From Algebra to Calculus: Financial Planning in the XaaS Economy

For cloud businesses, planning, budgeting, and forecasting are worlds apart from the norms at traditional enterprises.
Hyoun Park and Scott PezzaJune 30, 2015
From Algebra to Calculus: Financial Planning in the XaaS Economy

When it comes to cloud-based anything-as-a-service (XaaS) businesses, the types of planning, budgeting, and forecasting (PBF) strategies that have worked for more traditional product-focused enterprises just don’t fit. From long-term strategic plans to annual budgets, the reality of recurring revenue businesses calls for a different — and more agile — approach to these processes.

Hyoun Park

Hyoun Park

While software-as-a-service (SaaS) companies tend to get most of the press in the recurring-revenue arena, they’re not the only ones working through these issues. Any business that augments its asset sales models to include asset rental (or lease) needs to adjust its PBF practices. So too does any organization that features usage-based pricing such as per-sheet fees for photocopiers, per-gigabyte bandwidth fees for website hosting, or per-processor core hour fees for cloud computing.

In all of these models, customers forego longer-term asset ownership to reap short-term savings. The result, however, is that the cycle time for contract expiration — and potential customer churn — is accelerated. It’s all a function of time, and shows how a compression of the customer lifecycle forces a readjustment of PBF processes to respond in turn.

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Doing the Math: Algebra vs. Calculus

Why are things so different now? At base, it all has to do with business velocity. In the older, product-centric environment, you think about your business in annual cycles, with starting periods adjusted to smooth out any predictable seasonality in your particular industry. You look at growth linearly, plotting out fiscal years 2012, 2013 and 2014 and finding the line of best fit to predict what 2015 will look like.

Try this analogy: traditional planning is like algebra: plotting some points, and finding the old-school y = mx + b slope to understand what’s coming.

Scott Pezza

Scott Pezza

Recurring-revenue business planning, in contrast, is like calculus. With business viewed on the basis of monthly recurring revenue (MRR), the relevant time periods for analysis are much, much shorter. We look at those recurring revenues, new-customer-acquisition velocity, and churn rates to paint a picture of the rate of change at a given point in time.

In this environment, this-coming September’s expected revenue pays a lot more attention to August’s base, new acquisitions, and churn than it does to last September’s numbers with a reasonable growth factor applied. It’s a fundamental difference: that of moving from a static representation of what the business is to a dynamic, constantly changing understanding of what it will be.

Less Sizzle, More Steak

Until now this article has been, admittedly, a bit heavy on analyst-speak. Let’s be a bit more practical from here on. Your planning process focuses on setting realistic goals and tactics for attaining them. Budgeting then picks up to allocate internal investments to support those plans. And forecasting provides — in the best-case scenario — a reality check on where the business is headed from a results perspective.

Planning. When constructing our one-year operational plan, we’d traditionally have our eye on the popular metrics like gross income, net income, earnings per share (for publicly held companies), and EBITDA. Our growth projection is based on a linear projection of earnings. That’s what we’d feed into the budgeting process: expecting a 5% increase in sales, derived from a corresponding 5% increase in units shipped (assuming we maintain pricing).

But in a subscription-based world, we care much more about the activity associated with customer acquisition, customer churn, and product utilization in understanding what will happen in the future.

Budgeting. With that 5% expectation in mind, our functional heads provide their bottom-up budgets for what it will take to achieve the goal. In its most charitable form, it’s an exercise in allocating resources, deciding how many dollars are necessary to provide some required amount of capacity. In its least charitable form, budgeting is an exercise in expanding fiefdoms, with managers seeking to grow their spheres of influence — and ensuring, over the course of time, that those budgets are exhausted to prevent them from being cut in the next round.

In a more subscriber-driven world, budget is based on the expectations of utilization and activity. As capex flip-flops from being the majority of budgeted costs to a category subservient to opex and activity-dependent spend, budgeting changes from a fixed cost to a variable percentage of revenues that may be gated or altered at various levels of commercial activity.

Forecasting. Rather than looking at goals, now we switch to actuals. We’re most likely exporting some historical balance sheet and income statement lines to Excel and looking for trends: 1 million widgets shipped in 2012, 1.1 million in 2013, and 1.21 million in 2014, so we’re expecting 1.33 million this year. We see 10% bumps in past periods and expect similar results.

Some industries might have a bit more nuance, so we’d recognize that our sales track with some industry-wide metric, like doorbell sales tracking to economy-wide new housing starts. There, still, we’d look at annual changes in the underlying driver, expecting what has come before to continue, absent more informed economic guidance to the contrary.

With the subscription-revenue model, not only is it important to forecast based on corporate, microeconomic, and macroeconomic drivers, but based on solution adoption, upselling, and expectations for service and product updates, either to stay ahead of the pack or maintain parity with competitors.

Getting to the Point

So what does all of this mean? It means we have a lot more work to do — and more quickly.

Planning metrics for recurring-revenue businesses look a lot like those for traditional companies, with lifetime customer value, customer acquisition cost, upsell velocity, cross-sell growth, and things like seat-based or usage-based utilization measures loaded on top. To properly budget for operations in a dynamic environment, we need accurate financials as a starting point. That means being able to run through consolidation and close in days, not weeks. That’s the only way to accurately plan resource allocation and ensure adequate capacity to support a business whose growth can look a lot more like the so-called hockey stick than a straight line.

In traditional environments, we may expect to sell a million widgets, and we can plan backward from there to ensure adequate logistics support, manufacturing capacity, and raw materials inventory. In a recurring-revenue business where the number of seats required, processing cores utilized, or transactions processed can grow exponentially, we don’t have the luxury of planning technology infrastructure, sales headcount, or support capacity on an annual basis. We need to not only have visibility into performance close to real-time, we need to have planning and budgeting processes that operate in this accelerated timeframe as well.

That’s why companies across all industries need to think about their subscription billing strategy in the context of existing financial planning and financial accounting tools. Without a subscription strategy, companies will be left unable to effectively bill and manage a new business environment dependent on complex and recurring revenue transactions.

In this context, Blue Hill looks forward to seeing how financial software solutions and financial modules will continue to partner with the likes of Aria, goTransverse, MetraTech, Monexa, Recurly, Vindicia, and Zuora to integrate the future XaaS world into existing corporate finance operations and bridge the gaps to the future of conducting and managing customer and service-centric business.

Hyoun Park is chief research officer and Scott Pezza is principal analyst at Blue Hill Research. This article was first published on Blue Hill’s website.