Predictable business model: finding stability in economic uncertainty

When the economy faces volatility, CFOs have the daunting task of delivering a healthy balance sheet regardless of market uncertainty.

While major unexpected events like the pandemic could thwart even the most detailed plans, careful planning can give CFOs a better position to deal with the challenges ahead.

At a time when job security and revenues are at risk due to an economic downturn, Todd McElhatton, CFO at Zuora, believes that CFOs can leverage predictable business models to mitigate the impact of economic fluctuations and position themselves for success.

Businessses opt for predictable business model

A predictable business model gives CFOs an estimate of how much revenue their business will generate in a given year. Such information gives CFOs a better insight into their financial situation to plan for the future.

The framework has gained traction in recent years as firms look to navigate through economic uncertainty and operate with more confidence.

A 2022 EY survey of 1,200 businesses found that 52% of companies intended to shift from subscription to consumption models to pursue a more predictable revenue stream, highlighting the increasing popularity of predictable models among CFOs.

Stability via predictability

Having revenue forecasts enables CFOs to better plan for the future and make informed investment decisions. This improves business stability because CFOs can then plan the year ahead based on available or predicted resources to reach their objectives.

“When CFOs have secured the majority of the revenue for the year, they can better plan for the period,” McElhatton says.

“They can plan what investments to make in their products, marketing, and human resources. They do not need to constantly shift priorities, which leads to better satisfaction for everyone involved.”

With funding allocated, businesses can continue to invest in their priorities without making many changes.

This boosts confidence among the employees as they do not face sudden project cancellations due to economic challenges. Investor and customer confidence also improve as companies continue to deliver on their targets despite market volatility.

Challenges in implementing the model

However, establishing an effective predictable business model is not a straightforward task.

Varying revenue streams and data points deliver different predictable models. Since new products and customer behavioural changes impact the revenue streams, businesses need to be able to assess the data points for forecasts.

Taking an example of a subscription-based business, McElhatton explains, “in a subscription-based model, businesses are super dynamic, because companies are always innovating, adding new products, and needing to make changes. Maybe when the time comes for renewal, customers’ priorities may have changed. They may want to switch to a consumption type model because they are unsure about their consumption pattern.”

Businesses can rely on third parties to analyse those data for the predictability. However, he believes that they also need to have the “agility and flexibility to meet the customer where they want to be.”

Influence of customer relationships

Complexity also lies in establishing customer relationships in a subscription model.

Businesses need to look beyond the delivery of their product and track the changes to their subscription plans.

He says that there is an added layer of complexity because firms need to establish ways to bill the customers to recognise revenue.

“Because if CFOs do not get their revenue recognition, the last thing they want to be in is in a situation where they have to go back and do a restatement. So, they need real-time visibility into their metrics and dashboards,” he adds.

Having real-time visibility gives the CFOs a reliable indication of their cash management strategy, which they can adjust as required.

Transitioning to a predictable business model

As businesses adopt the predictable business model, McElhatton says that it is important to realise the likely changes to the revenue streams. Therefore, they need to set up an appropriate infrastructure involving the finance team as well as the rest of the organisation, including the operations, products, and customer success.

Firms will need to prepare for ongoing collections and revenue recognitions while being well prepared to manage and oversee their customers’ satisfaction.

Additionally, he says that organisational understanding of the situation is also imperative for a successful transition.

After all, alignment from different teams within the organisation will enable the business to successfully deliver its service to the satisfaction of its customers.

State of automation and AI 

According to McElhatton, automation can give CFOs a huge advantage in delivering their objectives.

He says, “Automation eliminates repetitive tasks, low value and unexciting. Eliminating such tasks can lead to increased costs and efficiency. That is a net improvement.”

Designating such tasks to automation leaves employees to focus on high-value responsibilities, which he says leads to better employee satisfaction.

A 2022 Gartner survey revealed an increasing CFO focus on automation investments to drive down costs and boost efficiency. 32% of respondents identified pricing optimisation analytics as one of the top three priorities.

Besides automation, he also notes the potential capabilities of AI to further support CFOs in delivering a successful business model.

CFOs have been deploying generative AI within their ecosystem to better communicate with customers to offer quicker resolutions, providing greater customer satisfaction whilst saving costs for the business.

However, he adds that since technology is new CFOs are slower to implement AI solutions to take on the bulk of finance work.

He explains, “From a CFO perspective, I need to have absolute accuracy when reporting numbers. Until we are comfortable that AI is bulletproof and gives a high level of accuracy, it will probably take CFOs a little bit longer to implement AI solutions for taking over work in a CFO function.”

His sentiments are echoed in a Deloitte report, which states that CFOs are yet to witness the full potential of machine-powered forecasting.

It reads, “CFOs may be hampered by fragmented data, inconsistent processes, and limited reserves of talent. Or maybe finance leaders have yet to master data quality or to aggressively pursue the replacement of outdated systems.

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