Performance Measurement and Benchmarking Training Course

Duration 10 days 16 modules · 65 contact hours
Level Intermediate Certificate on completion
Who attends Operations Managers, Continuous Improvement Managers and others
Fee from USD 2,200 KSh 190,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 16 Nov 2026 Course code SD-QP-069

Before you join: Participants should have experience working with operational reports, service measures, process data or improvement initiatives.

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

Performance measures often fail because they are poorly defined, disconnected from decisions, based on unreliable data or compared without accounting for differences in volume, complexity and service mix. Managers then receive dashboards that report activity rather than results, improvement teams pursue symptoms rather than causes, and benchmarking produces targets that teams cannot credibly achieve. This course addresses the design, governance and use of measurement systems that support better operational decisions and sustained productivity improvement.

Participants learn to translate strategy and customer requirements into outcome, quality, productivity, cost and delivery measures. They build KPI hierarchies, metric dictionaries, baselines, process maps and dashboards; analyse variation using statistical process control; and distinguish useful benchmarks from misleading comparisons. The course covers internal, competitive and functional benchmarking, including peer selection, normalisation, percentile analysis and evidence-based target setting. It also connects measurement to PDCA, A3 problem solving, DMAIC, corrective action and benefits realisation.

Teaching combines concise instructor briefings with cases from manufacturing, financial services, public administration, healthcare, utilities and service operations. Participants work progressively on a selected operational problem, developing a measurement and benchmarking package through the course. They leave with a practical set of templates and a reviewed plan containing defined metrics, baseline findings, benchmark evidence, targets, dashboard requirements, governance arrangements and an improvement action register.

The course is suited to managers and specialists responsible for operational performance, quality, service delivery, continuous improvement, reporting or transformation. It is delivered over 10 classroom or live-online days, each running from 08:30 to 16:30, and participants receive a certificate of completion.

What you will be able to do

  • Design a KPI hierarchy linking strategic objectives, process drivers and frontline measures
  • Create metric dictionaries with formulas, ownership, data sources and validation rules
  • Map processes using SIPOC, value stream mapping and critical-to-quality requirements
  • Calculate quality, productivity, capacity and process capability measures consistently
  • Interpret run charts, control charts and Pareto analysis to identify performance signals
  • Conduct internal, competitive and functional benchmarking using normalised comparison data
  • Set evidence-based targets using baselines, capability, benchmarks and risk assumptions
  • Produce a performance measurement and benchmarking package for an operational process

Benefits of attending

For you

  • Ability to challenge weak KPIs, unclear targets and unsupported performance claims
  • Practical capability to build dashboards that prompt decisions and accountable action
  • Confidence interpreting variation before escalating apparent performance problems
  • A reusable approach for comparing sites, teams and peer organisations fairly
  • A completed measurement and benchmarking package for a current operational priority

For your organisation

  • More consistent performance definitions across functions, sites and reporting cycles
  • Earlier detection of quality, capacity and service-delivery problems
  • Better-targeted improvement investment based on quantified gaps and causes
  • More credible external comparisons through normalised benchmark data
  • Clearer accountability for actions, benefits verification and control measures

Course modules

16 modules over 10 days

Participants can define a measurement system that connects operational activity to intended results.

  • Purpose statements translated into measurable service, quality, cost and delivery results
  • Performance measurement system architecture: inputs, processes, outputs, outcomes and impacts
  • Logic models distinguish controllable activities from external outcome drivers
  • Stakeholder requirements converted into critical-to-quality performance measure definitions
  • Leading and lagging indicators linked through explicit cause-and-effect hypotheses
  • Metric dictionaries define owner, formula, source, frequency and decision use

Participants can establish reliable data definitions and controls for performance reporting.

  • Operational definitions remove ambiguity from numerator, denominator, population and exclusions
  • Data collection plans specify source systems, sampling and validation checks
  • Baseline measures established using historical trends, targets and tolerance bands
  • Attribute and variable data distinguished for appropriate analytical treatment
  • Data lineage maps trace reported figures to source transactions
  • Missing values, duplicates and outliers handled under documented rules

Participants can design aligned KPI sets and set targets using sound operational evidence.

  • SMART criteria test indicator relevance, controllability, timeliness and actionability
  • Balanced scorecard perspectives connect strategic objectives with operational KPI sets
  • Driver trees show relationships among volume, yield, capacity and cost
  • Outcome measures separated from output, efficiency and compliance measures
  • Metric hierarchies align enterprise, unit, process and frontline measures
  • Target-setting methods use baselines, benchmarks, capability and policy commitments

Participants can map processes to identify measurable drivers of quality and productivity.

  • SIPOC diagrams establish process boundaries, customers, suppliers and handoffs
  • Value stream maps expose waiting, rework, queues and non-value-added work
  • Process-cycle efficiency quantifies value-added time against total lead time
  • Critical-to-quality trees translate customer needs into measurable process requirements
  • Service blueprints identify customer-facing steps, support activities and failure points
  • Swimlane maps assign accountability across functions and external partners

Participants can calculate and diagnose core measures of process quality and loss.

  • First-pass yield, defect rate and rework rate calculated consistently
  • Pareto charts prioritise defect categories by frequency, cost and risk
  • Fishbone diagrams structure potential causes using people, process, equipment and materials
  • Five Whys tests causal chains before corrective action selection
  • Failure mode and effects analysis ranks failure risks using RPN
  • Cost of quality separates prevention, appraisal, internal and external failure

Participants can select and interpret productivity, capacity and throughput measures.

  • Labour productivity ratios separate output volume, hours and skill mix
  • Overall equipment effectiveness combines availability, performance rate and quality rate
  • Capacity utilisation distinguishes designed, effective and actual operating capacity
  • Throughput accounting identifies constraints limiting system-wide productive output
  • Work sampling estimates productive, delay and support time proportions
  • Standard work establishes repeatable sequences, takt time and expected workload

Participants can distinguish normal variation from signals requiring management action.

  • Run charts reveal shifts, trends, cycles and unusual variation
  • Control charts distinguish common-cause variation from special-cause signals
  • Process capability indices Cp and Cpk compare variation with specifications
  • Histogram shapes indicate skewness, spread, clustering and possible mixed populations
  • Scatter plots test associations before claiming operational causation
  • Sampling plans balance inspection effort, risk and decision confidence

Participants can create decision-focused dashboards and performance reporting packs.

  • Dashboard design starts with decisions, users, thresholds and escalation routes
  • Visual hierarchy directs attention to exceptions, trends and material variances
  • Traffic-light rules use explicit thresholds rather than subjective status labels
  • Time-series charts retain scale consistency and clearly mark target lines
  • Drill-down paths connect executive indicators to process-level diagnostic measures
  • Monthly performance packs pair results, causes, actions, owners and due dates

Participants can select an appropriate benchmarking method for a defined performance question.

  • Benchmarking scope defines process, peer group, metrics and comparison purpose
  • Internal benchmarking identifies performance differences among sites, teams and shifts
  • Competitive benchmarking uses public disclosures, customer evidence and market intelligence
  • Functional benchmarking compares transferable processes beyond direct competitors
  • Benchmark normalisation adjusts for volume, complexity, geography and service mix
  • Data-sharing protocols protect confidentiality, definitions and comparability during exchanges

Participants can assess benchmark quality and quantify credible performance gaps.

  • Peer selection tests similarity of mandate, scale, maturity and constraints
  • Benchmark scorecards document definitions, sources, adjustments and confidence limitations
  • Percentile analysis positions local results against median and upper-quartile performance
  • Frontier analysis distinguishes attainable practice from unrealistic aspirational comparisons
  • Gap statements quantify performance shortfalls without assuming causes
  • Site-visit questions examine practices, controls, capabilities and adoption conditions

Participants can set realistic performance targets and document the assumptions behind them.

  • Target cascades translate strategic commitments into process and team milestones
  • SMART targets specify baseline, deadline, owner, measure and required improvement
  • Stretch targets tested against process capability, resources and risk exposure
  • Tolerance bands trigger review before performance breaches formal thresholds
  • Forecasting separates expected trajectory from desired target achievement
  • Target negotiations document assumptions, trade-offs and resource dependencies

Participants can turn performance gaps into prioritised improvement initiatives and verified benefits.

  • PDCA cycles connect measured gaps with tested countermeasures and review
  • A3 reports frame problem, current condition, root causes, actions and follow-up
  • Kaizen events focus improvement effort on a bounded process problem
  • DMAIC phases structure improvement from definition through control
  • Prioritisation matrices rank initiatives by impact, effort, risk and urgency
  • Benefits realisation plans assign measures, owners, checkpoints and verification dates

Participants can establish controls that retain improvement results after implementation.

  • Corrective actions distinguish containment, correction, root-cause removal and prevention
  • Control plans specify monitoring method, frequency, response and accountable owner
  • Standard operating procedures incorporate revised controls and performance checks
  • RACI matrices clarify decision rights for metric review and action closure
  • Escalation rules define response times for threshold breaches and recurring failures
  • Audit trails retain evidence supporting reported results and improvement claims

Participants can design governance routines that convert performance information into action.

  • Performance review cadences match indicator frequency, decision rights and action cycles
  • Tiered daily management connects frontline huddles with executive performance reviews
  • Meeting agendas separate signal review, diagnosis, decisions and action tracking
  • Metric owners explain variance, validate data and coordinate recovery actions
  • Countermeasure logs record commitments, status, barriers and verified results
  • Governance charters define sponsorship, challenge roles and reporting escalation

Participants can assemble the core analysis for a measurement and benchmarking project.

  • Charter a measurement and benchmarking project around a priority operating problem
  • Select outcome, driver, quality and productivity measures for the project
  • Build a metric dictionary with formulas, owners and data controls
  • Map process boundaries and identify benchmarkable performance comparison points
  • Develop baseline analysis using trends, variation and peer comparison evidence
  • Draft dashboard views, targets and an improvement action register

Participants can build, review and present a complete performance measurement and benchmarking package for a selected process.

  • Complete an end-to-end performance measurement and benchmarking package for a selected process
  • Present a metric hierarchy, data definitions and baseline performance narrative
  • Defend benchmark choices, normalisation assumptions and gap calculations
  • Show diagnostic evidence linking process causes to priority improvement actions
  • Review dashboard design, targets, governance and control arrangements
  • Receive peer and instructor challenge on feasibility, data quality and adoption

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

What you take back to work

  1. KPI hierarchy template
  2. Metric dictionary template
  3. Performance dashboard specification
  4. Benchmark scorecard and peer comparison analysis
  5. Target-setting and benefits realisation plan
  6. Performance governance and action-tracking checklist

Who should attend

  • Operations Managers — responsible for service, cost, quality and productivity results
  • Continuous Improvement Managers — need evidence to prioritise and verify improvement work
  • Quality Managers — require reliable measures for defect reduction and control planning
  • Performance Analysts — build reports, dashboards and management performance packs
  • Project Managers — track benefits, milestones and operational outcomes after delivery
  • Public Sector Service Managers — compare service performance while accounting for demand and complexity

Skills and tools covered

KPI system designBenchmarking analysisProcess performance analysisStatistical process controlDashboard reportingImprovement governance

Tools and standards

Balanced Scorecard, SIPOC, PDCA, DMAIC

How the course runs

Training methodology

The course uses short instructor briefings to introduce methods, followed by case analysis, group work, calculations, dashboard critiques and structured simulations of performance-review meetings. Cases examine operational situations such as rising defects, delayed public services, inconsistent branch productivity and equipment losses. Participants apply each method to a selected work process or a supplied case, building their measurement package in stages. Instructor feedback and peer review test metric definitions, benchmark assumptions, target logic and proposed improvement actions.

Requirements and prerequisites

Participants should have experience working with operational reports, service measures, process data or improvement initiatives. They should be comfortable reading tables, percentages, ratios and basic charts, and should understand the main activities of at least one process in their department. Experience with Excel or another spreadsheet tool is useful for interpreting examples and building draft measures. Prior statistical training, Six Sigma certification, specialist data-analysis software and prior benchmarking experience are not required. The course explains the statistical and improvement methods needed for the work.

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

Participants should be familiar with basic operational reporting and comfortable interpreting percentages, ratios and charts. Statistical training, Six Sigma certification and prior benchmarking experience are not required.

Participants should bring examples of current reports, KPI definitions, process maps or performance issues where confidentiality permits. Those without suitable material can use the supplied cases and templates.

It is designed for operations, quality, continuous improvement, service delivery, transformation and performance-reporting professionals. It is particularly useful for people who must explain why performance changed and what action should follow.

This course concentrates on building and governing performance measures, using benchmarks and turning evidence into management action. It uses selected Lean, Six Sigma and statistical methods, but does not focus on certification-level project methodology or advanced predictive analytics.

Participants develop a measurement and benchmarking package around a live operational issue or a realistic case. The templates can then be adapted for monthly reporting, improvement projects, service reviews or cross-site comparisons.

The first week builds measurement foundations, process analysis, quality and productivity metrics, statistical interpretation and dashboard design. The second week develops benchmarking, target setting, improvement control, governance and a 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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