4 strategies to rethink customer and employee experience in the post-COVID-19 landscape

4 strategies to rethink customer and employee experience in the post-COVID-19 landscape

Posted | Updated by Insights team:
Dr. Evangelo Damigos; PhD | Head of Digital Futures Research Desk
  • Competitive Differentiation

Publication | Update: Oct 2020

COVID-19 has dramatically impacted how we interact in society and in the enterprise. From emerging technologies that deliver new experiences to new working arrangements, evolving relationship dynamics between employers and employees, and new consumer behaviors and demands.

According to Donna Tuths, Chief transformation and innovation officer at Sutherland, to prepare for and compete in this post-COVID-19 landscape, CIOs and other C-suite leaders must transform how they think about “experience” as a whole and redefine their strategies accordingly.

COVID-19 has forced us to reimagine and create a new business environment that is still being shaped. Amidst all the unknowns, one fact is clear: It completely alters our experiences and accelerates us into a digitized world, where the future is now. Innovate and embrace this experience-centered paradigm or risk being left behind.

In response to the COVID-19 pandemic, CIOs and other C-suite leaders must transform how they think about “experience” – for both customers and employees – or risk losing them.

Resilient leaders need to fundamentally re-think their customer and employee touchpoints, redesign current practices, modernize their technology backbone, and ensure digital literacy across their organization. They must gain a deep understanding of customer behaviors and preferences to design new experiences and interactions — or risk losing customers and employees and earning a negative brand perception.

Here are four strategies to help your organization shift to an experience-based approach.

1. Ensure your digital workplace is set up for the long haul

As companies shift their business operations from in-person to virtual, more employees are discovering that they prefer the flexibility of remote work. According to SHRM research, more than 93 percent of part-time workers said they would work longer hours if they had flexible work arrangements and 85 percent of millennials prefer to work from home all the time.

These workstyle preferences demonstrate the importance of designing new experiences around a virtual future. To do so successfully and ensure longevity, companies must deploy intelligent technologies that enable employees to work and interact outside the bounds of geography.

To build engaging new experiences, focus on deploying end-to-end solutions that touch on all aspects of people, process, and technology.

To build engaging new experiences, focus on deploying end-to-end solutions that touch on all aspects of people, process, and technology. These digital solutions must include cloud-based productivity tools that bolster employee engagement, along with project management tools that manage workflows and allow managers to provide instant feedback on specific tasks. Network security tools are also critical as they align employers with the altered business reality, increased threat landscape, client needs, and the sensitivity of data they handle.

Additionally, monitoring tools can provide analysis on employee productivity, which is paramount to ensure operations and projects remain on track. Although monitoring tools are widely beneficial to ensuring business continuity, Gartner finds that only 16 percent of businesses are using such tools, reflecting a major gap in many businesses’ remote work strategy.

2. Reskill and engage employees

Use this time as an opportunity to train and upskill employees, as an entirely new set of skills is necessary to make long-term remote work sustainable. While training an entire workforce to become digitally literate may seem like a daunting task, start with basics such as teaching employees how to master the virtual meeting.

When the pandemic struck, many businesses overlooked this critical step, and as a result, many employees struggled to engage in virtual meetings. According to BBC News, this may be because video requires individuals to work harder to process non-verbal cues. Educate employees on how to recognize signs of fatigue early on and how to address them by turning off video or taking longer breaks between meetings. If employees can’t stay productive online, learning new digital skills virtually will be almost impossible.

A great way to foster enthusiasm is to offer open forums where employees can ask questions and learn from each other.

Consider incorporating short digital training sessions into the everyday schedule. Remote working comes with many distractions that can decrease employees’ attention spans, so incorporating brief training opportunities can make lessons easier to learn and apply. Also, try to create personalized training sessions based on each employee’s individual learning style and needs to ensure the best results.

A great way to foster enthusiasm is to offer open forums where employees can ask questions and learn from each other. Topics can include anything from how to ensure digital security to how to navigate work across different devices and platforms to how to improve digital literacy.

3. Strike the right balance of AI and human interaction to transform the customer experience

The pandemic has heightened expectations on brand communication and customer service. Leaders must respond by re-thinking their customer engagement strategies and adopting forward-thinking approaches to ensure long-term sustainability.

A recent survey from CGS revealed that the pandemic has caused consumers to crave more human connections in their service interactions. They also expect instantaneous and personalized interactions, and failing to deliver these could damage your relationship with your customers. That means it’s never been more important to deploy AI-powered solutions like chatbots, virtual agents, and intelligent tools that enable excellent customer service and new experiences.

These intelligent technologies remove high-friction moments in the customer journey and create new touchpoints through advanced personalization. Empowered by real-time feedback and guidance, they increase productivity, accuracy, and customer satisfaction. Machine learning (ML) also can also boost customer engagement through personalization and prediction services.

In retail, for example, organizations can use ML-powered engines to suggest products based on a customer’s purchase history. On a more sophisticated level, prices and promotions can be customized based on consumer demographic data, increasing conversion and retention rates.

4. Prioritize the emotional connection

Perhaps the most essential strategy is to lead with empathy and prioritize the human element. Remember that many employees are struggling to balance their day jobs with looking after loved ones and managing kids who aren’t in school. Findings from McKinsey state that a CIO’s first order of business is to lead with kindness and compassion and recognize the new challenges employees face on a daily basis.

Before the pandemic struck, it was far too easy to get swept up in the realm of digitization and optimization and disregard the human connection. However, as delivering engaging new experiences becomes a mandate, leaders must incorporate a human touch into organizational culture as well as relationships and interactions with stakeholders, customers, and employees.

For employees, a successful remote work model requires the right mix of technology and human-centric strategies. As a manager, be sure to provide your team members tools, resources, and support to address the pitfalls they may face — whether that means offering flexible work hours, promoting habits that enhance well-being, or even mandating a daily lunch hour or other means for employees to break up their day.

Source: The Enterprisers Project

...Digital Themes: Competitive Differentiation
Framed Content Aggregator - Publisher | Sponsor
...Industry: Post-COVID-19-Jumpstart
SKU code : 412183FF-B726-0E3E-D521-29147554F46B
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.