Accelerating Supply Chain Scenario Planning

The pandemic showcases a need to make slow-moving supply chains nimbler. Using data and collaborating with partners on scenario planning can empower companies to adapt.

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In spring 2020, when the COVID-19 pandemic had disrupted supply chains across numerous major industries worldwide and showed no signs of abating, most organizations had limited vision in terms of how they should prepare to resume business activities. This lack of clarity resulted from a confluence of uncertainties, including when an effective vaccine might be widely available and what mandates governments might implement to curb the coronavirus’s spread. As organizations and their supply chain partners have turned to scenario planning to help them “see” actionable paths amid the pandemic, such planning has become faster, nearer term, more inclusive, and digital.1 Our field research has found that digital technologies, data, and collaboration with supply chain partners are central to this effort.

Conventional scenario planning involves considering possible future states for a planning horizon ranging from three to 30-plus years. It requires a multistep deliberation process within the boundary of a single organization or its supply chain that may take a few months after the data has been analyzed. (See “A Primer on Supply Chain Scenario Planning.”) Planners revisit these scenarios when uncertainties emerge, especially as a crisis becomes evident.

Developments in the past five years have triggered widespread applications of scenario planning, but with shorter time frames and different methods than in the past. U.K. citizens’ 2016 vote to leave the European Union, as well as issues emerging from U.S.-China trade negotiations that began in 2017, raised concerns about major supply chain disruptions whose precise nature was unpredictable — and that was before the COVID-19 pandemic emerged as a global risk.

Disruptions caused by the pandemic put new urgency into scenario planning for all types of supply chains, such as those for delivering personal protective equipment or servicing the flow of patients through hospital systems. These scenarios have used planning horizons of a few weeks instead of several years, and organizations are creating scenarios in a few days or weeks instead of months.

How can supply chain executives create scenarios at such a rapid pace without compromising the quality and the extent of information needed to create relevant scenarios?

First, by taking advantage of digital capabilities: up-to-date data — including data from new types of sensors and social media — and the means to analyze this data using advanced analytic tools and artificial intelligence techniques. And second, by engaging in collaborative scenario planning, in which upstream and downstream organizations in a supply chain jointly create scenarios.

Collaborative scenario planning can take several forms. It can involve two independent organizations in a buyer-supplier relationship, or separate business units (such as different geographical units) or functional units (such as manufacturing in China and distribution in the U.S.) within one company.

How might adopting digital capabilities and collaborative scenario planning improve an organization’s core processes for creating supply chain scenarios at such a rapid pace? We’ve identified four mechanisms that draw on digital capabilities and/or collaborative planning to enable accelerated scenario creation.

1. Convert driving forces into local factors. An organization can convert global driving forces that one of the organizations faces into local factors through the deployment of digital capabilities.

Consider an example from higher education, in which a university creates a service supply chain, with students entering to attend classes and leaving upon graduation. During the COVID-19 pandemic, investments in digital and biomedical technologies could turn the uncertainty associated with the pandemic into a factor over which university administrators can exert more influence.

For instance, educational institutions can now count on low-cost audio and videoconferencing technologies, such as Zoom and Microsoft Teams, to continue to teach courses. In addition to Zoom, Boston University (where one of us teaches) has invested in a rapid COVID-19 testing and sample-analysis capability in this service supply chain. The process includes robots for automated processing of the tests for students and staff members. The university’s laboratory can process nearly 5,000 tests daily, delivering the results within 24 hours. The institution could not influence external test providers’ capacity to process excessive numbers of COVID-19 test samples, so it turned that global driving force into a local factor that it can influence. Investments in these biomedical and digital technologies have enabled the university to create new options for planning and delivering educational services. More than 20,000 students can learn by either attending classes in a safe on-campus setting or by accessing lessons through distance learning.

2. Convert local factors into focal decisions. This mechanism applies to a collaborative setting for supply chain scenario planning and turns local factors that either organization in the collaborative relationship cannot control into focal decisions that the two members can make jointly.

The health care industry offers a useful illustration in the service supply chain context. During the pandemic, driving forces include spikes in COVID-19 cases and governmental guidance on reserving hospital bed capacity for seriously ill patients. Local factors include the hospital’s capacity in terms of available beds, surgery units, and staff. By using telemedicine to screen patients and decide who needs to come in, hospitals can gain control over some of their patient inflow and decrease the likelihood that their capacity will be overwhelmed.

Collaborative planning, meanwhile, can help control the flow of elective-surgery patients to hospitals. This pairs organizations that offer primary care with the hospitals and ambulatory care centers to which they make referrals. When a referral organization and a downstream hospital plan collaboratively, demand for elective procedures can be better matched with capacity.

One enabler for addressing the complexity is rapid what-if analysis (such as system dynamics simulations) to characterize scenarios for which precise data is not available.2 Primary care clinics and hospitals could use such simulation scenarios to incorporate local factors such as hospital bed capacity constraints into focal decisions for scheduling elective surgeries. Options that emerge could be to schedule surgeries for after the COVID-19 patient demand declines and to identify alternative surgery centers that do not have bed-capacity constraints.3

3. Use collaborative exchanges to improve supply chain visibility. Including more than one organization’s experts and data in developing scenarios can improve views into potential futures and help executives to more quickly understand risks and opportunities. Our behavioral experiments have shown how collaborative scenario creation can enable decision makers to consider a broader range of potential outcomes for their supply chains than they would working independently. In joint scenario development, each organization evaluates the upstream and downstream variables it can either control or influence, and the parties can then use data analysis to identify those variables that might be relevant to the supply chains of both participants. This can increase the visibility of some variables that an organization might be unaware of without collaborating with its supply chain partner.

For example, a chemical company that we have followed uses bulk ocean carriers to ship its finished goods from the production country to the market country. It may be possible for this chemical manufacturer to locate a ship’s movement using a global tracking system such as Shipfinder. However, the manufacturer’s plans are also affected by variables such as the shipper’s fleet capacity, its crew availability, delays in port inspections for toxic materials, and other legal restrictions on bulk shipping during a rapidly evolving situation like the COVID-19 pandemic.4 The chemical maker can gain visibility into such issues only by joining forces with its shipping company. Such details and their influence on scenario planning are accessible only through collaboration with supply chain partners.

4. Use collaborative information to eliminate bias. A limitation of accelerated scenario creation by a single organization is the possibility that managers’ biases may affect the assessment of whether factors can or cannot be influenced. An important observation in our study of collaborative scenario creation was a reduction in the risk of being biased or blindsided.5

A collaborative scenario planning approach, and access to additional data, can potentially minimize debates within a single organization and speed up decision-making for the supply chain. Information of potential relevance can be shared with upstream partners faster when they jointly consider scenarios.

For example, in field work we observed that one U.S.-based apparel company’s operations group based in Asia decided to expand its base of fabric suppliers in January 2020. At the time, the COVID-19 virus was spreading in China but was not yet considered a global pandemic. In this case, there was broad information sharing. The operations group pointed out that without alternative fabric sourcing in Vietnam, the company’s production in Thailand and Vietnam could be shut down, which would impair its ability to meet U.S. market demand. Such visibility and a contingency planning exercise eliminated the bias against broadening the supplier base as both the manufacturing and distribution teams recognized the planning need. As a result, the company brought in new alternate fabric suppliers.

In supply chain planning, joint efforts (such as sharing demand information) are common. However, collaboration for the purpose of scenario planning, and allied organizational learning with the goal of just-in-case preparedness, are emergent phenomena in terms of strategic supply chain decision-making.

Collaborative scenario creation based on data and digital capabilities and supply chain partners’ information exchanges can improve the quality of both the process and the outcome of supply chain scenario planning. Such approaches create opportunities for managers to access higher-quality information for scenarios, create more scenarios with deeper visibility, and have more information for faster decision-making.

It’s clear to us that supply chain organizations that do not have access to data and digital capabilities will be at a competitive disadvantage now and after the pandemic.6 Digital capabilities and collaborative development between buyers and suppliers, while accelerating supply chain scenario planning, will make these scenarios less susceptible to biases and open up valuable views into both risks and opportunities.

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References

1.How to Adopt the New Style of Scenario Planning,” The Economist, June 2, 2020, https://applied.economist.com.

2. E.G. Anderson, R. Freeman, and N. Joglekar, “Ramping Up Elective Surgery After COVID-19 Disruption: Service Capacity Analysis,” SSRN, May 6, 2020, https://ssrn.com.

3. Anderson, Freeman, and Joglekar, “Ramping Up Elective Surgery.”

4.Operational Considerations for Managing COVID-19 Cases/Outbreak On Board Ships,” World Health Organization, March 25, 2020, www.who.int.

5. S. Phadnis and N. Joglekar, “Configuring Supply Chain Dyads for Regulatory Disruptions: A Behavioral Study of Scenarios,” Production and Operations Management, forthcoming.

6. N. Joglekar, G. Parker, and J. Srai, “Winning the Race for Survival: How Advanced Manufacturing Technologies Are Driving Business-Model Innovation,” SSRN, May 27, 2020, https://ssrn.com.

i. C. Caplice and S. Phadnis, “Strategic Issues Facing Transportation, Volume 1: Scenario Planning for Freight Transportation Infrastructure Investment” (Washington, D.C.: The National Academies Press, 2013).

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