1. Maximization of Vengo Profit
via Product Mix Analysis and Advertisement Reform
Consultant Name/ Members: CU Vengo 1 / Johnny Fells (Project Manager), Chloe Shih, Yao He, Ayana Dawkins
Client: Vengo Labs
Project Overview
Objective: To maximize weekly profits for Vengo machines on New York college campuses
Scope
● Restructure Current Product Mix
● Redesign Vending Machine Advertisement Layout
Synopsis: Vengo’s current product mix model are based solely past product sales. Given the past years transactions including
data on: location, time, item purchased, quantity purchased, amount paid, and the user name, CU Vengo 1 plans to provide a
model that focuses on the company’s untapped profit potential by considering factors such as:
● Machine revenue that is based on demands of “single buyers”
● The effects of product price on demand
● Changes in demand based on discount/giveaway promotion
● Demographic product variability
● Product and cartridge ratios
● Outcome of reducing product shelf­life
● Updating vending machine product advertising
The expectations of the CU Vengo 1 is to provide the company with findings that show that by making modifications to their
current model for sales that they may significant increases in the Vengo’s revenue.
Deliverables: CU Vengo 1 will provide the company with a typed report of their findings. The report will include: mathematical
methods and models used to determine the optimal product mix and possible alternatives for the vending machines and low
fidelity models including sketches and images for alternative advertising designs that may be implemented for future Vengo
vending machine generations. To supplement the report, the consultant will also present their findings to the client at Columbia
University that is to be determined in the future.
Timetable
The following list provides details of when CU Vengo 1 plans to have specific task completed for the agreement to be fulfilled.
Tasks may be added or deleted at the discretion of the consultant and client. Dates are subject to change based on the
availability of the consultant and client:
September 22, 2014 Video conference between company and consultant
October 6, 2014 Project Proposal completed
October 9, 2014 On­site
meeting with the client
October 13, 2014 First discussion of consultant’s findings with Professor Riccio
October 16, 2014 Agreement signing completed
October 19, 2014 Analysis of large single consumer revenue data completed
October 20, 2014 Second discussion of consultant’s findings with Professor Riccio
October 26, 2014 Research on machines’ product price vs demand data completed
October 27, 2014 Third discussion of consultant’s findings with Professor Riccio
November 2, 2014 Investigation on company discounts and giveaways completed
November 4, 2014 Vending machine site visit
November 9, 2014 Collection of data on demographics completed
November 10, 2014 Fourth discussion of consultant’s findings with Professor Riccio
November 16, 2014 Analysis on optimization based cartridge manipulation completed
November 17, 2014 Fifth discussion of consultant’s findings with Professor Riccio
November 23, 2014 Research on the effects product shelf life on revenue completed
November 24, 2014 Final discussion of consultant’s findings with Professor Riccio
November 30, 2014 Advertisement image models completed
December 8, 2014 Deliverables presented to company at Columbia University
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