In utility field service, the customer does not experience a process map. They experience minutes without electricity or water.
Every minute spent waiting for fault categorisation, switching authority, crew allocation, travel, parts, repair or closure contributes to customer minutes lost. Value Stream Mapping (VSM) makes that end-to-end flow visible. It connects information, people, vehicles, materials and decisions from the initial outage call to supply restoration and job closeout.
This worked example uses an illustrative dataset for residential and small commercial unplanned outages on a low-voltage network. The average restoration time is 178 minutes, although only 41 minutes represent true field work. The remaining time is consumed by queues, coordination, travel, rework and administrative processing.
The objective is not simply to make crews work faster. It is to design a more reliable value stream that restores supply safely, correctly and predictably.
Define the Utility Field Service Value Stream
Scope boundary
The value stream begins when the utility receives a customer fault call or outage notification and ends when:
- Supply is restored and verified.
- The permanent repair or approved temporary solution is recorded.
- The customer receives an accurate update.
- The job is closed in the operational systems.
The work type in scope is:
- Residential and small commercial unplanned outages.
- Low-voltage network faults.
- Normal operating conditions, excluding major storm restoration.
- Jobs requiring a field crew, remote switching or both.
Customer definition of value
The Voice of the Customer is straightforward:
- Safe supply restored quickly.
- Correct repair on the first visit.
- Accurate estimated restoration information.
- No need to repeat the fault report.
- Clear confirmation when the service is stable.
The Voice of the Business adds network safety, regulatory compliance, workforce utilisation, cost per job and asset reliability. The Voice of the Process comes from actual timestamps, queue lengths, travel records and repair outcomes.
For this example, the service-level driver is a customer minutes lost target of 4.5 minutes per interruption, supported by a guaranteed service-level payment scheme when restoration performance exceeds the agreed threshold.
Build the Current-State Map
A practical workshop should include the control room, customer contact centre, dispatch, network operations, field crews, stores, safety and customer communications.
The map below shows the average values across 18,000 annual outage jobs.
Current-state step-by-step walk
| Process step | Touch time | Waiting time | What happens |
|---|---|---|---|
| Call intake and fault categorisation | 8 min | 0 min | Customer call, outage notification, location validation and priority code |
| Remote network checks and switching | 10 min | 4 min | OMS, SCADA and network diagram checks; remote switching where available |
| Crew allocation and dispatch | 7 min | 38 min | Crew selection, approval, briefing and dispatch queue |
| Travel to site | 28 min | 0 min | Crew travels to the address, often across zone boundaries |
| Site safety and isolation | 9 min | 8 min | Site assessment, isolation, permits and switching authority |
| Fault location | 10 min | 3 min | Inspection, testing and asset identification |
| Repair or partial restoration by switching | 12 min | 0 min | Temporary restoration or switching to restore supply |
| Permanent repair | 10 min | 12 min | Repair, replacement, testing and final verification |
| Notify and close | 4 min | 9 min | OMS, CRM and customer communication updates |
| Customer follow-up if no supply | 0 min | 6 min | Weighted average for jobs requiring additional confirmation |
| Total | 98 min | 80 min | 178 minutes elapsed |
The 41 minutes of true field work comprise:
- Site safety and isolation: 9 minutes.
- Fault location: 10 minutes.
- Repair or partial restoration: 12 minutes.
- Permanent repair: 10 minutes.
Worked PCE calculation
Process Cycle Efficiency (PCE) shows how much of the elapsed time is value-adding work:
[
PCE = \frac{Value\ Added\ Time}{Total\ Lead\ Time} \times 100
]
[
PCE = \frac{41}{178} \times 100 = 23.0%
]
The current state therefore has a 23.0% PCE. This does not mean the other 77% is unnecessary in every case. Safety checks and technical approvals remain essential. However, the map identifies where the operating model can remove avoidable waiting, repeated information entry and preventable travel.
Current performance is:
- First-time-fix rate: 82%.
- Second-visit rate: 12%.
- Repeat-fault rate within 30 days: 6.4%.
- Average customer minutes lost: 6.4 minutes.
- Jobs per crew per day: 3.1.
- Travel share of crew time: 34%.
Customer minutes lost example
Single interruption: 240 customers lose supply for 16 minutes.
[
240 \times 16 = 3,840 \text{ customer minutes lost}
]Annual baseline: 18,000 interruptions at an average of 6.4 minutes lost.
[
18,000 \times 6.4 = 115,200 \text{ annual customer minutes lost}
]
The operational benefit of reducing dispatch queues is therefore also a customer-experience benefit.
Identify the Eight DOWNTIME Wastes
The eight DOWNTIME wastes appear differently in a network service environment.
| Waste | Utility field service example | Quantified impact |
|---|---|---|
| Defects | Incorrect asset details, incomplete job notes or wrong parts cause repeat work | 12% of jobs require a second visit; approximately 2,160 jobs annually |
| Overproduction | Duplicate outage records, repeated status reports and premature job documentation | 6 minutes of duplicate administration per job; 1,800 annual labour hours |
| Waiting | Crews wait for switching authority, dispatch approval or customer confirmation | 80 minutes of combined waiting per job; 24,000 annual labour hours |
| Non-utilisation of talent | Skilled coordinators spend time chasing missing information instead of managing flow | Approximately 25% of coordination capacity absorbed by follow-up |
| Transportation | Crews travel across zones because work is not dynamically sequenced | 28 travel minutes per job; 8,400 annual travel hours |
| Inventory | Excess consumables and rarely used parts remain in vehicle stock | Approximately $27,000 tied up across 32 vehicles |
| Motion | Technicians search for tools, diagrams, paperwork and parts in poorly standardised vehicles | 11 minutes per job; 3,300 annual labour hours |
| Extra processing | Data is entered into mobile forms, OMS, CRM and spreadsheets more than once | 10 minutes of avoidable processing per job; 3,000 annual labour hours |
These figures are not simply a list of symptoms. They show where the current value stream is consuming capacity without improving restoration quality.
Use the Right Analysis Tools
A strong VSM workshop combines observation with data.
- An Affinity Diagram groups large volumes of crew, dispatcher and customer ideas into natural categories such as dispatch, information quality, travel, materials and safety.
- The Analyse Phase of DMAIC uses Pareto charts, process stratification, cause-and-effect diagrams and statistical tests to identify root causes.
- Attribute data, such as Pass/Fail switching plans or First-Time-Fix/Repeat Visit, supports quality analysis.
- ANOVA can compare restoration means across three or more zones, while Bartlett’s Test checks whether group variances are sufficiently equal before ANOVA.
- A Box Plot reveals the median, quartiles, skewness and extreme outage durations.
- A Z-score allows a 420-minute outage to be compared with distributions from different zones or job types.
- Measurement bias must be checked because inconsistent timestamp definitions can make one depot appear faster than another.
- An X-bar chart with an R chart can monitor average restoration time and variation after implementation.
- Yield should include First Pass Yield and Rolled Throughput Yield, not only the number of jobs closed.
- The relationship Y = f(x) reminds the team that restoration time is the outcome influenced by inputs such as dispatch queue, switching readiness, travel distance, parts availability and crew capability.
Agile methods complement Lean Six Sigma here. The future state can be piloted in short iterations, reviewed weekly and adjusted using evidence rather than waiting for a large technology release.
Design the Future State
The future-state map should remove avoidable delay while preserving network safety and regulatory control.
Future-state kaizen bursts
-
Remote switching before dispatch
Complete approved remote checks and switching before a crew is assigned wherever network conditions allow. -
Dynamic scheduling and zone-based dispatch
Assign work using location, skill, vehicle capability, traffic, switching status and customer priority. Keep crews within defined zones unless the constraint requires cross-zone support. -
Standard job kits and truck-stock levelling
Create standard kits for the most common low-voltage faults. Use minimum and maximum stock levels rather than identical overstocking in every vehicle. -
Pre-approved switching plans
Prepare standard plans for the highest-volume fault categories. The control room retains authority, while routine decisions are made from validated templates. -
First-time-fix checklists
Confirm asset data, fault history, required tools, parts, isolation steps and restoration tests before dispatch. -
Mobile data capture
Enter information once at the point of work. Automatically pass verified data to OMS, CRM and customer notification workflows. -
Depot performance boards
Review restoration time, customer minutes lost, dispatch queue, first-time-fix, repeat visits and jobs per crew each day.
The mapping work can be run digitally in Ci Flow, which provides value stream mapping, process mapping, tool outputs, evidence-based analysis, actions and portfolio governance in one workspace. Ci Flow is a separate operational-excellence product from SigmaFlow. It is designed to connect the project record to the evidence used in the improvement decision.
Current State Versus Future State
| Metric | Current state | 90-day future-state target | Improvement |
|---|---|---|---|
| Average restoration time | 178 min | 112 min | 37% reduction |
| Value-added time | 41 min | 41 min | Preserved |
| Total process time | 98 min | 75 min | 23% reduction |
| Waiting time | 80 min | 37 min | 54% reduction |
| PCE | 23.0% | 36.6% | +13.6 percentage points |
| Customer minutes lost | 6.4 | 4.2 | 34% reduction |
| First-time-fix rate | 82% | 94% | +12 percentage points |
| Repeat visits | 12% | 5% | 7 percentage-point reduction |
| Travel share of crew day | 34% | 23% | 11 percentage-point reduction |
| Jobs per crew per day | 3.1 | 4.2 | 35% increase |
| Cost per job | $486 | $408 | 16% reduction |
The future state retains 41 minutes of field value-added activity but reduces the total elapsed time to 112 minutes by removing queues and reducing avoidable processing.
The business case is also measurable. At $78 saved per job across 18,000 annual jobs, the annualised benefit is approximately $1.404 million before implementation costs. If the programme requires $150,000 in technology, training and standardisation investment, the simple break-even point is approximately 1.3 months of annualised benefit.
30/60/90-Day Kaizen Sequence
Days 0–30: Establish the baseline
Owners: Continuous Improvement Lead, Outage Control Manager, Field Service Manager
Milestones:
- Map 50 representative outage jobs.
- Confirm timestamp definitions and measurement bias.
- Establish the 178-minute baseline.
- Pilot pre-approved switching plans for three common fault types.
- Create a depot board showing dispatch queue, restoration time and first-time-fix.
- Build the current-state map in Ci Flow.
Days 31–60: Pilot the flow
Owners: Dispatch Manager, Network Operations Manager, Fleet and Stores Manager
Milestones:
- Launch zone-based dynamic scheduling in one service area.
- Introduce standard job kits on 10 vehicles.
- Pilot first-time-fix checklists.
- Implement mobile capture for safety, repair and closure information.
- Target 135-minute restoration, 5.2 customer minutes lost, 89% first-time-fix, 8% repeat visits, 28% travel share and 3.6 jobs per crew per day.
Days 61–90: Control and scale
Owners: Operations Manager, Customer Operations Manager, Network Planning Manager
Milestones:
- Extend the future-state design across all low-voltage outage crews.
- Review weekly X-bar and R charts for restoration time.
- Use ANOVA to compare zone performance.
- Introduce Andon-style visual signalling when a job exceeds its queue or safety threshold.
- Apply autonomation, or Jidoka, by triggering an exception response when incomplete data, unsafe conditions or abnormal network states are detected.
- Confirm final targets of 112-minute restoration, 4.2 customer minutes lost, 94% first-time-fix, 5% repeat visits, 23% travel share and 4.2 jobs per crew per day.
Governance Without Creating Another Bottleneck
Approval is valuable when it protects safety, compliance and investment discipline. It becomes a bottleneck when every routine switching plan, vehicle stock change or dispatch decision requires the same approval path.
Use a tiered governance model:
- Pre-approved standards for routine, low-risk fault categories.
- Supervisor approval for exceptions within defined limits.
- Network control approval for switching, isolation and safety-critical decisions.
- Leadership tollgates for investment, service-level and portfolio decisions.
A Business Case should connect the problem to customer minutes lost, cost per job, capacity, risk and regulatory performance. Break-Even Analysis then identifies the point where the cumulative benefits equal the improvement investment.
Zero Defects is a useful aspiration for job information, switching documentation and safety-critical work: do it right the first time, while recognising that network conditions will always create some variation.
White Belt practitioners can support basic awareness. Yellow Belts can collect data and facilitate local improvements. Green Belts can lead the VSM project, while a Black Belt can manage the statistical analysis, coach Green Belts and connect the work to enterprise capability.
Make the Next Dispatch Better Than the Last
A utility field service VSM should end with ownership, not simply a finished diagram. Walk the process, validate the numbers with crews, separate value-added work from waiting, and sequence kaizen around the constraints that affect customer minutes lost.
The most important question is not, “How can each department work harder?”
It is:
“What must change across the entire value stream so the right crew, information, authority and parts arrive together?”
For practitioners ready to lead this type of improvement, explore CSSC-accredited Lean Six Sigma online training. The Lean Six Sigma Green Belt course develops the skills to lead data-driven projects, while Lean Six Sigma Black Belt online training prepares experienced professionals to lead complex transformations and mentor improvement teams.
Pursue Lean Six Sigma certification and build the capability to turn service delays into measurable customer value.
Kaizen. Kai-Care. Kai-Done. Lean Six Sigma
