Model Build

Foxtons

Leading London estate agency Foxtons wanted to understand the impact of changes to tenancy legislation on their lettings division. Numeritas supported them with rental portfolio

Enhanced Resilience

By assessing the impact of legislation and strategic mitigations, we strengthened our client’s ability to cope with disruptive change.

In-depth Scenario Analysis

We collected, managed and analysed data from across the agency’s varied portfolio of tenancies to develop reliable forecasting for a range of scenarios.

Decision-making Intelligence

By improving the visibility of core portfolio metrics and KPIs, we enabled informed and effective decision-making.

Challenge

The Renters Reform Bill is the largest shake-up of tenancy regulations for many years and our estate agent client required a robust financial model to support its scenario planning. This included a spreadsheet forecasting solution for the portfolio of active tenancies and a substantial dataset for each, covering elements such as lease lengths, billing cycles and break clauses.

In particular, the move to end fixed-term tenancies in favour of periodic tenancies with a two-month break clause, would mean the revenue the estate agent could recognise upfront would drop considerably, which would impact year-on-year revenues during the transition.

To ensure resilience, the business needed to understand how this transition phase could be managed from both a revenue planning and working capital requirement perspective, as well as assess potential contingency plans to reduce the impact on its business model.

 
Solution

Using Microsoft’s Power Query, we transformed underlying tenancy data, provided a forecasting starting point and a detailed forecast of the existing portfolio of tenancies. 

We worked with the client to identify and define cohorts of typical tenancies within its portfolio and those that would evolve in the post-Renters Reform Bill world. This enabled us to produce a forecast for each cohort, which was stored and aggregated.

We also developed a forecasting engine that could deal with the existing regime up to the transition date. It could model a hard transition from a designated date and consider mitigating strategies to reduce the impact. At the same time, we tracked the core portfolio metrics and KPIs to support decision-making during this period.

 
Results

Our model gave the client a robust suite of tools to forecast performance and assess strategic options in detail. It also enabled effective assessment of working capital requirements and which billing options they could afford to introduce. This included the ability to create multiple rental price/portfolio growth rate assumptions and compare the impact of these scenarios without having to re-run the model for each scenario in turn.

The outputs and data generated supported the evaluation of upcoming changes in legislation and clearly demonstrated the positive effect of contingency planning by management. The model has now become part of the estate agent’s ongoing budgeting and re-forecasting process.

 
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