SPECIAL REPORT: Coronavirus disruption to sales forecasting has made an already complex process seemingly impossible. Until a vaccine is widely available to the public and infection rates are under control globally, businesses face many confusing demand signals from their own data and a barrage of ever-changing news updates. Navigating supply chain disruption amidst a pandemic is confusing everybody, including the experts.
This article offers guidance on S&OP process management to help your teams make clearer business forecasting decisions during the current Coronavirus pandemic. For small businesses and international corporations alike, this article offers examples and demonstrates the value of integrating new data and gaining new insights for optimal strategic and operational decisions to survive the Covid-19 pandemic.
Sophisticated tracking devices to monitor different aspects of your operations offer real time data, illustrating moment to moment changes. Shortcomings in supply chains can be explored, and scenarios split tested against each other for comparison for flexible, speedy decisions. Over the course of the pandemic, tracking evolving consumer behavior and changing supply chain capabilities help build the new baseline forecasting assumptions we need.
Incorporating Changing Assumptions Is A Must
Patrick Bower, Senior Director, Global Supply Chain Planning and Customer Service at a multinational consumer goods company, believes that scenario planning depends upon the specific needs of each business. He uses tools to help balance emerging changes in supply and demand. For example, if a 20 percent increase in demand occurs, capacity impacts are investigated immediately and resources are planned accordingly.
For some businesses, capacity in terms of available personnel as well as supply chain disruptions inject unanticipated consequences into planning, at least until the pandemic is under control. While tracking a fall or lift in demand or supply will already be a familiar continual assessment for many, forecasting now demands integration of government policy on social distancing and availability of a vaccine into analyses. Covid-19 related events represent new indicators to build into time-series forecasting. Incorporating new assumptions is critical and simply looking at the past no longer works.
The point is to “get comfortable” in knowing you may be wrong
The point, says Bower, is to “get comfortable” in knowing you may be wrong in scenario planning under the present circumstances. Nevertheless, he acknowledges that being data focused offers the best insurance against error. Interpretations of recent data may suggest “what if” questions and testing scenarios, highlighting the gaps that a collaborative S&OP process can fill.
As there is a great degree of uncertainty given a lack of data and rapidly evolving events, he suggests collaboration with external stakeholders wherever possible to gather (and share) as much information as possible. Supply chain partners need to be supported. An example is sharing POS data with them which helps improve their planning which, in turn, helps secure the supply you need. For consumer goods companies, there is value in contracting market research partners to guide your risk management. Insight into consumer behavior at a time like this is King.
His team reviews potential “weak links” in supply chain data projections. During a pandemic, where government policy surrounding lock-down is unclear, some companies may not define themselves as an “essential business”. Suppliers that have identified themselves as non-essential businesses and have shut down are a serious problem for many companies. Depending upon the Covid-19 trajectory, more “weak links” like this in the supply chain could unfold.
Collaboration and Communication Key As Judgement Comes To The Fore
Collating and interpreting novel internal data, flagged by colleagues, particularly those on the front line, as well as supply chain partners, could be essential to enhanced and agile decision making. Crises offer opportunities for staff contributions to identify new performance markers and future indicators during disruption. For Andrew Schneider (ACPF), Manager of Corporate Quality at Medtronic, transparency is key, and new internal and external relationships must quickly be forged to ensure timely production and delivery of products.
Where machine learning does not suggest appropriate substitutes, companies have to use their best judgement, unless alternative suppliers can be mobilized rapidly.
Demand planning software systems must facilitate integration of up to date information from upstream, where products may be drying up, as customers switch lines. Where machine learning does not suggest appropriate substitutes, companies have to use their best judgement, unless alternative suppliers can be mobilized rapidly. Weighing risk and acting accordingly should involve continual monitoring of implications of changes made.
Regular Monitoring & Tracking Of Data Is Critical
Any tweaks to procedure need to be systematized for close monitoring within key S&OP cycles, which vary between businesses. Small adaptations can be tested against emerging data to review impacts. This necessarily involves open communication with relevant stakeholders for the benefit of all moving forward, including end users.
Holding onto life-saving products is not only immoral but can damage business reputation.
Dramatic operational changes may also be entirely appropriate. However businesses choose to adapt, close observation and consistent, regular tracking of results is essential. Comparisons against data from economists and epidemiologists as well as against data from previous disruptions are recommended. Cross-functional teams need to support interpretation of forecasting results, facilitating rapid decision making.
For retailers panicking about lack of inventory, it is also worth bearing in mind that it may be entirely justified to run out of stock, such as face masks, or bleach. During this catastrophe, say Patrick Bower, holding onto life-saving products is not only immoral but can damage a business’s reputation.
Now’s The Time To Use Wider Indicators
Individual companies will have individual balancing acts and assumptions to include in their forecasts, focusing on a wider variety of key indicators than usual. If cash flow, as opposed to inventory or service levels, is the main priority, then demand planning managers will benefit from integrating wider indicators, such as the shape of a forthcoming recession/recovery, for instance. Segmenting historical data sets according to test scenarios around a ‘V’, ‘U’ or ‘W’ shaped recovery will reveal implications for S&OP and cash-flow.
However, given that time series forecasting cannot predict unprecedented events, disruptions like staff absenteeism, supplier or line loss, and even switching to producing a new product, requires using cleansed historical data. Data can be split tested in forecasts allowing implications to be explored before decision are made.
Jonathan Schwartz (CPF) is a Supply Chain Analysis Manager at WD-40. He remarks that the baseline ‘steady state’ looks different depending upon a company’s fiscal year – forecasts for April-end could look good, but not so if your year end is December. He adds that fast production and distribution is essential before absenteeism from sickness or changes in business partner behavior disrupts either business function.
While we wait for a vaccine, confidence and behavior will continue to shift, changing consumer, supply chain and staff priorities.
While we wait for a vaccine, confidence and behavior will continue to shift, changing consumer, supply chain and staff priorities. This requires daily, weekly and monthly reviews of demand variables, KPIs, macro-economic indicators, and the spread of Covid19.
Matt Hoffman at John Galt Solutions believes 12 month planning to be a key timeframe as companies must be must be positioned appropriately when things return to normal. During these initial stages in the pandemic, where social distancing is the norm, there will be pent up demand. As businesses ‘return to business as usual’ environments, regular re-assessments of assumptions will be necessary before forward planning. It is recommended that companies understand in detail their inventory carrying plan for this next year (during which time there may yet be a second wave in the pandemic) as lock-down restrictions are lifted.
Make no mistake, Coronavirus has changed consumer behavior and some of those changes are here to stay.
When combining data sets in scenario planning, John Galt Solutions observe income and consumer confidence, deploying regression modelling for understanding consumer impacts during these times of social change. He cites health and beauty product consumption shifting from salons to home application under lock down. Thus price points and or marketing messages need recalibrating. Make no mistake, Coronavirus has changed consumer behavior and some of those changes are here to stay.
Forecasts Will Be Wrong & That’s OK
Industries and businesses are at risk during the current unprecedented circumstances. However Coronavirus and the responding policies develop, and whatever the impact on the economy, experts are consistent in their message: Closely monitor the data and compare against historical data from previous disruptions and downturns. Furthermore, collaboration and communication in demand planning have also never been more necessary. If S&OP as a collaborative, cross-functional forum was important before this crisis, it is a life saver now.
Forecasting models will not be “correct” in the near term.
During a potentially dangerous new phase as world leaders to seek to balance public safety with a return to work, the coming weeks will provide yet more tests of companies’ forecasting and planning abilities. As Eric Wilson, Director of Thought Leadership at the Institute of Business Forecasting, notes, the concern of many of the businesses contacting him is the duration of disruption. This shines a spotlight on the importance of looking beyond sales data and integrating economic and epidemiological data into forecasting.
He adds that while forecasting models will not be “correct” in the near term, it is times like these that reveal how critical forecasting and planning are to a company’s survival.
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