Why finance leaders need predictive intelligence now

There will be no return to ‘business as usual’. The COVID-19 pandemic has seen CFOs and business leaders across HR, supply chain, and sales make difficult decisions that balanced short-term choices with long-term impact. Now, finance teams need to consider all options and be confident they are making the best choice, whether that impacts employees, customers, suppliers, partners – or all of the above.

The pandemic upended ‘business as usual’ so quickly that businesses lack the historical data to guide solid decision-making. However, scenario modelling can fill in those gaps, helping finance leaders and the C-suite anticipate the future. 

Swift decision-making

CFOs and finance leaders should look at their key stakeholder groups, identify their risks, and create models for the worst-case and most likely outcomes of the business decisions you could make. Then, you can weigh up the costs and make a final decision with confidence.

Start by deciding the scope and issues that need to be addressed immediately, while defining your key drivers – it may have been growth a week ago, but now it might be a question of continuity. Next, collect and analyse the quantitative and qualitative data you’ll need to make your key assumptions.

Once you have the foundation in place, you can start developing the different scenarios. Consider what scenarios are most important or likely for your LoB, and start there. Define what the impacts of each will be on sales, cash flow and capex, then decide what metrics you’ll use to measure each. Finally, monitor the plan constantly and consider if you’ll need more frequent reporting to respond to changing metrics. 

However, current disruption can make accurate scenario modelling a tall order. There are a huge number of stakeholders to consider, and the data they need is often scattered across different data environments. 

To make the task easier, business leaders need to involve fewer people in the process and limit the number of scenarios they consider. Modelling no more than four is advisable, but be sure to spend equal time on each, even if you think certain models are less likely.

Making the most of AI

Of course, scenario modelling is only one part of the solution. Unprecedented amounts of data can be a blessing and a curse without the right support. CFOs, like all leaders, can be overwhelmed by masses of new data alongside the many data management responsibilities that come with them. Data collection, cleansing and security can drag business leaders away from prediction and strategising. Without assistance, they can’t work at the speed required.

To help carry the load, leaders should consider what they can streamline and automate with AI. AI solutions can analyse and interpret vast quantities of data in little time, making it invaluable for scenario planning. It can also automate the many repetitive but necessary tasks associated with data management.

However, it’s worth tempering expectations and being realistic with where the technology is deployed. Companies often struggle to deploy the technology at scale and have unrealistic expectations for it. The last thing you want now is to embark on a costly and ambitious moon shot that fails to meet your objectives.

To make the most of your AI investment, you should both buy and build applications. You don’t need to build everything from scratch, and doing so could create compatibility issues later on. What you need is a strategic approach that delivers interrelated solutions that maximise the benefits of AI, rather than rolling out a series of disparate solutions.

Special attention should also be paid to data quality. It needs to be complete, cleansed and up-to-date for an AI solution to deliver accurate insights. Fortunately, AI-driven data engines can cleanse and enrich data records before they are served up for analysis.

Another important consideration is tuning. AI ‘maintenance’ is usually performed expensively and manually by data scientists, but it’s hardly feasible when your organisation has hundreds of AI models to maintain. Applying machine learning to this process automates this expensive task, keeping costs under control. 

Weathering the storm

There’s no silver bullet for business disruption – and there’s no quick fix for CFOs and finance teams who want to do the job right. However, scenario modelling and AI intelligence can help organisations weather the storm. When detailed, comprehensive models are combined with AI efficiency and human judgement, businesses will make better, more impactful decisions that help shine a way through the crisis.