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ASHY PLC SALES REPORT

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 Introduction

Ashy PLC is a large retail company with a many outlets across the United States. The company sells variety of products ranging from electronics, offices supplies to home appliances. 
The company want to expand its operation across the globe and management want to have a comparative analysis of its sales performance from 2014 to 2017.

Purpose of Project

This project is aimed at comparing revenue performance of Ashy for the period 2014 to 2017 and advice management on best ways to maximize profit. 
The project will discuss as much insights as possible to improve performance.

Asking the Right Questions

I started this project by asking some vital questions which are fundamental to the success of this project. I need to understand who the stakeholders are, the source of data and the business problem. I asked the following questions;
  • Who are the stakeholders
  • What is the business problem the company want to solve
  • What are the sources of data
  • Which people will make use of the final findings
The vice president Anold Wagner and head of  marketing Jossy Brown are the two stakeholders for the project.

Preparing and Processing Data

Data for this project will all come from internal sources. The company has 4 datasets consisting of all regions and their sales figures over the years.
These datasets were stored in csv files named; customers, orders, geography and products
  • I started by importing all four csv files into excel and inspecting them.
  • Data was then imported into power query editor for cleaning. 
  • Row number columns deleted for each data set.
  • Data types were changed to the appropriate type.
  • Null values were deleted for all tables.

Data Modeling

With 4 datasets, I need to create a relationship between them to get accurate analysis. Datasets were transformed into power bi for modelling. 
  • The orders table was made the facts table with orderid being the primary key.
  • Customers data made dimension table with customerid being the primary key.
  • Geography a dimension table with postalcode the primary key.
  • Products also a dimension table with productid the primary key.
  • Relationship created by mapping customers, geography and products tables unto orders table.

Data Analysis Expression (DAX)

In order to create a comparative report, new dimensions need to be created using DAX.
These DAX were used;
  • CALENDARAUTO() Calendar table was created containing all transaction months from start to end date of the datasets.
  • YEAR() Year column extrated from calendar date
  • MONTH() month and quarter columns extracted from calendar date.
  • CALCULATE()
  • FORMAT()
  • SPLM()
  • SPLY() 

Visuals

Visualizations were designed and created with power bi.

Revenue by Year and Category













Revenue by Segment













Sales Forecast for 2018













Month on Month Percentage Variance













Revenue v Revenue Same Period Last Year













Sales Dash Board





















Insights

  • A total of 38,000 items were sold
  • Total Revenue for the period was $2,300,000
  • Total Profit amounted to $286,400
  • Consumer segment accounted for over 50% of total sales
  • Technology category consistently enjoyed highest sales value

   RECOMMENDATIONS

  • Sales should be monitored in January to ascertain the causes of consistent decrease from December.
  • Shipping costs should be reduced to increase net profit.
  • Marketing efforts should be focused on office supplies to maintain its upward trajectory. 

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