Demo Video: Anaplan for Hypergrowth & Fintech Organisations

Use Anaplan to plan and compare customer growth, revenue projections and cost forecasts both quickly and flexibly. Create a continual, real-time process, which can keep up with the rapidly changing organisation and markets.

To find out how Anaplan can help, contact us for a personalised demo.

Transcript

[Music]. In this session today, we’re going to take a look at how connected Financial Planning and Reporting in Anaplan can right across the organisation help hyper-growth and fintech companies to both plan and compare customer growth, revenue projections, and cost forecasts, both quickly and flexibly with the data plan. It becomes a continual real-time process that can keep up with rapidly changing markets as well as the rapidly growing organisation. The result? Well, this allows companies to make the best use of their data, turn it into information in the business to make better-informed decisions.

So let’s begin then by taking a look at what we have on screen here. Well, to start with, we’re in an app within our plan. This app is focused around generating customer forecasts for new customers. It’s also looking at churn around those customers as well. Now, once we’ve got that information, we want to think about how much those customers are interacting with us on the basis of the number of transactions and the value of those transactions. When we’ve got that information, we can then start applying revenue drivers to work out a revenue plan, a revenue forecast, as we go through our planning horizon. And indeed, as we extend this model into a rolling forecast, we’re also thinking about other revenue. In this case, advertising revenue.

Now, in this model, we go down as far as gross margin and net income by bringing in our cost of sales based on driver-based calculations. But we’ll also be seeing how we want to extend right through to a full P&L, balance sheet, cash flow. Ultimately, you might want to produce an IRS consolidation out of Anaplan as well. All that’s possible.

Now, when we’re doing that planning, we can very quickly make use of what-if scenarios within our plan. Versions are built into the DNA of the product, so it’s very easy for us to quickly spin up new versions, change some of the drivers, our assumptions. In this case, maybe around customers and churn, maybe around our revenue drivers to very quickly and effectively see what the impact would be when we look at those scenarios side by side. Everything’s driven in here by assumptions, drivers around what we’ve talked about around revenue, around customer churn, and so forth. But all the time, there’s the ability to have just purely keyed-in costs and revenue figures as you would do in a grid of an existing spreadsheet, for example.

Ultimately, we want to make use of this data both within these planning screens that we’ll be looking at, but also we might want to generate some management reporting output. The extent of that might be a reporting pack that’s produced monthly. It might go down to those full financial statements. It might be something around KPIs. It’s really down to you to decide, but we have those rich management reporting capabilities built into the software.

So we want to cover off as much of that today. Now, I briefly mentioned apps, and I briefly mentioned connected planning. Let’s think about how they fit together. So if we look at the process flow here, a typical Anaplan implementation. You’ve got, of course, source data coming into Anaplan. Source data you need for planning purposes. That may come from other cloud data sources, it may come from on-premise relational data sources. It can, of course, come from spreadsheets and flat files as well.

We’ll bring into Anaplan all the data that’s needed for planning into the concept of a data hub application. From there on, you’ve got your various example apps, just like my revenue app we saw just now as an example of an app in our plan. So, connected planning means connecting the people, connecting the data, and connecting the processes. Well, we can see here we’re connecting the data, all the data we need into one verified, reliable source for planning purposes, and we’re connecting the processes as well. So, people are involved in FP&A, people involved in demand planning can not only share the same reliable source historic data for planning purposes, but also, if you’ve got an output, for example, from demand planning that says we need to hire 10 new people next year, workforce planning can be connected across all these apps, seeing just the output data they need to see from here, so they can then take forward their plans based on what other people are doing within their applications as well.

Back in the app that we’re going to focus on today then, in our plan, let’s jump in straight away and look at the output. In this case, it’s a gross margin and net income output, and we can see very quickly one of the main differences of how we differ from spreadsheet-based modelling, and that’s through the use of what we call multi-dimensions. Up here, we can see we’re looking at a combined, aggregated data set for all channels, in this case, all cohorts and across one of our versions that we have available at our fingertips within the model. We’re going with the best-case books, so we can easily compare and work with many versions.

I’m also looking at all my channels, but I might want to go down and split my channels between face-to-face and my app-based channels. I might particularly want to look at Affiliate 1, who’s using the app and where the revenue is coming from or where the costs are coming from. And there, I’m looking at all my cohorts. I might want to split that out and start to investigate individual cohorts in terms of customer numbers and influence where my revenue sits today.

Now, here, this particular business is earning a lot of its revenue from a share of interchange fees from transactions. I want full visibility of where that detail comes from. And it’s simply a case of clicking F8 or drilling down on a particular calculated line. And then anywhere in our plan, we always have that full visibility of what’s generating this output. In this particular model, we can see here it’s total number of transactions multiplied by our revenue drivers, which are our average transaction value multiplied by our interchange fee percentage, and we can see all the elements that are generating that 131,000 that we see there as a result of our calculation.

So how did we build that final gross margin and net income position up? We built it up by driver-based modelling. We’ll look at one or two of those elements of that now. Here, we’re looking at the customer growth. Okay, so we have cohorts month by month. They will get older, of course, as time progresses, and a term will then apply to the age of those cohorts. Here, anticipating, as customers get to two or three months, the churn rate, which falls dramatically. We might want to base that on directly entered figures in here. We might want to revise that churn rate as we go forward and get more actual data to give us a better feel for how customers are churning.

We’re deciding on a cohort by cohort basis how many customers we’re anticipating signing up. Here, we’re applying individual manual adjustments, maybe locally to a planning manager. But then globally, they’ve decided, “Look, we really need to have a 10% uplift in the number of customers we are generating.” So we’re applying a 10% uplift that’s going to override any individual adjustments, and that gives us a starting point on a month by month, cohort by cohort basis of how many customers we’re going to be acquiring and churning, giving us a closing number of customers per period.

We can then think about, in the same manner, the transaction value, number of transactions, and the value of those transactions that will be applied to those customers and how those customers will engage with us. And those transactions will be subject to revenue drivers. In this case, we are looking at an affiliate by affiliate, cohort by cohort, across our different versions, earning money via interchange fees, percentages, and amounts, other fees. It may be a subscription amount on a monthly basis. The interest is how you have how you want the revenue model, revenue or any other things within Anaplan is totally down to your processes, but Anaplan’s got the power to cope with that on the level of granularity that you require.

Now, when I’m modelling, I want to be able to take all of my output that I’ve generated from my plans and start to think about what happens if I change some of those drivers. What are the what-if capabilities within Anaplan? Well, here, we can quite clearly see that I’ve got my multiple versions across the top here. My best case, middle case, comparable. At the moment, there’s no difference between the two. I’m allowing myself very quickly, though, to be able to say, “Okay, if I take my middle case, my middle case version, and apply an adjustment here from 1.4 to 10, I can immediately see the impact of that on my net transaction value right through to my head income.

I might want to overlay a new adjustment on top of that. Equally, by changing maybe the number of customers that are going to be interacting with me, therefore, my middle case, I want to double that. Let’s make a big change on there just to illustrate the point. That’s going to go to 20,000, and now I can see immediately, instantaneously, the impact of those two adjustments on my best case versus my middle case scenario.

We’ve just moved across to another application here where we’re focusing on another very big cost for organisations, and that’s, of course, workforce costs. We can see we’re planning that in a similar way, using the power of dimensions in our previous model. We’re looking at this down to an individual person level, to cost centre, to business unit. Of course, we can apply security at that level as well to restrict this obviously sensitive information. We’re splitting it between existing and new hires. We’re splitting our plans between different roles, and we’re also doing this on a version by version basis, and of course, for a specific time period. So we’re capturing an individual level all the relevant information we need to drive our costs. For example, start dates, end dates, termination dates. We’ve got salaries per role with the capability to do manual overrides. We’re looking at salary increase percentages, salary increase months. Really, this is an example. So all the drivers you need to generate all your full people costs within your business can be built into the model. The output of this becomes reports around what’s my employee headcount looking like between my different versions, that one down here. What’s my total salary cost looking like between different versions? What’s my split of individual all individual people costs but also aggregated up to a full picture of how that looks for the organisation. So, it’s a very important part of planning that we need to think about as well in Anaplan.

Of course, we also need to think about the concept of rolling forecasts as well because we’re not just planning in isolation. When those actuals start to come in, we want to be able to attract those actions against the remaining forecast, revise that forecast, and also not just look out to the end of the year but potentially look out further forward as well, indeed as far as you want to look out within our plan. It’s easy to create those rolling forecasts and combine the actuals when available and then start to reconsider the remaining values in those open periods. So, a fundamental part of how we allow you to plan in Anaplan as well.

And finally, I want to make the most of the output from my planning and forecasting processes, and I want to do that still within the Anaplan tool. I don’t have to shift any data outside of Anaplan, and I can do that within the management reporting capability that’s built into Anaplan. Any of the output we’ve seen today, any of the data input screens can all be dropped into a management report or reports within Anaplan, which gives you a very rich reporting layer which can be, if I just jump into the page of my report here, this can be extracted out as a whole copy out to PDF and distributed as required. Alternatively, and perhaps more useful, is as a replacement for an online deck of slides whereby I can present my output within a meeting and have full ability to filter my views up and down to find exactly the data I want to focus on and find exactly the result of a variance, for example. All built into Anaplan and improving a very popular in terms of making greater use of that output, enabling that decision-making process to take place [Music].