Service Improvement and Innovation Training Course

Participants can convert customer evidence and demand patterns into prioritised service requirements.

• Voice of the customer sources: complaints, surveys, calls and observations
• Customer journey evidence separated from internal assumptions and anecdotal feedback
• Kano model classifying basic, performance and attractive service requirements
• Demand analysis distinguishing value demand, failure demand and unwanted demand
• Segmentation by customer type, channel, urgency and transaction complexity
• Translating customer needs into service standards and measurable CTQs

Participants can map an end-to-end service process and expose handoffs, delays and ownership gaps.

• SIPOC diagrams defining suppliers, inputs, process boundaries, outputs and customers
• Swimlane maps revealing handoffs, decisions, queues and role responsibilities
• Value-stream maps measuring touch time, waiting time and rework loops
• Service blueprints connecting customer actions, frontstage work and backstage processes
• Decision rules documented at approval points and exception pathways
• Process boundaries agreed before collecting performance and cost data

Participants can establish a reliable baseline for service quality, speed, capacity and cost.

• Balanced service measures covering quality, time, cost, demand and customer experience
• First-time-right rates calculated from completed transactions and error records
• Cycle time, lead time and queue time distinguished precisely
• Capacity analysis comparing workload, available hours and productive time
• Service-level agreements translated into operational performance measures
• Run charts displaying baseline variation, trends and unusual performance patterns

Participants can identify waste and flow constraints within a mapped service process.

• TIMWOODS waste categories interpreted for administrative and customer service processes
• Waiting caused by batching, approvals, handoffs and incomplete information
• Rework loops traced from defects, unclear requests and weak decision rules
• Overprocessing identified through duplicate entry, unnecessary checks and reporting
• Work-in-progress limits used to expose overload and stalled cases
• Little's Law relating queue size, throughput and lead time

Participants can create an evidence-based charter for a focused service improvement project.

• DMAIC phases matched to service improvement project decisions
• Project charters defining problem, goal, scope, team and business case
• SMART targets expressed through measurable quality, time and productivity outcomes
• Baseline data plans specifying measures, sources, frequency and ownership
• In-scope and out-of-scope boundaries preventing uncontrolled project expansion
• Benefits registers separating cashable, capacity, risk and customer benefits

Participants can test likely causes of service performance problems using structured analysis.

• Pareto charts identifying high-frequency defects, delays and complaint categories
• Fishbone diagrams organising causes across people, process, technology and policy
• Five whys applied to evidence rather than untested assumptions
• Stratification by channel, team, customer group, product and case type
• Scatter plots testing relationships between workload, complexity and completion time
• Cause-and-effect matrices ranking suspected causes against customer requirements

Participants can develop practical solutions that address validated causes and service requirements.

• Countermeasures matched directly to validated root causes and control points
• Brainstorming rules separating idea generation from option evaluation
• TRIZ contradiction thinking applied to conflicting service performance requirements
• Mistake-proofing methods preventing incomplete forms, omissions and incorrect routing
• Simplification opportunities removing low-value approvals, checks and duplicate requests
• Future-state maps showing redesigned flow, roles, measures and customer touchpoints

Participants can select improvement actions using transparent value, effort, risk and feasibility criteria.

• Impact-effort matrices comparing expected benefit against implementation difficulty
• Weighted decision matrices scoring customer value, cost, risk and feasibility
• Cost-of-poor-quality estimates covering rework, complaints, delay and escalation
• Benefit hypotheses linked to baseline measures and expected performance changes
• Assumptions registers documenting data limitations, dependencies and unresolved questions
• Business cases presenting options, recommendations, costs, benefits and risks

Participants can design service innovations that respond to defined user needs and operating constraints.

• Jobs to Be Done identifying customer progress, barriers and desired outcomes
• Value proposition canvases matching service features to customer pains
• Design thinking stages used to frame, test and refine service concepts
• Service blueprint redesign identifying new channels, roles and support processes
• Channel-shift analysis assessing digital, assisted and self-service options
• Innovation assumptions tested against customer value, feasibility and viability

Participants can specify standard work that improves consistency without blocking justified exceptions.

• Standard work sheets defining sequence, timing, quality checks and escalation
• Visual work instructions reducing variation in recurring service transactions
• Checklists designed for high-risk handoffs, approvals and customer communications
• Poka-yoke controls preventing incorrect data entry and missed mandatory fields
• Exception pathways distinguishing legitimate variation from process non-compliance
• RACI matrices clarifying accountabilities for redesigned service activities

Participants can design daily management controls for service flow, workload and priorities.

• Kanban boards visualising workflow stages, blockers, ownership and ageing
• Pull systems releasing work according to downstream capacity and priorities
• Daily huddles reviewing safety, quality, delivery, cost and people measures
• Escalation triggers defined for breached service levels and ageing cases
• Workload balancing using skills matrices, demand forecasts and queue data
• Visual management boards linking local actions to improvement targets

Participants can distinguish normal variation from signals requiring service management action.

• Common-cause and special-cause variation distinguished using operational examples
• Control charts selecting appropriate measures for counts, proportions and times
• Process capability assessed against customer requirements and service-level targets
• Sampling plans balancing data quality, effort and decision risk
• Measurement-system checks testing consistency between reviewers and data sources
• Management responses matched to signals rather than single-point reactions

Participants can plan controlled pilots that test improvements before wider implementation.

• Pilot charters defining hypothesis, scope, participants, duration and decision criteria
• A/B testing principles applied to customer communications and service options
• Before-and-after measures selected for quality, speed, demand and satisfaction
• Pilot risk registers covering customer impact, compliance and operational disruption
• Feedback loops collecting frontline observations and customer response data
• Decision gates determining stop, adapt, extend or scale outcomes

Participants can plan adoption activities that address resistance, capability and stakeholder needs.

• Stakeholder analysis mapping influence, impact, concerns and engagement actions
• ADKAR model applied to awareness, desire, knowledge, ability and reinforcement
• Change impact assessments identifying altered roles, controls, skills and workloads
• Communication plans matching messages, channels, timing and accountable owners
• Training needs analyses defining capability gaps for redesigned service processes
• Resistance logs converting objections into risks, questions and response actions

Participants can prepare an implementation plan with clear controls, ownership and review routines.

• Implementation roadmaps sequencing quick wins, pilots, dependencies and scale-up actions
• RAID logs tracking risks, assumptions, issues and dependencies
• Governance structures defining sponsor decisions, project roles and escalation routes
• Benefits-realisation plans assigning measures, owners, review dates and evidence
• Control plans specifying process checks, thresholds and corrective actions
• PDCA cycles establishing regular review, learning and adjustment routines

Participants can establish routines that maintain gains and identify further improvement opportunities.

• Control plans linking critical measures to owners and response actions
• Layered process audits checking adherence to standard work and controls
• Monthly performance reviews analysing trends, exceptions, benefits and priorities
• Knowledge capture documenting revised procedures, lessons and reusable countermeasures
• Improvement backlogs managing future opportunities, evidence and prioritisation decisions
• Recognition mechanisms reinforcing desired service behaviours and local ownership

Participants can build, review and present a complete Service Improvement and Innovation Plan for a selected service process.

• Project charter, customer requirements and baseline assembled into one proposal
• Current-state maps supported by demand, quality, flow and capacity evidence
• Root-cause findings linked directly to prioritised improvement and innovation actions
• Future-state service blueprint defining processes, roles, channels and controls
• Pilot, implementation and benefits plans tested through structured peer review
• Executive presentation communicating recommendation, evidence, risks and expected results