Robert F. YostLeadership & Operations

Work samples

Examples
of the Work

Four documents I produced, with client names and internal identifiers removed. They are here because claiming a turnaround is easy and showing the analysis behind it is not. Read the reports, or read the short version below — the charts are drawn from the same data.

The five-year arc

What the data shows

Five operating periods. More than 320,000 tickets. A four-hour first-reply SLA with a 70% attainment goal that had never once been met on an annual basis — until it was.

Combined SLA attainment by year

Percent of tickets answered within 4 hours
70% target 50.1% 50.2% 54.5% 32.3% 76.3% 2021 H2 2022 2023 2024 2025

2024 was the worst year in the dataset and the forcing event for everything that followed. 2025 is the first year the target was met on an annual basis, by either team.

Average first reply

Hours
4h target 15.1 15.8 20.8 68.9 5.5 2021 H2 2022 2023 2024 2025

A 92% reduction. In 2024 the average customer service reply took nearly four days; in 2025 it took under six hours.

Tickets waiting 24h+

Combined, March–December
19,164 1,667 2024 2025

17,497 fewer customers waited more than a full day for a first reply. December 2024 alone produced more outliers than all of 2025 combined.

Documents

Redacted work samples

Client identifiers and internal references have been removed. The analysis, structure, and conclusions are unchanged.

Operational analysis  ·  Word document

Five-Year Ticket Operations Performance Review

A full retrospective on five operating periods, framed as a three-phase story: structural struggle through 2021–2023, critical failure in 2024, and the 2025 turnaround. It works through year-by-year performance, splits the analysis by team, identifies the recurring Q4 regression as the primary forward risk, and states plainly where the operation still falls short of the 85% stretch target.

I wrote it to be read by someone who would push back on it. Every claim is tied to a figure, the failure year is described without softening, and the recommendations are specific enough to be argued with.

  • PeriodH2 2021 – Dec 2025
  • Sample320,000+ tickets
  • TeamsTech Support & CSR
  • Format.docx, with figures
Download ↓

Year-over-year comparison  ·  Word document

Queue Performance Analysis: 2024 vs 2025

A tighter, decision-oriented document answering one question: did 2025 represent meaningful progress toward the SLA target? It establishes the 2024 baseline in detail — including the months where roughly 90% of replies missed the four-hour mark — then works through the 2025 results month by month for both teams.

It also names what did not work. The 85% target was reached exactly once, the Q4 regression repeated, and average reply times stayed above target in most months. A report that only reports wins is not a report.

  • ComparisonJan–Dec 2024 vs 2025
  • Headline+32pp Support, +56pp CSR
  • Outliers−88% year over year
  • Format.docx, with dashboard
Download ↓

Underlying data  ·  Excel workbook

Ticket Performance Dataset, 2021–2025

The workbook the two reports are built from: monthly volume, SLA attainment, average first reply, no-reply rates, and 24-hour-plus outlier counts for both teams across the full period.

This is the part of the job most people skip. The reports are readable because the data underneath them was cleaned, reconciled across two ticketing platforms, and structured before anyone tried to draw a conclusion from it.

  • Range2021 – 2025, monthly
  • MetricsVolume, SLA, FRT, outliers
  • Format.xlsx
Download ↓

Academic writing  ·  Word document

Generative AI — Technology Case Study

A case study written during my Business Administration degree, examining generative AI’s productivity impact, the technology behind it, and where it sits on the innovation S-curve. It argues the foundational innovation has already spiked and the field is approaching maturation, and it is candid about the limits: computational cost, shallow understanding, and the gap between pattern-matching and creativity.

Included as a writing sample rather than a technical one. It shows how I structure an argument when I am not the subject of it.

  • ContextBA coursework, ODU
  • ScopeTechnology & innovation analysis
  • Format.docx
Download ↓

Also built

Tools, not just reports

Internal tooling

Leadership portal

A single web-based portal consolidating every scattered leadership tool — coaching, reviews, reporting, reference material — into one interface. Built and maintained without a development team.

Reporting

Queue health dashboard

An interactive dashboard with trend visualization, built so a supervisor can see what needs attention in under five minutes rather than reading a spreadsheet.

Performance

Agent metrics tracker

Scores and ranks productivity across the team, turning coaching conversations from impressions into evidence.

Development

Peer-led gap training

A program in which team members identify their own skill gaps, lead topic-focused sessions, and document what they learn in a shared knowledge repository.