How to improve forecast accuracy

Are your forecasts as close to reality as possible – or are they missing the mark?

The reliability of your forecasts can only be as good as your data. Because without reliable, high-quality data? It’s near impossible to produce accurate forecasts the business can depend on.

So, how do you know if your data passes the data reliability test? And what can you do to improve it, and in turn, improve forecast accuracy?

How reliable is your data?

Reliable data is fit for purpose, accurately represents the business, and supports better decision-making. It’s essential to improve forecasting and provide financial reports your business can trust.

To measure the reliability of data in your business, assess your data against these key measures:

Accurate

How well does the information align with what is really happening?

Data accuracy refers to how correct your data is and how well it reflects reality. With many finance teams relying on Microsoft Excel for their data analytics, this can be a serious problem. Spreadsheets are prone to errors, thanks to version control issues, manual data entry, and time delays. These errors multiply when combining data from multiple spreadsheets and can lead to costly reporting errors.

Unbiased

Is your data skewed by opinion?

Complete

Do you have any gaps in your data?

Incomplete data gives an incomplete picture of the truth. This can include data with incorrect values, missing information, or inadequate representation in the data sample. A lack of connectivity between different data access points can exacerbate this issue.

Up-to-date

How up-to-date is your information?

72% of organizations want to improve the dependability and reliability of their forecasts.

How to improve data reliability

If you’re working with unreliable data, there are practical steps you can take to improve data quality and provide your organization with dependable forecasts.

Review data objectives

What key performance indicators will have the most impact in driving business performance? What information do you need to create those metrics and where will it come from? It’s important to review your metrics and their relevance as business objectives change.

Aggregate data

Another key consideration is consolidating information into a central system. This can help connect different areas of the business, ensure people don’t miss out on important information and provide a clearer picture of performance.

Phocas provides a single source of truth that can pull data from multiple locations by connecting directly with your ERP and other third-party applications.

Use quality data

Improving data quality begins with defining standards of quality data. You can assess data against these standards, and work on ways to reduce errors, keep data clean, and fill in information gaps. Incorporating this as an ongoing process will help with maintaining data quality over time.

Make data accessible

To add real value, data needs to be shared and understood across your organization. This means making data accessible, easy to digest, and useful.

‘Phocas makes me feel empowered to give this information to all the people in an easy-to-understand format. Now we have a meeting, and we all know what we are talking about. Everyone is coming in with their information, that makes for a lot more productive time’

– Nick Aversano, CEP of Trade Supply Group

Start trusting your data with Phocas

The right software solution can improve data quality and as a result, help you create more reliable forecasts. With flexible budgeting and forecasting identified as a top focus area for CFOs, now is the ideal time to explore your options.

Phocas makes accurate forecasts a reality by consolidating data, accessing real-time information, and encouraging collaboration. You can see how it works for yourself with a free guided trial of Phocas.