Frequently Asked Questions

OXYGEN Job Redesign is a guided 8-step workflow that uses AI to analyse how automation reshapes every role in your organisation. It breaks each job into individual tasks, assesses the impact of AI on each task across multiple time horizons, classifies every task into a human role category, and produces a board-ready financial model showing FTE savings, investment required, and return on investment.

Job Redesign is for the Chief of Work, CEOs, CFOs, and senior executives who need to understand the financial and structural impact of AI on their workforce before committing to a transformation programme. It is particularly useful for organisations preparing a board-level business case for automation investment, quantifying the return on workforce transformation, or modelling the shift from human-only to human-agent hybrid teams.

Every task is classified into one of five categories: Full Control (1.0x FTE, 0% automated), Augmented (0.7x FTE, 30% saved), Supervised (0.4x FTE, 60% saved), Exception Only (0.15x FTE, 85% saved), and Eliminated (0.0x FTE, 100% automated). Automation can only increase over time, making the model logically consistent and fully defensible in any governance review.

The Results Dashboard generates a full set of deliverables: an executive summary PDF, an Excel workbook covering task breakdown and financials, a transition CSV with employee-level fit scores and categories, a 3-phase transformation roadmap, newly redesigned job descriptions ready to use in OXYGEN, and a saved shareable project state. Every number is traceable back to its source assessment.

The financial model is deterministic, not estimated. It is driven by your actual headcount data, real salary and cost inputs from your MTP, and task-level automation assessments. Change an assessment in Step 3 and every downstream financial figure recalculates instantly. The model does not use industry benchmarks or consultant assumptions.

A single job can be fully redesigned in under an hour. A full portfolio of 50-100 jobs typically takes 1 to 3 days with a small team. The AI task decomposition and automation assessment steps dramatically reduce the time compared to manual job analysis, and the financial model and roadmap are generated automatically once the assessments are complete.

Transformation Readiness is a 6-step guided workflow that answers one critical question: can your team be ready in time? It analyses your actual employees against the competencies required for a transformation, models week-by-week skill development, evaluates up to 1,000 strategic paths for closing skill gaps, and delivers a definitive YES or NO verdict with a costed implementation plan.

Use it whenever your organisation faces a transformation with a hard deadline and a people readiness requirement. Common triggers include new technology adoption (AI, cloud, automation), mergers and acquisitions, digital transformation programmes, regulatory compliance deadlines, strategic business pivots, and post-restructuring capability assessments. Any situation where you need to know if your team can get there in time.

The verdict is based on your real data: actual employee competency levels, real skill growth rates from your OXYGEN competency catalog, and the required competency levels you define for the transformation. The system models how each person's skills develop over the available time, tests every combination of training, hiring, reallocation, and other interventions, and determines whether the required readiness percentage is achievable within your deadline.

OXYGEN evaluates up to 1,000 paths across 10 scenario types: Pure Training, Hiring + Training, AI Augmentation, Redeployment, Outsourcing, Phased Delivery, Scope Reduction, Timeline Extension, Hybrid Mix, and Extreme Options. Each scenario is scored on feasibility, time to readiness, total cost, readiness percentage achieved, risk level, and FTE impact during transition.

AI similarity matching finds employees with related skills who could be transfer candidates rather than pure training or hiring cases. For example, an employee with strong Cybersecurity skills gets partial credit toward a Cloud Security gap. This prevents false negatives, reveals hidden strengths in your existing workforce, and typically reduces the cost and time of the recommended readiness plan.

For a team of 100 to 500 people with a well-defined transformation scope, the full analysis from setup to final verdict typically takes a few hours. The AI competency suggestion, gap analysis, and scenario scoring all run automatically once the project is configured. The one-click "Run Full Analysis" button executes the entire pipeline end to end. Results are ready to present to leadership the same day.

We provide end-to-end support including workforce process design, skills taxonomy development, training programmes, tool implementation, and business case development. Each engagement is scoped to your specific situation rather than delivered from a generic template.

Yes, building data-driven business cases is a core part of what we do. We quantify the value of workforce planning, connect it to strategic priorities, and help you secure internal commitment and investment.

Organisations undergoing significant transformation, restructuring, or moving toward data-driven HR strategies. We work best with clients who have made a commitment to Strategic Workforce Planning rather than those still in an exploratory phase.

We combine deep workforce strategy expertise with hands-on integration support for our proprietary tools OXYGEN and OXYGEN AI. We are focused on measurable outcomes, not advisory reports that sit on a shelf. Every recommendation comes with an implementation pathway.

Anywhere from one month to one year, depending on scope and complexity. After a discovery session we provide a detailed project timeline. Agile engagements can deliver first results within weeks.

Half-yearly maintenance and updates, customisation requests, user training refreshes, technical support, data audits, and performance tuning. We remain a committed partner well beyond go-live.

Yes. OXYGEN integrates with major HR platforms including Workday, SAP SuccessFactors, and Oracle, via API or file-based methods. We scope integration requirements during discovery and handle technical setup as part of the implementation.

Yes. We run hands-on workshops, train-the-trainer sessions, and provide ongoing user support. Our goal is to build internal capability so your teams can run SWP independently over time.

The Chief of Work is a new C-suite role that orchestrates how all work gets done across an organisation: by humans, by AI agents, or by hybrid teams. Unlike the CHRO, the Chief of Work reports to the CEO, speaks the CFO's language, and is accountable for the return on every workforce transformation investment.

CHROs have had over 30 years to adopt strategic workforce planning as an operational discipline. Fewer than 11% of organisations achieved mature SWP capabilities. With AI agents now automating entire workflows and organisations flattening rapidly, the speed and scale of change requires a leader with a fundamentally different mandate: one focused on work design, workforce economics, and P&L accountability, not people operations.

Not necessarily. The CHRO may still own people operations, employee experience, and compliance. But the Chief of Work owns the strategic question of how work itself is designed and who or what performs it. In some organisations, the CHRO evolves into this role. In others, it is a new appointment that sits alongside the CHRO.

Five domains: (1) Work Architecture: designing how every process gets done by humans, agents, or hybrid teams. (2) Workforce Economics: translating workforce decisions into financial returns. (3) Talent Supply Chain: operating the TSCM framework as a continuous system. (4) Organisational Redesign: navigating the structural shift to flatter, supply-chain-driven organisations. (5) Continuous Transformation: embedding transformation as a permanent operating rhythm.

Yes. We help organisations define the Chief of Work mandate, design the role's scope and reporting lines, build the business case for the appointment, and implement the TSCM + OXYGEN operating system that enables the role. This is a core part of our consultancy offering.

The Talent Supply Chain applies supply chain discipline to work itself: how tasks are designed, how capabilities are sourced, how humans and machines collaborate, and how every investment returns measurable value. It is the umbrella concept that encompasses Talent Supply Chain Management (TSCM) as the operating framework and OXYGEN as the execution platform.

"AI-First" is a technology-centric framing. The Talent Supply Chain is a discipline-centric framing. AI is one input into the supply chain, alongside human talent, contingent workers, and organisational design. The difference matters: a supply chain approach demands measurable returns, structured processes, and continuous optimisation. A technology label does not.

(1) Workforce Flow: the sourcing, developing, deploying, and retaining of human talent. This is where TSCM has operated for 15+ years. (2) Skill Supply Chain: how skills are identified, built, maintained, and retired as the half-life of knowledge accelerates. (3) Work Architecture: designing how every process gets done, by whom or what, at what cost, and with what governance. This is the new frontier that includes AI agents and hybrid teams.

Time-to-Skill is the supply chain velocity metric for workforce capability. Just as Time-to-Market measures how quickly products reach customers, Time-to-Skill measures how quickly your organisation can develop or acquire a capability. With the skills half-life now at 2.5 years (down from 10-15 years in 2010), Time-to-Skill is the metric that determines competitive advantage.

For every capability gap, the Talent Supply Chain framework evaluates four sourcing strategies: Build (develop internally), Buy (hire externally), Borrow (use contingent or redeployed talent), or Bot (automate with AI). A fifth option, Redesign, restructures the work itself to eliminate the gap. OXYGEN provides the data and simulation tools to quantify each path before committing resources.

OXYGEN is our dedicated platform for workforce planning, analytics, simulations, and plan tracking. It creates a consolidated data layer that spans historical, current, and future workforce states, giving planners a single source of truth for all workforce decisions.

The Chief of Work, CEOs, CFOs, CXOs, workforce planners, and business strategists. Anyone accountable for workforce transformation outcomes, workforce economics, or Talent Supply Chain operations benefits from OXYGEN's analytics and simulation capabilities.

Historical workforce analytics, taxonomy and competency mapping, Strategic Workforce Planning, dynamic scenario modelling, gap analysis, HR transaction tracking, and real-time dashboards. It covers the full SWP lifecycle from analysis through to execution monitoring.

Yes. OXYGEN includes dynamic scenario modelling that lets you test hiring strategies, upskilling programmes, or restructuring options before committing. You can model multiple futures simultaneously and compare their outcomes side by side.

Yes. OXYGEN connects with Workday, SAP SuccessFactors, Oracle, and other major platforms via API or file-based methods. It also consolidates data from L&D systems, performance tools, and spreadsheets to give a complete workforce picture.

Yes. OXYGEN follows EU data privacy regulations and applies enterprise-grade encryption and access controls. Crucially, sensitive SWP data is hosted at the client site and never stored in cloud environments.

Yes. OXYGEN is designed for HR and business users, not data scientists. Visualisations, guided workflows, and intuitive dashboards make it accessible. OXYGEN AI further simplifies complex tasks with natural language assistance.

The licence covers use of the software, half-yearly maintenance with updates, and help desk access. Consulting services are available as add-ons. Pricing is based on resource count rather than a flat fee, making it scalable to your organisation's size.

Fast: rapid implementation and near-immediate insights from day one. Flexible: fully customisable taxonomy, roles, and dashboards to match your organisation's frameworks. Future-safe: modular design built to support AI integration and adapt as workforce planning evolves.

OXYGEN AI assists SWP practitioners in creating and customising workforce planning processes, identifying critical workforce challenges, and serving as a collective knowledge base for scenario construction and transformation planning. It adds artificial intelligence and machine learning on top of OXYGEN's planning engine.

OXYGEN is the proven SWP execution and analytics platform. OXYGEN AI layers on artificial intelligence, machine learning, advanced predictive modelling, and real-time decision-making capabilities. Together they allow you to model hundreds or thousands of workforce scenarios overnight, compared to the traditional three-scenario approach.

Medium-to-large organisations with complex staffing needs that require holistic workforce transformation planning. It is particularly valuable for businesses preparing proactively for significant changes in the nature of work.

Access to a secure large language model (LLM), either your organisation's existing corporate LLM or one we help you set up. OXYGEN AI can run as a standalone product or integrated directly within OXYGEN.

Yes. OXYGEN AI capabilities are integrated at no additional cost for OXYGEN users. The only additional expense is LLM access, which is minimal for enterprise-grade models and higher for third-party options.

Curated SWP knowledge access, process templates, competitive benchmarking, taxonomy definition assistance, guided planning workflows, future-of-work insights, and customisable reports. As AI capabilities evolve, so do OXYGEN AI's features.

Yes. OXYGEN AI analyses trends and suggests emerging skill needs, helping you plan capability building programmes and model training ROI before committing budget.

Yes. It is built with modular architecture designed to adapt to the evolving AI landscape. As advances in AI emerge, OXYGEN AI will incorporate them. The system continuously integrates the latest SWP research, industry trends, and generative AI advancements.

Data privacy concerns are addressed via secure corporate LLM deployments. There may be costs associated with advanced model access, and adoption typically requires some training to help teams interpret and use AI-generated outputs effectively.

OXYGEN PLAY is a hands-on sandbox for experimenting, learning, and scaling agile Strategic Workforce Planning. It brings together proven SWP practices and industry-specific workflows in an interactive, workshop-style format where your teams co-create real outputs in real time.

HR and business leaders who want to move beyond theory and build, evolve, or scale their Strategic Workforce Planning capability into actionable implementation. OXYGEN PLAY is ideal whether you are starting from scratch or maturing an existing practice.

OXYGEN PLAY emphasises rapid co-creation and design thinking. Rather than us delivering recommendations to you, we work alongside your team to design, test, and iterate workforce planning elements together. You shape the outputs in real time.

Capability frameworks, workforce segmentation models, SWP dashboards, planning cycle design, role definitions, and connections between L&D and talent strategy. If it relates to workforce planning, it can be tackled in a Lab.

Either. OXYGEN PLAY can be a single focused sprint or an iterative series of sessions, customised to your goals and internal capacity. We design the format together during the initial discovery conversation.

No. OXYGEN PLAY is tool-agnostic and can be adapted to your current technology stack. That said, clients using OXYGEN will find the Lab outputs integrate naturally into the platform.

Cross-functional teams deliver the best results: HRBPs, data analysts, learning leaders, business strategists, and talent management stakeholders. We recommend including decision-makers alongside practitioners for maximum impact.

Tangible co-developed outputs ready for piloting or scaling: draft capability models, process maps, planning dashboards, or templates. Every lab ends with something concrete your team can take forward immediately.

Yes. Labs are delivered virtually, in-person, or in a hybrid format depending on your team's location and preference. The co-creation approach works equally well across all formats.

Talent Supply Chain Management (TSCM) applies the principles of traditional supply chain management to the planning, development, and deployment of human talent. Just as supply chains ensure the right components arrive at the right place at the right time, TSCM ensures your organisation has the right capabilities, in the right roles, at the right moment - before the business need becomes urgent.

Traditional SWP typically asks: how many people do we need, and when? TSCM goes deeper - it treats capability as a supply chain problem, meaning it accounts for lead times, probability-weighted demand forecasts, and the cost of under- or over-supply. Where SWP is often reactive, TSCM is inherently proactive: development and redeployment begin before the need is certain, based on assessed probability.

The TALENT on demand 5-Step model covers: (1) Business Strategy Alignment - connecting workforce decisions to the strategic direction of the business; (2) Current Workforce Analysis - understanding what capabilities exist today; (3) Future Workforce Forecasting - modelling what will be needed and when; (4) Gap Analysis - identifying the delta between current and future state; and (5) Action Planning and Execution - closing gaps through build, buy, borrow, or automation decisions.

Supply Chain Management (SCM) manages the flow of physical goods and components from source to customer. Talent Supply Chain Management (TSCM) applies the same logic to human capability - treating skills and roles the way SCM treats inventory and production capacity. The analogy is direct: lead times for building capability mirror lead times for manufacturing; demand forecasting applies to talent requirements just as it applies to product demand; and shortage costs are just as real when a critical skill is missing as when a component is out of stock.

Time-to-skill is the elapsed time between identifying a capability need and having a fully capable person in that role - whether through hiring, upskilling, or redeployment. It is the talent equivalent of time-to-market. Organisations that reduce their time-to-skill gain a measurable competitive advantage: they can respond to strategic shifts faster, without the disruption and cost of last-minute hiring. TSCM is specifically designed to minimise time-to-skill through proactive planning.

Rather than waiting for a capability need to be confirmed before acting, TSCM plans in proportion to probability. If a role has a 30% chance of requiring a new capability within 18 months, preparation begins for 30% of the relevant employee population - building partial readiness at a fraction of the cost of full preparation. As probability changes, the plan updates. This mirrors how supply chains pre-purchase components before orders are confirmed, reducing lead times without over-committing resources.

Organisations undergoing significant transformation, operating in fast-moving industries, or managing large and complex workforces gain the most from TSCM. It is particularly valuable where the gap between identifying a skill need and filling it is typically long - such as in regulated industries, technical roles, or senior leadership pipelines. That said, any organisation that wants to move from reactive workforce management to proactive capability building will benefit.

OXYGEN is the platform purpose-built to operationalise TSCM. It consolidates historical, current, and future workforce data into a single planning environment, enabling skills mapping, gap analysis, scenario modelling, and execution tracking. OXYGEN AI adds predictive capability - suggesting emerging skill needs, modelling hundreds of scenarios simultaneously, and keeping frameworks aligned with the latest workforce research and market trends.

Yes. While TSCM delivers the greatest value when applied enterprise-wide, many organisations begin with a single function - technology, finance, or operations - where skill gaps are most acute or where business transformation is moving fastest. A focused TSCM programme in one area builds the data foundations and planning disciplines that can then be scaled across the organisation over time.

OXYGEN STAR -- Strategic AI-Augmentation Roadmap -- is a 5-level maturity framework that measures how effectively your organisation augments human capability with AI. It benchmarks where you stand across five critical dimensions: AI Strategy and Vision, Data and Infrastructure, AI Talent and Culture, Governance and Ethics, and Business Impact. Each dimension is scored across five levels -- from Ad Hoc through to Leading -- giving you a clear, actionable picture of your augmentation maturity and priority gaps.

OXYGEN STAR is designed for the Chief of Work, CEOs, CFOs, and Boards who need to make strategic decisions about how AI augments human capability. It gives each audience a relevant lens: the Chief of Work uses it to design augmentation strategy across the workforce; CIOs and CTOs use it to evaluate data and infrastructure maturity; CEOs and Boards use it to govern augmentation responsibly at the enterprise level.

The five dimensions are: (1) AI Strategy and Vision - whether AI is embedded in corporate strategy with board-level ownership; (2) Data and Infrastructure - whether your data foundations are reliable, governed, and scalable enough to support AI at production scale; (3) AI Talent and Culture - whether AI fluency exists across the organisation and the culture supports experimentation; (4) Governance and Ethics - whether AI is deployed responsibly with oversight, bias monitoring, and regulatory compliance; and (5) Business Impact - whether AI investments are tied to measurable outcomes and generating verified competitive advantage.

⭐ Ad Hoc - AI use is uncoordinated, ungoverned, and without strategic direction. ⭐⭐ Experimenting - pilots are underway but not formalised or resourced for scale. ⭐⭐⭐ Scaling - AI strategy is defined, data foundations are in place, and programmes are being rolled out. ⭐⭐⭐⭐ Optimising - AI is actively tracked against business outcomes and continuously improved. ⭐⭐⭐⭐⭐ Leading - AI is core to corporate strategy, fully governed, and generating verified competitive advantage.

The full OXYGEN STAR assessment is conducted with our consultancy team and typically involves structured interviews, data review, and stakeholder workshops across the five dimensions. There is also a self-assessment tool on the OXYGEN STAR page that gives a rapid indicative score based on descriptive questions. The self-assessment takes around 5 minutes; the full assessment takes 2 to 4 weeks depending on organisational complexity.

The full assessment delivers a scored maturity profile across all five dimensions, a benchmarked view of where your organisation stands relative to peers, identification of your highest-priority gaps, and a tailored action roadmap with specific recommendations for each dimension. This gives leadership a structured basis for AI investment decisions and governance conversations.

Most AI maturity models focus primarily on technology - data architecture, model deployment, and infrastructure. OXYGEN STAR equally weights the human dimensions: talent, culture, and governance. This reflects our view that the gap between AI leaders and laggards is not primarily technical - it is organisational. The framework is also directly connected to actionable SWP interventions, so assessments lead to concrete workforce planning programmes rather than just scores.

We recommend a full reassessment annually, with a lighter self-assessment check every six months. AI maturity evolves quickly - both in terms of what organisations are doing and in terms of what "leading" looks like as the field advances. Regular reassessment ensures your roadmap stays relevant and your progress is being measured against an up-to-date benchmark.

Through Strategic Workforce Planning: assess your current skills landscape, prioritise critical roles, redesign jobs to integrate AI and automation, test new approaches through pilots, and continuously evolve your plans based on data. The key is treating workforce strategy as an ongoing discipline, not a one-off project.

Not all. Many roles will evolve rather than disappear. Routine and repetitive tasks will increasingly be handled by AI and automation, while human roles will shift toward creativity, critical thinking, emotional intelligence, and leadership. New roles are already emerging in AI governance, sustainability, and human-machine collaboration.

Skill gaps that slow execution, lower innovation capacity, talent loss to more forward-thinking competitors, costly redundancies, declining morale, and ultimately poor business performance. Organisations that ignore workforce evolution do not just fall behind, they create structural problems that become increasingly expensive to fix.

Apply Strategic Workforce Planning systematically: assess current capabilities honestly, identify and prioritise critical roles, redesign jobs with AI integration in mind, test approaches through focused pilots, and regularly update plans as conditions change. Invest in both the technical tools and the human capability to use them well.