Author: Jiamin Chen
The inspiring art in data analytic is visualized information. The booming of data visualization is changing how we think and feel. Data visualization convey complex concepts and stone-cold data into something more understandable and communicative.
The goal of this article is to demonstrate how data visualization could add value to business decision making process by providing information quickly and crisply based on a real case study for worldwide small business analytic. The dataset studied here is called “Doing Business”, which is provided and downloaded by World Bank, http://databank.worldbank.org/data/views/variableselection/selectvariables.aspx?source=doing-business.
Our analysis could be used to determine the best economy that provides conducive business environment to start and run a small business. In addition, the obstacles of doing business in each country will be identified and visualized in a dashboard.
1. Why should we love small business?
Small businesses make up:
- 99.7% of U.S. employer firms,
- 64% of net new private-sector jobs
- 98% of firms exporting goods, and 33% of exporting value.
2. Analysis:
2.1 Software used:
Tableau and Excel
2.2 Dataset:
DoingBusiness: http://databank.worldbank.org/data/views/variableselection/selectvariables.aspx?source=doing-business
10 measure areas from the data set:
2.3 Major concentration areas in our analysis:
We only focus on two areas in this study as a demonstration: “Starting a Business “ and “Trading Across Borders”.
2.4 Approaches:
2.5 Results and Summary:
The final dashboard, Figure 1, shows the top two economies in each areas (starting a business and trading across boarder) with the detailed rank information of each evaluation dimension. The number annotation beside the bars indicates the actual value of the corresponding dimension. The overall top 30 economies based on these two areas are mapped in a world map and colored by its rank. Figure 1 shows that Singapore and Hong Kong, China are the best economy entities that provide conducive business environment to start a small business.
The information of this dashboard could be used as guidance in making overseas expansion plan. The detailed information and rank help business owners better understand business regulations in every country.
Figure 1, Example of a Business Ready Dashboard
The integrated Tableau table below shows the percentage of a dimension with respect to the world average in difference countries. The largest difference indicates more challenge for small business owner. By clicking on the bars in a country, users can get information on how difference of its domestic factor deviate from the world average. For example, the cost to import of Botswana is 98.14% of the world average in 2012. This interactive Tableau graph could be used to analyze the challenges of doing business in a certain country.
In this study, two important questions in making business strategy are answered through those more actionable and communicative information that support decision making. And more information about this study could be find at: https://public.tableau.com/profile/jiamin.chen#!/.
This article is derived based on a course project entitled ‘ISYE 691 Data Analysis” offered in Spring 2015, at University of Wisconsin-Madison. Thank Professor Kaibo Liu for his instruction. And thanks my teammate Hwankok Yeo and Guangda Shi for their efforts.
Source: U.S. Census Bureau, SUSB, CPS; International Trade Administration; Bureau of Labor Statistics, BED; Advocacy-funded research, Small Business GDP: Update 2002- 2010, https://www.sba.gov/content/small-business-gdp-update-2002-2010.
I think this is a very interesting data analysis project. However, the visualizations are kind of hard to understand and it is kind of unclear whether or not Singapore and China/Hong Kong are the best of both categories or only one. Perhaps focusing in on a few categories and showing these countries compared to more countries would be a better way to get the point across.
I agree with Michael. It would have been more interesting if you would have dont top ten or fifteen or comparing some countries to each other. However it still is interesting to see
I agree with Michael that it is difficult to tell when a measure is good or bad by just a quick visual inspection of the graphs. However, I bet that this information would be very valuable in the hands of decision-makers who know what to look for. This information about the barriers and regulations could be combined with information about markets and demand to pick a country in which a business is likely to boom.
I like how you started off the analysis by relaying the importance of small businesses showing why we should care about this study. I agree with the above comments that the visualizations are a bit hard to interpret at first. Maybe different colors or graph types could have fixed this issue.
I think that the project had a good scope but I also agree with the other comments that the graphics and tables are unclear.
I had to struggle a lot to understand everything and I think that it should be more easier taking into account that this kind of graphics are usually analized by people who are working in a bussy evironment. A more visual presentation with clear legends and bigger labels would be easier to understand.
On the other hand, I like a lot the topic since it is very useful for people who are interested in start a new business and don’t care about the geographical location.
The article definitely makes a compelling case for data analytics/visualization in general and why we should care about small businesses and improving them. However, the way they got to some of the results is unclear and could be better interpreted with more analysis. Definitely a topic I would like to see looked into more in the future, especially with analytic tools like Tableau.