The need for finance resilience has taken new meaning since 2020 as the pandemic led businesses to cope with the unexpected turn to remote working and the harsh economic impact. Hence, they have been under pressure to rethink crucial processes like cash flow management, demand forecasting, risk mitigation, etc. Now, the finance function is at the front and center of ensuring operational excellence in a business world that continues to be unpredictable.

These recent changes have also led to another emergence – the rise of predictive data analytics as both a continuity enabler and a value creator. Even before the pandemic, enterprises had tons of structured and unstructured finance data flowing through multiple channels. The more future-ready teams already had the analytical firepower to turn this enormous load of information into actionable and predictive finance insights.

And it proved to be hugely beneficial, considering how the pandemic had blindsided enterprises across the world and put them in a tough spot with unpredictable cash flow.

Why CFOs are eyeing at data-driven enterprises

The use of predictive analytics in the finance function runs the gamut – from accelerating routine tasks of finance teams to empowering CFOs to take decisions. It can be used to understand, assess, and predict forecasts relating to sales, volume, or bottom-line profitability. Predictive analytics, also known as predictive modeling, leverages AI, ML, and big data and transforms existing data into key insights for planning, forecasting, and decision-making.

CFOs get armed with the ability to identify opportunities to reduce expenses, manage vendors, and unearth hidden risks. They can strategically increase the financial health of the enterprise by finding answers to questions, such as:

  • What is likely to be spent on manufacturing and distribution?
  • Will the overheads remain constant, or will there be an increase?
  • When is the right time to capitalize on product upgrades?
  • Can future revenue be estimated on new product lines?

The power of predictive analytics cannot be fully tapped into unless it is integrated into the overall financial planning process. Otherwise, it would involve managing inconsistent workflows and dependence on other teams to get timely insights. By creating baseline predictive scenarios, CFOs would be able to plan quicker and more strategically while adjusting them based on expected business changes.

It is also important to note that the predictive analytics solution deployed should come with easy-to-use dashboards with graphs and reports to efficiently showcase the data. The more cutting-edge solutions are interactive too, which means that users can modify the variables and look at real-time results. After all, great user experiences can make a lot of difference to how successfully predictive analytics can be harnessed.

How predictive analytics can transform finance capabilities

Enhancing supply chain management

Inefficiencies in the supply chain can be detrimental to profitability because vendors and third parties can make or break enterprise adaptability, flexibility, and momentum. With predictive analytics, it becomes easy to accurately evaluate vendors based on performance and vulnerability – thereby strengthening the supply value chain.

Managing cash flow

Cash flow management and forecasting are key to planning the annual budget. Data insights can reveal gaps in receivables, identify trends in delayed payments, helping the finance team to streamline the process to avoid pitfalls. Predictive analytics can improve the receivables aging processes and highlight any deviation from payment patterns, making collections faster.

Ensuring smarter budgeting

Developing the right budget is a pivotal moment because it sets the pace for the year ahead. But underestimation can prove to be a big hurdle later on while trying to cope with market dynamics or respond to customer demands. Overestimation is just as bad since it can lead to missing out on timely investments. So, predictive analytics can be a lifesaver for budgeting. It can spot the most granular of trends, understand current patterns, and provide insights to maximize enterprise-wide budget ROI.

Strengthening demand planning

Accuracy in demand planning is dependent on the accuracy of forecasting data on products, partners, and customers. Predictive analytics takes into account several internal and external factors to enable CFOs to help eliminate bad investment decisions. As product teams grapple with developing features and pricing plans, finance team members often play a passive role in the product journey. With predictive analytics, they can provide key information to reduce product returns, decide the right time for a product to be scrapped, etc.

Identifying financial risks

Financial risks, if not addressed, often cause a severe cash crunch. Predictive analytics can help establish the baseline criteria, identify outliers, and provide insights to avoid any impact on the bottom line. For example, it can detect potential instances of fraud across internal workflows like purchase orders and external workflows like vendor invoicing.

Optimizing resource management

These days, managing resources can be an insurmountable task without the availability of predictive data. CFOs and their teams can use it to assist HR and other business functions to better shape hiring decisions, increase retention and even improve employee engagement.

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As evidenced by recent events, no finance team wants to be caught off-guard by external factors that could potentially derail operations. However, unpredictability is such just when they think they have all the answers – the questions are inevitably changed. It’s why predictive analytics plays such a critical role – it can empower the CFO to predict tomorrow’s questions today.

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Chenthil Eswaran