Many companies now require predictive analytics when looking to purchase a budgeting solution. While there is logic to this because predictive analytics comes with a lot of benefits, there is somehow a misconception that predictive analytics works like magic where when you plug in data you get exactly the insights and predictions you want.
What many companies do not realize is that predictive analytics is not the miraculous solution that provides all the answers and predictions to everything they want to know. Regardless of the predictive analytics techniques employed, it can really only predict four things – risk, opportunity, fraud, and demand.
In fact, building one model is not enough because in the areas mentioned above, it may most likely require different models or it may require a different model for every question an analyst or decision maker may have.
When it comes to the world of budgeting or forecasting, predictive analytics indeed offer huge help especially in providing estimations for the company´s spending for incoming periods. Here are a few other finance areas where predictive analytics come in handy:
- Keeping Track of Key Performance Indicators
Predictive analytics is very useful across different types of industries. For example, as the in charge for a specific cost center, it is normal to have indicators by which you evaluate performance against. Keeping track of your center´s KPIs and having the ability to forecast for future periods through the tracked KPIs is very useful.
- Cashflow Projection
Being able to accurately forecast your company´s cash flow is very tricky. However, if you employ predictive analytics, you can use historical data and historical project plans data in order to forecast the cash flow more accurately and promptly. In fact, using these same historical figures, you can even spot areas that need prompt attention.
- Learning from Past Projects
Another notable predictive analytics benefit is that by using project and financial data, you can see emerging patterns from past project in terms of overall revenue and payment history.
- Identifying Key drivers
When it comes to budgeting and forecasting, it is important to look at key drivers and one of the important things for a finance person to look at is identifying key drivers for late payment.
- Payment Probabilities
Using several forecasting techniques and predictive models as well as dashboards analysis, it becomes possible to calculate the probability of late payment given a new project.
This is in no way an exhaustive list and there are many other areas by which predictive analytics can optimize financial budgeting and forecasting but it is important to remember that before predictive analytics can really kick in and be useful for your company, a lot of time will be spent on ensuring clean and quality data is easily available for use. As mentioned above, predicting as accurately as possible requires the use of historical data to identify trends therefore, you first need to make sure you have a few years’ worth of data available.
Today, many companies face the peril of having massive amounts of data but have sheer inability to produce insights. It has therefore become a priority for many finance managers and CFOs to find an easy to use software that can help them stay ahead of their competitors in such a tough economic climate.
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