Governance, Ethics, Implementation and Future Workforce Planning

Introduction

Human resource planning is not complete when an organisation has estimated future labour demand, identified skill gaps, and prepared staffing scenarios. A plan must also be governed, implemented, reviewed, and adjusted. Workforce decisions affect livelihoods, privacy, equality of opportunity, organisational performance, and compliance with employment law. Consequently, workforce planning is both a strategic management activity and a system of institutional accountability.

Contemporary workforce planning is increasingly influenced by artificial intelligence, people analytics, remote work, demographic change, automation, climate-related disruption, and changing employment relationships. These developments create opportunities for more accurate planning, but they also create risks. Poorly governed data can expose sensitive employee information. Predictive models can reproduce historical discrimination. Workforce reductions can damage trust if employees are not consulted. A technically sophisticated plan can therefore fail if stakeholders regard it as unfair, opaque, or illegitimate.

This chapter examines the governance structures, ethical principles, legal considerations, implementation practices, monitoring systems, and future-oriented capabilities required for responsible workforce planning.

Learning Objectives

By the end of this chapter, students should be able to:

1. Explain why governance is essential to workforce planning.
2. Apply principles of privacy, fairness, transparency, accountability, and employee consultation.
3. Identify major legal and regulatory considerations affecting workforce plans.
4. Design an implementation and monitoring framework.
5. Evaluate workforce-planning outcomes using appropriate indicators.
6. Analyse resilience, skills disruption, and emerging workforce trends.
7. Recommend responsible uses of analytics and artificial intelligence in workforce decisions.

1. Workforce-Planning Governance

1.1 Meaning and purpose

Workforce-planning governance is the system of roles, decision rights, policies, controls, evidence standards, and review processes through which workforce decisions are made and held accountable. Governance answers questions such as:

• Who owns the workforce plan?
• Who may approve hiring, restructuring, redeployment, or automation decisions?
• What evidence is required before a decision is taken?
• How are employee data collected, protected, and retained?
• How can employees challenge or appeal a decision?
• How are outcomes monitored after implementation?

Governance differs from administration. Administration concerns the execution of procedures, whereas governance establishes the authority, principles, and controls under which those procedures operate. It also differs from compliance. Compliance is adherence to applicable rules; governance includes compliance but additionally addresses ethical conduct, organisational values, stakeholder legitimacy, and long-term consequences.

1.2 A governance architecture

An effective governance architecture normally includes several layers.

A written terms-of-reference document should specify membership, authority, meeting frequency, records, escalation routes, conflicts-of-interest rules, and reporting obligations. For high-impact decisions, a cross-functional workforce committee is preferable to unilateral decision-making by a single manager or analyst.

1.3 Decision rights and accountability

Accountability requires more than naming a responsible department. A useful governance design distinguishes between:

• Accountable: the person or body answerable for the final decision.
• Responsible: the person or team performing the work.
• Consulted: those whose expertise or interests must inform the decision.
• Informed: those who must receive an explanation or result.

For example, the HR director may be accountable for a strategic workforce plan, workforce analysts responsible for modelling, legal advisers consulted on employment law, and employees informed and consulted about changes affecting them. These categories should be documented before implementation, not reconstructed after a dispute.

2. Ethical Foundations of Workforce Planning

Ethics concerns what an organisation ought to do, not merely what it is legally permitted to do. A lawful action may still be unfair, deceptive, or harmful. Five principles are particularly important.

2.1 Privacy and proportionality

Employee information should be collected and used only for legitimate, clearly communicated purposes. The principle of proportionality asks whether the information is necessary for the decision and whether the same objective could be achieved with less intrusive data.

Good practice includes:

• collecting the minimum necessary information;
• defining the purpose before collecting data;
• separating identifiable information from analytical datasets where feasible;
• restricting access according to role;
• encrypting data in storage and transmission;
• setting retention and deletion periods;
• maintaining records of data access and changes;
• explaining automated processing in understandable language; and
• providing channels for correction of inaccurate data.

Sensitive information, such as health, biometric, genetic, trade-union, or protected-characteristic data, requires heightened safeguards. Aggregated information can still create privacy risks when small groups can be re-identified. Therefore, anonymisation claims should be tested rather than assumed.

2.2 Fairness and non-discrimination

Fairness has multiple meanings. Procedural fairness concerns whether the decision process is consistent, impartial, and open to challenge. Distributive fairness concerns whether benefits and burdens are allocated equitably. Interactional fairness concerns whether people are treated respectfully and given an adequate explanation.

Workforce plans may create direct discrimination, indirect discrimination, or systemic disadvantage. Direct discrimination occurs when a person is treated less favourably because of a protected characteristic. Indirect discrimination may arise when a neutral criterion disproportionately disadvantages a group and cannot be justified as necessary and proportionate. Systemic disadvantage can arise from repeated practices that appear neutral but reproduce historical inequalities.

Fairness should be examined throughout the planning cycle:

1. Problem definition: Is the organisational problem correctly framed, or is a group unfairly blamed?
2. Data selection: Do historical data reflect unequal access to opportunity?
3. Model design: Are variables acting as proxies for protected characteristics?
4. Decision threshold: Are different groups exposed to unequal error rates?
5. Implementation: Are managers applying recommendations consistently?
6. Outcome review: Did the plan produce unequal effects?

No single statistical test proves that a decision is fair. Fairness measures may conflict, especially where groups have different base rates. Quantitative analysis must therefore be combined with legal interpretation, contextual inquiry, employee voice, and human judgement.

2.3 Transparency and explainability

Transparency means that affected stakeholders can understand the purpose, inputs, decision process, and consequences of a workforce plan. It does not necessarily require disclosure of confidential commercial information or proprietary code. At minimum, employees should be able to learn:

• what decision is being made;
• what categories of data influence it;
• whether automated tools are used;
• who reviews the result;
• what limitations apply; and
• how to request correction, reconsideration, or appeal.

Explainability should be meaningful rather than merely technical. Telling an employee that a complex model produced a score is not an explanation. An adequate explanation identifies the relevant factors in accessible language and indicates what evidence could change the decision.

2.4 Accountability and human oversight

An organisation must not transfer responsibility to software. A manager cannot justify an unfair outcome by saying that “the algorithm decided.” Human oversight requires competent reviewers, documented approval, authority to override an output, and a record of the reasons for doing so. Oversight is ineffective if the reviewer lacks time, expertise, or independence.

2.5 Employee voice and participation

Employees possess knowledge that may not appear in administrative data. They understand workload, informal skills, safety conditions, customer pressures, and the practical effects of proposed changes. Consultation can improve information quality and implementation, as well as satisfy legal or collective-bargaining duties.

Consultation is not the same as announcing a decision. Meaningful consultation occurs early enough to influence alternatives, provides relevant information, allows reasonable time for response, and gives a considered reply to material concerns. Employee representatives, trade unions, works councils, equality bodies, and occupational health specialists may all be relevant participants.

3. Legal and Regulatory Considerations

Employment law differs across jurisdictions, so workforce planners must obtain current local advice. Nevertheless, several recurring areas of legal responsibility are widely relevant.

3.1 Employment protection and restructuring

Hiring freezes, redundancies, transfers, changes in working time, and outsourcing may trigger requirements concerning notice, consultation, selection criteria, severance, redeployment, collective bargaining, or protection against unfair dismissal. A workforce plan should identify legal requirements before public commitments are made.

Selection criteria should be job-related, documented, consistently applied, and reviewed for discriminatory effects. Performance records should not be used uncritically if employees had unequal access to resources, training, or opportunities.

3.2 Data protection and employment privacy

Data-protection regimes commonly require a lawful basis for processing, purpose limitation, data minimisation, accuracy, security, retention control, and rights of access or correction. Some jurisdictions impose additional restrictions on automated decision-making and cross-border transfers. Workforce planners should complete a privacy or data-protection impact assessment where processing is extensive, sensitive, or likely to affect individuals significantly.

3.3 Equality, accessibility, and accommodation

Workforce plans should account for disability accommodation, equal pay, pregnancy and family responsibilities, age, race or ethnicity, religion, sex, gender identity, and other protected characteristics defined by applicable law. Accessibility must be considered in recruitment technology, training, communication, workplace design, and redeployment.

3.4 Health, safety, and psychosocial risk

A plan that increases workloads, night work, monitoring, travel, or job insecurity may create physical or psychosocial risks. Legal duties often extend beyond preventing physical accidents to managing stress, fatigue, harassment, violence, and unsafe work organisation.

3.5 Employment classification and external labour

The use of contractors, agency workers, platform workers, and contingent labour may create classification, tax, social-protection, and joint-employer risks. Workforce planning should examine the substance of the relationship rather than relying solely on contractual labels.

4. Implementing the Workforce Plan

A workforce plan becomes operational through a controlled implementation process. Implementation should connect strategic intentions with budgets, roles, timelines, communication, and measurable results.

4.1 From plan to portfolio of initiatives

The plan should be translated into initiatives such as recruitment, internal mobility, reskilling, succession development, job redesign, technology adoption, retention measures, or managed reductions. Each initiative needs a business rationale, owner, milestones, resources, dependencies, risks, and success measures.

A practical implementation register may include:

4.2 Change management and communication

Employees are more likely to support a workforce plan when they understand why it is needed, how it affects them, and what support is available. Communication should be timely, consistent, two-way, and adapted to different audiences. It should distinguish confirmed decisions from scenarios and assumptions.

Managers require briefing materials and escalation guidance. Employees may need skills assessments, career counselling, training time, redeployment support, or fair selection information. Communication that exaggerates certainty can damage trust when assumptions change.

4.3 Piloting and staged implementation

Where uncertainty is high, organisations should pilot new processes or technologies in a limited context. A pilot should have a defined population, comparison or baseline where feasible, stop criteria, privacy safeguards, and an evaluation plan. Piloting is not a way to avoid consultation; affected employees should know that a pilot is occurring and how evidence will be used.

4.4 Capability and resource alignment

Implementation fails when the organisation approves objectives without supplying capacity. Workforce planners should check whether managers have time to coach employees, whether training providers can meet demand, whether systems can exchange accurate data, and whether the budget covers transition costs. The cost of implementation may occur before benefits are realised.

5. Monitoring, Evaluation, and Corrective Action

Monitoring determines whether implementation is producing intended results and unintended harm. It should not be limited to counting activities, such as the number of training sessions delivered. It must examine outcomes and distributional effects.

5.1 A hierarchy of indicators

Indicators should be defined precisely. For example, retention can be expressed as:

The period must be specified, and the numerator and denominator must be defined consistently. A short-term retention rate can conceal later departures, while an organisation-wide rate can conceal severe losses in a critical occupational group.

A training completion rate may be calculated as:

This measures completion, not learning or job performance. Assessment results, observed application, and business outcomes are needed for a fuller evaluation.

5.2 Baselines, targets, and disaggregation

A target is meaningful only when the baseline, time frame, population, and measurement method are clear. Indicators should be disaggregated where lawful and statistically meaningful by relevant dimensions such as location, job family, grade, employment status, gender, disability, or other protected characteristics. Small groups require confidentiality safeguards and cautious interpretation.

A simple gap measure is:

The sign and interpretation depend on the indicator. For a desirable outcome such as retention, a positive gap may indicate underperformance. For an undesirable outcome such as involuntary turnover, the interpretation reverses. Analysts must therefore label indicators as higher-is-better, lower-is-better, or target-range measures.

5.3 Review cycles and adaptive control

A workforce plan should be reviewed at predetermined intervals and when trigger events occur. Triggers may include a major change in demand, unexpected turnover, a safety incident, a legal development, a cyberattack, a supplier failure, or a significant model error. Review meetings should examine assumptions, leading indicators, risks, employee feedback, and corrective options.

Corrective action may involve revising targets, reallocating resources, changing selection criteria, pausing a technology, adding safeguards, or abandoning an initiative. A plan is not a failure because it changes; failure occurs when evidence is ignored.

6. Resilience and Future Workforce Planning

6.1 Workforce resilience

Resilience is the capacity of an organisation and its workforce to anticipate disruption, absorb shocks, continue essential operations, and adapt without unacceptable harm. Resilience is broader than maintaining headcount. It includes critical skills, leadership capacity, health and safety, alternative work arrangements, supplier dependencies, knowledge continuity, and recovery capability.

Useful resilience practices include:

• identifying critical roles and single points of failure;
• maintaining succession and cross-training arrangements;
• documenting essential processes and tacit knowledge;
• developing internal talent marketplaces;
• using multiple recruitment and supply channels;
• testing remote-work and emergency communication capabilities;
• protecting employee wellbeing during disruption; and
• conducting scenario exercises.

6.2 Scenario planning

Scenario planning does not predict one certain future. It tests how alternative conditions could affect workforce demand and supply. Scenarios may include rapid automation, prolonged labour scarcity, recession, climate disruption, geopolitical instability, or a sudden change in customer demand.

Each scenario should state assumptions, time horizon, affected roles, leading indicators, strategic options, and no-regret actions. No-regret actions are beneficial across several plausible futures, such as strengthening foundational digital literacy, improving data quality, and building internal mobility.

6.3 Skills disruption and reskilling

Technology may eliminate tasks, transform jobs, or create new occupations. Workforce planners should analyse work at the task and capability level rather than assuming that an occupation disappears as a whole. A role may contain routine tasks suitable for automation and interpersonal, judgement-based, or creative tasks requiring human contribution.

A responsible skills strategy includes:

1. mapping current capabilities;
2. identifying future capability requirements;
3. estimating gaps by role and employee group;
4. prioritising skills that are strategically important and realistically developable;
5. providing learning, practice, mentoring, and job opportunities; and
6. evaluating whether learning leads to productive and equitable mobility.

Reskilling should not be used as a symbolic response when employees are given no time, support, or vacancies in which to apply new skills.

6.4 Emerging workforce trends

Important trends include hybrid and remote work, ageing populations, multigenerational teams, portfolio careers, contingent labour, global talent sourcing, employee expectations of flexibility, and the growth of people analytics. These trends are not universally beneficial or harmful. Their effects depend on job design, managerial capability, infrastructure, regulation, and employee circumstances.

Artificial intelligence can support demand forecasting, skills inference, scheduling, and recruitment administration. However, it may also amplify biased historical patterns, infer sensitive attributes, produce confident errors, and reduce meaningful human contact. Before deployment, organisations should define a legitimate purpose, test data quality, conduct impact assessment, validate performance across groups, establish human review, document model changes, and provide challenge mechanisms. Generative AI outputs should be treated as drafts or decision support, not as authoritative employment records.

7. Illustrative Case: Northstar Health Services

Background

Northstar Health Services, a fictional regional provider, faced rising patient demand, shortages of specialist nurses, high overtime, and the introduction of digital diagnostic systems. Its executive team proposed reducing administrative positions, recruiting internationally, and using an algorithm to identify employees suitable for accelerated promotion.

Problem

The algorithm was trained on five years of promotion data. Historical promotions had favoured employees who worked standard daytime schedules and had frequent visibility with senior managers. The initial model consequently gave lower advancement scores to many part-time employees, carers, and staff working night shifts. At the same time, the proposed administrative reductions had been announced before consultation with employee representatives.

Analysis

The workforce committee identified four risks. First, the training data reflected historical inequality. Second, some variables were proxies for availability and family circumstances. Third, the model’s score was not sufficiently explainable to employees. Fourth, the restructuring process threatened legal and trust consequences because alternatives had not been discussed.

The committee also examined resilience. Reducing administrative capacity too rapidly could shift work to nurses, increase errors, and worsen burnout. The organisation’s apparent labour surplus was therefore partly a classification problem: some administrative tasks could be redesigned, but essential coordination work remained.

Approach and solution

Northstar paused automated promotion decisions and conducted a data and equality impact assessment. It removed unnecessary proxy variables, added validated evidence of competencies, tested outcomes across employee groups, and required trained human panels to review recommendations. Employees could request correction of records and appeal decisions.

For restructuring, Northstar began consultation before finalising job reductions. It mapped tasks rather than simply eliminating job titles, offered digital-skills training, created redeployment pathways, and piloted automation in two departments. It introduced a dashboard containing vacancy fill time, overtime, sickness absence, training participation, internal movement, patient-service indicators, and fairness measures. Results were reviewed quarterly by the workforce committee and reported to employee representatives.

Outcome

The revised plan reduced projected administrative savings but avoided transferring excessive workload to clinical staff. Internal mobility increased, and the promotion process became more trusted after explanations and appeals were introduced. The pilot also showed that some automation benefits depended on process redesign and training rather than technology alone.

Learning points

1. Historical data are not automatically objective.
2. Workforce planning must examine tasks, not only job titles.
3. Consultation is a source of operational intelligence as well as a legal safeguard.
4. Efficiency measures should be tested against quality, safety, equity, and wellbeing.
5. Human oversight must include authority to challenge technology.
6. Resilience may require preserving apparently non-core capacity.

8. Challenges and Limitations

Governance systems can become bureaucratic and slow. Excessive approval layers may prevent timely action, especially during crises. The solution is proportional governance: low-risk routine decisions can use simpler controls, while high-impact decisions require stronger review.

Fairness assessment is also limited by incomplete demographic data, small populations, changing job structures, and disagreement about the relevant fairness standard. Refusing to measure inequality does not make it disappear, but collecting sensitive data without safeguards creates new risks. Organisations should explain why data are collected, protect confidentiality, and avoid using demographic information for unrelated purposes.

Forecasts are uncertain. A workforce plan based on a single scenario can create false confidence. Multiple scenarios, sensitivity analysis, and regular review are more reliable than pretending to know the future. Finally, governance cannot compensate for poor management culture. If leaders reward concealment, speed at any cost, or retaliation against dissent, formal policies will have limited effect.

9. Best-Practice Checklist

A responsible workforce-planning system should:

• connect workforce decisions to organisational purpose and strategy;
• assign clear decision rights and named accountability;
• involve HR, finance, operations, legal, privacy, risk, and employee representatives;
• assess privacy, equality, safety, and legal impacts before implementation;
• use accurate, relevant, proportionate data;
• explain decisions in language affected people can understand;
• retain meaningful human review and appeal;
• consult employees early enough to influence decisions;
• define baselines, targets, owners, and review dates;
• monitor unintended effects and disaggregated outcomes;
• test resilience through scenarios and exercises;
• treat AI as decision support rather than a substitute for responsibility; and
• revise or stop initiatives when evidence shows unacceptable harm.

Chapter Summary

Governance gives workforce planning legitimacy, direction, and accountability. It establishes roles, decision rights, evidence standards, controls, and review mechanisms. Ethical workforce planning requires privacy, proportionality, fairness, transparency, human oversight, and meaningful employee participation. Legal responsibilities commonly concern employment protection, data privacy, equality, accessibility, health and safety, consultation, and employment classification.

Implementation requires more than approving a strategy. Plans must be converted into resourced initiatives with owners, milestones, communication processes, capability support, and risk controls. Monitoring should distinguish inputs, processes, outputs, outcomes, and impacts. Indicators need clear definitions, baselines, targets, time frames, and appropriate disaggregation.

Future workforce planning must prepare for disruption rather than rely on one forecast. Scenario planning, cross-training, internal mobility, knowledge continuity, and employee wellbeing strengthen resilience. Automation and artificial intelligence may improve planning, but they also create risks of bias, privacy loss, opacity, and misplaced accountability. Responsible practice therefore combines analytics with professional judgement, consultation, legal compliance, and continuous review.

Key Terms

Governance: The structures and processes used to direct, control, and hold workforce decisions accountable.

Accountability: The obligation to justify decisions and accept responsibility for their consequences.

Proportionality: The principle that an intervention or data use should not be more intrusive or burdensome than necessary.

Procedural fairness: Fairness in the process through which a decision is made.

Distributive fairness: Fairness in the allocation of benefits, opportunities, and burdens.

Transparency: The provision of understandable information about purposes, evidence, processes, and consequences.

Explainability: The ability to provide meaningful reasons for a decision or recommendation.

Human oversight: Competent human review with authority to question, override, or stop an automated output.

Employee consultation: A structured process through which employees or representatives can influence decisions affecting them.

Data minimisation: Collecting and using only the data necessary for a defined legitimate purpose.

Impact assessment: A systematic evaluation of likely effects, risks, and safeguards before an initiative is implemented.

Discrimination: Unjustified unequal treatment or disadvantage associated with a protected or otherwise relevant characteristic.

Workforce resilience: The capacity to anticipate, absorb, recover from, and adapt to disruption.

Scenario planning: Exploring plausible alternative futures to test strategies and identify robust actions.

Skills disruption: Change in the skills, tasks, and capabilities required because of technology, markets, or other forces.

Internal mobility: Movement of employees among roles, projects, departments, or career levels within an organisation.

Leading indicator: A measure that provides early evidence of future performance or risk.

Outcome indicator: A measure of the effects produced by an initiative.

Model governance: Controls for developing, validating, using, monitoring, and changing analytical or AI models.

Psychosocial risk: Risk to mental or social wellbeing arising from work organisation, workload, insecurity, harassment, or related conditions.

Review Questions

Short Answer Questions

1. What is workforce-planning governance, and how does it differ from administration?
2. Explain the difference between procedural and distributive fairness.
3. Why is employee consultation important in workforce planning?
4. Distinguish an output indicator from an outcome indicator.
5. What is meant by workforce resilience?

Long Answer Questions

1. Explain how an organisation can design governance arrangements for high-impact workforce decisions.
2. Discuss the main privacy, equality, and employment-law issues that should be assessed before implementing a workforce plan.
3. Analyse the role of transparency, explainability, and human oversight when AI is used in workforce planning.
4. Describe how a workforce plan can be implemented, monitored, and corrected over time.
5. Evaluate the contribution of scenario planning, reskilling, and internal mobility to future workforce readiness.

Analytical / Application Questions

1. An organisation plans to use historical promotion data to identify future leaders. Explain how you would test the data and process for bias, privacy risk, and explainability before deployment.
2. A proposed automation project will reduce administrative work but increase workload for frontline employees. Design a governance and monitoring approach that balances efficiency, safety, service quality, and fairness.
3. A company experiences a sudden loss of a critical supplier and several specialist employees. Using resilience principles, recommend immediate actions and longer-term workforce-planning measures.

Multiple Choice Questions with Answers

Question 1

Which statement best describes workforce-planning governance?

A. The routine processing of payroll and attendance records

B. The system of roles, decision rights, controls, and accountability for workforce decisions

C. A forecast of the number of employees needed next year

D. A communication campaign used only during restructuring

Correct Answer: B. The system of roles, decision rights, controls, and accountability for workforce decisions

Question 2

Which principle requires an organisation to collect only information necessary for a defined legitimate purpose?

A. Data minimisation

B. Distributive fairness

C. Scenario planning

D. Internal mobility

Correct Answer: A. Data minimisation

Question 3

Why can historical promotion data create bias in an automated workforce model?

A. Historical data always contain too few observations

B. Historical decisions may reflect unequal opportunities and past discrimination

C. Promotion data cannot be stored digitally

D. Algorithms cannot process numerical information

Correct Answer: B. Historical decisions may reflect unequal opportunities and past discrimination

Question 4

Meaningful employee consultation occurs when employees can do which of the following?

A. Receive a final decision after implementation only

B. Influence alternatives before a decision is finalised

C. Approve every operational decision personally

D. Replace all legal and managerial responsibilities

Correct Answer: B. Influence alternatives before a decision is finalised

Question 5

Which indicator type measures whether a workforce initiative produced a change in capability or performance?

A. Input indicator

B. Process indicator

C. Outcome indicator

D. Governance indicator

Correct Answer: C. Outcome indicator

Question 6

If 180 of 240 assigned learners complete a programme, what is the completion rate?

A. 60%

B. 75%

C. 80%

D. ใน 90%

Correct Answer: B. 75%

Question 7

What is the main purpose of scenario planning?

A. To predict one certain future with complete accuracy

B. To eliminate the need for workforce data

C. To test strategies against several plausible futures

D. To replace employee consultation with statistical modelling

Correct Answer: C. To test strategies against several plausible futures

Question 8

Which practice most directly supports workforce resilience?

A. Depending on one employee for a critical process

B. Eliminating all surplus capacity immediately

C. Cross-training employees and documenting essential knowledge

D. Using only short-term contractors for specialist roles

Correct Answer: C. Cross-training employees and documenting essential knowledge

Question 9

What is a necessary feature of meaningful human oversight of an AI workforce recommendation?

A. The reviewer must accept the model output without alteration

B. The reviewer must have authority and competence to challenge or override the output

C. The model must be kept secret from all affected employees

D. The organisation must avoid recording the decision rationale

Correct Answer: B. The reviewer must have authority and competence to challenge or override the output

Question 10

A workforce plan reduces administrative positions but causes overtime and safety risks among clinical staff. What is the most appropriate governance response?

A. Ignore the effects because the original cost target was achieved

B. Expand monitoring to include workload, safety, service quality, and employee impacts

C. Remove all outcome indicators from the dashboard

D. Automate additional work without consultation

Correct Answer: B. Expand monitoring to include workload, safety, service quality, and employee impacts