ANLY482 AY2017-18T2 Group18/TeamDAcct Project Methodology

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Project Overview

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Methodology

Data Preparation:

All the files acquired have helped us deepen our understanding of the company’s business and ultimately the business problem. However, not all files were crucial to formulate recommendations to the business problem on hand. The following are the list of data-sets prepared:

• Master Client Listing

• Facility Details

• Manpower Details

Exploratory Data Analysis (EDA):

Following which, EDA (e.g. through the usage of graphs or tables of summary measures) was conducted to get a better understanding of the data. From the EDA, we will have a better understanding of the relationship amongst the explanatory variables (factors that drives the expenses such as wages) as well as provide us with a general direction and size of relationship between explanatory and outcome variables. In the analysis of data, we will be using the software SAS JMP Pro 13 as our main tool for data cleaning, data preparation and EDA. Our choice of this software is that it allows us to conduct statistical analysis on big datasets and can generate results that are easy to understand for end users. In addition, due to its popularity of being widely used, tutorials are readily available on the web, should we encounter any problem.

Thereafter, we can formulate and suggest a model to the client that forecast the expenses incurred for an anticipated project site with certain characteristics. From a business perspective, this would point to possible approaches management wish to take (i.e. minimise cost, bid at higher price, pegged to industry price, market share growth), in using our proposed model to assist in shortlisting future project sites and to drive business strategy overall.

Analytical Methods:

After cleaning and preparing the data, we decided to work on our confirmatory analysis to assess the appropriateness of the explanatory variables to be used for our regression analysis. Thereafter, we performed multiple linear regression to build an explanatory model to analyse whether an increase in any of the explanatory variables (determined in our confirmatory analysis) has an impact on any of the various cost components incurred for a cleaning project type. The four major cost components that we have identified in a cleaning project are namely:

• Total Project Costs

• Manpower Costs

• Chemical & Materials Costs

• Equipment Costs

For this project, we will be focusing on one specific cleaning project type - conservancy sites (zones).