Having sufficient forecast information to enable your sales and operational teams to make effective decisions (e.g. forecasts by SKU, region, etc.)
Ensuring your forecast tools can adequately capture “downside” scenarios, incorporating impacts of fixed, variable and step-variable costs as well as sales and operational planning issues (e.g. supply chain).
Ensuring you have robust forecast assumptions/drivers to allow you to confidently communicate the expected impact of COVID-19 on your business. For example:
What is the overall impact on demand for our sector and business compared to others?
How would a lockdown impact our business (e.g. demand, sales channels, workforce productivity, etc.)?
What is our exposure to “at risk” markets (e.g. demand, supply chain, counterparties, etc.)?
Understanding the potential impacts on your bank covenants, credit agreements and normalization adjustments for EBITDA.
Leveraging data and analytics to provide better business intelligence supporting your forecast assumptions (e.g. extracting data on demand and supply chain trends by SKU/region).
Leveraging external data sources and predictive analytics to enhance the forecast process, including consideration of impact of comparable incidents (e.g. SARS, swine flu, etc.)
Development of 13-week cash flow models (based on receipts and disbursements of the business) that incorporate demand and supply chain realities to better manage day-to-day cash flow.
Leveraging data and analytics to develop better business intelligence for forecast assumptions that incorporate internal and external data sources.
Utilizing predictive analytics to help forecast demand based on key variables (e.g. demographic, macroeconomic trends, prior incidents, etc.)
Detailed scenario modelling, including the impact on covenant, credit agreements and normalized EBITDA.
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