Building an Effective Budgeting and Forecasting Pipeline with Microsoft Fabric

In our recent Friday Fabric Lunch n’ Learn session, we discussed advanced techniques for building a comprehensive budgeting and forecasting pipeline using Microsoft Fabric and Power BI. Here’s how you can leverage these tools to enhance your budgeting and forecasting processes.

Introduction to the New Financial Year

As we enter the new financial year, budgeting and forecasting become critical activities for businesses. Whether you completed these tasks in March or are catching up now, it’s essential to have a robust pipeline to handle multiple budgets from various departments and organizations. Using DataOps and advanced visualization techniques can help create an efficient and insightful budgeting and forecasting system.

Key Steps in Building the Pipeline

1. Standardizing the Data Architecture

Entry to Insight Value Stream:
  • Create a structured pipeline that begins with data entry and leads to valuable insights.
  • Use a standardized architecture to ensure consistency and accuracy across all departments.

Excel Integration:
  • Utilize Excel for initial forecasting due to its strong capabilities in handling complex forecasting models.
  • Update your budgeting and forecasting sheets regularly to reflect new versions and improvements.

2. Consolidating Multiple Budgets

Multi-Department and Multi-Organization Budgets:

  • Consolidate budgets from different departments and organizations into a single unified view.
  • Ensure that the budget and forecast data for each department are integrated effectively to provide a comprehensive overview.

3. Building Key Performance Indicators (KPIs)

KPI Calculation:
  • Separate KPI calculations from the budget and forecast spreadsheets to handle complex metrics like EBITDA.
  • Use specialized buckets for KPIs to ensure precise calculations and easy updates.

Department-Level Forecasting:
  • Perform forecasting at the department level using Excel’s forecasting functions.
  • Gradually automate these processes as the manual methods are perfected.

4. Implementing Workspace Branching and Git Integration

Workspace Branching:
  • Create separate development workspaces for different team members to work on features without affecting production.
  • Use Azure DevOps for managing branches and synchronizing changes to ensure a smooth development process.

Git Integration:
  • Integrate your workspaces with Git to maintain version control and facilitate continuous integration and deployment (CI/CD) pipelines.
  • Address any syncing issues and ensure that unsupported items like data flows are managed effectively.

5. Automating Data Ingestion and Management

Data Ingestion:
  • Set up a data ingestion process that brings in data from various ERP systems into your centralized lake house.
  • Use file drop scenarios or SharePoint sites to facilitate easy and secure data uploads.

Managing Forecasts and Actuals:
  • Keep a rolling forecast model that uses historical data to improve accuracy.
  • Ensure that your budget includes forward-looking data for at least the next 12 months, updated regularly.

Practical Tips and Considerations Currency Conversion:
  • Address currency conversion issues by applying business rules retrospectively or ensuring transactions are recorded in local currency.
  • Consider setting up a standardized exchange rate for budgeting purposes.

Department-Specific Budgets:
  • Focus on expenditure accounts for departmental budgets.
  • Allow sales and revenue-generating departments to manage their own revenue forecasts.

Automation and Governance:
  • Aim to automate data entry and updates to reduce manual effort and improve accuracy.
  • Maintain strict governance and security practices to protect your data and ensure compliance.

By following these steps and utilizing the capabilities of Microsoft Fabric and Power BI, organizations can build an effective budgeting and forecasting pipeline that enhances financial planning and decision-making. Integrating DataOps and DevOps practices ensures efficient, accurate, and robust models, facilitating better collaboration and insights across the organization.