ANLY482 AY2017-18T2 Group26 Project Overview

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Project Overview

Findings & Insights

Project Management

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Geospatial Analysis

Geospatial Analysis is the technique of using geospatial data – from mobile devices, location sensors, social media, etc – to build maps, graphs, statistics and analytical models to make complex relationships understandable. The benefits of using geospatial analysis is that it is a step above regular analytical insights; more engaging and more understandable and recognizable, it helps managers move from hindsight to foresight and develop location-based targeted solutions. Focussing on this aspect of geospatial analysis, we aim to come up with a method that takes into consideration past location data, and its impact on other aspects of the business, to help optimize future location based decision making.

(Referenced: Geospatial Analytics The three-minute guide. (2012). Retrieved from https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Deloitte-Analytics/dttl-analytics-us-ba-geospatial3minguide.pdf)

Company PQR

PQR is a Singapore based company with over 100 branches spread across Singapore as well as a growing online presence. They have a pronounced focus on providing aid to the community. Their employees are committed to helping the community albeit the elderly, challenged youth or the environment. The company itself, contributes over 60% of their profits to the betterment of the community each year.

Motivation & Objectives

Company PQR has been facing a road block while optimizing their sales targets, in order to meet their demand and serve their customers better. They have conquered central Singapore and need a smart method to estimate their demand considering the anomalies of each branch location. An accurate demand estimation will make it easier to predict or set sales targets. By analyzing mobile data and points of interest around Singapore, we can optimally estimate demand for their outlets. Our project will use these data sets and its relationship with the financial performance of PQR branches all over Singapore.

Therefore, our objectives are: To understand the existing model Company PQR is using to do their estimations. To learn the correlations between population variables from mobile data, and points of interest to aid our regional demand estimations. To develop an equation that weighs these variables in a way that optimizes the financial outcome of potentially suggested outlet locations. We aim to create our own model that builds on their existing one but includes our insights. To create a dashboard that summarizes these relationships and behaves like an interactive visualization of our formed equation. This is in order to give managers an overview of the most influential variables and their effect on the financial outcome which will help them set accurate sales targets.

Methodology