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How can predictive analytics and financial forecasting help finance teams?
Blog //22-02-2022

How can predictive analytics and financial forecasting help finance teams?

by Amanda Grant, Chief Product Officer

One of the most important Financial Planning & Analysis (FP&A) trends to watch is predictive analytics. Over the past two years, many businesses uncovered glaring points of weakness in their financial, planning, and analysis processes and systems as a result of unprecedented world events.

In FP&A, financial analysis is vital for enterprises to maintain their financial health. The problem with traditional planning strategies, however, is that it keeps finance teams busy acquiring data rather than spending time on higher-value tasks. Using outdated technology in conventional forecasting leads not only to inaccurate results, but also delays the decision-making process.

The ability to provide more accurate and better forecasting is every finance team's goal. In the world of financial planning, predictive analytics can make it easier for finance teams to make timely and accurate financial decisions to help them achieve their organisational goals.

As a CFO, looking out for only a single scenario is not enough. Planning for the future will help you anticipate risks and opportunities and better understand these uncertainties. With predictive analytics, financial data can be used as a tool to identify trends for better planning, forecasting, and decision making.

What is real time predictive analytics?

CFOs can use real-time predictive analytics to analyse historical data and seasonal insights in order to make business-wide decisions that make it easier to accelerate growth and make more robust decisions.

Utilising Cloud accounting software to enhance forecasting is key; it pulls in real-time data from sources across the organisation and updates projections automatically to account for market changes or missed assumptions.

By using advanced data analytics methods, predictive analytics allows for the prediction of future events and outcomes. This approach is agile, comprehensive, and data-driven, which supports overall planning and executive decision-making.

Finance teams can then focus on analysis and enable appropriate business decisions instead of just collecting data. Finance teams can forecast mission-critical actions that impact the business by utilising this ability to "see into the future." Such endeavours include sales trends, consumer behaviour, and supply and demand.

Although it's not possible to completely prevent economic downturns, using predictive analytics can help organisations become more prepared. Ultimately, businesses who embrace and analyse data to predict and identify scenarios will be able to reap long-term rewards as a stronger ability to forecast will pay dividends.

What is an example of predictive analytics?

Using predictive analytics to forecast financial results provides finance teams with insights to answer questions, identify trends, and analyse data, as well as helping executives strategise and make critical business decisions faster.

The process of conducting a predictive analysis can be carried out manually or through the use of machine-learning algorithms. Both approaches use historical data as a basis for making future predictions. Using forecasting combined with predictive analytics can help finance teams make better decisions and formulate more data-informed strategies based on fact instead of assumption.

Which financial processes can be improved using predictive analytics?

To efficiently forecast future performance of your organisation, you must keep periodic financial records. Predictive analytics can play a big role in forecasting your organisation's future.

Using historical data from previous financial statements, as well as data from the broader industry, you can project sales, revenue, and expenses to craft a picture of the future and make decisions. Bottom line, CFOs need to be looking ahead to plan for the future health of their business. 

Predictive analytics can be used to improve or enhance many routine processes, such as:

Forecasting cash flow

Managing cash flow is a critical element of planning a business' future cash needs to avoid a liquidity crisis. Insights from data can assist financial professionals in identifying slow payers, recognising and resolving system issues, and improving receivable management.

Identifying financial risks

To make it easier for financial departments to identify outliers before they cause harm to the overall performance of the company, predictive analytics can be used to establish baseline criteria.

Demand planning

With predictive analytics, it is possible to forecast sales over a period of time, determining the demand for the product. This will reduce returns by customers and scrapping of products, boosting profitability.

Risk management of company performance

Finance professionals can also use predictive analytics to gain a “sneak preview” of the upcoming financial mid-period and avoid surprises.

Receivables aging

Setting alerts when customers deviate from past payment patterns allows finance professionals to optimise receivables aging processes and collect overdue amounts efficiently.

How can predictive analytics and financial forecasting help finance teams? 

Essentially, it allows your finance team to predict outcomes more accurately, expose hidden risks, act quickly, and gain a 360-degree view of your current and future finances.

With data-driven stories used to make better and faster decisions, CFOs and their finance teams can become trusted business advisers that organisations can rely on to guide them even during the most uncertain and turbulent times.

Finance teams will need effective methods for generating and distributing real-time forecasts that respond to rapidly changing conditions in order to meet business demands. For the same reason, it is critical that FP&A processes be automated via dashboards and other digital tools, so that data can be updated frequently and viewed from multiple perspectives.

This vision is crucial to widespread adoption of advanced analytics and CFOs are well positioned to provide it. Most of the necessary data is in their hands, and they have the traditional quantitative expertise to assess the real value to be gained from analytics.

CFOs and senior management require financial models that inform strategy at the speed and with the insight of true innovation as finance enters a new era of digital transformation. However, forecasting work is often created ad hoc and done on a siloed basis.

You need the right FP&A solution to succeed - and the financial health of your company depends on it. To be digital-first in FP&A, you need to adopt strategies that are centred on automation, agility, transparency, and metric-based insights. This is where Cloud accounting software comes into play.

What are the benefits of predictive analytics?

Get your business future-ready

Even though it is impossible to fully prevent economic downturns, predictive analytics in the Cloud can help organisations plan ahead and be prepared for them if they were to occur.

Forecasts that are accurate

In the modern corporate landscape, forecasting plays a critical role in planning and production. By choosing the right predictive analytics, your finance team does not need to rely on external sources or lose time manually inputting complex formulas into Excel spreadsheets for data-driven planning.

Systems for Cloud accounting software pull in real-time data from a variety of data sources throughout the organisation and re-forecast automatically to take into account market changes or missed assumptions. As a result, the finance team is focused on analysis and business decisions instead of data collection.

Make decisions with agility

Your finance team can confirm, enhance, and review financial decisions with data-driven predictive analysis, leaving less room for errors and more room for valuable and constructive decisions.

Automate tasks to save time

Data is analysed, compared, and converted in real-time using automated predictive analysis and machine learning algorithms. By automating these previously manual tasks, finance teams have more time to focus on the value-adding work of carrying out agile finance predictions by leveraging real-time analysis.

Campaign planning

Consumers today have more options than ever before. You can determine the most beneficial time and channel for marketing campaigns by analysing all of the data you have to hand, such as purchasing patterns, buying behaviour, and web browsing. A detailed forecast will help you avoid wasteful spending and boost the effectiveness of your finance team.

Reduce cost and effort

This approach allows for cost-effective planning and sourcing while minimising manual data collection and analysis. The approach can assist finance teams with financial budgeting, evaluating external suppliers, and determining internal policies.

Predictive analytics: the next step in business intelligence  

CFOs looking to leverage predictive analytics are positioning themselves not just as forward-thinking finance leaders but also as valued business partners to other leaders in their companies.

Those who aren’t will need to reconsider how analytics programs could change the way they work—and then lead by example. But of course, CFOs cannot lead digital transformations alone; they should serve as global conveners and collaborators, encouraging everyone, including leaders in IT, sales, and marketing, to own the process.

At OneAdvanced, we hold expertise in forecasting, automated planning, budgeting, and robust reporting. We are committed to providing practical and strategic guidance to prepare your company for increased success in the future.

Our Financials accounting software is here to empower your finance team through the use of predictive analytics, with forecasting, automated planning, budgeting, and robust reporting in real time. 

Blog Financial Management Advanced Financials
Amanda Grant

Amanda Grant

PUBLISHED BY

Chief Product Officer

Amanda joined OneAdvanced in 2018 and was promoted to CPO in 2019 following a successful stint as Product Strategy Director, being responsible for the correct investment decisions.

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