The Scoop n' Scootery - It's all about the delivery
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Operations Management class project. We worked with the Scoop n' Scootery to evaluate their existing delivery process and provide recommendations on how they can improve in-order to increase their ROI. I handled - client communication - market research - digital solutions - presentation design and layout
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The Scoop n' Scootery - It's all about the delivery
- 1. The Scoop N Scootery Sarah Barone, Kelly Bowker, Kate McCormack, Henry Ortiz, Chrislene Paillant, Shaun Rull
- 2. Founded in 2012 Year-round since June 2014 Ice cream & frozen yogurt sundaes Plus root beer floats Average 40 deliveries daily Competitive advantage: Delivery Ice Cream Food Truck
- 3. Customers & Expectations Customer Base: Young professionals College students Young parents Found via: Word of mouth Online recommendation Delivery Expectations: Consistent quality Timely delivery Responsive customer service
- 4. Very Much a Lean Start-Up Face-to-Face Meeting Intuition Real-Time Data MEASUREMENTS! Tools to Capture
- 5. SundaesOrderto Delivery Throughput time: 3603 seconds (2.65 order per delivery) 38 deliveries/day/person Order Online Sundae Assembly 146 sec Truck Freezer 1207 sec Delivery Cooler 2250 sec Scootery Inbox Write Down Order Weigh & Add Ingredients Prep Cover & Store SundaeAssembly Process Cycle time: 146 seconds/unit
- 6. Peak Time Analysis Current wait time per customer varies between 56 to 63 minutes Sundays between 7 – 11 P.M 0 100 200 300 400 500 600 700 Revenue Days Average Sales per day
- 7. Improving Delivery Improves Business Focus of current model leads to unforeseen inefficiencies Our recommendation: Drivers should leave at predetermined intervals o 30 minutes for off-peak o 15 minutes for two drivers at peak times
- 8. Drivers come and go 6:00 7:00 8:00 9:00 10:00 11:00 12:00 1:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 1:00 Ad hoc driver departure Depart every 30 minutes Depart every 15 minutes (2 drivers needed)
- 9. Delivery Interval Optimization 0 2 4 6 8 10 12 14 0 10 20 30 40 50 60 70 80 6 PM 7 PM 8 PM 9 PM 10 PM 11 PM 12 PM #ofOnlineOrdersperHour WaitTime(Min) Average Customer Wait time by Hour number of orders Current Wait Time Optimized Wait Time AM
- 10. Six Sigma Analysis Pre-optimization 100% of orders during peak hours not meeting benchmark advertised on site Post-optimization 40% will arrive on time during peak times ~1 sigma level Six Sigma Level Defects per Million 1 690k 2 308k 3 67k 4 6.2k 5 .2k 6 3.4
- 11. Tools to Improve Route optimization app for delivery drivers Optimize The Scoop n’ Scootery Website Promotional materials for repeat business
- 12. Improving Delivery with Technology Speedline LiveMaps Lavu BestRoute Pro Road Warrior Delivery Droid Complete POS system Complete POS System App App App Groups Orders Group Orders Integrated with Google Maps & Waze Integrates with 3rd party Apps Totals all data at end of shift Best Route Best Route Optimize up to 85 spots Add Time Windows Archives data Customer Communication Sends route to driver via text Share routes via email or text Automatic route optimization Return Times iPad POS Add new Cloud Backup Requires Call $88+ Free - $6.99 Free - $50.00 Free - $2.99
- 13. Questions
Editor's Notes
- First name 2012: Scoop n’ Scoot New Name 2014: The Scoop n’ Scootery
- - Very much a "Lean Startup" - Intuition --> Real-time Data Tools to Capture embed video clip (file 0121)
- In watching the video, it became clear that Scootery was focused on keeping the driver at 100% capacity utilization and as a result, neglected to consider the effects on overall customer wait times and product quality. As soon as the driver returns, Austin hands him however many orders are completed at that very moment and sends him on his way. Even with two drivers during peak times, average total wait time for customers averaged about an hour and sundaes were idling in the truck for an average of 20 minutes after assembly and before they were taken by the driver to be delivered. Anecdotally, there was one instance during observation where both drivers were coming and going at about the same time—if you were the first person to place an order after the driver left you could be waiting upwards of 80 minutes for your ice cream which is a far cry from the 30 minutes they boast on their website. This line depicts the linear view of how this erratic delivery cadence impacts the variance of wait times. While orders placed within the 6:00-9:00 time frame have a relatively consistent wait time, as walk up orders increase at the end of the peak time frame, the efficiencies of the delivery process breakdown. As soon as the owner is forced to multitask between walk ups and online orders he loses sight of servicing the customers which are not in front of him and average wait times increase by 20-25 minutes during the rest of the peak period. By putting guidelines in place that strive to have drivers depart the truck every 30 minutes during off peak and 15 minutes during peak intervals, we were able to project a 54% improvement in ice cream idle time and 39% improvement in total customer wait time. With this model, instead of waiting 60 minutes for your ice cream, it’s more likely that you’ll be waiting around 35 minutes or less.