HTS Field Services — Service Operations Dashboard

Executive Summary

Service health, scheduling performance, quality, and financial snapshot.

New vs Closed — Monthly Trend

Teal bars = new tickets created · Blue bars = tickets closed · last 16 months

⠿

Status Distribution

Count and share of all tickets by service status · hover a segment for detail

⠿

Monthly Volume

Count of new service tickets created each month · teal bars

⠿

Financial Type Mix

Share of tickets by category · Billable = revenue · Warranty = rework · SSC = support contract · Internal = no customer charge

⠿

Volume & Status

Scheduling

Operations

Backlog health, scheduling, bottlenecks, aging, and open ticket drill-down.

Status Counts

Performance

All Service Statuses

Every status including zero-count

⠿

Open Backlog by Status

Where active tickets sit

⠿

Open Ticket Aging

How long currently open tickets have been waiting · each bucket shows count and % of open total

⠿

Service Bottleneck

Average days an open ticket remains in each status before moving forward · longer bars = longer delays

⠿

Days to First Scheduled Visit — Distribution

Count of tickets by how many days elapsed from ticket creation to the first scheduled visit date

⠿

New vs Closed Monthly

Teal = new tickets created · Blue = tickets closed each month

⠿

Open Ticket Drill-Down

Sorted by days old

⠿

SO#	Created	Customer	State	Fin. Type	Status	Days Old	Days to Sched.	Supervisor

Customer Impact

Volume, revenue, open exposure, warranty burden, and scheduling by customer.

Top 15 Customers by Ticket Volume

Count of all tickets (open + closed, all types) per customer · highest-volume customers first

⠿

Open Tickets by Customer

Count of currently open tickets per customer · highest open-ticket exposure first

⠿

Top 10 Customers by Billable Revenue

Total billable revenue billed to each customer · excludes Warranty, SSC, and Internal tickets

⠿

Slowest Average Time to Close

Average days from ticket creation to close for each customer · color = urgency (green <45d, yellow 45–90d, red >90d)

⠿

Financial Type Mix

Billable / Warranty / SSC

⠿

Market Vertical Distribution

Count of tickets by customer vertical segment · shows which industries drive the most service activity

⠿

Customer Detail Table

Click headers to sort

⠿

Customer	Tickets	Open	Revenue	Avg TTC	Avg DTS	Warranty	SSC	Warr. Risk %

Financials

Billable = customer revenue. Est. Internal Cost = hours × $75/hr.

Revenue by Financial Type

Total dollar revenue per category · only Billable generates customer revenue · others are cost centers

⠿

Est. Delivery Cost

Estimated HTS internal expense by ticket type · (labor hours + travel hours) × $75/hr rate

⠿

Labor vs Travel — Actual Charges

Total dollar value of labor hours charged vs. travel hours charged · billed to customer or tracked internally

⠿

Revenue by State — Top 12

Total dollar revenue across all financial types per state · top 12 revenue-generating states

⠿

Financial KPIs

Financial Type Summary

Revenue, profit, cost, hours by category

⠿

Type	Tickets	Revenue	Gross Profit	GP %	Est. Cost	Labor hrs	Travel hrs

ⓘ Est. Internal Cost: (labor hours + travel hours) × $75/hr — represents HTS operational expense, not a cash transaction. ⓘ Labor/Travel Charged: dollar value of hours billed to the customer or tracked internally on the ticket. ⓘ Billable Revenue: actual customer invoice value. Only Billable-type tickets generate revenue.

Team Performance

Supervisors with 25+ tickets.

Ticket Volume by Supervisor

Total tickets ever assigned to each supervisor · only supervisors with 25+ tickets shown

⠿

Avg Time to Close by Supervisor

Average days from ticket creation to close · green = under 45d · yellow = 45–90d · red = over 90d

⠿

Avg Days to First Scheduled Visit

Average days from ticket creation to first visit date per supervisor · green ≤5d · blue ≤10d · yellow ≤20d · red >20d

⠿

First-Time Fix Rate by Supervisor

% of field visits that resolved the ticket on the first attempt · only supervisors with 3+ FTF-tracked tickets shown

⠿

Warranty Return Trips by Supervisor

Count of warranty tickets per supervisor (return visits to fix unresolved issues) · bar label shows count and % of their total tickets · red >20% · yellow 10–20% · green <10%

⠿

Supervisor KPIs

Warranty Return Trips

Supervisor Detail

Efficiency = FTF(50pts)+TTC speed(50pts)

⠿

Supervisor	Tickets	Open	Avg TTC	Median TTC	Avg DTS	FTF Rate	Labor hrs	Warranty	Eff. Score

Business Case for Growth

Performance since April 2025 · staffing gap · path to 10-business-day TTC.

Your Impact Since April 2025

Gap to Goal & Capacity

Median TTC by Month

Since takeover · dashed = 14-day goal

⠿

TTC Decomposition

Scheduling wait vs. work/close time

⠿

State Hiring Priority

Priority Ranking

Post April 2025 · 🔴>65 · 🟡36–65 · 🔵16–35 · 🟢≤15

⠿

How this score is calculated: Each state gets a raw score = Tickets per Month × Avg Days to First Scheduled Visit × Avg Time to Close. The highest-scoring state becomes 100 and all others scale proportionally.

This captures three compounding pressures at once: Volume (how many tickets need coverage), Scheduling Gap (how long customers wait for a visit — the main bottleneck), and Close Time (how slowly work is actually finishing). A state that scores high on all three is where adding a local technician would have the biggest immediate impact.

Reading the table: Tix/Mo = new tickets per month since April 2025 · Avg TTC = average days from ticket creation to close · Avg DTS = average days from creation to first scheduled visit · Supervisors = distinct supervisors who have touched tickets in this state · % ≤14 Days = share of tickets that closed within the 14-calendar-day goal.

Supervisor Throughput

Tickets closed/month since April 2025

⠿

Recommended Hires

Based on volume, DTS, TTC by state

⠿

Visits & Field Activity

Visit counts from First Time Fix (XLSX) and Technician(s) field. 939 of 1,144 tickets have no FTF data.

Visit Summary KPIs

Visit Distribution

Based on First Time Fix field

⠿

Team Size per Visit

Technicians per ticket

⠿

TTC: 1 Visit vs 2+ Visits

Cost of a return trip in days

⠿

Multi-Visit by State

FTF=No tickets

⠿

Multi-Visit by Type

FTF=No by financial type

⠿

Multi-Visit by Supervisor

FTF=No per supervisor

⠿

Ticket Visit Detail

Tickets with FTF or tech data · first 100

⠿

SO#	Customer	State	Fin. Type	Visits	Team Size	TTC	Supervisor

Visits: 1=FTF=Yes, 2+=FTF=No, —=not tracked. Team Size = names in Technician(s) field.