Every CFO is concerned with analytics in finance, but they don’t have the capacity to be bogged down with irrelevant or inaccurate data. The importance of financial analytics is far-reaching as it impacts every major business decision, so it’s of great emphasis to prioritise data and analytics.
In this article, we will dive deeply into the world of financial analytics, from covering the challenges of procuring analytics to unraveling the solutions that can help make it easier on your team.
Finance analytics are the result of large volumes of financial data that provide insights into the financial health and status of a business. Depending on the data used and methods applied, financial analytics can offer different views and perspectives of a business. So, it’s important to know what you are looking to answer or achieve before you get started with analytics in finance.
In many cases, financial analytics are based on historical data which can be used to forecast and predict future events through the application of big data analytics.
With access to accurate and timely financial analytics, business leaders are equipped with the knowledge they need to make optimal and strategic business decisions.
There are massive amounts of data being collected on a daily basis. This can become a major challenge for businesses who have disconnected systems or rely on manual computation.
While relying on manual efforts to collect, transform, and utilise data, financial teams end up spending valuable time in the details of the data rather than being able to gain insights and share their analysis.
From a broader perspective, CFOs and business leaders need up-to-date access to the financial analytics they need for their situation at hand. This requires being able to source and pull specific business information at a moment’s notice, which again, is hard to do without the use of technology or automation solutions.
Furthermore, it’s not just the internal considerations of finance analytics that need to be taken into account. There’s more regulation and compliance required with each passing day. CFOs and finance teams need to be able to report data analytics to both regulators and stakeholders with utmost accuracy or they risk facing detrimental and costly consequences.
This is why so many companies are turning to finance automation software to help ease the burden of analytics in finance. They realise the value that exists in having centralised, controllable, and transparent data and data analytics that are streamlined and accurate.
With the ability to execute data analytics on data you can trust at any point in time because it’s connected, cleansed, and concise, finance teams, stakeholders, and regulators alike can all access reliable finance information.
When faced with any decision, you’d probably want to look at data and references to know how to move forward. In terms of making business decisions, it’s an absolute must because otherwise you will be left guessing on decisions that can end up making or breaking the business.
The finance function is at the heart of every organisation, so being able to understand and interpret financial data is what creates both a competitive and strategic advantage.
Since the world of business is fast-paced and constantly changing as new data is generated, financial analytics can only be as strong as the data that is used.
Analytics in finance play a role in impacting all business units, and also are responsible for:
Both the C-suite, IT teams, and finance departments get involved with the ins-and-outs of finance analytics. As such, it requires a cohesive approach to make the most out of the resources that you have available.
You’ll want to make sure that every department is able to get the answers they need using financial analytics for their respective concerns (i.e. marketing can understand how campaigns impact sales, sales can access quotas and commissions, CFOs have what they need to make timely decisions, etc.).
In order to design your business’ infrastructure to optimise analytics in finance, there are core capabilities that should remain at the top of your mind. These include:
Having the ability to make quick decisions based on financial analytics and to execute continuous improvement with time.
Being able to respond and adapt to changes in regulations or anything else without having to totally reinvent systems, processes, or workflows.
The alignment of execution with strategy to achieve business goals and gauge success based on a clear set of metrics.
The possibility to expand finance analytics capabilities as the business grows or more data is collected without having to start from the beginning again.
Providing CFOs with detailed insights and a deep understanding of the interaction between costs and revenues so that CFOs can make decisions that maximise revenue while minimising costs.
Once you’ve made a mental note of the core capabilities of analytics in finance, you’re on your way to being able to utilise the various types of financial analytics to benefit your business.
Here’s a look at some of the many types of financial analytics and what they can each be used for:
Sales revenue is a primary concern for any business. With predictive sales analytics, finance teams can create forecasts based on past trends or correlation analysis. This helps to manage the business optimally in times when sales are booming and also when sales are slacking.
When businesses offer various products, it literally will pay them to know where they make and lose money. It could be the case that the cost of producing and marketing an item will end up outweighing the sales of said item.
Product profitability analytics will provide you with this knowledge. This way, business leaders can choose where to allocate their resources to make the most impact on the company’s bottom line.
Cash flow can be considered to a business what blood is to a body. It’s necessary to function and stay alive.
Cash flow analytics stem from real-time data such as the working capital ratio and cash conversion cycle. It’s also possible to perform statistical functions like regression analysis to predict cash flow in the future.
Remember when we said that analytics in finance isn’t just valuable for the internal business functions? Shareholder value analytics takes into account the return on investment that a business provides to its investors.
Going deeper than that, shareholder value analytics are used to determine if a business’ strategy is working or not.
We’ve given a high level view of the type of analytics in finance. But even from the summarised list above, it’s clear to see that financial analytics affect every aspect of business.
As the volume of data exponentially grows, it becomes increasingly difficult to rely on the manual execution of financial analytics. It’s also highly error prone by nature. To overcome challenges of analytics in finance, financial automation solutions can be implemented to ingest, process, and report analytics in finance more quickly and with fewer errors.
With an automation solution, each respective stakeholder, both internal and external, can gain access to the exact type of analytics they need through customisable dashboards and reports.
Connecting to all system including legacy systems automation removes tedious manual tasks freeing up time for insightful, value add analytics. With access to data analytics in real-time, each user can make informed decisions that are based on up-to-date data.
Automation solutions also contribute to reduced compliance risk and make it seamless to run audit reports, as well as full access to audit trails should it be necessary.
Regardless of the size or type of business you work in, analytics in finance are a crucial component of the job. They are used to manage, assess, and monitor the business’ financial health and future expectations.
With financial automation solutions, finance analytics becomes second nature. This way, your finance department can spend more time focusing on strategy and interpreting analysis rather than having to conduct the busy work to get to the answers.
By basing every business decision on reliable and informative data, you are able to make better and smarter choices.
Want to find the best data management software for your organisation? We’ve compiled a list of 8 of the best solutions out there.
Need to know how to process data? There are six main steps, but with an automation solution, you don’t have to worry about any of them.