“When the dust settles down, we will see some substantial changes in supply chains. This disruption has been a wake-up call for many supply chains. In my opinion, the new changes will be the positive outcome of the pandemic. More and more supply chains now realize that they cannot operate effectively in the long run unless they account for the possibilities of disruptions. This is pushing them to design resilient and transparent supply chains,” believes Prof. Subodha Kumar, Paul R. Anderson Distinguished Chair Professor of Marketing and Supply Chain Management and the Founding Director of the Center for Business Analytics and Disruptive Technologies, Temple University’s Fox School of Business.
During and just before COVID-19 pandemic struck business in the end of 2019, businesses couldn’t forecast demand patterns. How did companies deal with such uncertainties?
Let me answer this question by first discussing the key causes of disruptions in demand forecasting and then comparing/ contrasting the response of different supply chains. During the pandemic, businesses had problem in forecasting demand because of multiple factors. First, the forecasting models are usually based on repeating patterns, but what we saw during the pandemic was unprecedented. Therefore, our models were unable to capture the continuously moving unforeseen parts (especially for those products/services that got severely impacted by the pandemic). Second, for many products/services, we do not have clear visibility in the supply chain. Therefore, the fast-moving pattern at the retailer level was not easily visible to the manufacturers. Because of how many of the supply chains are designed, time delay from purchase to signal at the manufacturer level is up to 50 days or even longer for some of the products. Such delays not only hurt the response time, but it also leads to more inventory at each step of the supply chain (referred to as the Bullwhip Effect).
Different supply chains handled the situation differently, and some could not manage it at all. Their reaction depended on multiple factors, e.g., (i) how resilient the supply chain design was, (ii) how much technology was being used, and (iii) how agile the firms involved in the supply chain were.
For example, to meet the demand for N95 mask, 3M employed multiple strategies. First, 3M had designed a lot of resilience in the supply chain following the SARS outbreak by investing in extra capacity. This capacity was mostly idle before the pandemic, but they were able to respond quickly during the pandemic because of this extra capacity. Second, the COVID response caused huge changes for 3M’s supply chain because they were faced with more than one wave, and therefore more than one demand spike. Hence, they needed to somehow accelerate the need for real-time visibility. However, what helped them was their supply chain team had a plan in place. They were already working with FourKites to improve visibility in the supply chain. They had to prioritize the management of at-risk shipments and specific SKUs. They tagged the priority SKUs, such as personal safety and healthcare items, and sent them to the FourKites team. The FourKites data science team was then able to pull those isolated SKUs with the most recent tracking data and put it in to a power BI dashboard to send to all stakeholders. This allowed disparate systems to become one platform where all stakeholders could get the information they needed. As a result, 3M was proactive with customer communication, and they were able to manage the disruption much better than the others. In my opinion, this is a great case study and a great learning experience on how to be ready for such disruptions.
On the other hand, many supply chains were unable to handle the situation in an effective manner. For example, it took a long time for the toilet paper supply chain (and other similar supply chains) to recover from the pandemic. Food supply chains (especially the meat supply chains) were also unable to recover from the disruption quickly. Some of these supply chains have not recovered yet. Most of these supply chains were slow to respond mainly because they did not have much resilience and flexibility in their supply chains, as well as the visibility was very poor.
How should companies prep themselves to sustain in such volatile and uncertain times? Any successful example you would like to share of the companies who led the way during such times exceptionally well?
Ernst & Young conducted a survey of 200 senior-level supply chain executives in late 2020. In this survey, only 2% of companies said they were fully prepared for the pandemic. Therefore, clearly, the supply chains need to prepare themselves well. As I mentioned earlier, 3M is a great example of how they recovered from the supply chain disruptions quickly. When we learn from this example is that (i) supply chains should not only focus on getting lean, rather they should also think of keeping some buffer in a strategic manner, (ii) supply chains need to keep investing in emerging technologies to improve visibility, and (iii) they need to be agile. In 1990s and 2000s, many companies started moving more and more towards lean. This was a great movement to reduce cost and improve efficiency. However, at the same time, supply chains somehow ignored the possible disruptions and lost resilience. This is a good time for supply chains to reflect and modify their objective functions to include the possible disruptions.
Transparency & visibility have become the keywords during these times. How can companies ensure visibility & transparency in their supply chains? How can this same strategy be applied in the warehouses of tomorrow?
Supply chains lack transparency and visibility because of the following reasons: (i) strategic reasons (e.g., some companies may be afraid of inadvertently leaking too much information to their competitors, suppliers, or customers), (ii) lack of proper IT systems (sharing information, especially in the real-time, require a robust IT system at each step of the supply chain), (iii) culture of the companies involved in the supply chain, and/or (iv) lack of top-level commitment. Some of these may require different solutions, but at the broad level, supply chains need to start looking at the possible IT solutions to share information (in possibly real-time) without hurting their strategic positioning. This applies for both within an organization and across the organizations in a supply chain. In late 1990s, many organizations started moving towards ERP systems that could allow them to have a good visibility within an organization. However, even till now, many organizations (both large and small) do not have good visibility even within their own systems. This needs to change if we want to avoid what happened during the COVID-19 pandemic.
In 2000s, many companies started using RFID-based sensors in their warehouses. This helped them in consolidating and collecting data in an efficient manner. This also helped in improving the visibility. Warehouses of tomorrow need to go a step further by utilizing modern sensor and robotic technologies. Warehouses also need to use more IoT infrastructure effectively. For example, Amazon recently opened their largest warehouse in Delaware that has more robots than people.
What are the inherent challenges that companies need to work on in order to harness supply chain opportunities?
Companies need to overcome the reasons discussed earlier for the lack of transparency in supply chains. First, they need to find innovative solutions to share data without disclosing confidential information. Second, companies need to keep using emerging IT solutions to enable real-time (or near real-time) communication. Third (which is maybe most challenging), companies need to work on changing the culture of keeping data/information in silos. Finally, the support of top management is essential.
How can companies enhance their existing supply chains and make it sustainable & agile?
To keep their supply chains sustainable and agile, companies need to take a holistic approach to supply chain management. First, rather than just focusing on reducing cost or improving profit, they need to systematically include the sustainability component in their objective functions. For example, DHL redesigned their routing solutions to develop green logistic solutions. In order to improve agility in their supply chains, companies need to reduce overemphasis on being lean. This requires a fundamental change in the mindset of organizations. If companies don’t start incorporating unexpected future disruptions in their decision-making process, we will not be able to find a long term solution.
Can you kindly enlighten us on innovations in supply chain networks?
All the technology trends I discussed above are leading to interesting innovations in supply chain networks. For example, Wal Mart have started collaborating with several suppliers to share their point-of-sales data in real-time (or near real-time). Wal Mart has also mandated many of their suppliers to join blockchain. On the other hand, the logistics companies are collecting and analyzing real-time data to improve their logistics operations. For example, based on the data from their sensors, UPS decided that their trucks should try to avoid left turns. Amazon Logistics is taking a step further by measuring and analyzing data at the granular level to optimize their logistics operations. Many of these innovations are also looking at reverse logistics in supply chain, which is not only helping companies in reducing their costs but also leading to green supply chains.
How can companies work towards achieving forecasting right?
To get the forecasting right, companies need to include as many factors and moving parts as possible. For example, they should analyze past data rigorously to predict any possible disruptions in advance so that they can update their forecasts proactively. For example, studies have shown that flu trends can be predicted effective using Google Trends and social media data. Similarly, some recent studies have shown how social media data can be used to predict the actual number of COVID cases. Companies need to start utilizing these techniques along with cutting-edge machine learning and deep learning based methods for forecasting. This requires them to get out of the mindset of simply using traditional forecasting techniques.
Kindly share insights with us on your award-winning paper ‘Competitive Strategies for Brick & Mortar Stores to Counter ‘Showrooming’.
In this paper, we first show that the emerging showrooming phenomenon (where customers evaluate an item in a brick-and-mortar store but purchase it from a competing online store) can hurt the profits of the brick-and-mortar stores significantly. Then, we analyze multiple strategies used by the brick-and-mortar stores to reduce the negative impacts of showrooming. We find that the price-matching strategies used by some of the retailers (e.g., Best Buy, Office Depot) can work only in certain situations. More interestingly, if the retailer advertises its price-matching strategy more aggressively, it benefits more in the long-run. We also look at the strategy of making showrooming harder for customers. For example, Macy’s has singed exclusive agreements with Tommy Hilfiger to sell some of their clothes. Clearly, customers cannot find the same item in a competing online store. Some other firms, e.g., TJ Maxx, has started selling more store-brand products that are not possible to find at a competing online store. On the similar line, Target has collaborated with some of their suppliers to use a unique bar code so that it is difficult for customers to easily scan and find the item at a competing online store. We show which strategy works better in what scenarios and provide useful actionable insights for brick-and-mortar stores to combat showrooming.
What are the ways in which companies can build resilient, responsible & sustainable supply chains?
This is very important for supply chain managers to understand that data is the new oil. In order to build resilient, responsible, and sustainable supply chains, companies need to (i) collect real-time data from various courses (e.g., sales data, reviews, social media data, images, videos, etc.) both within the organization and from outside organizations, (ii) analyze them rigorously using machine learning methods, and (iii) develop prescriptive analytics-based solutions. To collect more real-time data, companies need to move more towards blockchains, sensors, IoT, etc. Similarly, to develop meaningful solutions based on prescriptive analytics, companies need to change their objective functions by including reverse logistics, carbon footprint, landfills, life saved, etc. Companies should also work on sharing data in an effective manner so that the both the response time and safety stock can be reduced at the same time.
Share with us the expanse of Supply Chain analytics.
Supply chain analytics can help in each step of the supply chain improvement process. For example, it can help in collecting and curating appropriate data. It can also help in developing predictive and causal models that could help supply chain managers in understanding the process better so that they could act proactively. Finally, the supply chain analytics can help in developing and solving optimization models so that the managers can move from data to decisions. Supply chain analytics also helps in looking at the whole supply chain as one unit rather than looking at each driver of the supply chain (e.g., facility, transportation, inventory, and information) separately.
How do you foresee the future of supply chain shaping up as the COVID-19 dust settles down?
When dust settles down, we will see some substantial changes in supply chains. This disruption has been a wake-up call for many supply chains. In my opinion, the new changes will be the positive outcome of the pandemic. More and more supply chains now realize that they cannot operate effectively in the long run unless they account for the possibilities of disruptions. This is pushing them to design resilient and transparent supply chains.
How would you define Next Generation supply chains?
Next generation supply chain will be informed, analytics-driven, forward looking, transparent, proactive, and agile based on real-time data communication among supply chain partners so that they can predict future well in advance and act accordingly in a timely manner. Next generation supply chain will consider sustainability as an integral part of their operations. The supply chain technology trends that we need to watch are blockchain, Internet of Things (IoT), robotic process automation (RPA), AI/Machine Learning platforms, mixed reality (along with augmented reality and virtual reality), autonomous vehicles, Industry 4.0, and 3D printing.
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