Predictive Forecasting
in an Industrial Construction Firm
CLIENT
Mid-sized U.S. engineering and industrial construction company
INDUSTRY
Engineering, Procurement & Construction
SERVICE
Project cost forecasting | Data integration | Resource allocation dashboards | Predictive analytics | Power BI implementation
Overview
The company struggled with delayed financial visibility across its projects. Project managers maintained separate Excel trackers for budgets, purchase orders, and labor hours. Accounting used a legacy ERP system that did not communicate with project-control spreadsheets.
As a result, executives had no consolidated view of project financial health. Forecasts were inconsistent, cash-flow reports were outdated, and resource allocation decisions were often reactive.
The leadership team engaged us to implement a cost forecasting and resource visibility dashboard that would unify project data, automate reporting, and introduce predictive analytics for proactive budget control.
Challenges
Our Solution
1. Unified Project and Financial Data Model
We began by consolidating all project, procurement, and accounting data into a centralized model. Historical cost, PO, and labor data were extracted from Excel trackers and synchronized with the ERP system through automated connectors. This eliminated manual data reconciliation and enabled daily refresh cycles, ensuring every stakeholder had access to current information.
2. Power BI Cost Forecasting Dashboard
A dynamic Power BI environment was developed to visualize cost performance and cash flow projections across all active projects.
- Project managers could monitor committed vs. actual spend in real time.
- Executives gained a portfolio-level view of financial health with drill-down access to individual projects.
- Controllers received automated variance alerts for early detection of overruns.
Interactive dashboards replaced static reports, reducing reporting cycles from days to hours.
3. Predictive Forecasting Engine
Using historical project performance data, a predictive model was introduced to estimate cost-to-complete and detect early budget risks. The system continuously learned from new data, improving accuracy with every reporting cycle. Managers could simulate “what-if” scenarios, assess impact of resource shifts, and adjust procurement or staffing plans proactively.
4. Resource Utilization and Allocation Insights
Labor and equipment data were integrated to show real-time utilization rates across sites. A resource heatmap allowed supervisors to identify idle teams or overburdened crews, enabling better redistribution of capacity. This supported smoother project execution and reduced downtime between jobs.
5. Data Governance and Change Management
To ensure sustainability, data governance policies were introduced, defining ownership, refresh frequency, and access control. Project and finance teams were trained to use the dashboards, fostering trust in the system and enabling the shift from manual spreadsheets to automated insights.
Key Achievements
Result
The transition from fragmented spreadsheets to an intelligent forecasting system reshaped the company’s financial culture. Project managers stopped chasing numbers and started managing outcomes. Finance no longer reacted to overruns – they prevented them.
With unified dashboards, the leadership team could finally see where every dollar and hour was going – and what would happen next.
The organization moved from firefighting to foresight, setting a new operational standard:
predict before it happens, act before it costs.
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Luke Suneja
Client Partner
