Supply Chain Framework, Logistics Simulation Model for Food Delivery business. This SCM Logistics Model has the simulator, modeller, scenario builder, database and customized reports.

1. FOOD DELIVERY - LOGISITCS FRAMEWORK
MODEL
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2. Model:
An Overview
This work describes a five stage model to build a preliminary business plan.
- Stage I is the collection of basic data which would work as input masters to plan the
logistics in stage II. Note: When initiating the model i.e pre launch phase, the model will be fed
with all the Input data and then model starts validating the initial data and refine them with
actual data.
- Stage III is the optimization phase wherein the data is further drilled down to optimize
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- Stage III is the optimization phase wherein the data is further drilled down to optimize
the resources.
- Stage IV is for scenario building which works on creating various scenarios to
understand the dynamics of the business.
- Stage V describes the type of MIS reports and dashboards to be maintained to
continuously monitor and improve the operations to achieve cost – service level
optimization.

3. Model:
Modules Resource
Optimizer
Scenario
Builder
REPORTS
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Logistics PlannerDATABASE
ASSUMPTIONS

4. Model:
The Framework
Database
A master database capturing a wealth of information about
restaurants, service providers, demand (customers), supply
(restaurants), peak time zones, TAT, constraints, pin codes,
seasonality factors, fixed and variable cost components,
resources for office set-up.
Logistics Planner
Decide on the number of bikers required based on the network
model , demand and zones created with-in the serviceable area.
Resource Optimizer
Strategically optimizing resources through various options like
staggering shifts depending on peak times, order consolidation,
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Scenario Builder
Reports/ Dashboards
staggering shifts depending on peak times, order consolidation,
route optimization, cost-service level optimization etc.,
Building scenarios based on What-If analysis to understand
business dynamics.
Designing daily/ weekly/ monthly MIS reports to monitor the
key parameters defining the business which would in turn help
in resource planning and optimization.

5. Model:
The Schema
Input/ Raw Information:
Supply Locations
Speed of Vehicle
Max. Distance in a zone
Skewness of orders
Demand
Supply
Runner Cycle Time
Module I: Database
Data in measurable/ analytical format
for modeling
Module II: Logistics Planner
Plans resources and
operations in terms of:
No. of bikers
No. of orders/ grid etc
By using data from Mod
I viz.:
No. of deliveries/ grid
Orders/ day
Orders/ hour
Module III:
Optimizer
Cost – Service
Level
optimization
Daily and Predictive /
Forecasted S & OP
Output
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Orders/ hour
Deliveries/ day
Avg. speed/ delivery
Module IV:
Scenario Builder
What if analysis on the optimized
parameters from Module III
-What if Demand Increases (Predictable)
-What if a Zone doesn’t have enough orders
-What if lead time variability is more
-What if Demand drops sharp
Module V: MIS Reports
Fill Rate Report
Orders/ biker-day
Orders/ hub-day
TAT
Orders/ hour
Orders/ restaurant-day
OTIF
Total Cost/ Order
Cycle Time for delivery is used as follows:
- It is calculated from total time from picking
and delivering to customer.
- Any variations in this would be compared
with the Industry standards to target low
performing lanes to action on them.

6. Stage I:
Database
Locations and Pin
Codes
1. Locations and Pin Codes of pick-up points/ Restaurants.
2. Locations of supply clusters/ pin code density.
Demand and
Supply
(In terms of orders)
Data on demand and supply in terms of number orders per day,
time of order considering skewness.
This culminates to decision making on zoning, number of bikers and
runner boys required.
Vendors/
Service Providers
List of various service providers to be considered. It includes bikers,
runner boys, software consultants for real time network routing and
order processing, SCM partners in case of hub & spoke model of
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Service Providers
order processing, SCM partners in case of hub & spoke model of
delivery
Constraints
Delivery constraints, if any. For example, customers in Zone X can
not be serviced by restaurants in Zone Y. Helps in deciding the
delivery model. Delivery constraints can be minimized by going for
hub & spoke model. However, feasibility to be understood post
comparison of both models in terms of capital investment.

7. Stage II:
Logistics Planner
Restaurants
Based on the Volume pattern, the resources
are deployed. Ensure in the contract the
flexibility to ask Field Executives to come on
odd shifts and a change with a notice of a
week is written.
Each delivery location is mapped as a GPS
coordinate and mapped to a particular zone.
This is the base for the Routing.
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• The data on locations of customers and restaurants helps us in arriving at the resources required in each grid of 4 X 4 km.
• The data on day-wise and hour-wise demand pattern and skewness will give us the exact picture of the resources based on
the number of orders that can be handled by each biker on an average. The planning is done by GPS Coordinates only.
• Data on constraints shall help us in deciding the model. Suggested model would be hub & spoke, as the restaurants are not
evenly situated across Dubai but are more towards the city borders and the distance range is between 2 – 56 km as shown in
the map. Hence, the delivery constraints such as servicing the customers from restaurants present in the same grid or
immediate adjacent grids will not work. Stocking points for order consolidation shall be decided upon for optimization.
Deliver Points
Restaurants

8. Stage III:
Resource Optimizer
Locations and Pin
Codes
Demand and
Supply
(In terms of orders)
Orders/ day
Orders/ hour
Deliveries/ day
Avg. speed/ delivery
Peak hours
No. of bikers
No. of orders/ grid
No. of deliveries/ grid
Database Resource OptimizerLogistics Planner
Staggered shifts based
on peak hours gives
revised number of
bikers and bikes
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Vendors/
Service Providers
Constraints
Operating Costs
Operating Model
Last Mile Costs
Capital costs based
on number of hubs
and other resources

9. Stage IV:
Scenario Builder
Locations and Pin
Codes
Demand and
Supply
(In terms of orders)
Vendors/
Orders/ day
Orders/ hour
Deliveries/ day
Avg. speed/ delivery
Peak hours
No. of bikers
No. of orders/ grid
No. of deliveries/ grid
Database Resource OptimizerLogistics Planner
Staggered shifts based
on peak hours gives
revised number of
bikers and bikes
Scenario Builder
No. of bikers
No. of orders/ grid
No. of deliveries/ grid
Orders/ day
Orders/ hour
Deliveries/ day
Avg. speed/ delivery
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Vendors/
Service Providers
Constraints
Operating Costs
Operating Model
Last Mile Costs
Capital costs based
on number of hubs
and other resources
Fixed Costs
Variable Costs
No. of hubs

10. Stage IV:
Scenario Builder
(Contd.)
A what-if scenario builder on increase/ decrease of no. of bikers due
to absenteeism or vendor service discontinuity or any other reason
Simulation of orders
Simulation of revenue based on fulfilment
Develop an understanding on productivity benchmarking by creating
simulation of orders per day to achieve optimization.
Develop an understanding on top line and bottom line by analyzing
various scenarios of costing obtained by dip-stick analysis of vendor
No. of bikers
No. of orders/ grid
No. of deliveries/ grid
Orders/ day
Orders/ hour
Deliveries/ day
Avg. speed/ delivery
Fixed Costs
Variable Costs
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various scenarios of costing obtained by dip-stick analysis of vendor
benchmarking.
Addition and deletion of hubs from the model creates substantial
change in the revenue and expenditure as well as service levels.
Simulation of this parameter is necessary to achieve cost – service
level optimization
Variable Costs
No. of Hubs

11. Stage V:
Reports
In terms of number of orders delivered vis-a- vis number of orders
raised.
Grid-wise no. of orders per biker per day.
Turn around time of bikers to measure the productivity in terms of
time take per order.
Fill Rate Report
Orders/ biker-day
Orders/ hub-day
TAT
Orders/ hour
No. of orders serviced in any given hour. Gives an understanding
about peak hours.
Orders/ Orders served by restaurants for an idea about top performing
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On-time In-full report for preventive and corrective actions.OTIF
Orders/
restaurant-day
Orders served by restaurants for an idea about top performing
restaurants.
A report to keep a check on the total cost incurred and as a thumb
rule the total cost/ order decreases as the number of orders
increase due to economies of scale.
Total Cost/ Order

12. HESOL is in business to be a 'RELIABLE BUSINESS PARTNER' by
providing ‘Cost Effective Solutions’ and work as 'ONE TEAM' to
implement the solutions and increase the profitability of the
company.
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