Yeshwant Naik
Sample audit

Sample audit: field sales team at a dealer-services company

An illustrative example based on a real engagement. Names and figures are changed.

This is the kind of report the Operations & AI audit ends with. It says where time and money go today, which fixes are worth doing, in what order, and what to leave alone.

The short version

The team sells finance and insurance products to car dealerships. Reps spend their days on the road, and every visit has to be logged through a long form on a phone.

So visits get logged late, from memory, or not at all. Managers can't see what's open, promises to dealers slip, and reps prepare for each visit by digging through old entries.

The biggest win is not AI. It's a shorter form. After that, summaries and briefs written by AI save the most time, and voice is worth a field test once the basics work.

01 · What we looked at

Scope, people and systems

Scope

  • How a dealer visit is booked, recorded and followed up, from the calendar invite to the next visit
  • How managers see what the team is doing
  • Out of scope: commissions, product pricing and dealer onboarding

People interviewed

  • Four field reps, from new starters to the longest-serving
  • Two regional sales managers
  • The sales director
  • The person who looks after the CRM
  • Plus a day riding along on dealer visits

Systems

  • The team's own field-sales CRM, running on AWS
  • Outlook, for booking visits
  • A weekly spreadsheet the managers build by hand
  • A sample of recent visit records
02 · Where time and money leak

What we found

Impact figures are rough estimates from interviews and the record sample. They show scale, not a promise.

  1. Finding 1

    The visit form is too long for a phone

    Over twenty fields per visit, including five goal dropdowns. Reps fill it in between dealers or at night, from memory. Managers only use about eight of the fields.

    ~3 hours per rep per week on visit admin

  2. Finding 2

    Many visits are never logged

    When the day runs long, the form is the first thing to go. In the sample, a large share of visits had no record, or one added days later.

    Roughly 1 in 4 visits missing or late

  3. Finding 3

    Goal statuses are out of date

    Goals only change when a rep remembers to update them. Managers can't tell what is really open, so they ask in calls and messages instead.

    ~half a day per manager per week chasing updates

  4. Finding 4

    Promises to dealers get lost

    Follow-ups agreed in the meeting live in the rep's head or a notebook. Some never happen, and dealers notice.

    Several dropped follow-ups per rep per month

  5. Finding 5

    Prep means digging through old entries

    Before each visit, reps scroll back through past records to work out what was said and what is still open.

    ~15 minutes of prep per visit

  6. Finding 6

    Visits are booked twice

    Visits are booked in Outlook, then entered again in the CRM. The two drift apart, and the manager's view is only as good as the CRM side.

    ~1 hour per rep per week, plus missed clashes

03 · Ranked fixes

What to fix, in what order

Ranked by impact against effort. Each fix is labelled with the kind of work it needs, because not all of it is AI.

  1. Order: 1Process change
    Cut the visit form to the fields people actually use

    Agree the short list with managers. Everything else becomes optional or goes.

    Impact
    High
    Effort
    Low
  2. Order: 2Custom build
    A phone-first visit screen on the existing CRM

    Big buttons, one hand, saves as you go. Same data underneath.

    Impact
    Medium
    Effort
    Medium
  3. Order: 3Integration
    Book visits in the CRM and send them to Outlook

    One place to book. Calendars stay in sync and clashes show up.

    Impact
    Medium
    Effort
    Low
  4. Order: 4AI agent
    Automatic visit summary and a brief before the next visit

    AI writes what was covered and agreed, then pulls open goals and promises into a short brief.

    Impact
    High
    Effort
    Medium
  5. Order: 5Automation
    Weekly manager summary and a needs-attention list

    Replaces the hand-built spreadsheet. Visits with no record stand out.

    Impact
    Medium
    Effort
    Low
  6. Order: 6AI agent
    Voice debrief that drafts the record and suggests goal updates

    Reps talk it through in the car. Nothing is saved until they confirm. Field test first.

    Impact
    High
    Effort
    High
  7. Order: Not recommendedLeave it alone
    Replace the CRM with an off-the-shelf sales tool

    It would mean moving every record and retraining the team, to fix problems the steps above already solve.

    Impact
    Low
    Effort
    High
04 · Recommended roadmap

Three phases, each useful on its own

You can stop after any phase and keep what it delivered.

  1. Phase 1

    Make the record easy

    • Shorter visit form, agreed with managers
    • Phone-first visit screen
    • Booking in the CRM, synced to Outlook

    Delivers: Every visit is booked and logged in one place, on the phone, the same day.

  2. Phase 2

    Let the record do the work

    • Automatic summary of every visit
    • A brief before the next visit
    • Weekly manager summary and needs-attention list

    Delivers: Reps walk in prepared. Managers see what's open without chasing anyone.

  3. Phase 3

    Test voice, then decide

    • Voice debrief with a few reps on real visits
    • Suggested goal updates and follow-ups, each one confirmed by the rep
    • Roll out only if the field test shows it saves time

    Delivers: A clear yes or no on voice, based on real visits rather than a demo.

05 · What we'd leave alone

Not everything needs fixing

The CRM itself
It holds years of dealer history, the team knows it, and it can be extended. Replacing it would cost more than the problems it causes.
Outlook for everything else
Reps keep their email and calendar as they are. Only visit booking moves.
Emails to dealers
Dealers value the personal relationship. AI can draft a follow-up, but the rep sends it. Nothing goes out automatically.
AI that predicts which dealers to visit
Tempting, but the visit records aren't reliable enough yet to learn from. Worth a look once Phases 1 and 2 have been running a while.
See what got built from a roadmap like this →

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