Companies nowadays are looking at using specialised FP&A solutions to help improve the accuracy and efficiency of the forecasting process.
Depending on the maturity of the FP&A function, we can roughly divide companies into the following three levels of maturity in terms of their use of specialised FP&A solutions.
1. Early stage
These companies are probably in their infancy when it comes to FP&A. They may have basic accounting functions but just started trying to do more analysis and to improve performance by implementing a forecasting and budgeting process. Most of the time these companies are using spreadsheets to collect and collate information, as they probably neither have the scale nor see the value of investing in a system solution for FP&A.
However, with some good planning and expertise in spreadsheets, this approach may make sense as the organisations are still changing and discovering what works best for them. Also, spreadsheets do not require specialised software knowledge and can engage young teams in early-stage companies in the budgeting and forecasting exercise.
In order to succeed in this environment, the organisation will need outside help with designing the spreadsheet and defining the requirement. This will provide invaluable insights that the organisation can refer back to in the future when the time comes for a more structured approach.
At this stage, a lot of companies use a combination of a spreadsheet and a system for their forecasting and budgeting processes. Most companies will fall under this category. Do not be surprised if you find really established and mature companies still going through their forecasting or budgeting exercise with this approach.
For companies in this category, it is typical to use spreadsheets to perform a lot of the analysis and then use a system to help consolidate information and organise the data for different kinds of reports and further analysis.
The benefit of this approach is an opportunity to use spreadsheets to provide a lot of analysis, especially around the business drivers, so assumptions and backup information are kept. The system is then used mainly for consolidating data and providing different levels of reports.
This approach is also easier to manage, as reports and analysis are typically more finance-based, e.g. divisional or regional P&Ls or cash flow analysis. The obvious downside is that the data used to come up with the financials are kept in separate and often non-standard spreadsheets so it will be more difficult to refine the analysis or drill down on more details.
3. Advanced stage
At this stage, specialised FP&A solutions can automate and improve efficiencies of the forecasting and budgeting process. Data are automatically retrieved from various data sources, consolidated into appropriate levels of details in order for different finance teams to dig into the areas they are responsible for very quickly.
There is also the benefit of getting accurate data into the model and avoid errors that may be present in spreadsheet models. This type of FP&A solutions is especially useful today when businesses are collecting more and more information about their business drivers, not only financial data.
FP&A teams can also engage in better discussion with their business partners to understand how to adjust the forecast instead of disengaging the business because the forecast is too “financially drive” and lack business relevance. Joint ownership by both finance and the business can improve forecast accuracy and accountability to the budget.
By deploying specialized FP&A software for forecasting and budgeting, businesses can
- take advantage of the flexibility offered by this software,
- improve data accuracy by directly integrating data source to the analysis,
- provide better analytics and reporting capability by using tools like scenario analysis, data visualisation and easy access to all stakeholders.
In the end, more engagement and ownership by all parties involved will be achieved. It will improve the overall quality of the process.
The article was first published in Unit 4 Prevero Blog.