Practical resources
Start with a complete Function template or learn how to define competencies, career levels, and observable expectations.
Function template
This Backend Engineering Function defines communication, ownership, service design, and delivery quality with evidence a manager can cite. Use it as a starting draft, then edit names, levels, and examples to match how your team actually works.
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This Frontend Engineering Function defines communication, ownership, interface quality, and product implementation with evidence a manager can cite. Use it as a starting draft, then edit names, levels, and examples to match how your team actually works.
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This Data Analytics Function defines communication, ownership, analysis quality, and decision support with evidence a manager can cite. Use it as a starting draft, then edit names, levels, and examples to match how your team actually works.
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This Product Management Function defines communication, ownership, discovery, and delivery judgment with evidence a manager can cite. Use it as a starting draft, then edit names, levels, and examples to match how your team actually works.
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This Product Design Function defines communication, ownership, problem framing, and interaction craft with evidence a manager can cite. Use it as a starting draft, then edit names, levels, and examples to match how your team actually works.
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This Sales Development Function defines communication, ownership, discovery conversations, and handoff quality with evidence a manager can cite. Use it as a starting draft, then edit names, levels, and examples to match how your team actually works.
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This Account Executive Function defines communication, ownership, commercial judgment, and cycle management with evidence a manager can cite. Use it as a starting draft, then edit names, levels, and examples to match how your team actually works.
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This Customer Success Function defines communication, ownership, adoption, and renewal health with evidence a manager can cite. Use it as a starting draft, then edit names, levels, and examples to match how your team actually works.
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This Marketing Function defines communication, ownership, audience insight, and channel execution with evidence a manager can cite. Use it as a starting draft, then edit names, levels, and examples to match how your team actually works.
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This People Operations Function defines communication, ownership, policy design, and cycle operations with evidence a manager can cite. Use it as a starting draft, then edit names, levels, and examples to match how your team actually works.
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This Finance Function defines communication, ownership, reporting integrity, and business partnership with evidence a manager can cite. Use it as a starting draft, then edit names, levels, and examples to match how your team actually works.
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This Operations Function defines communication, ownership, process reliability, and cross-team coordination with evidence a manager can cite. Use it as a starting draft, then edit names, levels, and examples to match how your team actually works.
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Use this Site reliability engineering competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this DevOps engineering competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Quality assurance competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Data engineering competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Data science competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Machine learning engineering competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Engineering management competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Technical program management competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Product operations competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Revenue operations competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Sales operations competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Customer support competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Implementation consulting competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Solutions engineering competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Content marketing competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Demand generation competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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Use this Growth marketing competency framework template to define clear career levels, observable expectations, and evidence managers can apply consistently.
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To build a competency framework, define the Functions and role tracks you need now, choose distinct competencies for each Function, and write observable expectations for every level. Review the draft with managers using real work examples, publish a version for the next review cycle, and revise it only after you learn where the wording fails.
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Build a career ladder by defining the role tracks people can follow, limiting them to levels your company can support, and describing how work changes at each step. Adjacent levels should differ through observable scope, autonomy, complexity, or influence, so promotion decisions can point to evidence instead of reputation.
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A competency matrix is usually a grid that maps skills against people, roles, or levels. A competency framework defines the competencies, level expectations, behaviors, and examples used to make people decisions. The matrix can be a useful view, but reviews and career progression need the fuller standard behind its cells.
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A startup competency framework should cover the job families and levels the company uses now, not a future enterprise org chart. Start with the Functions in the next review cycle, write a small set of observable competencies for each one, and publish a version that managers can test and improve after the cycle.
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A level expectation states the work someone at a specific role track and level is expected to handle. Write it in the present tense, identify scope, autonomy, and complexity, and make every adjacent level distinguishable through evidence. Add short behaviors and examples so managers can apply the standard consistently.
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Use competencies in performance reviews by rating each person against the expectations for their Function, role track, and level, then supporting the rating with evidence from the review period. Keep one Function version fixed for the cycle, discuss rating differences in calibration, and update unclear criteria only for future cycles.
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Communication means sharing information clearly, listening to understand, and adapting the message to the audience and situation so people can act.
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Collaboration means combining work effectively, building working trust, and contributing to outcomes shared with other people or teams.
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Ownership means taking responsibility for an outcome, following through on commitments, and acting on blockers before they become surprises.
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Learning and growth means seeking useful feedback, learning from evidence, and applying that learning to improve personal and team capability.
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Customer focus means understanding customer needs, weighing relevant trade-offs, and delivering value that matters to users or buyers.
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Adaptability means adjusting plans and working methods when priorities, evidence, or conditions change, while protecting the intended outcome.
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Decision quality means making timely choices with relevant evidence, clear criteria, and judgment proportionate to the stakes and uncertainty.
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Inclusion means creating fair opportunities for people to contribute and considering perspectives that could materially affect the outcome.
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Reliability means meeting agreed expectations predictably and communicating early enough to respond when a commitment is at risk.
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Ethical judgment means recognizing ethical risk and choosing actions that protect people, trust, and the standards the organization states.
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Code quality defines the evidence that code is understandable, safe to change, and aligned with agreed engineering conventions.
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System design defines how to assess technical boundaries, interfaces, data flow, and failure choices at increasing scope.
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Testing strategy assesses how someone selects evidence that catches meaningful failures without making delivery needlessly expensive.
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Debugging assesses structured investigation from an observed symptom to a supported cause and verified correction.
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Technical documentation assesses whether recorded knowledge lets its intended reader operate, maintain, or change a technical system.
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Performance engineering assesses measurement-led work on speed, capacity, and resource use against explicit needs.
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Reliability engineering assesses how systems meet explicit availability, degradation, and recovery expectations.
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Security engineering assesses how technical security risk is identified, reduced, and verified within the person’s scope.
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Delivery planning assesses how technical outcomes become sequenced work with visible dependencies, risks, and checkpoints.
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Technical debt management assesses how technical constraints are evidenced, prioritized, and reduced according to delivery or operating impact.
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Product sense connects a clear customer problem to a product decision and the outcome that decision should change.
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Product strategy sets a coherent product direction by connecting customer needs, market context, and organizational goals.
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Roadmap planning sequences product investments around outcomes, dependencies, evidence, and available capacity.
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Requirements definition turns a validated need into clear constraints and acceptance conditions without prescribing unnecessary solution details.
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Experiment design creates tests with an explicit hypothesis, useful measures, and decision rules that produce actionable evidence.
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Outcome measurement defines and evaluates evidence that shows whether an initiative produced its intended result.
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Market analysis examines evidence about segments, alternatives, shifts, and opportunities to inform a product choice.
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Product operations creates repeatable workflows that improve product planning, visibility, and access to decision records.
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Launch planning coordinates readiness, sequence, and feedback so a product change reaches its intended audience safely and usefully.
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User research plans and conducts inquiry that produces credible evidence about people, needs, and behavior. It helps teams replace assumptions with findings they can examine when making product and service decisions.
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Interaction design defines how people move through and control an experience to complete intended tasks. It covers task flow, controls, states, feedback, and recovery rather than the visual treatment of the interface.
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Visual design uses composition, type, color, and hierarchy to make information clear and usable. It turns content and interaction requirements into a coherent presentation without defining the underlying task flow.
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Information architecture organizes and labels information so people can understand and find what they need. It defines structures, categories, relationships, and navigation logic rather than the behavior or visual treatment of a task.
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Prototyping creates fit-for-purpose representations that make ideas testable before full implementation. It measures how well a prototype answers a question, not how closely every prototype resembles finished work.
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Design systems creates and maintains reusable design standards that improve consistency and delivery. It covers shared foundations, components, documentation, contribution, and change management across teams.
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Content design structures and writes interface content that helps people understand choices and complete tasks. It covers the purpose, sequence, wording, and maintenance of content within an experience.
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Accessibility design creates experiences that people with varied access needs can perceive, understand, and use. It integrates access requirements into design decisions, states, documentation, and verification throughout delivery.
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Design critique evaluates design work against goals and evidence, then gives specific feedback that guides revision. It makes the reasoning, strengths, risks, and next design decisions visible without rating the person presenting the work.
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Data analysis turns a defined question into a defensible conclusion by selecting relevant data, checking limitations, and connecting findings to the decision at hand.
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Data modeling defines durable concepts, relationships, and grain so people can interpret information consistently as systems and reporting needs change.
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Statistical reasoning helps people choose methods whose assumptions fit the question, quantify uncertainty, and avoid conclusions the available evidence cannot support.
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Data visualization turns measures and uncertainty into a visual form that helps a defined audience see the intended comparison without being misled.
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Data quality makes important data fit for its intended use by defining acceptable conditions, detecting failures, tracing causes, and verifying repairs.
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Analytics engineering turns source data into dependable analytical datasets through versioned transformations, tests, documentation, and operating practices.
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Machine learning develops models that turn data into predictions or decisions, with evaluation tied to the real use, constraints, and ongoing behavior of the system.
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Data governance makes decisions about data rights, definitions, retention, and use explicit by assigning accountable owners and workable controls.
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Experiment analysis estimates what a controlled change caused by checking assignment, exposure, outcomes, uncertainty, and practical importance together.
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Discovery identifies whether a sales opportunity has a verified problem, a plausible buying path, and enough fit to justify further work. It turns research and buyer conversations into evidence for qualifying or ending an opportunity.
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Negotiation works through differences in price, scope, terms, and risk to reach an agreement each party understands and can sustain. It relies on explicit trade-offs, decision authority, and accurate commitments.
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Pipeline management keeps the active body of sales opportunities accurate, actionable, and current. It uses verified stages, dated next steps, and deliberate closure so attention goes to work that can progress.
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Account planning turns evidence about an organization, its priorities, stakeholders, and current relationship into a coordinated development plan. It makes choices about where to focus and what must be learned next.
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Solution selling connects a buyer's verified problem to relevant capabilities, limits, and expected outcomes. It explains fit with evidence and avoids presenting features that do not address the stated need.
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Sales forecasting estimates which revenue is likely to occur within a defined period using current opportunity evidence, timing, and risk. It makes uncertainty visible and changes when the underlying facts change.
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Objection handling clarifies what is behind a buyer's concern before offering a response. It addresses the specific issue with relevant evidence, acknowledges limits, and checks whether the concern is resolved.
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Closing guides a qualified buying process from unresolved actions to a clear decision. It confirms decision criteria, owners, approvals, and final commitments without manufacturing urgency or treating every outcome as a win.
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Territory planning allocates sales attention across a defined market using available evidence about fit, potential, timing, and coverage. It creates explicit priorities and revises them as market or account conditions change.
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Customer onboarding guides new customers through the knowledge, setup, and early outcomes required for effective use. Assess the work through plans, completed handoffs, documented decisions, and responses to onboarding risks, not through customer sentiment alone.
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Adoption management uses available evidence to identify gaps in meaningful use and coordinate actions that address them. Assess how a person interprets defined signals, tests explanations, and follows through on actions, not whether usage rises for reasons outside their control.
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Account health assessment evaluates defined signals and documents risks before they become urgent. Assess the consistency of evidence gathering, interpretation, and risk documentation, not the health status of an account or a prediction treated as certainty.
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Renewal management plans and advances renewal decisions with clear value evidence, timing, and commercial context. Assess preparation, decision clarity, coordination, and risk handling, not renewal outcome alone when authority and market conditions sit outside the role.
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Customer advocacy creates appropriate opportunities for satisfied customers to share credible experiences and feedback. Assess consent, fit, preparation, and follow-through, not the number of public endorsements a person secures.
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Success planning defines shared outcomes, measures, responsibilities, and checkpoints for an ongoing relationship. Assess whether the plan supports clear decisions and shared follow-through, not whether every outcome is achieved regardless of changed assumptions.
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Escalation management coordinates urgent customer issues with clear ownership, updates, and resolution criteria. Assess triage, coordination, communication, and closure within the role, not whether the underlying issue was caused or solved by that person.
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Value realization measures and communicates outcomes relative to agreed goals. Assess how evidence is defined, interpreted, qualified, and used in decisions, not whether a customer achieves an outcome shaped by many factors outside the employee's control.
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Customer education creates learning experiences that help customers use relevant capabilities correctly and independently. Assess learning design, delivery, accessibility, and revision from evidence, not learner attendance or product usage alone.
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Brand strategy defines how an organization should be understood and turns that position into clear choices about messages, identity, and experience.
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Content strategy plans useful content around audience needs, business goals, channels, and measurable outcomes, including what to create, update, and retire.
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Campaign planning turns a defined marketing objective into a coordinated plan for audience, message, channels, measures, timing, dependencies, and ownership.
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Demand generation creates and improves coordinated programs that produce measurable interest from relevant prospective buyers without confusing activity with demand.
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Marketing analytics uses reliable marketing data to evaluate performance, explain likely drivers, state uncertainty, and guide decisions about future work and investment.
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Audience research builds credible evidence about people's needs, context, language, and behavior so communication choices reflect observed reality rather than internal assumptions.
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Lifecycle marketing designs relevant communications for distinct relationship stages so each person receives context that supports the next useful action.
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Channel management selects, operates, and improves distribution channels by matching audience behavior and content fit with reliable execution and measured results.
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Marketing operations maintains dependable processes, systems, and data flows so marketing work can run, be traced, and be evaluated without avoidable manual repair.
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Talent acquisition is running a fair hiring process that identifies candidates against defined job needs. It rates process quality and evidence of fit, not charm or volume of offers.
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Employee relations handles workplace concerns through timely, impartial, and well-documented processes. It rates triage, fact-finding, and closure, not loyalty or toughness.
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Performance enablement designs and operates clear processes that help people understand expectations and improve. It rates cycle quality and usable guidance, not how inspirational the kickoff sounds.
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Compensation design builds pay structures and decisions from defined principles, market evidence, and internal equity. It rates the quality of the structure and the decision record, not secrecy or toughness in offers.
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Benefits administration operates benefit programs accurately and explains eligibility, choices, and changes clearly. It rates correct records and usable explanations, not how generous the package is.
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Workforce planning forecasts workforce needs and identifies practical actions to close capacity or capability gaps. It rates the quality of the forecast and the options, not how large a hiring request sounds.
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Organizational design defines roles, responsibilities, and reporting relationships that support the intended work. It rates whether people know who owns what, not how neat the chart looks.
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Learning program design creates learning with explicit needs, outcomes, practice, and evaluation. It rates whether people can do something new at work, not how polished the slides look.
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People analytics is the craft of using workforce data responsibly to answer defined questions and improve people decisions. Use it to assess question quality, method, limits, and responsible sharing, not whether a dashboard looks busy or a metric moved after the fact.
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Financial planning turns organizational priorities into forward-looking financial plans built from explicit assumptions and scenarios. Use it to assess how someone structures, updates, and explains a plan, not whether actual results happen to match a forecast.
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Budget management keeps approved resource decisions visible by recording commitments, comparing actuals with budget, and updating expected outcomes. Use it where someone is accountable for budget control, not merely for producing forecasts or explaining financial results.
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Financial analysis turns financial data into explanations and decision-relevant comparisons. Use it when a role investigates performance or evaluates choices, and assess the traceability of the analysis rather than whether stakeholders select its recommendation.
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Accounting controls keep records accurate, authorized, and traceable through defined checks and retained evidence. Use this competency for executing or designing financial controls, while keeping record preparation and business analysis as separate capabilities.
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Cash flow management tracks and forecasts when cash enters and leaves so obligations and funding needs are visible. Use it for operating cash visibility and timing decisions, not for the broader banking, investment, and financial-risk mandate of treasury management.
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Revenue recognition applies the organization's defined accounting policy to determine the amount and period recorded as revenue, supported by evidence. Use it for revenue accounting judgments and execution, not for commercial forecasting or general control design.
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Tax compliance organizes records, calculations, filings, payments, and documented interpretations against defined obligations and deadlines. Use it for operational tax responsibility, with specialist review where required, and do not treat this competency catalog as tax advice.
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Treasury management governs liquidity, banking, funding, investments, and financial risk within approved policies. Use it where a role manages financial counterparties or instruments, while assessing documented decisions and controls rather than market outcomes alone.
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Process design turns work into a repeatable workflow with clear steps, ownership, controls, and measures of success. This catalog separates following and documenting an existing process from designing a workflow independently and improving processes that cross teams.
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Capacity planning matches expected demand to available capacity through explicit assumptions and constraints. This catalog progresses from maintaining inputs, to independently planning for a team, to shaping cross-team capacity choices under uncertainty.
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Quality management defines acceptable outcomes, monitors results, and addresses the causes of recurring defects. This catalog progresses from applying checks, to owning quality for a team, to improving quality systems across connected work.
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Vendor management monitors external providers against agreed service, cost, risk, and performance expectations. This catalog progresses from maintaining records and follow-ups, to owning a provider relationship, to shaping decisions across a vendor portfolio.
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Inventory planning balances supply, demand, lead times, and service goals to set appropriate stock levels. This catalog progresses from maintaining planning inputs, to independently setting inventory positions, to shaping policy across connected locations or categories.
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Logistics coordination manages the timely movement of goods or resources across parties, locations, and constraints. This catalog progresses from tracking defined movements, to independently coordinating routes and exceptions, to improving multi-party logistics flows.
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Operational risk identifies and reduces process risks through proportionate controls, monitoring, and escalation. This catalog progresses from applying established controls, to independently assessing a workflow, to shaping risk practices across connected operations.
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Business continuity prepares and tests practical responses that keep critical work operating through disruption. This catalog progresses from following and maintaining plans, to owning continuity for a workflow, to coordinating responses across interdependent services.
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Service management is the capability to operate services against defined expectations and improve them using incidents, requests, and performance data. It makes service outcomes, ownership, and improvement work visible enough to assess.
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Identity management controls digital access through accurate identities, appropriate permissions, and timely lifecycle changes. It gives managers observable evidence from approvals, access records, reviews, and resolved exceptions.
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Network administration configures and maintains networks for reliable, secure, and observable connectivity. The ladder separates guided changes, independent ownership of a network area, and standards that work across environments.
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Cloud operations operates cloud resources with controlled changes, clear observability, and accountable cost. The expectations focus assessment on change artifacts, operating signals, recovery work, and cost decisions.
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Security operations detects, investigates, and coordinates responses to security events using defined evidence and procedures. It provides a fair ladder from guided alert handling to cross-team detection and response standards.
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Contract review evaluates proposed agreements for obligations, ambiguity, and risk, then records clear recommendations. These expectations assess review work and decision support without claiming a legal outcome.
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Regulatory compliance translates applicable requirements into documented controls, evidence, and timely reporting. The ladder assesses traceable compliance work without promising that an organization will avoid every violation.
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Privacy management applies privacy requirements to the collection, use, sharing, retention, and deletion of personal data. It assesses documented decisions and controls without claiming that risk can be eliminated.
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Strategic sourcing evaluates supply options against defined needs, total cost, risk, and long-term value. It separates evidence-based market and option analysis from the negotiation of final supplier terms.
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Supplier negotiation reaches clear supplier terms by preparing evidence, testing trade-offs, and documenting agreements. The ladder assesses preparation, exchanges, and accurate handoff rather than savings claims alone.
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