 

Yes, not only enable the decision making, but it's also the foundation of getting all the data in one place so that we can get on with AI and everybody's talking about it. 

EJ Tavella 1:06:16.7: 

That’s right, and I think we were talking a little bit about what the legacy landscape looked like and then what it's gone to, to talk about simplification. I think that's a great story. 

Sankar Karuppasamy 1:06:27.4: 

Yes, so I touched upon it, right? Like I said, our sales organization used different systems, some in our European organization used a different system than the US organization. So every part of S*OP was done in legacy systems, right? So the first thing we want to do is to get on with Anaplan, with the due diligence that we decided, and then we took a journey of getting all the team into Anaplan. So we're not done there yet, that transformation's still ongoing. The way we took an approach is we implemented this whole system for European business and learned lessons from there, and we're applying the lessons as we are going through the journey in the US. 

EJ Tavella 1:07:11.1: 

I love it. I think that's a great, logical way of doing it. Crawl, walk, run, but make incremental steps quickly starts to pay for itself, lessons learned improve the overall cycle. It's a key to success. So let's talk about AI for a minute, right? So it's the hot topic, everybody's talking about it. How do you think about AI as part of this journey? We can talk a little bit about maybe the forecasting type analytics, versus the big AI, gen AI type analytics. 

Sankar Karuppasamy 1:07:36.6: 

Right, so I've been joking with my team in the last 48 hours, I'm Claudeified, talking about tokenmaxing and skills and all the other things with Claude. Yes, just unbelievable growth in the innovation happening in that space. We're very thoughtful on where do we apply these within the organization. So for example, with the demand planning we did introduce a machine learning model that we built. It's for a very specific use case, for our seasonal products. So the good news is Anaplan is pretty open platform, you could use the AI capability that you provide, and also you also provide integrating your own AI model in it. So we are being very thoughtful, EJ, in terms of how do we use AI? We want to get our basics done first, before we run wild on AI, that's the approach we're taking. 

EJ Tavella 1:08:31.1: 

I think that makes sense, and I love that strategy. I think we want to be an open architecture. We obviously have the forecaster there and it's running, but if you've got some special ML analytics that you've got a team that's doing, great, how do you integrate both of them? No problem, right? Bring them together. We see this a lot, I think we see this kind of model a lot at customers. So let's talk about adoption, right? Get into a little bit of change management. So tell us what's helping to drive the best adoption and how you guys are thinking about driving change in the organization, now that you're past it in Europe and you're moving into North America now. What are the things that are the keys to success for you guys? 

Sankar Karuppasamy 1:09:03.6: 

Change management is the biggest challenge, right? To make the change management easier, as I mentioned, you really need to have a board buy in. What that means, it translates to executive leadership sponsorship, whether it's sales organization, or operation, or finance organization. So you have leaders completely aligned, right? That translates to getting the right people for the roles that S&OP process will play. That makes the change management so much easier, right? Because everybody's aligned and you have the right talent in place. Combine that with a great partner, who you partner with and take you through the journey, and have a best outcome for whether it's demand planning, supply planning or financial planning, right? I think those are all the key things that we have learned from our UK implementation, we are applying it here. The good news is we just finished our demand planning implementation in the US, great success, right? Because of all of these things, right? 

EJ Tavella 1:10:11.8: 

Yes, I love it, and I think you've said it, but I think just to summarize, the combination of having the top-down leadership, executive buy in. This is the transformation we're on, this is why we're doing it, this is important. Then the bottoms up, having the - you've said, the key superusers involved, from the very beginning of the process. So they adopt it, it becomes part - they're the owners of it, right? It makes a huge difference. 

Sankar Karuppasamy 1:10:33.2: 

Oh, absolutely, that's the recipe for success, right? 

EJ Tavella 1:10:35.7: 

Yes, I totally agree. So we've got a couple of minutes left. Let's talk about the value. Where are you starting to see early value? I know you're not all the way through the journey. Where are you seeing value now and where do you expect to see the biggest value as you roll this out? 

Sankar Karuppasamy 1:10:48.3: 

So I think, like I said, we are still in the journey of transformation in the US and I hope that we get this transformation done probably by end of the year. We have more to do, we're doing - we just finished demand planning, we are planning to do supply planning, inventory planning, trade promotion planning, FP&A planning, all of that. So it's all in the plan. 

EJ Tavella 1:11:13.4: 

In the year? 

Sankar Karuppasamy 1:11:13.6: 

In the year, throughout the year, right? First quarter, next three quarters. End of the quarter I want to be able to say to my boss, 'Hey, we've now got a better platform where our teams are working in one single source of truth to be able to make decisions in an integrated fashion, at speed,' right? That's a key. The second thing is we have all this data in one place, that itself gives a lot of benefits. Your CTO talked about working capital management, making inventory - optimized inventory to be able to react to supply chain situation. All of that is possible when I get this transformation done, right? There are ways specific KPIs within the different models of Anaplan, but at a very macro level this is what I am looking to get done with it, when we're done with the journey. 

EJ Tavella 1:12:04.6: 

I love it, and obviously, as you get into demand planning and inventory planning, hopefully we utilize your inventory as efficiently as possible. So when people go out and buy 400 or 500 Ring Pops, you're going to have a problem with supply. 

Sankar Karuppasamy 1:12:18.9: 

Absolutely! 

EJ Tavella 1:12:20.3:  

We're trying to move the needle. We really appreciate the partnership and we're super excited to have you on the journey and thank you for coming and joining us today. 

Sankar Karuppasamy 1:12:27.6: 

Thank you so much, EJ, appreciate it. 

EJ Tavella 1:12:32.4: 

Thank you. Okay, thank you very much. With that I would love to introduce one of our great partners, Deloitte, Dounia Senawi is going to join. She's going to be moderating the next section, talking with a couple of customers. So welcome Dounia.  

Dounia Senawi 1:12:53.3:  

Right.  

EJ Tavella 1:12:54.8: 

Just click the green button. 

Dounia Senawi 1:12:54.8: 

All right, thank you, EJ. Hello everybody, it is wonderful to be with you this morning. I have the honor and the privilege of leading Deloitte's Alliances business, and we've had a relationship with Anaplan for over a decade. So we're extremely proud to be here today. As I am in the market with our clients and teams, one theme that's really prevalent today is the difficulty in navigating in today's environment. If you happen to be in New York this past Monday, it was super foggy, so I would liken it to that. We've got this clear vision, we've got data, we know where we want to go, but that visibility keeps changing. That fog is really showing up in a few ways, and we heard some of that this morning. It's the disruption that continues and accelerates at a pace that is extremely high. It's that regulatory changes are happening across almost every single industry. Supply chains being reconfigured in real time and then you've got AI accelerating that pace of decision making. Then you look inside organizations and whether it's supply chain or operations or finance or commercial teams, in many organizations that planning is still happening in siloes. So that's where powerful platforms like Anaplan come in and transformation really requires a clear vision, a discipline to execute, and really the courage to make bold decisions. So we've got three amazing leaders here with us today that have driven major transformations at their organizations. They're going to share some of their perspective with all of us. 

Dounia Senawi 1:14:46.4: 

So if you would please join me in welcoming Ellen Sipos, from J&J. We've got Inderdeep Brar, from Medtronic, and my colleague, Kim Kim, from Deloitte. Well, we didn't plan this, but it's pretty amazing to have three ladies on the stage sharing their perspective. Women's History Month, so I know I'm super excited to be here with all of you. We've got 20 minutes, so we're going to get right into it. So Ellen, I'm going to start with you. If you could share a little bit about your work at J&J, but also talk about what sparked the transformation and, as you were navigating, how you chose what was a non-negotiable in terms of what stayed and then where to pivot. 

Ellen Sipos 1:15:39.9: 

Good morning everyone, it's a pleasure, I just want to thank Anaplan and Deloitte for including me in such a wonderful panel. My name's Ellen Sipos, I have responsibility for Johnson&Johnson's enterprise performance management organization. We're responsible for the integrated business plan. So we have all the enterprise, as well as the sector at P&A, planning and forecasting activities. We also have responsibility for the automated forecasting cycle, so things like computer-generated forecasts, as well as your driver-based forecasts. Then last, but not least, we do the - all the analytics around performance analytics. So Anaplan's been amazing for us to be able to really break down those siloes, just like Dounia said. So the catalyst for us was, I think, like many of you, we had commercial, we had supply chain and finance, with all different sources of data. People were coming in, they were, in essence, storytelling what they wanted to tell our leadership about what was happening in the business. So for us, it was about a business, a business transformation. We needed to make sure this wasn't about finance, this was about the business, and bringing the business silos together as one. This integrated business planning process has really changed the game for Johnson&Johnson. As some of you might know, we actually had a loss of exclusivity last year and it's the IBP that allowed us to look at the current year and the current year plus one and think about what our portfolio would evolve to. How we were going to manage margins. 

Ellen Sipos 1:17:17.1: 

That's across 82,000 skews, right? So we had one common understanding of what our demand forecaster looked like, we knew what our supply constraints looked like. Just like Dounia said, right? Tariffs were coming and all of a sudden we're like, okay, now we've got to ebb and flow with what's happening in the market. We were able to have accountability so that all of us knew what we needed to do from a management action plan perspective. We had risks and opportunities sitting on the side. So I just want to say that it's been a real incredible experience for us here at J&J, we're now looking at sales, we're now looking at GP, we're having one common conversation. Which has been really insightful for us to really change the game. We're making faster decisions and we're making better-quality decisions around what we want to do. So the standardization discussion is a really important one. I think for us it was about where do we want to have a common set of procedures across our organization and where would we allow, from a sector perspective, unique business events, right? Because not every component of our business in pharma runs the same as medtech. So for us, it was about a governing body. We went to the EC, we said, 'These processes are going to be standard,' and only in the case if there was a very strong value case that we would take to the governing body would we actually change it. 

Ellen Sipos 1:18:43.0: 

Because we know we want to do AI, so you can't do AI with bad data and customized processes, right? You need to have a standardized approach and even in the sectors we agreed that there would be one way of working in pharma and one way of working in medtech. So that's allowed us this platform to start to look at the other expansive areas that we can now do, because it opens the door for more technology and more analytical capabilities. If we allow for customization, it's just a lot more to maintain, it's an ROI, quite frankly, that's not paying out for us. So it's been a gamechanger for us to really live into - and you need the business aligned, right? So for us, it was all the way from our CFO to our GOC members across the sectors that were really championing this and making this a business transformation. 

Dounia Senawi 1:19:33.8: 

I love it, your comments remind me, clear vision, standards accountability and then success stemming from having open, honest conversations about those outcomes across every single division. Thank you. So Kim, maybe I go to you next? If you could share a little bit about what you do at Deloitte and I know that AI was a strategic differentiator in our approach. So maybe talk about that and also maybe some advice and counsel about the early-mover advantage. 

Kimberly Kim 1:20:04.8: 

Yes, so yes, my name is Kim Kim, I get that question all the time. I wish I had a great story, but I have parents with a sense of humor, so Kim Kim. You can add that one off your list, I've met Kim Kim. So I lead financial planning and analysis for Deloitte. Our US firm is about a $30 billion revenue firm and we have been doing Anaplan for a little over three years. When we first embarked on it, we had probably done the best you can do in Excel modelling, like it could almost jump off the page of Excel. So back then we recognized we needed to reimagine how we did all of planning, how you did forecasting, annual plan, long-term plan. So we really focused, when we started our implementation, on the predictive revenue aspect of it. So being able to load our sales, our backlog, our pipeline, our economic indicators into a tool that could then predict revenue for us and it's got over 30 algorithms that it runs. It's pretty fantastic. Then we also focused on machine learning to say, 'Hey, using a historical basis, how can it predict your costs?' So I don't think - we knew that we needed to do AI, we knew we needed to reimagine. It wasn't until you start seeing the outcomes of that and the real-time outcomes of that, where you can go, 'Hey, for this size of business across all of our businesses, it can produce our baseline forecast for us.' That is pretty fantastic. Produce it in a lot faster timeframe than what we had been used to, and obviously we were bringing together the forecasts for a long time. The speed with which we could do it had been significantly accelerated. Then, not only did you have that aspect, but you had - I loved hearing having the business come together with you, because you certainly had finance that had all the tools. 

Kimberly Kim 1:22:19.3: 

You could open the tool up to the business leaders, so you're actively talking with all your leaders using screens that they're looking at, you're looking at, to go, 'Hey, we produced a baseline, we haven't touched it yet, here are the numbers.' Then you can scenario what do you think is going to happen, plus or minus, so you can talk about it. Then the others, the center can also look. So we can come on over the top and go, when you roll all of this stuff up, where did we change numbers or where did we rely on the tool actually coming up with the number? That's transformational too, because it had been we had it, but it was in our siloes across our businesses. So someone in my role having access to something where I could see where machine learning is calculating numbers, versus what they were tweaking or our finance teams were tweaking was truly transformational. So that was a bit about our journey, how we thought about how it changed, it had me at hello. How we rolled it out does take a bit of time. We happened to start with our forecasts, we then moved it to plan, we certainly did pilots across the years to just make sure it was doing what we needed to do. Then it takes time to change your ways of working, right? You need to make sure that - people love Excel, so getting our users to go, I know you love it, but put it to the side, actually use this tool, takes a bit of time. The phased rollout really worked for us back in the day. 

Kimberly Kim 1:24:01.5: 

So that would be the advice of just how we pivoted to go live across the three years. 

Dounia Senawi 1:24:09.7: 

Yes, and so important to actually be - as you're talking about what's changing, using Anaplan versus recreating any of the dashboards and anything, and other PowerPoint, while you're actually demonstrating. So that changes adoption across every aspect of the company. Inderdeep, maybe I go to you next. You maybe share a little bit about what's happening at Medtronic, and then if you could also talk a little bit about the tradeoffs. Every transformation requires tradeoffs. So maybe one of the hardest decisions you made and what you learnt from it. 

Inderdeep Brar 1:24:47.1: 

Absolutely, first of all, thank you so much to Deloitte and Anaplan for having us here today, it's amazing to be part of this all-woman's panel, so thank you very much for that. So I'm at Medtronic, I'm part of the integrated business planning center of excellence. So every transformation really looks great on a slide, but the real tests are the tradeoffs you're willing to make, right? So in our Medtronic's - or Medtronic's integrated business planning transformation, the hardest decision that we truly had to make was standardizing the process, the metrics and the governance. Even when there were real and valid reasons for wanting exceptions, right? So there were pushbacks from the business, right? They weren't irrational, the business unit said, 'Our business unit is different.' The function said, 'Yes, but this is going to slow us down,' and the leader said, 'We're going to lose flexibility.' In the short term, they weren't wrong, right? It was going to slow down, but it was the opportunity to really take and understand that standardization is required in order to really make sure that we're not doing local optimization, but instead doing enterprise alignment. What that really allows us one source of the truth, right? Really getting to that one number. It ensures the ability to do enterprise tradeoffs all across, right? Cross functionally. So I would say the hardest decision really was ensuring that we can have standardization. Then really understanding where flexibility is allowed, right? So standardization more on the what, but maybe flexibility on the how. So how they maybe run their reviews or how they set it up, but really ensuring you have that, again, one set of definitions, one forecast logic, one operating cadence. Then IBP decision rights across each of those forums. 

Inderdeep Brar 1:27:05.5: 

So for us, it's been an interesting journey, and we continue to move forward with it. My comment here is transformation only works when you set that guidance. It's okay to give that flexibility, but just watch where you give that flexibility. Because when you give too much flexibility, yes, you get a lot faster adoption, but then you never get to that one set of the truth or one version of the truth. So yes, I would say, again, hardest decision really has been ensuring standardization and flexibility as needed. 

Dounia Senawi 1:27:48.0: 

I love that. All right, so close us out maybe I ask you all the same question. Piece of advice that you would give for others earlier in the transformation, or you would have wished you would have known early in your journey. So Ellen, I'll start with you. 

Ellen Sipos 1:28:04.7: 

I think that's a great question. If I could recommend a couple of things. One would be know your culture of your company, because change starts on day one and understand how behavior and people respond from a cultural perspective is actually going to impact their rationale for adoption. The reason I say that is because in Johnson&Johnson we're a very relationship-based company. So when we started to do very much like what Kimmy did, we had baseline forecasts. We started to have the transparency that the machine and Anaplan has a better accuracy rate than some of the human interventions that individuals were placing upon that. So that transparency and then what does that mean to me, personally, can really drive a negative consequence, right? Especially in our relationship, right? Am I going to be out of a job? What do I do differently? So having a vision for where you want your resources to be reallocated and spend that time actually will help them understand the vision for why you're trying to drive the change that you need to do. I'm not going to deny that some of it efficiency, but being transparent, understanding how you can take that level of transparency within the appropriate borders, and understanding how that needs to be amplified in a culture with those behaviors. That then a leader needs to exemplify. You can't do it from the center, you all need to be working in orchestration across your business to be able to explain what's in it for me. 

Dounia Senawi 1:29:46.8: 

I love it. Inderdeep, how about you? 

Inderdeep Brar 1:29:48.6: 

Yes, so I would say in my mind one of the most important things in any transformation is really getting your process defined first, before you start playing with the tool, right? When you don't understand the mechanisms and all of the crucial ins and outs that need to happen within the process, you'll never get your tool right, right? So for us, Anaplan has been a great tool, as we continue to build it as our end-to-end enabler of our IBP process. So we continue to first step back and remind ourselves, what are the different steps? What are the inputs that need to go in and what are the outputs that need to go out? So that we can really solidify and ensure that that Anaplan tool really becomes that end-to-end enabler of IBP. 

Kimberly Kim 1:30:41.8: 

I think, for us, it's - I love this term called divergent thinking, and it's thinking of as many ideas as possible for what you want to do, and think big, because I think sometimes we tend to think how we've done things and that feels comfortable zone. I love talking about the throw all your ideas down and make them big ideas and think about how you can do it. We've also been using this theme of tech forward leadership thinking, that we've got to change our mindsets and aligned with divergent thinking. That we all need to be tech-forward leaders. Particularly coming from Deloitte, we also want to be client zero, as much as we can, right? So we want to show that we can execute and we can do all the best-of-the-best processes for ourselves, and to hopefully share that experience with a lot of our clients, to demonstrate, yes, we've done it, this is what we're doing, this is what we've learnt from it. This is how we might share. You think about it [unclear words 1:31:56.7]. Obviously you've got to look at your culture and you need to invest, you need to invest in the technology that's going to get you there. It's a competitive advantage, we all need to figure out how we can free up our time and spend time on more value-added things. Like the machine can tell you the number, now what are you going to do about the number? That's a really important mindset shift. So that's how I think about it when I think about that question. 

Dounia Senawi 1:32:29.8: 

Awesome insights. So vision, divergent thinking, stakeholder alignment, process definition and standardization, finding what's unique to your organization and using that flexibility. Then culture and readiness for ownership. So ladies, thank you so much for sharing your time and your insights and your perspective with all of us. A huge thank you.  

Kerri Vogel 1:32:55.9: All right, thank you, Deloitte, Medtronics, Johnson&Johnson, four incredible women leaders. Does not get much better than this. Yes. [Applause]. Awesome, thank you all.