In a recent poll conducted by West Monroe with more than 150 C-suite leaders, 50% believe their operations will not stabilize from the COVID-19 crisis before the next planning process, and 26% feel their operations will not stabilize until 2021 or beyond. Due to the impact the pandemic has had on business operations, using historically based business planning and budgeting approaches run the risk of being significantly flawed and prone to repeat similar operational liquidity and execution challenges like they did in 2020. A combination of factors created challenges, including:
- Demand volatility and uncertainty – essential vs. non-essential channel shifts, e-Commerce growth, changing market dynamics with some industries surging, others lagging but most still in a wait-and-see mode. This has left product and customer mix difficult to predict and plan for.
- Increased operating costs, particularly COGS due to personal protective equipment (PPE) requirements, frequent cleaning protocols, and other health and safety requirements
- Reduced productivity and capacity due to distancing, frequent shutdowns for cleaning and other workplace safety measures
- Service-level impacts due to customer and employee safety requirements and field-service protocols
- Working capital impacts – finished goods inventory and overall impact on product portfolio complexity and obsolete or slow-moving products
- Complex year over year comparability reporting required to identify the underlying health of the business has been challenged by convoluted COVID impacts
Rethinking your approach
When planning and budgeting for 2021, many manufacturing businesses will need to look at data through a “pre-COVID” and “post-COVID” lens. In many cases, planning and budgeting with the “pre-COVID” data will paint a much different—and likely less accurate—demand and operating cost profile due to adjustments in product and channel mixes. Companies, therefore, need to re-think the overall planning approach considering the following drivers:
- Source data - Because of the number of disparate data sets that are used to build a bottoms-up forecast/business plan, these approaches tend to be labor-intensive, inefficient, and typically based on assumptions that are only relevant at that given time
- Revenue guidance - Demand forecasts built from sales-based account plans tend to be optimistic and aspirational with limited basis in fact or data
- Organizational buy in- Establishing a realistic budget and business plan for the post-COVID environment is a critical enabler of employee, customer, and shareholder confidence
- Flexibility and agility - A traditional, singular AOP will be inefficient due to the unprecedented level of uncertainty surrounding key assumptions
- Additional considerations - With the need to support employee and customer health and safety (PPE, cleaning, tracking and other protective/preventative measures), consider whether the real costs of these requirements have been determined to effectively budget for long-term needs
Planning through uncertainty
Given the COVID-induced shift in business variability, volatility and uncertainty, re-calibrating business and financial planning for 2021 is an imperative. We recommend several steps to improve both the accuracy and agility of this process while also overcoming a higher than normal degree of uncertainty.
- Review current business planning process and technologies - Review your current business planning process (workflow, data sources, assumptions, allocations, and probabilities) to determine the areas of highest risk, uncertainty and/or volatility. Pre-COVID demand by channel and operating costs, for example, will be susceptible to bias that will not be reflected in a post-COVID reality.
These high impact drivers should be isolated and used to drive key top down targets and assumptions for a multi-scenario AOP process. Your “watchlist KPIs” can serve as a true north in prioritizing actions to maintain cash flow and protect liquidity while supplying the levers to adjust in constructing good, best, and worst-case scenarios. Lastly, review your corporate performance management solution’s ability to rapidly produce multi-scenario financial modeling and complex driver-based forecasting.
- Revise your data analytics - Shorten the historic data window to rebuild the forecasting/planning model and analyze what is likely to be more accurate and relevant data (past 12 weeks rather than the past 12 months).
Secondly, build an additional data model that will support your watch list KPIs to be able to determine leading indicators of forecast variance (e.g. customer channel mix and customer inventory build/burn rates). This will provide rapid insights with variable degrees of confidence that can be referenced when rolling up the broader budget and business plans. Pre-COVID data will likely skew analysis and provide an inaccurate basis for planning.
- Adopt an agile forecasting/planning cadence - Establish an agile business forecasting/planning process with a shorter and more efficient re-forecasting cadence centered around your “watch list KPIs.” Because of a smaller data set and lower confidence, a business may need to shift from a quarterly to monthly forecast update cadence. Establishing a more efficient process while also shortening the span between forecast updates enables better decision making on evolving demand and cost-to-serve profiles.