Supply Chain Solutions Innovation Outlook | How COVID-19 disrupts supply chains

Supply Chain Solutions Innovation Outlook | How COVID-19 disrupts supply chains

Posted | Updated by Insights team:
Dr. Evangelo Damigos; PhD | Head of Digital Futures Research Desk
  • Supply Chain
  • Competitive Differentiation
  • Post-Covid-19

Publication | Update: Sep 2020

According to David Deans, Technology Media Telecom analyst, innovative supply chain technologies are proven to deliver, process performance and industry leadership.


Gartner studied current strategic supply chain technology trends that have a high potential for enabling a transformational impact. Some are now reaching critical tipping points in capability and maturity.

"The vast majority of organizations have a cautious approach to adopting supply chain applications and technologies,"
said Christian Titze, vice president analyst at Gartner.

According to Gartner study findings, only 21 percent of survey respondents are willing to consider or adopt early-stage technologies. However, even cautious supply chain leaders must keep an open mind and embrace long-term perpetual change. This is the path to rapid progress and growth.

Supply Chain Solutions Innovation Outlook

"Companies already see the benefits of immersive experiences in use cases like onboarding new factory workers through immersive on-the-job training in a safe, realistic virtual environment," Christian Titze concluded.

According to International Trade Center Research, the COVID-19 pandemic has already hit three major GVC hubs – China, the European Union (EU) and the United States –, creating an unprecedented combination of supply and demand shocks. The decreased demand for inputs by the G3 factories will lead to lower exports of raw materials, parts and components by their partners.


David Deans believes that as more manufacturing returns to a local operations business model, once again, the requirement for supply chain innovation intensifies. It's a key point of competitive differentiation.

Chinese manufacturers will likely continue to emphasize their low-cost advantage, but many of these government-controlled organizations are unable to respond to meaningful and substantive digital transformation. Therefore, it's a huge upside opportunity for changing the rules of the game.

According to Olga Solleder, Economist, ITC, and Mauricio Torres Velasquez, Associate Programme Officer, ITC, the European Union lockdown creates the largest supply chain shock.

The factory shutdown in the EU will have the strongest repercussion for the supply-chain exports of other countries. Why? Because the EU is the largest importer of manufacturing inputs (China is the largest exporter), the largest market for three of the world’s five geographic regions, and highly integrated into global value chains. The EU is the main importer of manufacturing inputs from both Africa and Asia and buys almost as much of manufacturing inputs from Latin America as the United States does.

Our estimations suggest that EU imports of manufacturing inputs will drop by $ 147 billion, out of which 1 billion is intra-EU trade, and billion is imports from other regions. China and the United States come second and third, with shutdowns in China and the United States triggering the reduction of imports of manufacturing inputs by billion and billion respectively (see the columns in the table below). The combined reduction amounts to 8 billion, or 2.4% of the total manufacturing imports by the G3, or 11% if only GVC trade is considered.


Countries in the Americas will export $ 24 billion less of manufacturing inputs, mostly caused by the pandemic-induced shutdowns of factories in the United States and the EU. The shock on Asia amounts to billion, with the majority of loss stemming from the effects of the pandemic in China and the EU. Europe is primarily affected by the factory shutdowns within the EU, amounting to an estimated 8 billion loss of manufacturing exports due to supply-chain disruptions, most of which linked to intra-EU trade in manufacturing inputs. Exporters in Oceania are projected to lose 0 million in exports of manufacturing inputs (see the rows in the table below).

Supply chain disruption will cause a trade plunge in all regions

Notes: Darker colours indicate higher reduction. Percentages are shares of projected reduction in the total manufacturing trade (the total refers to 2019). The values for the European Union include the United Kingdom for consistency across periods. Projected supply chain disruption is calculated as the reduction of imported inputs by the G3, assuming a two-month long shutdown of all factories within the G3, and taking into account the direct effect only (one link in supply chains, i.e. the reduction of exports in countries supplying inputs to the G3).
Source: International Trade Centre.  

Africa is less exposed to supply chain disruptions

African exporters may lose over $ 2.4 billion in global manufacturing value-chain exports due to the shock caused by factory shutdowns in the G3. About three quarters of this loss is caused by the temporary disruption of the supply chain linkages with the EU, while the remaining quarter of the reduction being caused by the shutdowns in China and the United States. When it comes to global value chains, Africa is one of the least integrated regions, and hence experiences the least severe effects of supply-chain disruptions originating in the G3.

Supply-chain disruption is strongest in machinery, plastics and rubber and electronic equipment sectors

The supply-chain disruption mostly affects the machinery, plastics and rubber, chemicals, and electronic equipment sectors. These sectors are likely to be the biggest losers in terms of value, with exports of manufacturing inputs dropping by billion, billion, billion and billion respectively (see values on the figure below). Looking at how big the loss is compared to the size of the sector, ferrous metals, mineral products, synthetic textile fabric, and glass articles top the list. We estimate that the loss of exports of manufacturing inputs due to supply-chain disruptions will exceed 7% of the total export value of these sector.

Sectors with production spread across borders will be hit most by supply-chain disruptions.


Notes: Percentages are shares of projected reduction of GVC imports in the total manufacturing imports of the G3 (the total refers to 2019). The value for the EU include intra-EU trade. The values for the European Union include the United Kingdom for consistency across periods. Projected supply chain disruption is calculated as the reduction of imported inputs by G3, assuming a two-month long shutdown of all factories in the G3, and taking into account the direct effect only (one link in supply chains, i.e. the reduction of exports in countries supplying inputs to the G3). Source: International Trade Centre.  

Rethinking supply chains

The economic consequences of the Great Shutdown are likely to trigger a rethink of how supply chains function, putting the emphasis on resilience. Reinforcing regional operations by shortening supply chains and staying closer to the consumer is one of the possible strategies . Yet, the resilience does not need to rely on self-sufficiency, and reinforcing regional integration is not a call for anti-globalism.

The return to full production requires re-establishing existing links, removing temporary barriers put in place during the emergency, and ensuring an open and predictable world trading system. Immediate attempts to onshore tasks or relocate them closer to home may delay restoring full production because finding alternative suppliers for specialized parts and waiting for deliveries in a travel-restricted world will be lengthy, costly and marred by uncertainty. Furthermore, switching away from the G3 hubs will not be fully effective as their scale of production is hard to compete with.

The solution to the current supply chain disruption and the preparedness for future shocks lies in creating more resilient businesses and more robust links, and not in reducing the size of the system.

¹ World Bank; World Trade Organization. 2019. Global Value Chain Development Report 2019: Technological Innovation, Supply Chain Trade, and Workers in a Globalized World (English). Washington, D.C.: World Bank Group. http://documents.worldbank.org/curated/en/384161555079173489/Global-Value-Chain-Development-Report-2019-Technological-Innovation-Supply-Chain-Trade-and-Workers-in-a-Globalized-World
² In this analysis, we focus on the export of manufacturing inputs within supply chains, defined as inputs used in the production located in at least three countries (or crossing two borders). We exclude final goods, inputs that go into final goods, and inputs that go into goods that are sold domestically. To put the concept in perspective, the world’s export of manufacturing inputs within supply chains in 2019 amounted to $ 2.2 trillion, corresponding to 12% of all manufacturing trade. For further methodological details and other enquiries contact Olga Solleder at Click to show.
³ See SME Competitiveness Outlook 2017 for further details on regional value chains. ITC. 2017. SME Competitiveness Outlook 2017. The Region: A door to Global Trade. Geneva: ITC

Framed Content Aggregator - Publisher | Sponsor
...Industry: Transportation and Logistics
SKU code : 5466293E-865D-D93A-5E71-D5E4AF1643CA
Delivery Format:
HTML ...
Immediate Delivery
...Access Rights | Content Availability:


Objectives and Study Scope

This study has assimilated knowledge and insight from business and subject-matter experts, and from a broad spectrum of market initiatives. Building on this research, the objectives of this market research report is to provide actionable intelligence on opportunities alongside the market size of various segments, as well as fact-based information on key factors influencing the market- growth drivers, industry-specific challenges and other critical issues in terms of detailed analysis and impact.

The report in its entirety provides a comprehensive overview of the current global condition, as well as notable opportunities and challenges. The analysis reflects market size, latest trends, growth drivers, threats, opportunities, as well as key market segments. The study addresses market dynamics in several geographic segments along with market analysis for the current market environment and future scenario over the forecast period. The report also segments the market into various categories based on the product, end user, application, type, and region.
The report also studies various growth drivers and restraints impacting the  market, plus a comprehensive market and vendor landscape in addition to a SWOT analysis of the key players.  This analysis also examines the competitive landscape within each market. Market factors are assessed by examining barriers to entry and market opportunities. Strategies adopted by key players including recent developments, new product launches, merger and acquisitions, and other insightful updates are provided.

Research Process & Methodology


We leverage extensive primary research, our contact database, knowledge of companies and industry relationships, patent and academic journal searches, and Institutes and University associate links to frame a strong visibility in the markets and technologies we cover.

We draw on available data sources and methods to profile developments. We use computerised data mining methods and analytical techniques, including cluster and regression modelling, to identify patterns from publicly available online information on enterprise web sites.
Historical, qualitative and quantitative information is obtained principally from confidential and proprietary sources, professional network, annual reports, investor relationship presentations, and expert interviews, about key factors, such as recent trends in industry performance and identify factors underlying those trends - drivers, restraints, opportunities, and challenges influencing the growth of the market, for both, the supply and demand sides.
In addition to our own desk research, various secondary sources, such as Hoovers, Dun & Bradstreet, Bloomberg BusinessWeek, Statista, are referred to identify key players in the industry, supply chain and market size, percentage shares, splits, and breakdowns into segments and subsegments with respect to individual growth trends, prospects, and contribution to the total market.

Research Portfolio Sources:

  • BBC Monitoring

  • BMI Research: Company Reports, Industry Reports, Special Reports, Industry Forecast Scenario

  • CIMB: Company Reports, Daily Market News, Economic Reports, Industry Reports, Strategy Reports, and Yearbooks

  • Dun & Bradstreet: Country Reports, Country Riskline Reports, Economic Indicators 5yr Forecast, and Industry Reports

  • EMIS: EMIS Insight and EMIS Dealwatch

  • Enerdata: Energy Data Set, Energy Market Report, Energy Prices, LNG Trade Data and World Refineries Data

  • Euromoney: China Law and Practice, Emerging Markets, International Tax Review, Latin Finance, Managing Intellectual Property, Petroleum Economist, Project Finance, and Euromoney Magazine

  • Euromonitor International: Industry Capsules, Local Company Profiles, Sector Capsules

  • Fitch Ratings: Criteria Reports, Outlook Report, Presale Report, Press Releases, Special Reports, Transition Default Study Report

  • FocusEconomics: Consensus Forecast Country Reports

  • Ken Research: Industry Reports, Regional Industry Reports and Global Industry Reports

  • MarketLine: Company Profiles and Industry Profiles

  • OECD: Economic Outlook, Economic Surveys, Energy Prices and Taxes, Main Economic Indicators, Main Science and Technology Indicators, National Accounts, Quarterly International Trade Statistics

  • Oxford Economics: Global Industry Forecasts, Country Economic Forecasts, Industry Forecast Data, and Monthly Industry Briefings

  • Progressive Digital Media: Industry Snapshots, News, Company Profiles, Energy Business Review

  • Project Syndicate: News Commentary

  • Technavio: Global Market Assessment Reports, Regional Market Assessment Reports, and Market Assessment Country Reports

  • The Economist Intelligence Unit: Country Summaries, Industry Briefings, Industry Reports and Industry Statistics

Global Business Reviews, Research Papers, Commentary & Strategy Reports

  • World Bank

  • World Trade Organization

  • The Financial Times

  • The Wall Street Journal

  • The Wall Street Transcript

  • Bloomberg

  • Standard & Poor’s Industry Surveys

  • Thomson Research

  • Thomson Street Events

  • Reuter 3000 Xtra

  • OneSource Business

  • Hoover’s

  • MGI

  • LSE

  • MIT

  • ERA

  • BBVA

  • IDC

  • IdExec

  • Moody’s

  • Factiva

  • Forrester Research

  • Computer Economics

  • Voice and Data

  • SIA / SSIR

  • Kiplinger Forecasts

  • Dialog PRO

  • LexisNexis

  • ISI Emerging Markets

  • McKinsey

  • Deloitte

  • Oliver Wyman

  • Faulkner Information Services

  • Accenture

  • Ipsos

  • Mintel

  • Statista

  • Bureau van Dijk’s Amadeus

  • EY

  • PwC

  • Berg Insight

  • ABI research

  • Pyramid Research

  • Gartner Group

  • Juniper Research

  • MarketsandMarkets

  • GSA

  • Frost and Sullivan Analysis

  • McKinsey Global Institute

  • European Mobile and Mobility Alliance

  • Open Europe

M&A and Risk Management | Regulation

  • Thomson Mergers & Acquisitions

  • MergerStat

  • Profound

  • DDAR

  • ISS Corporate Governance

  • BoardEx

  • Board Analyst

  • Securities Mosaic

  • Varonis

  • International Tax and Business Guides

  • CoreCompensation

  • CCH Research Network

Forecast methodology

The future outlook “forecast” is based on a set of statistical methods such as regression analysis, industry specific drivers as well as analyst evaluations, as well as analysis of the trends that influence economic outcomes and business decision making.
The Global Economic Model is covering the political environment, the macroeconomic environment, market opportunities, policy towards free enterprise and competition, policy towards foreign investment, foreign trade and exchange controls, taxes, financing, the labour market and infrastructure. We aim update our market forecast to include the latest market developments and trends.

Forecasts, Data modelling and indicator normalisation

Review of independent forecasts for the main macroeconomic variables by the following organizations provide a holistic overview of the range of alternative opinions:

  • Cambridge Econometrics (CE)

  • The Centre for Economic and Business Research (CEBR)

  • Experian Economics (EE)

  • Oxford Economics (OE)

As a result, the reported forecasts derive from different forecasters and may not represent the view of any one forecaster over the whole of the forecast period. These projections provide an indication of what is, in our view most likely to happen, not what it will definitely happen.

Short- and medium-term forecasts are based on a “demand-side” forecasting framework, under the assumption that supply adjusts to meet demand either directly through changes in output or through the depletion of inventories.
Long-term projections rely on a supply-side framework, in which output is determined by the availability of labour and capital equipment and the growth in productivity.
Long-term growth prospects, are impacted by factors including the workforce capabilities, the openness of the economy to trade, the legal framework, fiscal policy, the degree of government regulation.

Direct contribution to GDP
The method for calculating the direct contribution of an industry to GDP, is to measure its ‘gross value added’ (GVA); that is, to calculate the difference between the industry’s total pre­tax revenue and its total bought­in costs (costs excluding wages and salaries).

Forecasts of GDP growth: GDP = CN+IN+GS+NEX

GDP growth estimates take into account:

  • Consumption, expressed as a function of income, wealth, prices and interest rates;

  • Investment as a function of the return on capital and changes in capacity utilization; Government spending as a function of intervention initiatives and state of the economy;

  • Net exports as a function of global economic conditions.


Market Quantification
All relevant markets are quantified utilizing revenue figures for the forecast period. The Compound Annual Growth Rate (CAGR) within each segment is used to measure growth and to extrapolate data when figures are not publicly available.


Our market segments reflect major categories and subcategories of the global market, followed by an analysis of statistical data covering national spending and international trade relations and patterns. Market values reflect revenues paid by the final customer / end user to vendors and service providers either directly or through distribution channels, excluding VAT. Local currencies are converted to USD using the yearly average exchange rates of local currencies to the USD for the respective year as provided by the IMF World Economic Outlook Database.

Industry Life Cycle Market Phase

Market phase is determined using factors in the Industry Life Cycle model. The adapted market phase definitions are as follows:

  • Nascent: New market need not yet determined; growth begins increasing toward end of cycle

  • Growth: Growth trajectory picks up; high growth rates

  • Mature: Typically fewer firms than growth phase, as dominant solutions continue to capture the majority of market share and market consolidation occurs, displaying lower growth rates that are typically on par with the general economy

  • Decline: Further market consolidation, rapidly declining growth rates


The Global Economic Model
The Global Economic Model brings together macroeconomic and sectoral forecasts for quantifying the key relationships.

The model is a hybrid statistical model that uses macroeconomic variables and inter-industry linkages to forecast sectoral output. The model is used to forecast not just output, but prices, wages, employment and investment. The principal variables driving the industry model are the components of final demand, which directly or indirectly determine the demand facing each industry. However, other macroeconomic assumptions — in particular exchange rates, as well as world commodity prices — also enter into the equation, as well as other industry specific factors that have been or are expected to impact.

  • Vector Auto Regression (VAR) statistical models capturing the linear interdependencies among multiple time series, are best used for short-term forecasting, whereby shocks to demand will generate economic cycles that can be influenced by fiscal and monetary policy.

  • Dynamic-Stochastic Equilibrium (DSE) models replicate the behaviour of the economy by analyzing the interaction of economic variables, whereby output is determined by supply side factors, such as investment, demographics, labour participation and productivity.

  • Dynamic Econometric Error Correction (DEEC) modelling combines VAR and DSE models by estimating the speed at which a dependent variable returns to its equilibrium after a shock, as well as assessing the impact of a company, industry, new technology, regulation, or market change. DEEC modelling is best suited for forecasting.

Forecasts of GDP growth per capita based on these factors can then be combined with demographic projections to give forecasts for overall GDP growth.
Wherever possible, publicly available data from official sources are used for the latest available year. Qualitative indicators are normalised (on the basis of: Normalised x = (x - Min(x)) / (Max(x) - Min(x)) where Min(x) and Max(x) are, the lowest and highest values for any given indicator respectively) and then aggregated across categories to enable an overall comparison. The normalised value is then transformed into a positive number on a scale of 0 to 100. The weighting assigned to each indicator can be changed to reflect different assumptions about their relative importance.


The principal explanatory variable in each industry’s output equation is the Total Demand variable, encompassing exogenous macroeconomic assumptions, consumer spending and investment, and intermediate demand for goods and services by sectors of the economy for use as inputs in the production of their own goods and services.

Elasticity measures the response of one economic variable to a change in another economic variable, whether the good or service is demanded as an input into a final product or whether it is the final product, and provides insight into the proportional impact of different economic actions and policy decisions.
Demand elasticities measure the change in the quantity demanded of a particular good or service as a result of changes to other economic variables, such as its own price, the price of competing or complementary goods and services, income levels, taxes.
Demand elasticities can be influenced by several factors. Each of these factors, along with the specific characteristics of the product, will interact to determine its overall responsiveness of demand to changes in prices and incomes.
The individual characteristics of a good or service will have an impact, but there are also a number of general factors that will typically affect the sensitivity of demand, such as the availability of substitutes, whereby the elasticity is typically higher the greater the number of available substitutes, as consumers can easily switch between different products.
The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
Proportion of the budget consumed by the item. Products that consume a large portion of the consumer’s budget tend to have greater elasticity.
Elasticities tend to be greater over the long run because consumers have more time to adjust their behaviour.
Finally, if the product or service is an input into a final product then the price elasticity will depend on the price elasticity of the final product, its cost share in the production costs, and the availability of substitutes for that good or service.

Prices are also forecast using an input-output framework. Input costs have two components; labour costs are driven by wages, while intermediate costs are computed as an input-output weighted aggregate of input sectors’ prices. Employment is a function of output and real sectoral wages, that are forecast as a function of whole economy growth in wages. Investment is forecast as a function of output and aggregate level business investment.