Will dispatchers feel surveilled?

The scorecard is visible to the dispatcher and the manager — same as any sales-team scorecard. Most dispatchers actually like the data because it surfaces what they were doing well on top of where they could improve. The framing is coaching, not policing — and the playbooks make that explicit.

How is retention risk calculated?

Composite of mileage trend, income trend, HOS pattern shift, communication frequency, safety event count, and home-time satisfaction. Each signal is normalized against the driver's own historical baseline (not the fleet) so individual variation doesn't get smoothed away. Calibrated quarterly against actual quit data.

What if the system is wrong about why a metric moved?

The attribution shows its inputs, so the manager can sanity-check the recommendation before acting. When the manager logs a different cause, the model learns from that label and improves. Wrong attributions tend to drop fast — within 60 days the recommendations are calibrated to the carrier's reality.

Can drivers see the same data?

Drivers see their own scorecard via the Telegram bot in their language: RPM, miles, OTD, fuel MPG, HOS, current-period earnings. They don't see other drivers' data. The transparency reduces driver anxiety about performance reviews because nothing is hidden.

How does this affect comp plans?

Centrix doesn't push a comp plan, but most carriers move from revenue-based dispatcher pay to scorecard-based pay (RPM, margin, OTD, deadhead %, detention recovery) within 90 days. The data the scorecard needs is already collected; you choose how — or whether — to tie pay to it.

Driver and Dispatcher Performance Reports That Don't Just Score You — They Tell You What to Do Today

The performance report nobody opens

Every TMS produces driver and dispatcher reports. RPM by driver, miles by dispatcher, OTD percentages, fuel economy. The reports are accurate. They're also dead. They tell the manager what happened last month in numbers nobody can act on right now.

The actual question — what should I do today to improve performance? — is rarely answered by these reports. The data is there. The recommendation isn't.

Centrix's performance layer treats the data the same way but treats the output completely differently. Reports become a daily prioritized action list:

> Today: call driver Smith (mileage trend down 18%, retention risk score 71). > Push lane Houston→Dallas (RPM +12% vs 30-day average). Coach dispatcher Jones > (margin per load down $0.08 from cohort median).

Same data. Different output. Wildly different impact.

Per-driver performance — what's tracked

Every active driver, computed daily from the integration databases (Alvys, Samsara, Ensilog, Shopmonkey, Tenstreet):

Revenue per mile — net of deadhead
Total miles — 7-day, 30-day, 90-day rolling
On-time delivery percentage
Fuel economy (MPG) — vs the truck's baseline and the fleet's median
HOS compliance — violations, falsifications, adverse-driving claims
Safety score — composite from the driver-safety model
Pre-trip compliance — structured checklist completion via Telegram bot
Earnings projection — current period vs prior 3 periods
Retention risk score — quit-likelihood from the wellness model
Home-time satisfaction — actual vs requested home time variance

These are presented per driver in three views:

Driver scorecard — visible to the driver via the Telegram bot in their language
Manager scorecard — visible to the dispatcher / fleet manager
Aggregate reports — visible to the admin / CEO

Per-dispatcher performance — what's tracked

Every dispatcher gets a 30-day rolling scorecard:

Margin per load — revenue minus deadhead minus driver pay
Lane mix — high-RPM vs low-RPM lanes booked
Deadhead percentage — empty miles / total miles
OTD percentage — across their bookings
Detention recovery rate — billed / earned
Driver retention rate — drivers in their book who quit vs stayed
Booking volume — loads per week
Customer satisfaction — feedback on their handling

The dispatcher sees their own scorecard. The fleet manager sees the team. Comp plans tied to the scorecard reward profitable booking, not just volume.

The daily advice — what the system tells you to do today

This is the differentiator. Every morning, the dispatcher / fleet manager / CEO gets a prioritized to-do list:

"Call these drivers today"

Sorted by retention risk + actionability. Each entry includes:

Driver name + tenure
Current trend (mileage down, earnings down, etc.)
Suspected cause (home-time gap, equipment issue, dispatcher friction)
Recommended conversation angle
Last time anyone talked to them

"Push these lanes today"

Lanes with above-baseline RPM + truck availability:

Lane name + recent average RPM
Why it's hot today (market shift, customer demand spike)
Trucks that can reach the lane within HOS
Recommended counter rate

"Coach these dispatchers today"

Dispatchers tracking below cohort median on specific dimensions:

Dispatcher name
Specific gap (margin, deadhead, OTD)
Likely contributing pattern (lane mix, customer mix, negotiation style)
Specific coaching script

"Watch these customers today"

Customers showing concerning trends:

Customer name + revenue
Specific concern (slow pay, declining volume, complaint pattern)
Recommended action (sales call, credit limit review, escalation)

"Push these accessorials today"

Loads with unbilled detention or accessorial:

Load number + customer
Calculated accessorial amount + supporting data
One-click bill with prefilled documentation

The brief is short — under 90 seconds to read — and prioritized so the manager works the highest-value items first.

What deep analysis means in practice

"Deep analysis" doesn't mean burying the manager in charts. It means surfacing the why behind every score:

Driver Smith's mileage is down 18%? Centrix shows: 14% of the drop is

reduced load assignments, 4% is increased on-duty-not-driving. Reduced assignments came from dispatcher Jones (3 fewer loads per week than driver's average). Recommended action: ask Jones why the assignment pattern changed.

Lane Houston→Dallas RPM is up 12%? Centrix shows: market rate up 8%, our

customer mix shifted toward higher-paying customer XYZ (+3%), reduced deadhead from better reload booking (+1%). Recommended action: push the lane this week before the market normalizes.

Dispatcher Jones margin is down $0.08? Centrix shows: 60% from accepting

more low-margin reloads, 40% from declining to bill detention. Recommended action: 30-min coaching session on detention recovery + reload alternatives.

The depth is in the attribution. The data is decomposed enough that the recommendation is specific.

Real advice — the coaching playbook

For each common pattern, Centrix has a coaching playbook the manager can use:

Driver retention risk: 5-question check-in script in the driver's language
Dispatcher margin gap: lane-by-lane review template
Customer churn risk: sales call agenda with talking points
Driver safety regression: behavior coaching script with specific event examples
Mechanic productivity gap: 1:1 framework for the shop foreman

These aren't AI-generated platitudes. They're battle-tested scripts from managed fleets. The manager picks the playbook, has the conversation, logs the outcome.

What the math looks like

A 100-truck fleet running this layer:

Driver retention impact (from caught-early conversations): 25–40 retained

drivers/year × $14K = $350K–$560K saved

Dispatcher margin lift (from coaching to median): $0.08/mi × 9.6M miles ×

50% addressable = $384K of margin recovery

Customer churn prevention (from early intervention): 3–5 customers retained/year

× $200K avg = $600K–$1M of revenue preserved

Combined: $1.3M+ of margin and retention impact per 100 trucks per year from a layer that costs less than $10K to run.

The reports aren't expensive. The decisions they enable are.

Where to start

If you're 50+ trucks and have never run daily-advice reporting:

Connect Alvys + Samsara + Ensilog. Data quality determines recommendation

quality.

Run the daily brief in read-only mode for 30 days. The manager sees the

recommendations but isn't expected to act on every one — they're learning what the brief is good at.

Add the coaching playbooks after 30 days. By then the manager trusts which

recommendations are reliable.

Book a demo — bring 90 days of fleet data. We'll generate sample daily briefs against your actual operations.

The performance report nobody opens

The actual question — what should I do today to improve performance? — is rarely answered by these reports. The data is there. The recommendation isn't.

Centrix's performance layer treats the data the same way but treats the output completely differently. Reports become a daily prioritized action list:

Same data. Different output. Wildly different impact.

Per-driver performance — what's tracked

Every active driver, computed daily from the integration databases (Alvys, Samsara, Ensilog, Shopmonkey, Tenstreet):

Revenue per mile — net of deadhead
Total miles — 7-day, 30-day, 90-day rolling
On-time delivery percentage
Fuel economy (MPG) — vs the truck's baseline and the fleet's median
HOS compliance — violations, falsifications, adverse-driving claims
Safety score — composite from the driver-safety model
Pre-trip compliance — structured checklist completion via Telegram bot
Earnings projection — current period vs prior 3 periods
Retention risk score — quit-likelihood from the wellness model
Home-time satisfaction — actual vs requested home time variance

These are presented per driver in three views:

Driver scorecard — visible to the driver via the Telegram bot in their language
Manager scorecard — visible to the dispatcher / fleet manager
Aggregate reports — visible to the admin / CEO

Per-dispatcher performance — what's tracked

Every dispatcher gets a 30-day rolling scorecard:

Margin per load — revenue minus deadhead minus driver pay
Lane mix — high-RPM vs low-RPM lanes booked
Deadhead percentage — empty miles / total miles
OTD percentage — across their bookings
Detention recovery rate — billed / earned
Driver retention rate — drivers in their book who quit vs stayed
Booking volume — loads per week
Customer satisfaction — feedback on their handling

The dispatcher sees their own scorecard. The fleet manager sees the team. Comp plans tied to the scorecard reward profitable booking, not just volume.

The daily advice — what the system tells you to do today

This is the differentiator. Every morning, the dispatcher / fleet manager / CEO gets a prioritized to-do list:

"Call these drivers today"

Sorted by retention risk + actionability. Each entry includes:

Driver name + tenure
Current trend (mileage down, earnings down, etc.)
Suspected cause (home-time gap, equipment issue, dispatcher friction)
Recommended conversation angle
Last time anyone talked to them

"Push these lanes today"

Lanes with above-baseline RPM + truck availability:

Lane name + recent average RPM
Why it's hot today (market shift, customer demand spike)
Trucks that can reach the lane within HOS
Recommended counter rate

"Coach these dispatchers today"

Dispatchers tracking below cohort median on specific dimensions:

Dispatcher name
Specific gap (margin, deadhead, OTD)
Likely contributing pattern (lane mix, customer mix, negotiation style)
Specific coaching script

"Watch these customers today"

Customers showing concerning trends:

Customer name + revenue
Specific concern (slow pay, declining volume, complaint pattern)
Recommended action (sales call, credit limit review, escalation)

"Push these accessorials today"

Loads with unbilled detention or accessorial:

Load number + customer
Calculated accessorial amount + supporting data
One-click bill with prefilled documentation

The brief is short — under 90 seconds to read — and prioritized so the manager works the highest-value items first.

What deep analysis means in practice

"Deep analysis" doesn't mean burying the manager in charts. It means surfacing the why behind every score:

Driver Smith's mileage is down 18%? Centrix shows: 14% of the drop is

Lane Houston→Dallas RPM is up 12%? Centrix shows: market rate up 8%, our

customer mix shifted toward higher-paying customer XYZ (+3%), reduced deadhead from better reload booking (+1%). Recommended action: push the lane this week before the market normalizes.

Dispatcher Jones margin is down $0.08? Centrix shows: 60% from accepting

more low-margin reloads, 40% from declining to bill detention. Recommended action: 30-min coaching session on detention recovery + reload alternatives.

The depth is in the attribution. The data is decomposed enough that the recommendation is specific.

Real advice — the coaching playbook

For each common pattern, Centrix has a coaching playbook the manager can use:

Driver retention risk: 5-question check-in script in the driver's language
Dispatcher margin gap: lane-by-lane review template
Customer churn risk: sales call agenda with talking points
Driver safety regression: behavior coaching script with specific event examples
Mechanic productivity gap: 1:1 framework for the shop foreman

These aren't AI-generated platitudes. They're battle-tested scripts from managed fleets. The manager picks the playbook, has the conversation, logs the outcome.

What the math looks like

A 100-truck fleet running this layer:

Driver retention impact (from caught-early conversations): 25–40 retained

drivers/year × $14K = $350K–$560K saved

Dispatcher margin lift (from coaching to median): $0.08/mi × 9.6M miles ×

50% addressable = $384K of margin recovery

Customer churn prevention (from early intervention): 3–5 customers retained/year

× $200K avg = $600K–$1M of revenue preserved

Combined: $1.3M+ of margin and retention impact per 100 trucks per year from a layer that costs less than $10K to run.

The reports aren't expensive. The decisions they enable are.

Where to start

If you're 50+ trucks and have never run daily-advice reporting:

Connect Alvys + Samsara + Ensilog. Data quality determines recommendation

quality.

Run the daily brief in read-only mode for 30 days. The manager sees the

recommendations but isn't expected to act on every one — they're learning what the brief is good at.

Add the coaching playbooks after 30 days. By then the manager trusts which

recommendations are reliable.

Book a demo — bring 90 days of fleet data. We'll generate sample daily briefs against your actual operations.

Driver and Dispatcher Performance Reports That Don't Just Score You — They Tell You What to Do Today

The performance report nobody opens

Per-driver performance — what's tracked

Per-dispatcher performance — what's tracked

The daily advice — what the system tells you to do today

"Call these drivers today"

"Push these lanes today"

"Coach these dispatchers today"

"Watch these customers today"

"Push these accessorials today"

What deep analysis means in practice

Real advice — the coaching playbook

What the math looks like

Where to start

Frequently Asked Questions

Driver and Dispatcher Performance Reports That Don't Just Score You — They Tell You What to Do Today

The performance report nobody opens

Per-driver performance — what's tracked

Per-dispatcher performance — what's tracked

The daily advice — what the system tells you to do today

"Call these drivers today"

"Push these lanes today"

"Coach these dispatchers today"

"Watch these customers today"

"Push these accessorials today"

What deep analysis means in practice

Real advice — the coaching playbook

What the math looks like

Where to start

Frequently Asked Questions