Case Study: Harbour & Hearth Bistro
Business Overview
Type: Mid‑size dine‑in restaurant
Location: Fredericton, NB
Seats: 60
Average table value: $85
Reservations per week: ~120
Admin time spent manually taking reservations: ~10 hours/week
No‑show rate before automation: 12%
Primary challenge: Too much staff time spent on phones + costly no‑shows
1. The Problem
Harbour & Hearth Bistro relied on phone‑based reservations. This created several issues:
Operational inefficiencies
Staff spent 10 hours/week answering calls, taking names, confirming times, and updating the reservation book
Guests could not make reservations outside business hours
Day‑of confirmation calls took another 3 hours/week
No‑shows were frequent because confirmations were inconsistent
Annual labour cost of manual reservations
Assuming $20/hr labour cost:
(10+3) hours/week×52×$20=$13,520 per year
Annual revenue lost to no‑shows
120 reservations/week×12%=14.4 no‑shows/week
14.4×$85=$1,224 lost revenue/week
$1,224×52=$63,648 lost revenue/year
Even recovering a fraction of this would be financially meaningful.
2. The Solution
The restaurant invested $2,500 to implement an automated reservation system with:
24/7 online booking
Automatic confirmations + reminders
Credit card holds for peak times
Real‑time table management
No‑show protection
Integration with Google + website
Result: Reservation handling became nearly hands‑off.
3. Impact After Automation
Time Savings
Manual reservation time: 10 hrs/week → 1 hr/week
Manual confirmation calls: 3 hrs/week → 0 hrs/week
Total hours saved per week
10+3−1=12 hours saved/week
Annual labour savings
12×52×$20=$12,480 saved/year
4. No‑Show Reduction
Automated confirmations + credit card holds reduced no‑shows from 12% → 5%.
New no‑show volume
120×5%=6 no‑shows/week
No‑shows prevented
14.4−6=8.4 tables saved/week
Revenue recovered
8.4×$85=$714 recovered/week
$714×52=$37,128 recovered/year
5. Extended Booking Hours = More Reservations
Before automation:
Reservations only accepted during open hours (approx. 60 hours/week)
After automation:
Reservations accepted 24/7
18% of bookings now occur after hours
Additional weekly reservations
120×18%=21.6≈22 extra reservations/week
Additional annual revenue
22×$85×52=$97,240 additional revenue/year
Even if only 25% of these convert (very conservative):
$97,240×0.25=$24,310 annual gain
6. Total Annual Financial Impact
Realistic scenario
Labour savings: $12,480
No‑show reduction: $37,128
Additional bookings: $97,240
$12,480+$37,128+$97,240=$146,848 annual benefit
7. Payback Period Calculations
Scenario A — Realistic
$2,500÷($146,848/12)=0.20 months
≈ 6 days to pay back the investment
Scenario B — Conservative (50% of benefits realized)
$146,848×0.5=$73,424
$2,500÷($73,424/12)=0.41 months
≈ 12 days to pay back the investment
Scenario C — Ultra‑Conservative (labour savings only)
$2,500÷($12,480/12)=2.4 months
≈ 2.5 months to pay back the investment
8. Summary Table
Metric |
Before Automation |
After Automation |
Impact |
|---|---|---|---|
Weekly reservation admin time |
13 hrs |
1 hr |
12 hrs saved/week |
Annual labour savings |
— |
— |
$12,480/year |
No‑show rate |
12% |
5% |
8.4 tables saved/week |
Revenue recovered |
— |
— |
$37,128/year |
Extra reservations from 24/7 booking |
0 |
22/week |
$97,240/year |
Initial investment |
— |
— |
$2,500 |
Payback period |
— |
— |
6 days – 2.5 months |
Final Takeaway
A $2,500 investment in an automated reservation system pays for itself within days to a few months, depending on how conservatively you measure the benefits. The combination of time savings, reduced no‑shows, and increased booking volume creates a powerful, ongoing return on investment.
