Case study · Financial Services
Moving corporate planning beyond unsupported spreadsheets
Major real estate investment trust
A business architecture, data and transition plan for replacing complex Excel-based planning and forecasting models with a modern CPM platform.
Challenge
Complex, undocumented Excel models and end-of-life systems were limiting data quality, planning speed and confidence in decisions across property, investment and fund management.
Data was manually created, extracted and checked across separate asset and fund models, making the environment hard to scale or support.
The models overlapped, depended on end-of-life systems and were often poorly documented. Each asset and fund could require its own data handling, with people repeatedly creating, extracting and validating datasets.
The client had shortlisted a planning platform and needed a target architecture, quantified benefits and a practical transition path that balanced an achievable first release with the longer-term target state.
Approach
Map the modelling ecosystem. Visualised the models, their purpose, interactions and data needs to create a simpler, modular model ecosystem. Performance, storage cost and long-term sustainability were considered in the design.
Build the business architecture. Defined five layers of modelling architecture—from source systems and data integration through models, assumptions and reporting—then mapped the data flows and detailed planning and forecasting processes.
Match requirements to capability. Worked with model subject-matter experts to map each business requirement to the best future-state capability. Flexibility, current-system performance, cost, strategy and user needs determined what belonged in the new platform, integrated systems or retained Excel.
Plan the transition. Defined data governance, terminology, quality controls, access, user licensing, operating-model changes and conceptual architecture. A sequenced roadmap started with the underlying data model to address the largest inefficiencies first.
Business architecture for modelling
Five layers from source data to decisions
The target state separated data foundations, modelling logic and management reporting so each layer could be governed and improved deliberately.- 01
Data sources
External research, ERP, tenant and lease systems, Excel, CRM and other source applications.
- 02
Data hub
A governed integration layer that consolidates data needed across the models.
- 03
Models
Budgeting, forecasting, asset, portfolio, fund and feasibility models.
- 04
Assumption sets
Shared income, expense, capital, asset, funding and planning assumptions.
- 05
Reporting
Dashboards and reports that turn model outputs into management decisions.
Outcomes
The work set out a pragmatic path to a modern planning capability, including the target architecture, operating model, delivery schedule, costs and benefits. The business case passed every approval gate on its first submission.
The approved design reduced the number of systems required, shortened model calculation time and improved information granularity. It also established the data governance, automation and reporting foundations needed for faster decisions and lower operational risk.
- Business case approved at first pass
- Conceptual architecture and transition roadmap
- Defined data-governance and operating-model changes