Financial analytics: out with the old, in with the new
Financial analysis has traditionally involved looking back at past data, i.e. metrics or KPIs from the last week, month, or year, but it is time to acknowledge that this is only half of the picture. That is not to say we should do away with past data altogether. It is still important for analyzing performance, but it cannot be the sole basis for current action. Today, financial leaders must recognize financial analysis needs to take into account predicted future outcomes and forecasting to allow for effective decisions to be made in real-time.
There are subtle differences between predictions and forecasting, defined below using customer churn as a metric:
The example above clearly illustrates the importance of using modern analytics to project performance into the future as simply looking to the past cannot deliver the same level of insight.
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Using the right systems
Modern analytics solutions can be connected directly to company financials, allowing finance teams to track traditional metrics, for example, cash flow and revenue, as well as predictive insights. Predictive insights can help finance teams predict future rates of renewal, churn, and expansion as well as generate forecasts. However, new analytic solutions should be combined with new front and back-office applications because attempting to forecast and predict future outcomes using spreadsheets, or even a traditional ERP system, will create more work than is necessary. Instead, using next-generation systems will streamline this process of change.
These new platforms are able to do significantly more than traditional spreadsheets, with embedded business intelligence and AI technologies that allow for a greater depth of insight. Organization is a key element of efficiency, and these new platforms, such as Einstein Analytics, lay out the data at a row or transaction level rather than aggregated or summarized. This means that financial professionals do not have to search for the data but can immediately use it as it is already at their disposal and linked to financial reporting. Time savings like this will increase business efficiency.
The next step for financial professionals is to turn this data into visual depictions that can be easily shared and interpreted by those across the company who need it. Traditionally, through spreadsheets, this takes the form of a bar graph or pie chart. While these are useful, the heat maps, scatter plots, or bubble charts that more modern tools can create are able to highlight anomalies in a more eye-catching way. These new visualizations also remove the inconvenience of spreadsheets where one graph is often dynamically related to another, so small changes can cause chaos. Therefore, using these new systems has the potential to eliminate a lot of time-wasting data manipulation.
As remote working is becoming increasingly prevalent, especially in the current global climate where entire workforces are working from home as a result of COVID-19, more convenient, collaboration enabled reporting tools have never been so vital. One of the key issues with using spreadsheets is that they create version control issues, where multiple versions of the spreadsheet are sent across the enterprise making it difficult to keep track of the changes. Moving away from using spreadsheets and using these new systems instead will make it easier for people to share data remotely.
Some modern analytics platforms are now providing mobile versions of the desktop experience, giving those managing these processes more options still, expanding the working landscape, and introducing a greater element of flexibility. Phone screens may be small, but modern analytics platforms are so clear that it takes little away from the desktop experience. If you’ve ever tried viewing a spreadsheet on a mobile, you’ll understand what a boon that truly is.
The financial analytics landscape is changing, and it’s time to do away with the old and welcome the new. Take a look at a powerful analytics and reporting solution in action:
