Quick Summary

Bronson built a 25-year capital expenditure forecasting tool for a $50 billion capital-intensive global organization, automating long-horizon capital planning across hundreds of projects.

The tool replaced a manual, multi-day spreadsheet process with an automated Alteryx workflow, reducing planning cycle time by 96 percent (from 4 hours to 10 minutes per run).

15 quality assurance checkpoints were embedded directly in the workflow, catching data quality issues before they propagated into the long-horizon plan.

Analysts can now generate modified investment scenarios in under five minutes without reloading source data, supporting on-the-fly exploration of timing, contingency, and project-exclusion scenarios.

Outputs are produced on both Cash and Accrual accounting bases to satisfy the requirements of different audiences within DND and Treasury Board.

Project Overview

A capital-intensive global organization managing a $50 billion capital portfolio needed Bronson to develop a 25-year capital expenditure forecasting tool. The organization’s long-horizon capital planning process spanned hundreds of projects across multiple business areas, with capital decisions made years in advance and revisited annually through a structured planning cycle.

The existing process was largely manual. Analysts pulled project-level data from multiple source systems, applied inflation and escalation factors, mapped projects against the long-horizon plan, and produced both Cash and Accrual outputs. The work was time-consuming, prone to error, and difficult to audit. Each planning cycle absorbed significant analyst time and required multiple rounds of review to catch data quality issues.

Bronson was engaged to build a tool that would automate the forecasting workflow end to end, embed quality assurance checks throughout the process, and produce planning-ready outputs in both Cash and Accrual formats. The tool needed to handle the full 25-year horizon, scale across hundreds of projects, and support the organization’s annual planning cycle as well as ad hoc scenario analysis.

The Challenge

A 25-year capital forecasting tool is not a routine modelling exercise. It requires structured automation across multiple source systems, enforceable quality assurance, and outputs that meet both internal planning and external reporting needs.

The main challenges Bronson tackled:

  • Long-horizon scope. Capital forecasting across a 25-year horizon required handling escalation, inflation, project timing shifts, and portfolio rebalancing across decades, not just the upcoming budget year.
  • Multiple source systems. Project data was held across multiple source systems with different structures, naming conventions, and update cadences. The tool had to bring those sources together consistently without overwriting source-of-truth records.
  • Manual process inefficiency. The existing process consumed approximately four hours per planning run, limiting how many scenarios analysts could explore in a planning cycle and making error correction expensive.
  • Quality assurance gaps. Manual processes had limited inline quality checks, meaning data quality issues often surfaced only late in the cycle when they were most expensive to correct.
  • Cash and Accrual outputs required. Internal planning and external reporting required different views (Cash for cash flow planning, Accrual for financial reporting). The tool had to produce both from the same underlying dataset to avoid reconciliation gaps.
  • Auditability. Capital planning decisions of this scale require traceability. The tool had to produce outputs that could be traced back to source records and audit trail logic that could be reviewed by finance and audit functions.
  • Adoption by capital planning analysts. The tool had to be usable by the existing capital planning team, not require specialized data science skills, and integrate with the team’s existing planning cycle rather than impose a new process on them.

The organization needed a capital expenditure forecasting tool that was faster, more accurate, more transparent, and more flexible than the manual process it would replace, without sacrificing the rigour that a $50B capital portfolio demands.

Our Solution

Bronson designed and delivered the engagement as a structured Alteryx tool development program. The work was organized into the following streams:

1. Current Process Mapping and Requirements Definition

Bronson worked with the capital planning team to map the existing manual process, document the source systems involved, identify the inputs required at each step, and define the outputs required for both internal planning and external reporting.

2. Alteryx Workflow Architecture

Bronson built the tool on Alteryx, designing the workflow architecture to handle the full 25-year horizon across hundreds of projects. The architecture supported escalation and inflation assumptions, project timing adjustments, portfolio roll-ups, and exception handling.

3. Source System Integration

Bronson built the integration with the multiple source systems holding project data, mapping fields, reconciling naming conventions, and ensuring that the tool pulled current data on each run without overwriting source records.

4. 15 Quality Assurance Checkpoints

Bronson embedded 15 quality assurance checkpoints directly in the workflow. The checkpoints catch data quality issues (missing fields, out-of-range values, inconsistent project codes, escalation factor mismatches) at the point in the workflow where they are easiest to fix, rather than at the end where they are most expensive.

5. Cash and Accrual Output Generation

Bronson built the output generation supporting both Cash and Accrual views from the same underlying dataset. Outputs are structured for direct use in the organization’s annual capital planning cycle and external reporting requirements.

6. Project, Portfolio, and Exception Reporting

Bronson built project-by-project forecasts, portfolio-level roll-ups, and exception reports that surface projects requiring planner attention. The reporting structure supports both the standard planning cycle and ad hoc scenario analysis.

7. Knowledge Transfer and Adoption Support

Bronson supported the capital planning team in adopting the tool, providing documentation and walkthroughs that enabled analysts to run the workflow, interpret QA checkpoint outputs, and adjust assumptions for scenario analysis without specialized data science skills.

Key Deliverables

  • 25-Year Capital Expenditure Forecasting Tool – The completed Alteryx tool automating long-horizon capital expenditure forecasting across the $50B portfolio, handling hundreds of projects over a 25-year horizon.
  • Source System Integration – The tool’s integration with the multiple source systems holding project data, ensuring that the workflow pulls current data on each run without overwriting source records.
  • 15 Embedded Quality Assurance Checkpoints – Quality assurance checkpoints built directly into the workflow, catching data quality issues at the point where they are easiest to fix.

The Impact

Bronson’s work transformed the organization’s long-horizon capital planning capability from a manual, multi-hour process into an automated, traceable, faster workflow. Specifically, the engagement delivered:

  • 96 percent reduction in planning cycle time, from approximately four hours per run to ten minutes per run, freeing analyst capacity for scenario analysis and decision support.
  • 15 embedded quality assurance checkpoints catching data quality issues during the workflow rather than at the end of the cycle, reducing the cost and risk of late-stage corrections.
  • Cash and Accrual outputs from a single source of truth, eliminating reconciliation gaps between internal planning views and external reporting requirements.
  • Full 25-year horizon coverage across hundreds of projects, supporting both the standard annual planning cycle and ad hoc scenario analysis.
  • Audit-grade traceability linking outputs back to source records and embedded logic, supporting finance and audit review.
  • Capital planning team adoption without requiring specialized data science skills, integrating with the team’s existing planning cycle rather than imposing a new process.

The result is a capital planning capability that operates at the speed and scale a $50 billion capital portfolio demands. With the forecasting tool in place, the organization can run more scenarios, catch more issues earlier, reconcile internal and external views from a single source, and trust the long-horizon outputs that anchor its capital decisions.

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