About Project

Some details, including the collected data and the Python notebook for analysis, are not publicly uploaded for confidentiality reasons.

Link to Presentation

Guidelines

1. The student needs to collect the data pertaining to a business problem. It could be any business- organized or unorganized sector. E.g.: Manufacturing, automobile, IT sectors, supermarkets, laundry, vegetable vendors, restaurants, service businesses etc. Kindly note that only “primary data” is to be collected. Do not collect data from online sources like Kaggle, GitHub etc., as they constitute the secondary data sources. This is an independent research project.

2. Clearly explain the process of data collection.

   1. Prepare field notes describing the meeting between the two parties (Student and the business, the people involved etc.). Mention in brief, how many meetings were done and what was discussed?
   2. Understanding of the business (Type of Business-B2B, B2C or both) and nature of problem(s) the businesses encounter.
   3. How do businesses solve the problems they encounter? Are these problems recurring or one-time?
   4. How did the student narrow down the problem?
   5. How was the data collection done? Time period of data collection (Days/ Months/Years etc.).
   6. Tangible evidence (People, Processes (say an organization chart) or any form of physical evidence)

3. Details about the various variables collected as a part of data collection. Importance of these variables and their relevance.

4. Cleaning of the data – Describe the process in brief and how it was done.

5. Analysis of the data- While the students can use the case studies taught in BDM course as cues to conduct the analysis, the rationale for the same needs to be mentioned. We also encourage students to go through newspapers, journals, reference books, use learnings from other courses etc, and explore newer ways of conducting analysis.

6. Provide insights from the analysis conducted to the businesses.

   1. What should businesses do? (Continue doing and start doing)
   2. What is that they need to avoid?
   3. In what ways do your solution(s) address the business problem(s)? Kindly note these insights should be novel, as something that adds value to the decision maker. The insights should be derived from the analysis you conduct. So, the better the data, the richer the insights!

Objectives

1. Investigate the extent of tax theft by wage workers employed by APMC in collecting taxes from farmers and identify potential solutions to enhance accountability in tax collection.

2. Investigate the impact of considering a fixed price of | 650 per 100 bunches for every vegetable on the profit margins of APMC.

3. Investigate the causes of high traffic in the market during peak periods and develop strategies to optimize the verification of tax process and reduce traffic congestion.

Problem-Solving Approach

1. The study aims to investigate the disparity between the quantity of leaf vegetables arriving at the market and the quantity sold, with a focus on understanding the extent of tax theft by wage workers. By comparing the reported quantities of arrived and sold produce, we can estimate the amount of produce that is not being reported to the APMC and thereby suggest APMC analysts monitor daily quantity transactions closely and make sure they match.

2. The investigation is motivated by the observation that some vegetables in the market have priced up to | 1500. we compare the tax collection differences between the two approaches: using a fixed price of | 650 per 100 bunches and using the modal price. Suggesting APMC to employ the modal price as it yields higher tax revenues for APMC due to its correlation with the actual market prices.

3. The collected data will also track the time the slip was issued. Analyze peak hour traffic patterns and devise a strategy to reorganize vehicle movement within the market to mitigate congestion. This plan should also include measures to encourage early departures, thus spreading out the congestion over a longer period of time and enabling efficient tax verification at the exit gates.

Analysis Tools and Justification

1. VSCodium 1.83: With the Jupyter Notebook extension installed, it is easy to ana-lyze line code without running the whole code again.
2. Pandas 2.1.1: A Database manipulation tool, used to extract information from querying the database. Can handle large databases which won’t be possible using Microsoft Excel.
3. Matplotlib 3.8: A Data visualization library that allows visualization of large data sets.
4. seaborn 0.13: A Data visualization library based on Matplotlib with more color options and easy syntax.
5. Numpy 1.26: Library handles large arithmetic operations with ease.

Expected Outcome

1. The market’s profitability will enhance.
2. Wage workers will be monitored more effectively through daily data checks.
3. The APMC can adopt a dynamic pricing strategy, rather than a fixed price model, which is no longer questionable.
4. Traffic congestion will decrease.
5. Tax validation personnel at the exit gate will be able to work more efficiently