IBF recently asked demand planning leaders how they are guiding their companies through the pandemic. The following reveals the key insights from those conversations.

What Are Planning Leaders Doing Differently To Combat Covid-19?

Many companies have rushed to establish new, collaborative processes to understand the evolving demand and supply picture, and how to best respond from a supply perspective. In some cases, companies with mature planning organizations have realized that these processes are already in place, Camila Sierra, Sr. Director, Global Planning at Converse, commented, “We realized very fast that those forums that we were trying to create were just the S&OP forums we already had, and that all we needed was the right people round the table.”

“We realized very fast that those forums that we were trying to create were just the S&OP forums we already had”

An existing S&OP process has also proved valuable at Orchard Therapeutics, a global leader in gene therapy. Cristian Circiumaru, Associate Director, Global Supply Chain, revealed that before Covid-19, Materials Management and Inventory Management weren’t an issue – but they soon became one as supply suddenly became in doubt. They expanded S&OP to include Materials Management and Inventory management, as well segmentation of suppliers to better manage sourcing.

In Times Of Crisis, Get Back To Basics…

We may be embarking on the age of predictive analytics and big data, but a key theme for the planning leaders we spoke to is to recognize the limitations of new technologies when the inputs no longer make sense. “My biggest lesson learned last is to get back to basics”, observed Circiumaru. “Put the focus more on quantitative insights in demand planning rather than relying on sophisticated mathematical models. Yes, we have the technology now to support new models and those are in play as we speak, but refining qualitative insight is very important in 2021 to drive new changes in the forecast models”.

“My biggest lesson learned last is to get back to basics”

…Or Speed Up Innovation

Camila Sierra is currently drawing up plans for Converse to update their forecasting and planning systems, with Covid-19 having exposed the weaknesses of legacy systems and traditional modes of working. “We’re investigating automation because our teams are overworked, partly because they’re using too many spreadsheets”, she remarked. She continued, “We’re looking how to use technology to drive S&OP and create scenarios for more informed decisions. We’re creating an investment plan for the next couple of years to improve this area.”

“We’re investigating automation because our teams are overworked…too many spreadsheets”

A Temporary Return To Supply Driven Planning?

We asked Wallace DeMent, Sr. Demand Planning Manager at Pepsi Bottling Ventures how he is reacting to Covid-19 disruption, “I’ve been with the company 42 years now, but I haven’t seen anything like we’ve experienced with this pandemic. We’re used to basing forecasting financial plans and sales demand plans on what we thought the consumer would buy. We had a rude awakening having to base plans on what we are allocated from raw materials suppliers. It was a definite a paradigm shift in how we do business”.

“We had a rude awakening having to base plans on what we are allocated from raw materials suppliers”

Of course, S&OP doesn’t fix the supply shortages many companies are experiencing, but it can help companies work around them. At Pepsi Bottling, global aluminum shortages mean they must limit production of many of their core offerings – drinks cans. S&OP allows DeMent and his team react to a weekly allocation of raw materials from suppliers in a timely fashion. A weekly S&OP meeting adds value by communicating to Production what materials are available straight away. DeMent says that daily meetings are sometimes necessary to communicate changes, with early morning and late-night meetings currently the norm.

Combining S&OP & S&OE To Make Supply Chains More Agile

Circiumaru says that at orchard Therapeutics, they are relying on projections from their commercial and business development teams, employing forecast techniques based on population data and prevalence of diseases. He told us that the key is having a ‘control tower’ for supply chain, “As long as you have a solid foundation for S&OP, you have visibility into the entire supply and demand picture. We’re moving to a weekly S&OE process, which complements the full S&OP cycle. For Circiumaru’s therapeutics business, this visibility into demand and supply is not only desirable but absolutely critical, “Our service levels need to be 100% otherwise patients die.”

“Our service levels need to be 100% otherwise patients die”

Creating this control tower needn’t be complicated. Relatively simple and affordable tools can provide the much-needed visibility. “It can be as simple as, say, Tableau”, Circiumaru observes. “Someone who knows Tableau can plug in a bunch of data sources and spit out meaningful insights”.

Scenario Planning When You Cannot Forecast 6 Months Ahead

Forecasting is relatively straightforward when demand variability is stable. But when demand is highly volatile, new methods must be employed. Camila Sierra observed that at Converse “It’s been a challenge not being able to use any historical trends. We’re looking more at the last 90 days and where are our consumer buying. We also have to trust our senior leaders in terms of their bets on where the market will be in 6-12 months. Nobody has a crystal ball, but we need to make decisions. What has helped us is setting priorities like protecting margin vs revenue. That has helped us build a couple of scenarios that we can plan around.”

Cristian Circiumaru echoed the need for this kind of scenario planning to build demand plans around business priorities, “You need to take the principles of CPFR and expand them to Marketing, Brand teams, Product Development and Packaging teams. You want to have conversations where you explain different scenarios and their impact on cost-to-serve in terms of packaging and marketing etcetera.”

“Have conversations where you explain different scenarios and their impact on cost-to-serve”

For companies with existing S&OP processes, this is bread and butter; those without will have to scramble to establish the necessary collaborative forums.

KPIS In Times of Crisis

It’s not just processes that have to change when disaster strikes – performance metrics must change to. KPIs don’t always track what’s really going on in the business right now, says Wallace DeMent, “You have to be careful with your KPIs during Covid-19. Right now, some our forecast accuracy looks really amazing, but it’s really easy to get high forecast accuracy when you’re on allocation and you know exactly what you can sell! You have to go back a year prior to see what could have been sold, and use those findings to build the new business plan”.

“You have to be careful with your KPIs during Covid-19″

Of course, it’s not easy updating KPIs as market the environment changes. “Measuring S&OP is a tricky one”, says Cristian Circiumaru. “I have an S&OP scoreboard that I present monthly at the Executive S&OP meeting so all functions can see their own attendance and are held accountable. I have inventory min and max tracking for key materials as well as forecast accuracy, but not forecast bias at this point in time. Right now, making sure the right people are present at the S&OP meeting is the priority”. Having such KPIs established during normal market conditions is standard practice – having them in times like these is an absolute necessity.

Parting Thoughts

As vaccines are rolled out globally and lockdowns restrictions ease, the end is in sight. But, as Wallace DeMent observes, the challenges are far from over, “We still have a lot pandemic to get through which means more data having to be cleansed at a later date. My fun has just begun.”

Below are the updated forecasts of coronavirus cases and deaths in the USA. The forecasts are daily rolling forecasts, looking 2 months ahead. Alongside the forecast, you will find actuals and forecast accuracy expressed as MAPE. This rolling forecast is updated weekly.

These forecasts are generated by Dr. Chaman L. Jain, Professor of Economics at St. John’s University, and author of the book, Fundamentals of Demand Planning & Forecasting. For further information on this project, including forecast assumptions, click here.

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As we move into this next phase of this Covid-19 global pandemic with countries, states and businesses beginning to open back up, the importance of sound judgement and forecasting is critical. With these new times will come new factors, new information, and potentially new disruptions.

At the same time, we can learn from what we’ve been through so far as we begin to plan for today and what will come post crisis.

Based on our town hall meetings, talking with experts in the field from around the world, best practices, and my own experience, I have extracted these 7 lessons for navigating forecasting and planning as we come out of the pandemic.

1. Focus On Data

The past few months may not be representative of what is to come but we shouldn’t throw out that data. What we need to do is better understand the multiple drivers and begin to cleanse some of this data. We need to see what we can learn from it and possibly even discover new external variables that drive our business forecasts. Now, as we move into this next phase, is a critical time to evaluate the data we have and continue to collect as much data as we can that will help us in the future.

There is also bias and emotion that you need to filter out when faced with new, untested information.

2. Don’t Overreact

This has a couple of meanings for the Demand Planner. First, be careful with statistical black boxes or best pick forecast models. Many of these overreact to recent history or new information without enough consistency and skew trends up or down. Secondly, consider yourself and your own reactions. As we begin this next phase of this crisis there are still many unknowns. There is also bias and emotion that you need to filter out when faced with new, untested information. It is important to try to understand what information is going in and not overreact to what’s coming out, even if it’s negative.

As Erin Marchant, Associate Director for Global Demand Planning at Collins Aerospace, said in a recent article “Don’t panic…The organization will need level heads to lead in a time of uncertainty, and demand planning can provide this leadership.”

Latency in forecasting can be costly and we need to be able to update plans often and efficiently.

3. Update Often

We have been witnessing business and life change at an astounding speed. There is no sign this will change anytime soon. As things change daily, you need to develop a rapid reporting capability or, if you have such a capability in place, keep reporting. Even though we want to make sure we do not overreact to new information, we still need to capture and understand new information as it is made available. As we continue to navigate new consumer demand and environmental factors, ad hoc planning and the running of multiple scenarios will be needed.  Latency in forecasting can be costly and we need to be able to update plans often and efficiently.

Demand is not going to start looking like your historical data anytime soon so you need to look at the why consumers are making those purchases.

4. Continue To Ask Why (Predictive Analytics)

One of the big lessons companies are learning during this pandemic is that, in addition to forecasting with historical sales data, we need to look at external variables as well. Demand is not going to start looking like your historical data anytime soon so you need to continue to look at the why consumers are making those purchases, and why sales for certain products have risen while others have fallen. This is predictive analytics and maybe this pandemic is the impetus you need to get started with something you should have already been doing, or at least thinking about. These answers usher in a new era of predictive analytics and a forward-looking perspective that will help us navigate through this.

5. Don’t Focus Too Much On The “What”

The uncertainty has been horrible and it’s not getting any better. This correlates to poor forecast accuracy and sometimes bias. Measuring uncertainty by measuring forecast accuracy is important to tell other functions what to plan for and risk but does little to tell you how good of a job you are doing – right now your forecast accuracy will be poor and there isn’t too much you can do it about. Don’t focus too much on these numbers, rather focus on how you can use those numbers to improve your processes.

6. Communicate And Be Transparent

One of the best things a Demand Planner can have during these times is humility. We will be wrong, but what we are providing is a best estimate of what is going to happen based on data and collaboration. Do not be afraid to explain the uncertainty and do not shy away from forecast performance. Communicate a data-driven assessment and be transparent when it comes to risk.

7. Prepare For Possible New Norms

Part of humility is the willingness to change. We should expect that because of Covid-19 things will change. Consumers may purchase differently through different channels. Companies you deal with may change inventory policies or buying habits. The forecasting models you relied on no longer work. We must understand and not only prepare for possible new norms but be willing to abandon old assumptions that no longer provide the same results.

8. Get Ready For The Next Black Swan

While we cannot truly predict a black swan, we can see its shadows. Not surprising, history does, and will, repeat itself again and again. Rather than letting out a big sigh of relief and returning to normal routines when the crisis subsides, efforts should be made not to squander a valuable learning opportunity. Collect data now, focus on external variables and more predictive analytics now, and focus on a solid demand planning and forecasting function and best practices today. The one thing we have learned if nothing else is that preparing for the next crisis (or the next phase of the current crisis) now is likely to be much more effective than an ad hoc, reactive response when the next crisis hits.

The following is a daily rolling forecast of Covid-19 cases and deaths in the USA and New York State, looking 2 months ahead. It is prepared by Dr. Chaman L. Jain, Professor of Economics at St. John’s University, and author of the book, Fundamentals of Demand Planning & Forecasting. This forecast will be updated weekly as new data emerges. 

When preparing a forecast for something new, whether it’s a product or a virus, we typically identify an analogous “item”. We identify how the analogous item behaved in the past to predict how the new item will behave in the future. But the patterns of Covid-19 cases and deaths do not correspond with any virus we have experienced before, making this impossible. Further, the patterns in countries like South Korea and China that have nearly gone through the whole coronavirus cycle, do not match with what we are currently experiencing in the U.S.A. Therefore, the only option we have is to study the pattern of cases in the U.S.A. and then extrapolate it going forward. We now have enough data to do so.

Forecasting Coronavirus Cases & Mortality In The United States

Usually, the pattern of a virus (like a new product in business) forms a S curve where it first increases at an accelerated rate and then increases at a decelerating rate. This is exactly what we are seeing in the U.S.A. Covid-19 data. Data shows that we reached the point of inflection in the week of March 16^th, a key turning point when the daily percentage increase in total cases started increasing but at a decreasing rate. In that week, the weekly average of daily increases as a percentage of total cases hit 38%. Thereafter, it started declining and fell to 3.6% in the week of April 20th. I believe this pattern will continue and that the total number of cases in the U.S.A. will hit 1.7 million by June 30^th. After that, we will still have cases of coronavirus, though their number will be much smaller.

The U.S death rate from coronavirus also follows a similar pattern. It reached its point of inflection in the week of April 20^th when the weekly average of daily deaths as a percentage of total cases reached 0.2%. I expect this percentage will continue to slowly decline. With that, I expect the death toll in the U.S to reach 170,000 by June 30^th.

New York State Forecasts

Among all the states, New York state has been hit the hardest. In this state, the pattern of people affected by the virus is very similar to that of the  U.S.A. as a whole. The weekly average of daily percentage increases in total cases peaked in the week of March 16^th when it rose to 58%. Thereafter, it started declining and reached 2.5% in the week of April 20^th. I expect this pattern to continue and that the number of cases in New York will reach 385,000 by June 30^th.

Regarding the number of deaths in New York state, the pattern is the same as the total number of cases. The daily number of deaths as a percentage of total cases kept on rising until the week of March 30^th. Thereafter it declined and is expected to decline further. With that, the total number of deaths in New York State is predicted to reach 30,000 by June 30th.

It should be noted that every forecast is based on certain assumptions. A key assumption here is that things will continue the way they have in the past. During the time period observed to create our forecasts, no vaccine to treat this virus was available. The development of such a vaccine would cause us to revisit our forecasts.

 Daily forecasts are provided in Table 1. One can observe how accurate they are by comparing each day’s forecasts with actuals.

 Check back next week for the updated forecast.

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.

Useful Articles:

Demand Planning During A Recession

Planning During A black Swan Event

Supply Chain Planning During Covid-19

3 Veterans Give Advice On How To Plan For Coronavirus

The Impact Of Coronavirus On Your Forecasts