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Organizations spend a large amount of time and resources in preparing their budgets. Much of that work is repetitive low-value-added effort, such as gathering the data that's used in the budgeting process. Additional work is needed to prepare a line-by-line budget by department.
Budget proposals provide the following benefits:
The quality of the predictions depends on having sufficient cleansed data that are consistent for several years. In some cases, three years of consistent data are sufficient, but often five to 10 years is best. If 10 years of historical data do not exist in the system today, consider cleansing previous historical data that may not exist in the system, and uploading that as a historical budget.
The term cleansing data refers to ensuring that the data is consistent in terms of accounts and financial dimensions when a reorganization has happened, or importing legacy data generated before a change in the chart of accounts or financial dimensions.
Complete the following steps to set up the Budget proposals feature.
Budget proposals must go through the following steps to prepare the proposed budget as a draft budget register document:
The dates selected for output are generated by the system based on 12 months of predictions after the end date of the input. Consider the following example.
Input start date | Input end date | Out start | Out end |
---|---|---|---|
Jan 1 2017 | Dec 31 2019 | Jan 1 2020 | Dec 31 2020 |
Jul 1 2014 | Jun 30 2018 | Jul 1 2018 | Jun 30 2019 |
The budget models entered are checked against the dates to determine which budget register entries should be used and have individual budget lines included. Consider the following examples.
Input start date | Input end date | Budget model | Budget lines | Included |
---|---|---|---|---|
Jan 1 2017 | Dec 31 2019 | FY2017 | Jun 302017 | x |
Jan 1 2017 | Dec 31 2019 | FY2018 | Jun 30 2018 | x |
Jan 1 2017 | Dec 31 2019 | Annual | Jun 30 2017 | x |
Jan 1 2017 | Dec 31 2019 | Annual | Jun 30 2016 |
The Budget proposals feature uses historical data, as well as your input, to build a machine learning model. The following points offer guidance that can help optimize a model’s results, and guide your use of the data.
The actuals versus budget inquiry can be used to have a line-by-line view of actuals versus the budget proposal. In Inquiry parameters, set the start date and end date and your output budget model. Also set the Budget register entry status to Draft.
A yearly view that includes the actual amount, budget amount, variance amount, and percentage used is available in the results. This page can then open the Period balance page where you can review any account on a period-by-period basis for deeper evaluation showing variance amount.
You can use the Actual vs Budget - Default financial report to see summary and detailed views of actuals versus the budget proposal. The default report design includes a single yearly view for original budget, revised budget, actuals, variance amount, variance percent, and percent of budget. The report can be easily updated to include 12 monthly columns with corresponding values, rather than a single amount with variances. You can set the budget proposal budget model by selecting Report Options and then selecting the budget model from the Scenarios drop-down menu. This will refresh the report to the correct budget model.
When a 12-month financial report is exported to Excel, you can easily insert a line chart or sparkline to provide a graphical view of the input or output data that helps reveal trends in the data.
Events
Power BI DataViz World Championships
14 Feb, 4 pm - 31 Mar, 4 pm
With 4 chances to enter, you could win a conference package and make it to the LIVE Grand Finale in Las Vegas
Learn moreTraining
Module
Intelligent Budget Proposal in Dynamics 365 Finance - Training
Learn how to use machine learning to analyze historical data and generate a budget proposal in Dynamics 365 Finance.
Certification
Microsoft Certified: Dynamics 365 Finance Functional Consultant Associate - Certifications
Analyze and translate financial business requirements into processes and solutions that implement industry recommended practices.