...
...

8 Macro Factors for post- COVID-19 Scenario Planning

Posted | Updated by Insights team:
Dr. Evangelo Damigos; PhD | Head of Digital Futures Research Desk
  • Competitive Differentiation
  • Sustainable Growth and Tech Trends
  • Post-Covid-19


Publication | Update: Sep 2020

COVID-19 might dominate the headlines, but it’s just one of eight key macro factors that will reshape business in this decade. According to Mark Raskino, Distinguished Vice President Analyst at Gartner, the global pandemic will have a long-lasting and far-reaching impact on the business world, but other shifts in macro business environment areas — such as oil prices, weakening international relationships, and climate change — have not gone away.

Executives will have to grapple with a host of other challenges during the 2020s, but from that maelstrom will rise new business opportunities.  

No. 1: Global pandemic 

The impact of COVID-19 will depend heavily on how long the pandemic lasts. A shorter time frame means that people will revert more quickly to pre-pandemic ways of operating. For example, after 9/11, people reverted to normal flying behavior three years later. If the pandemic persists, it’s more likely to have long-lasting societal effects. For example, the Great Depression impacted food habits for decades. 

No. 2: Market crash and recession 

Although COVID-19 served as the visible catalyst for the 2020 market crashes and subsequent recovery, the reality is the markets were already fragile and precarious. In fact, Gartner found that in 2018 and 2019, half of CEOs were anticipating and preparing for an economic downturn, which makes this recession unique to those in 2002–2003 and 2009. 

No. 3: Tech exuberance fade

For the past 10 years, a variety of game-changing emerging technologies were a big focus for companies looking to innovate and differentiate. This tech enthusiasm may deflate during the next few years. Some technology, like artificial intelligence (AI), will continue to be popular, but uptake of more “bleeding-edge” technologies like quantum computing and blockchain, with less-obvious use cases, could slow. 

No. 4: Talent shortage 

Despite an increase in unemployment rates globally, key talent shortages will continue to plague executives. While COVID-19 has increased unemployment and underemployment, it has not created new pools of in-demand talent

No. 5: Systemic mistrust 

Even before COVID-19, global consumer and citizen trust was at an all-time low. Now, closed borders, combined with a mistrust of “other”— even previously close trading partners — threatens to widen the gap. However, it’s possible that over the long term, a common enemy in the virus will inspire empathy, common purpose and cooperation. 

No. 6: Weak productivity 

Slow productivity growth and a lack of focus on efficiency and productivity has been at odds with the economic growth of the past decade. COVID-19 could drive changes that require executives to take a closer look at operations of the organization, from out-of-date products to bureaucratic roadblocks.

No. 7: Oil price conflict 

The current global economy relies on oil. At its peak in 2008, oil reached a price per barrel of $ 150, but now faces the opposite and unplanned extreme. In March 2020, due to a dispute between Russia and Saudi Arabia, the price per barrel dropped to around and after recovering, has hovered around . This has the ability to reset assumptions that are the basis of global competition in many industries and reshape economies. 

No. 8: Climate change 

At the very start of 2020, climate change was moving to the forefront of framing long-term business strategy and plans. Although temporarily overshadowed by COVID-19, executives should assume it will continue to influence businesses for the next decade. 

Executive leaders must never short-change time spent on scenario planning and replanning.

The original article by Mark Raskino, Distinguished Vice President Analyst at Gartner, is here

 

 

Seven potential options for financial institutions to react to Fintechs

According to Alexis Krivkovich, Senior Partner and Zac Townsend, an Expert Associate Partner, both in McKinsey’s San Francisco office, over the past ten years, what started mostly as disruption in the payments space has expanded to every corner of finance. Wealth and asset management, wholesale banking, capital markets, regulation and risk (“regtech”), and trade finance are just the most recent areas to see innovation driven by small technology-first players.

Fintechs that are taking full advantage of increased digitization, heightened customer expectations, and operational efficiencies, continue to create new business models.

Leaders can pursue a combination of seven potential options / reactions:

  1. Buy a fintech. Strategic through-cycle M&A can be a powerful driver of growth even as valuations remain high, particularly among the most successful and largest fintech companies. Whether incumbents purchase a company for its traction (customer base, loan book), technology (user experience, core system, advanced data capability), or talent (engineering, product management, executive leadership), we frequently find that success depends on their developing strength in post-acquisition integration.
  2. Partner with a fintech. A carefully designed partnership can enable faster time to market and cost-efficient implementation, with the ultimate goal of enable enabling bottom-line business impact from accessing new customers or improving back-office processes.
  3. Invest in fintechs. Investing in fintech companies is frequently a way to learn more about the space and to hedge some of your downside potential from disruptive threats. Incumbents can choose to invest in companies they partner with or to focus on areas they know well or interesting adjacencies. We frequently advise clients to find ways of keeping corporate venture-capital groups slightly at arm’s length to attract skilled managers, and we recently have seen increased interest in investing in established outside managers who focus on financial technology.
  4. Transform yourself to be more like a fintech. Digital transformation is a difficult but necessary process for most incumbent financial institutions. Redesigning core infrastructure to be more modular and dynamic, driving a new agile operating model, and upgrading technology and workforce skills are all necessary to compete with outside threats, fintech and otherwise.
  5. Build your own (internal) fintech. The road for transformations is normally measured in years, but the competitive threat from fintechs is today. Increasingly, we are seeing financial institutions try to beat fintechs at their own game or self-disrupt areas of their business before others can. The key to success in new digital business building is to combine the agility, speed, and talent of a start-up with the “unfair advantage” of an incumbent by leveraging existing assets (e.g. customers, distribution, or infrastructure).
  6. Serve the fintechs. A few financial institutions can find their competitive advantage in creating scaled, efficient technology and operations to enable others to embed financial services in their customer experiences. This “banking as a service” business model depends on finding a profitable path to white labeling but draws on the inspiration of large tech platforms. Enabling the customer experiences of others has quickly moved beyond just enabling fintechs to also working with big technology companies, retailers, telecommunications companies, and beyond.
  7. Ignore fintechs. Although ignoring the competition is rarely the right choice, some businesses are built on moats—frequently regulatory—that are difficult to disrupt or they play within narrow markets. Companies should prioritize where they need to focus and in doing so know when they need to pay attention and when they need to avoid the distraction of disrupters.

Framed Content - Publisher | Sponsor:
...
APU Insights
...Industry: Cross-Industry
SKU code : E0AB6FFA-5EC8-7731-CFC7-ECE5D7269E47
Delivery Format:
HTML ...
Immediate Delivery
...Access Rights | Content Availability:
  • The Big Picture - Intelligence Center
  • The Big Picture - Platform

...

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.

CLICK BELOW TO LEARN MORE
...

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.

Revenues

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.

CLICK BELOW TO LEARN MORE
...

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.

Elasticities
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
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.

CLICK BELOW TO LEARN MORE