Operational Performance and Productivity Training Course

Duration 10 days 18 modules · 65 contact hours
Level Intermediate Certificate on completion
Who attends Operations Managers, Continuous Improvement Specialists and others
Fee from USD 2,200 KSh 190,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 9 Nov 2026 Course code SD-QP-036

Before you join: Participants should have practical exposure to an operational, service, production, logistics, administrative or project environment.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Operational performance problems rarely have one cause. Missed service levels, long lead times, rising unit costs, recurring defects, equipment downtime and overloaded teams are often symptoms of poorly understood work flows, unstable processes, unclear measures and weak problem-solving routines. Managers need to improve output without simply adding people, overtime or capital expenditure, while protecting quality, safety, customer commitments and staff capability.

This course teaches participants to measure operational performance, identify constraints, analyse waste and variation, and design practical improvements. Participants work with process maps, value stream maps, takt time, capacity calculations, overall equipment effectiveness, visual management, standard work and root-cause analysis. They learn to select useful performance indicators, establish baselines, prioritise improvement opportunities and control changes after implementation. The course also addresses productivity in service, administrative, production, logistics and public-sector operations.

Teaching combines short instructor briefings with realistic cases, data analysis, group diagnostics, simulations and structured application planning. From the first week, participants build an improvement case based on a real or representative process. They develop a current-state analysis, performance baseline, future-state design, implementation plan and benefits measures. Each participant leaves with a completed operational performance improvement pack that can be adapted for use with their own team.

The course suits operational leaders, continuous improvement staff, project professionals, supervisors and analysts who are responsible for improving how work is planned, executed, measured and controlled. It is particularly relevant where service demand is variable, resources are constrained, handoffs are frequent or performance data is available but not yet used consistently.

What you will be able to do

  • Measure operational performance using balanced KPIs, baselines and performance targets
  • Map end-to-end processes using SIPOC, swimlane mapping and value stream mapping
  • Calculate capacity, utilisation, takt time, cycle time and constraint effects
  • Identify waste, variation and failure demand using Lean and Six Sigma methods
  • Apply root-cause analysis tools to recurring quality, delay and productivity problems
  • Design standard work, visual controls and daily management routines
  • Prepare a quantified operational improvement business case and implementation plan
  • Present a complete operational performance improvement proposal for stakeholder review

Benefits of attending

For you

  • Diagnose productivity losses with evidence rather than assumptions
  • Lead structured improvement discussions with operational teams
  • Build credible cases for process, capacity and quality changes
  • Use daily measures to manage output and emerging exceptions
  • Present improvement proposals using recognised operational methods

For your organisation

  • Shorter lead times through removal of delays, queues and rework
  • Higher output from existing labour, equipment and process capacity
  • Reduced defects, complaints and failure demand in critical services
  • Clearer ownership of performance measures and corrective actions
  • Repeatable improvement plans linked to measurable business results

Course modules

18 modules over 10 days

Participants can define operational performance and connect measures to customer, cost, quality and delivery requirements.

  • Performance dimensions: safety, quality, delivery, cost, morale and productivity
  • Voice of customer translated into critical-to-quality operational requirements
  • Input, process, output and outcome measures distinguished clearly
  • Leading and lagging indicators used within performance management systems
  • Balanced scorecards linked to departmental operational objectives and targets
  • Metric ownership, data frequency and escalation responsibilities defined

Participants can define process boundaries, customers, suppliers, inputs and demand patterns.

  • SIPOC diagrams establish high-level process scope and stakeholder boundaries
  • Customer segments separated by demand type, volume and service expectation
  • Demand analysis distinguishes predictable, variable and seasonal work
  • Failure demand identified from avoidable contacts, corrections and repeat work
  • Process boundaries set from trigger event through customer outcome
  • Service standards converted into measurable operational process requirements

Participants can map a current-state process and expose handoffs, delays, decisions and rework.

  • Swimlane maps show roles, handoffs, approvals and decision points
  • Documenting actual work rather than written procedure or assumed practice
  • Queue points, batching rules and wait states recorded accurately
  • Rework loops traced from defect discovery through correction completion
  • Process observations capture exceptions, workarounds and informal controls
  • Current-state map validated with operators, supervisors and internal customers

Participants can calculate key flow measures and identify the capacity constraint.

  • Cycle time, lead time and touch time calculated correctly
  • Takt time derived from available time and customer demand
  • Capacity analysis compares workload, staffing hours and available equipment
  • Utilisation interpreted alongside variability, queues and service risk
  • Little's Law connects work-in-progress, throughput and elapsed time
  • Bottleneck resources identified through demand, capacity and queue evidence

Participants can establish meaningful productivity baselines without encouraging harmful local optimisation.

  • Labour productivity measures relate output to paid productive hours
  • Unit cost calculations separate fixed, variable and avoidable costs
  • Baseline periods selected to account for demand and operating conditions
  • Productivity measures balanced against quality, safety and customer outcomes
  • Normalising data for product mix, case complexity and seasonal variation
  • Data definitions documented to prevent inconsistent reporting and comparison

Participants can identify and prioritise waste that reduces flow, quality and productivity.

  • TIMWOODS categories applied to physical, service and administrative work
  • Overproduction exposed through batching, speculative work and excess reporting
  • Waiting waste measured at approvals, handoffs and constrained resources
  • Motion and transport distinguished through workplace observation methods
  • Inventory examined as work-in-progress, backlogs, files and unprocessed requests
  • Waste opportunities prioritised by impact, effort, risk and controllability

Participants can distinguish common-cause variation from special-cause variation in operational data.

  • Variation sources classified as demand, process, people or equipment
  • Run charts reveal shifts, trends, cycles and unusual observations
  • Control charts distinguish routine fluctuation from assignable causes
  • Process stability assessed before setting improvement targets or interventions
  • Stratification separates performance by product, team, channel and location
  • Data collection plans specify definitions, samples, timing and ownership

Participants can quantify quality losses and focus improvement effort on material failure modes.

  • Cost of poor quality includes prevention, appraisal, failure and recovery
  • Defect definitions agreed before counting errors or nonconforming outputs
  • Pareto analysis ranks defect categories by frequency, cost or customer impact
  • First-pass yield measures outputs completed correctly without rework
  • Rolled throughput yield reveals cumulative losses across multiple process steps
  • Quality loss translated into capacity, cost, delay and customer consequences

Participants can investigate recurring problems and distinguish root causes from symptoms.

  • Problem statements define the gap, scope, frequency and operational impact
  • Five Whys testing avoids unsupported assumptions and premature conclusions
  • Fishbone diagrams organise potential causes across relevant cause categories
  • Cause-and-effect matrices link input variables to critical output measures
  • Evidence tests confirm causal mechanisms before selecting corrective actions
  • Root-cause findings documented with data, observations and process evidence

Participants can select improvement work using evidence, strategic value and implementation feasibility.

  • Impact-effort matrices compare improvement options using agreed scoring criteria
  • Pareto priorities focused on high-frequency or high-consequence performance losses
  • Risk assessment considers safety, service continuity, compliance and customer harm
  • Benefits hypotheses state expected changes in time, cost, quality and capacity
  • Improvement charters define problem, scope, sponsor, team and measures
  • Quick wins separated from projects requiring deeper analysis and investment

Participants can design a future-state process that improves flow, control and customer value.

  • Future-state maps remove non-value-adding steps and unnecessary handoffs
  • Flow design reduces batching, queues, duplicate entry and approval delays
  • Pull systems match work release to downstream capacity and demand
  • Workload balancing redistributes tasks around takt time and constraints
  • Decision rules simplify routing, prioritisation and exception handling
  • Future-state assumptions tested against demand, resources and operational risks

Participants can develop standard work that protects quality while improving consistency and speed.

  • Standard work specifies sequence, timing, method and expected quality
  • Work instructions separate essential controls from unnecessary procedural detail
  • Poka-yoke methods prevent errors through prompts, constraints and checks
  • Checklists support high-risk steps, handovers and critical verification tasks
  • Skills matrices identify training needs, coverage gaps and task flexibility
  • Standard work reviewed after changes, incidents and recurring deviations

Participants can establish visual controls and daily routines for managing operational performance.

  • Visual boards display demand, output, quality, risks and priorities
  • Tiered daily meetings escalate exceptions through defined management levels
  • Red-amber-green indicators show status against agreed operational thresholds
  • Daily huddles review yesterday's results and today's operating plan
  • Action logs assign owners, deadlines, evidence and closure criteria
  • Andon-style escalation signals trigger timely support for abnormal conditions

Participants can assess equipment-related losses and organise workplaces for efficient, safe work.

  • Overall equipment effectiveness combines availability, performance and quality losses
  • Downtime codes distinguish planned stops, failures, changeovers and waiting
  • SMED principles reduce setup time through internal and external task separation
  • 5S audits organise workplaces around safety, access and visual control
  • Preventive maintenance tasks linked to failure modes and operating conditions
  • Asset constraints evaluated against demand, reliability and replacement options

Participants can align staffing and skills with workload, demand patterns and service requirements.

  • Workload forecasts convert demand volumes into required processing hours
  • Erlang considerations introduced for variable demand and queueing services
  • Rostering principles match staffing profiles to hourly demand patterns
  • Cross-training plans reduce dependency on scarce skills and single points
  • Span of control considered when redesigning supervisory and support roles
  • Overtime, agency labour and backlog decisions assessed using total cost

Participants can plan, test and control operational changes with clear ownership and measures.

  • PDCA cycles structure small tests before wider process implementation
  • Implementation plans sequence actions, dependencies, owners and decision gates
  • Pilot design sets scope, duration, measures and acceptance criteria
  • Stakeholder analysis identifies affected groups, concerns and communication needs
  • RACI matrices clarify accountability for change, approval and sustainment
  • Control plans define monitoring, response actions and review frequencies

Participants can track realised benefits and sustain operational improvements after implementation.

  • Benefits registers record baseline, target, owner, timing and evidence
  • Financial benefits separated from capacity release and service improvements
  • Before-and-after comparisons account for demand, mix and external conditions
  • Performance review cadences test whether gains remain stable over time
  • Audit checks verify adherence to standard work and control plans
  • Corrective actions triggered when performance falls outside agreed limits

Participants can build, review and present a complete operational performance improvement proposal with quantified measures, future-state actions and control arrangements.

  • Current-state evidence assembled into a clear operational problem definition
  • Baseline measures demonstrate performance gaps, variation and material losses
  • Root-cause findings linked to verified process and data evidence
  • Future-state design specifies flow, standard work and control changes
  • Implementation roadmap sequences pilots, ownership, risks and review points
  • Benefits case quantifies expected quality, productivity, capacity and cost effects
  • Peer review tests assumptions, measures, feasibility and stakeholder clarity
  • Final presentation communicates recommendations, decisions required and next actions

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Operational performance diagnostic template
  2. Current-state and future-state process maps
  3. Productivity baseline and KPI scorecard
  4. Root-cause analysis and corrective-action register
  5. Operational improvement implementation plan
  6. Benefits realisation and control plan

Who should attend

  • Operations Managers — responsible for service, cost, quality and delivery results
  • Continuous Improvement Specialists — need structured methods for diagnosing and sustaining improvements
  • Production Supervisors — manage daily output, labour allocation and process discipline
  • Service Delivery Managers — improve customer response, handoffs and case completion times
  • Project Managers — lead process change projects with measurable operational benefits
  • Business Analysts — translate operational data into improvement priorities and designs

Skills and tools covered

Process performance measurementCapacity and flow analysisWaste eliminationRoot-cause analysisDaily performance managementImprovement implementation planning

Tools and standards

Lean, Six Sigma, Overall Equipment Effectiveness, ISO 9001

How the course runs

Training methodology

The course uses short briefings to introduce methods, followed by worked examples, case analysis, group exercises and operational simulations. Participants interpret process data, map work flows, calculate capacity and investigate realistic performance failures. Instructor feedback is used to test assumptions, improve measures and strengthen proposed actions. Application planning runs through both weeks: participants progressively assemble an improvement pack for a selected process, then review and present it during the final capstone session.

Requirements and prerequisites

Participants should have practical exposure to an operational, service, production, logistics, administrative or project environment. They should be comfortable reading basic tables, charts and operational reports, and able to discuss a process they know well. Prior responsibility for staff, budgets or formal improvement projects is useful but not essential. No previous Lean, Six Sigma, ISO 9001 or statistical training is required. Advanced mathematics, specialist software, programming knowledge and prior certification are not required. Participants gain most when they can bring a current performance issue or process example.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

You should understand the basics of a process or operation in which work is planned, delivered and measured. Prior Lean or Six Sigma training is not required, and the course does not assume advanced mathematics.

Bring a current process challenge, performance report or improvement idea if you can do so within your organisation's confidentiality rules. Examples might include lead-time data, defect reports, workload figures, service levels or a process description.

It is designed for managers, supervisors, analysts, improvement staff and project professionals with responsibility for operational results. It applies to production, logistics, banking operations, government services, shared services, healthcare administration and similar settings.

This course uses selected Lean and Six Sigma methods within a wider operational performance system. It gives equal attention to capacity, workforce planning, daily management, benefits tracking and implementing practical changes.

Participants leave with an improvement pack built around a selected process or case. The pack includes measures, analysis, proposed actions, ownership and controls that can be reviewed with managers and operational teams.

Each training day runs from 08:30 to 16:30 and provides about 6.5 contact hours. The first week establishes measurement, mapping and diagnosis; the second week develops future-state design, implementation controls and the final capstone presentation.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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