IT Resources practice questions

Office facility maintenance

Why it fails: Office facility maintenance concerns physical premises, not the IT resources of infrastructure, applications, data, and personnel that IT resource management governs. It tempts because facilities often sit within a shared corporate services function alongside IT, blurring organisational boundaries without making it an IT resource component.

Customer relationship marketing

Why it fails: Customer relationship marketing is a business development activity, not a component of IT resource management, which covers infrastructure, applications, data, and personnel. It tempts because marketing depends on IT-delivered capabilities, so it appears in enterprise discussions without being an IT resource management component.

Public relations strategy

Why it fails: Public relations strategy addresses corporate reputation and stakeholder communication, sitting outside IT resource management's scope of infrastructure, applications, data, and people. It tempts because IT outages generate reputational fallout, so PR surfaces in incident discussions without being a resource management component.

Outsourcing all IT infrastructure management to a third-party service provider.

Why it fails: Outsourcing can be a valid sourcing strategy, but it does not inherently improve resource governance. Without strong contract management and oversight, outsourcing can lead to loss of control and visibility. Moreover, it does not address internal resource optimization. Governance requires active management, not simply transferring responsibility.

Deploying an automated network monitoring tool to track bandwidth usage.

Why it fails: Network monitoring is important for performance management but is too narrow to serve as a primary governance practice for all IT resources. It addresses only network resources and does not cover hardware, software, or human capital. While it can provide data for governance, it is not a comprehensive practice for optimizing and aligning all IT resources.

Establishing a service catalog that defines all IT services, owners, and service levels.

Why it fails: A service catalog is valuable for service management and communication with business stakeholders, but it is not primarily a resource governance tool. It focuses on services rather than the underlying resources. While it can support governance indirectly by clarifying service ownership, it does not directly address resource optimization or utilization.

Inability to scale infrastructure resources rapidly

Why it fails: SDI enables rapid, policy-driven scaling through software abstraction, so inability to scale rapidly is the opposite of its purpose. It is tempting because capacity planning failures do occur in virtualised environments, but the governance risk unique to SDI concerns the automation layer and its privileged access, not scaling capability.

Increased dependency on proprietary hardware vendors

Why it fails: SDI abstracts compute, storage and network from hardware, so it reduces vendor lock-in rather than increasing it; the governance risk lies in the software control plane. It is tempting because proprietary hardware dependency is a genuine risk in traditional, appliance-bound data centres, where refresh cycles and single-vendor contracts constrain the estate.

Decreased flexibility in managing application workloads

Why it fails: SDI increases workload flexibility by decoupling workloads from physical hardware, so decreased flexibility contradicts the model's purpose. It is tempting because poorly governed automation can entrench rigid templates, and that risk exists in any virtualised estate, but SDI's defining governance exposure is the software control plane, not reduced workload mobility.

Maximizing the utilization of all available hardware

Why it fails: Governance optimises value delivery and risk, not raw hardware utilisation; maximising utilisation can starve capacity and raise outage risk. It tempts because utilisation metrics genuinely matter in capacity planning and cost-optimisation scenarios, where consolidating workloads onto fewer hosts is the deliberate goal.

Minimizing the total number of IT personnel required

Why it fails: Infrastructure resource management aims to align IT infrastructure capacity and performance with business objectives and governance requirements, not to reduce headcount. Minimising personnel is tempting because cost optimisation is a legitimate governance concern, but staffing levels are a resourcing outcome, not the primary objective of infrastructure resource management.

Upgrading all infrastructure to the latest available versions annually

Why it fails: Version currency is a lifecycle tactic, not the governance objective of aligning infrastructure capacity, cost and risk with business needs. It is tempting because outdated components carry risk, and annual upgrades would be correct as an operational maintenance policy rather than infrastructure resource management.

Annual IT Operating Budget

Why it fails: An Annual IT Operating Budget records approved funding per line item; it does not define the criteria or governance process by which competing demands are ranked. It is tempting because budget figures do reflect prior allocation decisions, yet the framework itself sits in the IT strategic plan and portfolio governance.

Disaster Recovery Plan

Why it fails: A Disaster Recovery Plan defines recovery time and recovery point objectives and failover procedures for outages, not ongoing prioritisation of IT spend. It is tempting because it does allocate resources during disruption, but that allocation is event-driven and reactive, whereas the stem asks for the standing governance framework.

Service Level Agreement (SLA)

Why it fails: An SLA specifies agreed service levels and remedies between provider and consumer for defined services. It is tempting because service commitments influence where effort goes, but it governs performance against existing services rather than the enterprise framework for prioritising and allocating IT resources across competing demands.

Surveying staff on their preferred technologies for professional development

Why it fails: Preference surveys capture individual interest in technologies, not the organisation's required competencies against the transformation roadmap. A structured assessment mapping current skills to future role requirements would be correct, because preferences reveal no gap between capability supply and demand.

Reviewing employee performance appraisals from the previous two years

Why it fails: Performance appraisals assess past individual delivery against existing role objectives; they do not map current competencies against the future skills the transformation demands. A structured competency assessment against target-state capability requirements would be correct, since it exposes gaps rather than rating historical performance.

Increasing the budget for external recruitment to bring in new talent

Why it fails: Recruitment fills vacancies with external capability; it does not first establish which competencies the existing workforce lacks against the transformation's target operating model. A skills-gap analysis comparing current competencies with future role requirements would be correct before deciding whether to buy, build or borrow talent.

Greater reliance on long-term, detailed resource planning cycles

Why it fails: Agile shifts governance toward rolling, capacity-based forecasting tied to iteration cadence, so fixed long-term detailed planning cycles contradict the shorter replanning horizon Agile introduces. It tempts because annual resource plans suit stable waterfall portfolios, where demand is predictable and headcount is committed upfront.

Increased need for centralized resource pool management

Why it fails: Agile delegates resource decisions to self-organising teams, so governance shifts toward federated, team-level allocation rather than a central pool. It is tempting because portfolio-level visibility and cross-team dependency management do require coordination, and central pools suit plan-driven staffing — but that contradicts Agile's decentralised model.

Reduced requirement for developer cross-training

Why it fails: Agile's self-organising teams and shared ownership of backlog items increase, not reduce, the need for cross-training so members can cover varied work. It is tempting because Agile removes specialist hand-offs and role silos, which superficially suggests less training; in practice generalising specialists is a core enabler of team-level resource governance.

Audit all business units and penalize those using shadow IT

Why it fails: Auditing and penalising business units addresses symptoms after the fact, producing concealment instead of visibility, and does nothing to reallocate the duplicated spend. It is tempting because audits do establish accountability, and they fit scenarios where policy already exists and deliberate, known violations require enforcement action.

Restrict all unauthorized cloud service access via the firewall

Why it fails: Firewall blocking of unauthorised cloud services drives shadow IT further underground rather than governing it, since discovery and policy alignment are absent. It is tempting because firewalls do enforce egress control, and outright blocking suits environments with a strict allow-list mandate and no need for business-led SaaS adoption.

Mandate that all IT needs be submitted via the central IT ticketing system

Why it fails: A ticketing mandate only captures demand routed through IT; it neither discovers existing shadow usage nor assigns ownership, so resources stay unoptimised. It is tempting because central intake is genuinely correct when the problem is uncoordinated procurement, not unidentified consumption already running outside IT's visibility.

Total IT spend as a percentage of revenue

Why it fails: Total IT spend as a percentage of revenue measures overall cost intensity, not whether those funds were allocated to the highest-value initiatives, so it cannot evidence allocation effectiveness. It is tempting because it genuinely benchmarks IT investment against organisational scale, and would suit a question about cost ratios or spend benchmarking.

Average server uptime percentage

Why it fails: Uptime measures operational reliability of delivered services, not whether resources were allocated to the right priorities, so it cannot evidence allocation effectiveness. It is tempting because availability genuinely reflects service performance, and would be the correct indicator for a question about infrastructure stability or service continuity.

Number of IT staff certifications earned per year

Why it fails: Certification counts evidence staff capability, not whether resources are allocated to the highest-value initiatives, so they cannot indicate allocation effectiveness. They are tempting because they genuinely measure workforce development and skills coverage, and would fit a question asking how to gauge team competence or training investment.

Transition all workloads to on-demand instances to ensure maximum agility

Why it fails: On-demand instances carry the highest unit price, so running everything this way maximises spend whenever demand is predictable. It is tempting because on-demand guarantees elasticity for spiky or unknown workloads. Optimising expenditure instead reserves or commits capacity for steady-state workloads while keeping on-demand only for genuine peaks.

Standardize on a single cloud service provider to simplify vendor management

Why it fails: Single-provider standardisation optimises vendor management, not expenditure; it removes competitive pricing pressure and locks workloads to one rate card. It is tempting because consolidating contracts reduces administrative overhead. CGEIT-aligned optimisation instead matches each workload to the most cost-effective platform, using committed-use discounts and right-sizing across the hybrid estate.

Automate infrastructure provisioning through Infrastructure as Code (IaC) without budget gates

Why it fails: Automating provisioning without budget gates lets engineers deploy resources unchecked, so spend can grow faster than governance can detect it. It is tempting because IaC delivers consistency and speed. Cost optimisation requires guardrails such as budgets, quotas and approval workflows embedded in the pipeline, not unconstrained automation.

Writing code for new applications

Why it fails: Writing application code is a delivery task executed by development teams, not a governance activity that directs and oversees IT resources. It is tempting because software delivery consumes resources, but governance concerns decision rights, accountability and strategic alignment rather than hands-on implementation work.

Updating user passwords

Why it fails: This is a tactical security operation.

Purchasing new server hardware

Why it fails: Buying hardware is a procurement task, not governance; it addresses capacity, not the direction, risk and value oversight of IT resources. It tempts because infrastructure refresh genuinely supports service delivery, and would be the right answer to a question about scaling compute or replacing end-of-life servers.

The initial cost of implementing the system

Why it fails: Sunk implementation cost is irrelevant to forward-looking optimisation; retirement decisions hinge on ongoing support, licensing and integration burden. It is tempting because original spend feels significant, but that cost is unrecoverable, so this factor would matter only for historical cost accounting, not for planning resource reallocation.

The amount of documentation available for the system

Why it fails: Documentation volume does not determine resource optimisation; the critical factor is identifying which system capabilities are still consumed, so effort maps to actual business dependency. Documentation supports knowledge transfer and audit evidence during decommissioning, making it valuable once retirement scope is fixed — but it cannot reveal redundant capacity or duplicated function across the portfolio.

The age of the hardware

Why it fails: Hardware age says nothing about business value, dependency or migration effort, so it cannot drive optimisation decisions. It is tempting because older assets intuitively appear ready for retirement, but age is the right criterion only when the question concerns physical refresh cycles rather than resource optimisation across a portfolio.

Increasing the frequency of vendor contract renegotiations

Why it fails: Renegotiating vendor contracts more often addresses pricing terms, not the underlying governance of IT demand, portfolios and resource allocation that drives operational cost. It is tempting because contracts are a visible cost lever, and would be correct for a specific overpriced agreement, but frequent renegotiation is not a governance practice.

Outsourcing all IT infrastructure management

Why it fails: Outsourcing transfers cost to a vendor but does not by itself reduce total operational spend, and it removes direct governance control over service levels. It is tempting because outsourcing is often framed as a cost-cutting lever, and would be correct where the organisation lacks internal capability, but the question asks for a governance practice.

Eliminating the IT governance committee

Why it fails: Removing the IT governance committee strips the oversight that prioritises spend, so costs typically rise through uncoordinated investment rather than fall. It is tempting because the committee appears to add overhead, and would be correct only if it duplicated another active board, but eliminating governance removes the very control that curbs cost.

The current market salary for IT professionals

Why it fails: Market salary is a cost input, not a determinant of sourcing strategy; it says nothing about whether the capability is strategically differentiating or controllable internally. It would inform budgeting once the sourcing model is chosen. The deciding factor is whether the activity confers competitive advantage or is commodity work.

The historical preference of the IT department

Why it fails: Historical departmental preference is organisational inertia, not a strategic or economic criterion, and can entrench outdated arrangements. It might be weighed as a change-management consideration during transition planning. The decision is dictated by whether the activity is core to competitive advantage or a commoditised support function.

The availability of local outsourcing vendors

Why it fails: Vendor availability is a tactical supply consideration, not the strategic driver of sourcing decisions; business alignment, cost structure and risk appetite dictate the internal/external balance. It tempts because local vendors can ease delivery and support, making them decisive in narrow tactical procurements rather than enterprise-wide sourcing strategy.

Selecting the cloud vendor with the lowest price

Why it fails: Lowest price ignores alignment with business strategy, risk, compliance and total cost of ownership, which governance must weigh. A cloud-first policy still requires evaluating value delivery and risk appetite. Lowest-price selection would be correct only where cost is the sole, formally approved decision criterion.

Training all IT staff on a single cloud platform

Why it fails: Training all staff on one platform presumes a vendor decision before governance has evaluated business alignment, risk and value; it is an operational consequence, not an allocation focus. Training would be correct once the cloud strategy and platform choices are approved and skills gaps identified.

Mandating the migration of all legacy systems regardless of suitability

Why it fails: Cloud-first does not mean cloud-always; governance must assess each workload's suitability, cost and risk before migration. Mandating blanket migration ignores systems where latency, licensing or regulatory constraints make on-premises hosting the viable option, so resources get committed without a business case.

Review of individual employee performance metrics

Why it fails: Individual performance metrics measure employee output, not portfolio-level funding decisions, so they cannot realign investment with business priorities. It is tempting because metrics imply objective oversight, and it would be correct for appraising staff or managing talent, not for governing IT resource allocation.

Annual budgeting process

Why it fails: Annual budgeting fixes funding once a year, so it cannot respond to priorities that shift mid-cycle. It is tempting because budgeting is the formal mechanism that authorises IT spend, and it would be correct for establishing the yearly funding envelope, not for continuous realignment.

Monthly meeting with the IT help desk

Why it fails: Help-desk meetings address incidents and user tickets, carrying no authority over investment decisions or portfolio priorities. It is tempting because frequent operational contact feels like governance visibility, and it would be correct for resolving service-delivery issues, not for reallocating IT resources.

Policies and procedures

Why it fails: Policies and procedures are governance instruments that guide conduct; they do not consume capacity, so rapid demand does not exhaust them. It is tempting because rigid procedures frequently delay approvals and are blamed for slow delivery, which would make them the right answer if the question asked about process friction, not resource bottlenecks.

Organizational culture

Why it fails: Organizational culture shapes behaviour and adoption but does not physically constrain capacity, so it cannot bottleneck throughput during demand spikes. It is tempting because culture is often named the biggest obstacle to digital initiatives, making it the correct choice when the question concerns resistance to change rather than resource saturation.

Strategic documentation

Why it fails: Strategic documentation is static and does not constrain throughput; demand growth exposes outdated content rather than creating a capacity bottleneck. It is tempting because governance artefacts are frequently cited as blockers to change, so documentation would be the right answer if the question asked what slows transformation, not what saturates under rapid demand.

Force strategic projects to operate with lower performance requirements

Why it fails: Lowering performance requirements degrades the strategic outcomes the projects exist to deliver, leaving the resource starvation unresolved. Governance instead reallocates capacity by prioritising demand and reducing operational load. Reduced targets would only be defensible where a project's scope is formally descoped and re-approved by the investment committee.

Require all IT staff to work overtime to complete projects

Why it fails: Mandated overtime treats the symptom while entrenching the operational drain, and sustained overtime raises error rates and attrition. Governance addresses the demand-capacity imbalance through portfolio prioritisation and service improvement. Overtime would only be justified as a short, time-boxed response to a declared major incident, not as standing policy.

Increase the overall IT budget to hire more staff

Why it fails: Additional budget does not resolve starvation if operational demand keeps consuming the new capacity, and funding may be unavailable. Governance first rebalances demand against capacity via portfolio prioritisation and service optimisation. Hiring would be the right response only where analysis shows a genuine, sustained capacity shortfall rather than misallocated effort.

Reducing the need for IT staff

Why it fails: Asset management does not reduce IT staffing; accurate inventories typically increase accountability and workload visibility rather than removing personnel. It tempts because automation and consolidated records can trim manual effort, but the primary governance benefit is informed investment, risk and lifecycle decisions, not headcount reduction.

Ensuring all hardware is painted the same color

Why it fails: Hardware colour has no bearing on governance, inventory accuracy, lifecycle tracking or risk visibility, so it delivers none of asset management's control benefits. It tempts as a flippant nod to standardisation, but asset management is correct when the goal is knowing what exists, where, and its ownership.

Automating the password reset process

Why it fails: Password reset automation is an identity lifecycle operation, not asset management; it neither inventories IT assets nor tracks their ownership, location or lifecycle state. It tempts because automation reduces helpdesk effort, and it would be the right answer if the question asked how to streamline credential administration within identity governance.

The slower speed of provisioning resources

Why it fails: Provisioning speed is an operational performance metric, not a governance challenge for resource optimisation; multi-cloud governance must reconcile inconsistent tagging, quotas and utilisation visibility across providers. It is tempting because slow provisioning frustrates teams, but automation, not governance, addresses it.

The difficulty of finding cloud architects

Why it fails: Architect scarcity is a staffing and skills concern, not a resource-optimisation governance issue; multi-cloud resource optimisation centres on allocating, tracking and right-sizing workloads across providers. It is tempting because multi-cloud environments do demand scarce expertise, but that affects delivery capability rather than governance of resource usage.

The increased cost of data egress fees between clouds

Why it fails: Egress fees are a cost-management concern, not the governance challenge of optimising resource allocation across providers. It is tempting because multi-cloud billing is genuinely complex, but the question asks about resource optimisation — matching workloads to the right provider capacity — not transfer pricing.