Cashflow and forecasting model for fitness brand

Background

They are supported by millions of highly engaged social media followers and customers in 131 countries.

Their key information includes:

•       £240m income in 2019/20
•       Founded in 2012 with 45% of income from the US
•       Annual Profit Growth of 152%

They were referred to Mazars to provide a quick cash flow forecasting model that could be used in a submission to the bank.

Approach

The scope of the initial work was agreed to be the creation of a quick cash flow forecasting model based on assumptions.

1. Meetings – Several meetings with the CFO to design and scope.
2. Technical calculations – Reviewed current state actuals files. Developed a technical understanding of the underlying calculations required specific to the organisation (for example: what assumptions are required to extrapolate out to 2 years).
3. Technical development – Built the forecasting model using Mazars best practice modelling principles. Use of formulae and automation (VBA).
4. Testing – Scenario testing and facilitated stakeholder functional testing, to determine if the expected outcomes were achieved.
5. Implementation and training – Provided implementation support to the model owner and provided guidance and training as required. This included support in the creation of a "bank" version of the file.

Overall, the actuals data was used alongside a set of flexible variables to create an accurate view of the balance sheet and cash flow for the next 2 years and provide comfort to the bank.

Outcomes

The Power BI dashboard we produced was highly engaging, with interactive functionality for the user to slice and dice data based on their specific needs. Other outcomes included:

• Month on month comparison for the year (previously current vs last)
• Ability to filter by month, tax band, discount code, days empty, with all visuals and graphs updating as the user interacts with the dashboard.
• Interactive functionality with the ability to drill down from summary to insights, to detailed data
• Location graphs highlight geographical insights to where empty properties are, including the ability to zoom in on properties in street view.
• Drill down to detailed underlying data with the ability to export into an Excel sheet to be used as an actions log to drive action

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