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Contingency Planning 2.0: A Guide On Which Data To Use And Decisions To Make In Times Of Change

by Widget Brain, on Jul 7

As the challenges presented by COVID-19 continue to affect the workforce around the world, companies are finding new ways to prepare for the next unexpected crisis. The pandemic has highlighted how vitally important it is for businesses to be able to plan for anything and remain efficient, even when the next disruption hits.

 

Fortunately, various tech solutions provide the opportunity to do just that. In our eyes, one of the most important is automated scheduling, which enables companies to make operational decisions better and faster in volatile situations like COVID-19 but also other situations all around the world where you need to adapt fast.

 

The speed of decision making is important as it determines how fast companies react in the short, mid, and long term. It helps you to re-open faster and to cover the minimum requirements to be operational from the beginning and in the long term it allows you to outsmart the competition and come prepared for the full rebound – even when times are uncertain.

 

 

The impact of COVID-19 on businesses

  • Supermarkets and e-commerce based companies saw an increase in online orders up to 250%. They compared their sales with the sales typically seen during Christmas. In this situation, companies had to get new employees to meet that surge in demand fast.
  • Hospitality businesses like quick-service restaurants who stayed open to serve local communities have seen a decline in in-store purchases, but an increase in drive-thru orders. Sometimes this mounted to a 36% increase. This had a significant impact on how and who they staffed to meet this changing demand.
  • Other companies in this sector, including hotels, have seen a significant drop in bookings of up to 91%.

 

It’s clear that there has been an extreme variety in what companies had to cope with and the decisions they had to make during these unprecedented times, but what’s the best way forward?

 

Businesses are not made for change 

If there’s one thing that we have learned from this crisis, it’s that businesses are built around predictability, not change. Companies are extremely fine-tuned the way they approach their market and customers, which has rewarded them to be the best in their business and to deliver superior services. However, that does mean that change is very expensive and something established businesses can’t do fast. When companies can handle extreme change in situations like this, it means that they had resources that they weren’t using before. This often isn’t the case. 

 

On top of that, the way companies make operational decisions, like who to schedule tomorrow, when to distribute products or to come up with new services to cope with new situations, is often done manually. Current decision-making is often not rapid enough because a lot of people are involved in decision-making. That means that businesses are often too slow to respond to sudden changes because stakeholders need to be retrained to decide based on the new facts. 

 

The trust and accuracy that companies typically have when making decisions come from what they already know and have seen before. Companies, therefore, often lack the confidence to make new decisions because they aren’t familiar with new data and patterns they see and it’s, therefore, hard to judge if this data is actually accurate enough to make solid decisions on. Companies don’t know if the new uptake they see in the data also continues for a while. Since we don’t have experience with new data, it’s in our human nature to distrust it since that pattern can also decline or flatten for as far as we know. This lack of seemingly unpredictability further challenges us to make operational decisions, because how do you know if you have to staff up or down next week? So experts are being called in to make an experienced guess but in the end, they also do not know how the abnormal behavior of the market translates into the right decisions. Being able to incorporate more and more elements of the complete decision-making process will help you make better decisions faster. This means you need to start thinking about decision-making across HR, finance, operations, and back and front of the store.

 

It’s safe to say that people tend to rely on experience and knowledge to make decisions. And this knowledge is often what we call head knowledge, it’s not absorbed in any software and it basically sits in the head of the experienced managers. This head knowledge allows companies to run an efficient business with good people in a predictable environment, but it doesn’t really help you accelerate when we are in a volatile situation like COVID-19. Suddenly there is a new reality. That reality needs to be learned and old behavior needs to be unlearned. 

 

That’s why we’d argue that the solution to handling change in unprecedented times is to learn and decide faster than before. From our perspective, this means that you would have to automate your decision-making process and embed that head knowledge into the software you use. 

 

The knowledge, data, and decisions in the short, mid and long term

The key to surviving major disruptions lies in rapid adaptation, and in doing so, be able to adapt with all new relevant information at your disposal. You also have to consider that in times of disruption, past information, knowledge, and experience often become less relevant.  Therefore, information must be absorbed quickly as it comes to light. More importantly, we need to derive knowledge from it as soon as possible. Then we need to trust the new knowledge to act on it. 

 

What is knowledge? It’s a pattern that we suddenly recognize as being valid for this period. 

 

In the short term, you want to adapt your operating model fast. If we take the COVID-19 situation as an example, many companies had to close but others had to make decisions on what the minimum requirement was to remain open and which skeleton crew they could set up to stay operational. In the short term, the key focus is to stay in business, re-open and worry about margins later. 

 

 

An example of short term data: Foot traffic forecasts based on data from two weeks ago may be obsolete by the time the shift occurs. The normal patterns for foot traffic may have changed dramatically due to disruption. The new foot traffic of yesterday is already showing a new pattern. One that is maybe 40% lower but still recognizable. So when do you feel comfortable that the pattern stabilized and that you can trust it?

 

After a few weeks, in the mid-term, you’ll see that data and patterns will re-appear. You’ll have new sales data, even if it only represents the last couple of weeks. It’s the first indication of (new) services ramping up and you can decide to adapt your business model and the way you work. When adapting workforce strategies to fit these new conditions, previous calculations must be rapidly adjusted to optimize efficiencies. The data that you have gathered in the mid-term can be examined and executed on with more confidence than you did before, but since it’s still new data you’ll never really know if those patterns hold. You’ll probably see data stabilizing after a few months, patterns become clearer and you’ll have a better understanding of what the future will look like. 

 

Finally, while it can be nearly impossible to predict what lies ahead, you need to look at your decision-making holistically, take different future scenarios and make calculated decisions on what steps to take if each one happens.

 

 

An example of long term decisions: at the outset of a disruption that has no end in sight, many businesses may see the immediate need to shore up liquidity, cut costs, and freeze growth initiatives. But what if these actions render you non-competitive for the next phase of the disruption? What if there was a different opportunity or path to take? Continuously examining scenarios and projecting impacts opens a much broader set of possibilities for success.

 

 

Now, we understand that accounting for new data and the decisions that come with it is easier said than done. So, let’s double down with real-life examples, the measures to take and the role of technology in solving these challenges.

 

 

SHORT-TERM PLANNING: Adapting operating models

 

With any unprecedented challenge, businesses must adapt their operating models fast to fit new and changing conditions. They need to develop new schedules that account for new tasks and changing timelines. This year, businesses had to increase hygiene standards, stagger the number of people in-store, and perhaps expand different sides of their businesses. Dealing with these extra tasks and new services changes the timeline of a usual working day. These measures help you to keep your employees and customers safe, keep control of the process, but you still don’t know how long it will last. Technology can be used to help account for those short, immediate changes. 

 

  • Adjusting Labor Standards: As the workday changes, that has knock-on effects on the way tasks are normally performed. The new operating model, in its rudimentary form, should be modeled out in a simple exercise and readjusted each day to match the realities of yesterday. This shortens the cycle to get to the “new normal”. For example, you might find that you are selling more coffee and in their drive-thrus than you usually do. How do you make sure you have enough employees to meet that new demand in coffee and drive-thru orders when employees can’t easily get to work anymore. Labor standards should, therefore, be adjusted accordingly when businesses are looking at the work achieved in a certain amount of time by staff, test that for one location, and scale up if those newly defined labor standards work. 
  • Implementing New Services: In order to survive, sometimes you need to pivot your organization and start becoming smart again. What is required in the market now? If your customer can’t come to the store, let’s deliver the product to the customer. Restaurants all over the world experienced this and showed how fast you can create a new business model when it’s clear that the old one won’t suffice. These new services may include different tasks and other opening and closing hours than usual. It’s not uncommon for companies to find themselves new optimal opening and closing hours due to changes in customer behaviors caused by external disruption. 
  • Re-optimizing schedules: Disruptions may also prevent people from being able to work. Take, for example, if someone is sick with COVID-19. Or, if someone needs to remain socially distant due to being at-risk.  In the event that schedules need to be revised at the last minute with limited staffing availability, automated scheduling provides the ability to rapidly and automatically adapt shift assignments to account for such short-term callouts or shift assignments, and finds the minimum operating level in which your business can still run. It’s then important to signal to your customer base, what you are still capable of, and what is currently not possible.

 

 

THE HOTEL CASE 

Prior to COVID-19, one of our hotel customers used a complex variable labor standard. They built up this knowledge set in a period of many years, minutely measuring each task to the second

 

During the lockdown, two things happened: their business stopped and they needed to figure out what is required to run a skeleton crew in the hotels that were still open. We worked together on figuring out new rules around safety and introduced a team A/team B rule, also called A/B scheduling, where employees would not be exposed to the whole population but only their own team, to avoid possible infections across the whole population. 

 

Secondly, their labor standards dramatically changed due to extended cleaning and the hotel being used for other purposes. We jointly worked out a simple labor standards model and implemented this across their hotels. This significantly reduced the time for the hotel staff to be up and running and trusting the data helped to organize the new services.

 

MID-TERM PLANNING: Re-examining demand

Demand has been thoroughly disrupted by the global health situation. Customers are more accustomed to restrictions on how many times they can leave the house, meaning they visit supermarkets and shops significantly less than before. Restaurants and cafes have been operating on a delivery-only basis in many countries around the world. eCommerce, on the other hand, has experienced a boost as people stuck at home browse and buy online. 

 

Even though this data gives some indication of what to do next, many businesses are still unsure about the number of customers and sales that they’re due to see in the coming months. Businesses looking for that additional element of control may find it critical to discover their future demand patterns in order to continue running their business as efficiently as possible. 

 

But again, since this is new data, how do we identify short term trends and use this data to make reliable demand forecasts for the future? 

 

Businesses normally aim to forecast demand and schedule shifts at least 2 weeks in advance, often to comply with laws and regulations. During normal circumstances, forecasts are typically based on a large span of historical data, in order to improve precision and account for trends in seasons, holidays, peak business months, etc. In a disruption, demand forecasts can no longer be based on typical conditions or respective data, meaning what happened two or three weeks ago probably no longer applies. Think about it: Big changes can happen between that first schedule release and the shift itself. For example, people unable to work or footfall significantly decreased, leading to less staff required. It’s therefore important to make forecasts based on the data leading up to the day of operations. This allows you to discover new trends that you may have never seen before. 

 

This is what you can do:

 

  • Limiting the data scope: Normally, when it comes to forecasting, the more data the better! However, when disruption hits, historical data is not as relevant because the situation changes rapidly. Businesses, therefore, need to consider the most recent data in order to understand what will happen in the near future. The data that is most representative of the current trending situation can help achieve this.
  • Disruption events: In some cases, the disruption that a business is currently facing may have similar trends or similar nature of a previous disruption the business has faced in the past. If this is the case, the events of the past can be used to predict demand in the immediate future. Businesses should look at their past data and decide what is most relevant to the current situation. 

 

It’s imperative that you not only recognize the trends and patterns in the new data quickly but also build up the confidence that these patterns are reliable enough to execute on. These elements allow companies to act with their actual demand in mind. 

 

 

THE QSR CASE 

Prior to COVID-19, New York’s fair labor laws required schedules to be posted at least two weeks in advance. During the disruption, these laws were lifted, allowing businesses like QSRs to change employee schedules during the week of operation or even during the day of operation.

 

For our customer, we actually copied prior actual data from each week and used that as the forecast since the demand was so variable. Based on the actual data, Widget Brain then created headcount curves with a new labor standard and ran the schedules automatically for a whole chain of restaurants. 

 

Later on, we started creating forecasts based on new patterns. This, combined with the simple labor standard, turned out to be the best solution for this restaurant chain, which is still in use today.

 

SCENARIO PLANNING: Continuously test assumptions  

A couple of months in, you’re at a point when you start to look at events like COVID-19 holistically again. You pivoted your business, came up with new services and you’re trying to rebound. Now it’s important to start planning for the longer terms across all new data and variations that you see. That’s where scenario planning comes into play.

 

  • Scenario planning: Companies should create different scenarios, one conservative, normal, and positive scenario that each represents the different economic situations you could possibly go into. The key here is to check new data and to see if they match any of the scenarios you’ve defined before. This proactive behavior allows companies to take action and bounce back quicker. 
  • Skill inventory: Mapping out employee skills enables businesses to factor in how many employees, with which skills, would need to be retained in order to preserve the necessary institutional knowledge to continue running your business. Businesses should create hierarchical maps of their skilled workers, for an efficient downsizing or upsizing approach in each of the scenarios at hand. 

 

Scenario planning across your business enables you to understand and calculate through what certain assumptions and new data mean to your business and will accelerate your decision making. It gives companies confidence in their decision making and to absorb relevant data faster. If you, for example, see a downtrend, you can already see what other decisions will be necessary to be made, across multiple areas of your business. Not only operations but also HR, finance, and legal. 

 

How Widget Brain can help

It has become clear that the key to contingency planning 2.0 is to speed up your decision making. Your speed of decision-making is dependent on the level of automation implemented in your business process.

 

Widget Brain supports businesses in their future contingencies with the AI technology to automate your employee schedules, allowing you to navigate difficult times by making better decisions faster to stay open, safe, and cost-efficient.

 

We offer a suite of algorithms that help companies make better decisions faster in the immediate and far future. From recovery, forecasting to get accurate insights on when business is expected to pick up, to automatically creating schedules taking A/B teams, new regulations, and extra tasks into account, to planning months ahead based on various scenarios, start preparing for the next disruption. 

 

Contact Widget Brain to get a demo and learn how you can benefit from automated decision-making in workforce management and beyond.