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Top 5 challenges when migrating to the cloud

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Top 5 challenges when migrating to the cloud

Posted | Updated by Insights team:

Publication | Update:

Mar 2024
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Firstserv’s Sebastian Tyc outlines the risks of migrating to the cloud and how to best approach them

Cloud computing is seeing an inexorable rise as organisations worldwide continue to transition more services online.

The trend towards hybrid working, accelerated by the COVID-19 pandemic, has resulted in a huge increase in migrating to the cloud. Gartner research and consulting services firm recently forecast worldwide public cloud end-user spending to grow 21.7% to $ 597.3 billion in 2023.

While cloud adoption has its challenges, it is vital to protect against cybercrime. Experts like Firstserv can guide organisations through the process, ensuring a smooth transition.

“At Firstserv, we have enabled many organisations to realise their cloud ambitions using our Cloud Adoption Framework. We springboard workloads safely from legacy on-premises data centres to cutting-edge public, private and hybrid cloud environments.”

Using the Cloud Adoption Framework, Firstserv seamlessly navigates the challenges faced by organisations taking the plunge.

Data security and compliance risk

Data security and regulatory compliance are major concerns as organisations move to the cloud. Data and applications hosted on the cloud must be secured at the same level as on-premises data centres. Some cloud deployment models are better suited to this than others.

For example, a company shares servers and other infrastructure with other cloud customers in public cloud deployments. Vulnerabilities in the underlying servers or the isolation of the virtual machines (VMs) hosted on these servers could result in data leakage or other security incidents.

Additionally, an organisation may not have visibility into where its data and applications are hosted, which can be problematic for some data privacy laws, such as the General Data Protection Regulation (GDPR).

In addition to managing these risks, Firstserv will carry out a Cloud Assessment to evaluate redundant workloads that can be merged, ensuring more optimised costs in the future. Migrating to the cloud is more cost-effective than maintaining and managing a legacy on-premises infrastructure.

Unnecessary project spend

The most common mistake preventing organisations from fully reaping the benefits of the cloud is the lack of clear business objectives behind the move and/or a good migration plan.

Clients approach us after attempting cloud migration in-house, having already undertaken a great deal of work. In these cases, we often must go back to square one, helping formulate business goals and rebuild migration strategies from scratch.

A solid strategic plan ensures that you can easily navigate the transition and avoid analysis paralysis during later stages. This is especially important given the variety of choices along the way, starting from whether you opt for private, public, or hybrid cloud infrastructure to choosing between Infrastructure as a Service (IaaS), Platform as a Service (PaaS), or Software as a Service (SaaS) models.

Carefully planning each phase of the migration ensures that companies make the right choices, arrive at their target, and avoid unnecessary spending.

Skills gap

One of the primary challenges of migrating to the cloud is finding people with the skills to manage an effective migration. Despite the many benefits of cloud computing, the project’s complexity stops many organisations in their tracks.

Competition for migration experts has intensified. Unfortunately, the demand for cloud experts exceeds the supply, at least for now.

Firstserv’s team fills an organisation’s skills gap, enabling a seamless transition to the cloud without having to upskill, increase, and potentially decrease the current headcount.

Cloud migration complexity

Cloud migration involves moving data storage and applications from on-premises environments to cloud infrastructure. Often, this is accomplished in stages to ensure that one step is completed entirely successfully before moving on.

If an organisation has a complex IT architecture, developing and executing a cloud migration strategy may be difficult.

Certain systems may need to be collocated, and a complex architecture may make it challenging to identify and document interdependencies and develop a phased strategy for moving specific components or systems to the cloud.

Firstserv’s experience in providing managed solutions and secure cloud hosting, including disaster recovery, managed backups, and server monitoring, ensures the security of an organisation’s system during the migration project and beyond.

Resistance to cloud adoption

Regarding cloud adoption, the biggest challenge is not technology but people. We all tend to resist change, and migrating to the cloud brings a lot of change and disruption. Teams need to adapt and change their working processes.

Good people management is extremely important to ensure a successful migration. A properly thought-out change management plan can assist in this transitional journey.

Buy-in from the top level is crucial, heavily influencing employee engagement and adoption. By demonstrating support, excitement, and value for the new project, the leadership team will help disseminate these values to the rest of the team.

Constant communication encourages the workforce to adapt and progress. Investing in a strong onboarding programme and employing experts like Firstserv to train and support employees will ensure employee acceptance faster.

Embrace innovation, move to the cloud

Moving to the cloud is not a challenge but rather an opportunity to make existing business processes more agile and innovative.

Firstly, they can take stock of all the infrastructure components, business processes and in-house expertise at their disposal. Then, build a strategy that encompasses their organisation’s needs on their cloud migration journey. Firstserv can help develop and execute a cloud migration strategy that makes the most sense from the standpoint of businesses’ own objectives.

Based on an organisation’s actual and target digital maturity levels, our experts customise the migration programme for the organisation’s processes, people, and technologies.

Book a free one-hour consultation to see how Firstserv can help you migrate to the cloud faster and achieve scale optimisation.

Book a free consultation

 

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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.

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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.

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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

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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.

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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.

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