Project 2 - Supply and Demand Gap Analysis

• Aim :

This project is pertained to do the effective Analysis on Supply and Demand Gap Analysis, The Output of this project going to give us answers for many questions like What is the Target?, What we achieved?, Where is the lag if there is any?, And through those Insights Management can get the idea of what next.

• Introduction :

I have taken the “Uber Request Data” from the Kaggle which contains 6 Columns and 6746 Rows which contains details like Request ID, Pickup point, Driver ID, Status of the trip, Request time and Drop time. And it also contains Considerable amount of Null values in the table. Lets see the possible ways to do Effective Data formatting, meaningful Visualizations and feasible way to extract the meaningful Insights from the project.

• Problem statement :

The addressed Problem in the given data is Null values which is denoted as NA here. It won’t be meaningful if it is replaced with some mean or approximate values, Because it is not there because the data is not available due to some case, In this case: If the Trip was cancelled due to Non availability of cars then the Driver ID, Drop time won’t be available which is denoted as “NA”. So, changing the given data may give us the unreliable Output. So I have left the Null values (NA) to exist and proceed with the further process.

• Methodology :

Data Cleaning using Power query editor of Power BI -

After analysing the, we have found that the null value as NA need not to be changed. So, simple automated steps like, Promoting Columns names as header using “Promoted headers” and Changing data type of the columns as relevant using “Changed Data type” Options using Power query editor of Power BI desktop.

And Since I was provided with the single data table, There is no necessary to work with Data modelling and formatting.

• Analysis (Data sheets pertaining to it) :

In this case,We can consider that Supply is the count of trip what we achieved and Demand is the Count what the Customer expected to go with. So, I have created some DAX calculations using create measue option to segregate the Count of request into Target, Cars not available, Trip completed and Cancelled. And used me to figure out target count and achieved count. And by the analysis it can be observed that there is the big lag due to the Non availability of the cars.

Below is the Visualizations which I have created using some Cards, Donut chart, Gauge viz and Funnel viz. Using this we can know that Total request received is 6745, Trip completed is 2831, No cars available is 2650 and Cancelled request is 1264. So, we can say that Total request is the Limit available were Excluding Cancelled request is the Demand and Trip completed is the Supply

• Insights :

By the analysis, The meaningful Insights which we derived are

• Total request received is 6745
• Trip completed is 2831
• No cars available is 2650
• Cancelled request is 1264

So, we can get to Know that Supply has not met the Demand in the market.

• Recommendations :

Uber should hold the source of cars to allot them as per the customer’s request. Because the Revenue should not be restricted due to lack of source. And also They should get to know the reasons why the trip is being cancelled ( If it is addressed that it can be rectified from the Uber end, Then they can hold more customers than before )

• Conclusion :

We can conclude that Uber should have more Car and driver sources. Because, the Customers expecting more from User to provide and On the other hand they should address the reason for the Trip cancellation. Because it may also help them to hold their customers from cancelling the trip.