Introduction
The purpose of this report is to analyse the nature of visualization used to represent the financial aspects of the 1300 Smiles Limited. The graphical representations including bar graphs, line graphs, candlesticks, scatter plots, and area graphs will be classified as either good or bad depending on whether they meet the classified criteria outlined in this report. As such, this report will encompass an overview of the case company, evaluation criteria, and analysis of the visualizations based on the evaluation criteria and a conclusion.
About 1300 Smiles Limited
The 1300 Smiles Limited is a company that specializes in dental and management services in Australia. According to the Memorandum (2014), the company owns and operates full-service dental facilities at its sites in South Australia, New South Wales and in more than ten centres in Queensland. Clients who require dental services approach this company for surgeries, among other dental health services through self-employed doctors who work under the name of the company. The dental experts pay a fee for using the company name and infrastructure to carry out their own dental practice. 1300 Smiles carry out services including administration, marketing, billing, facilities certifications, licencing of all the partner dentists. Further, the company avails equipment, facilities, support staff, in addition to sourcing all consumables. 1300 Smiles Limited was listed in the ASX directories in 2005, it has a market capitalization value of 167.64M with a bid or offers ranging between 6.780 to 7.080 as of the time of the preparation of the current report.
Part A: Evaluation Criteria
Bar Charts
Bar charts are more suitable for comparing categories of data than spans many days, weeks or years. For an appropriate bar chart, data should be arranged intuitively or easier visualization, random data makes it difficult to visualize. According to Mansour & Shabani (2019), the Y-axis should start at 0 for bar; if it does not start at zero the viewer risks misinterpreting the data insights as more or less significant than they actually are. Mansour & Shattuck (2020) argue that chart 3D visualization should be avoided to prevent data skewness. The bar width, size and internal spaces should be appropriate and consistent should be appropriate. The bars should take a proper direction (horizontal or vertical); wordy labels should make use of the horizontal bar. Consistent colouring should be applied to the bars since a significant variation could cause distraction from the data. When presenting a bigger picture, gridlines should not be used however if details are required, they can be used.
Scatter Chart
Scatter charts are useful for observing relationships between variables and describe the linearity, strength and direction of the association of the variables. All data elements should be well presented using a suitable scale to ensure they are not lost in the visualization. Different but consistent colouring can be used for different elements to ensure the categories can be distinguished appropriately. Just like the bar charts, the scatter graph should also start at zero (Wang, Huang & Nguyen, 2016). The Y-axis should be started at 0 for accurate data representation. Also, it is essential to use not more than 2 trendlines to ensure the plot can be understood easily.
Line Graph
Line graphs are critical for tracking changes over a long or short period, and also over the same period. Line graphs are suitable for data with peaks and valleys. The Y-axis represents what is being measured and should start at zero. When comparing sets of data, it is important to ensure they are well labelled and possibly represented in an indifferent colour for easy distinction. In some cases, gridlines are important to present the details of the trend. The X-axis represents the different periods or labels of the items being compared. Lastly, it is critical to include a source of the data being resented. Similarly, Chai, Li, Fan & Luo (2020) add that the legend should be availed if the goal of the visualization is to depict more than one data series. The axes should be named, however, gridlines are not compulsory.
Candlestick
Useful for detecting possible price movements based on the previous patterns. It is imperative to use appropriate colour coding for the candlestick price bars and teacher real bodies; this helps an analyst to easily view the open and the closely
Area Chart
According to Ho, Zhang & Singh (2018), an area chart represents the change in a quantity over time; this type of chart is only implemented to show the development of values over time, it also works best with multiple values to enable a comparison. In the case of large differences between values area charts are considerably useful under such circumstances. Further, area charts are helpful in presenting data with many dates.
Part B: Report Evaluation
This section presents an analysis of the suitability of the visualizations based on the presented criteria.
Figure 1: Bar graph 1, and Time Series Forecast
Figure 1 below represents the trading characters for the last quarter of 2020 for the 1300 Smiles Limited. The data set is appropriate for the graph since it demonstrates change over a longer period making it easy to identify a trend as well as compare the performance at different times. The graphs are consistent n times os size colour and spacing for legibility making it easy to understand and observe the trend these show a good visual representation. However, from the bar graph, it is clear whether the Y-axis does not begin at 0, the axes are also not labelled appropriately, the figure also lacks an appropriate title. Id these are fixed the representation would be considered good.
Figure 2: Scatter Plots and a trendline
Figure two represents a scatter plot for the trading person of August to December 2020, at a glance the trend can be seen as a linear trend. The gridlines have also been used to separate the different months; this is arguably a good representation; however it lacks proper labelling, a proper title and the Y-axis ought to start with a 0. The trendline and the plots could also utilize different colours for easy distinction. The choice of the visualization method is however right as line graphs are useful to show change over a given period. The trendline helps in identifying the nature of the change, which in this case is linear.
Figure 3: Line Graph
The current representation, though suitable for the provided data set, falls short of the best presentation in several ways; it lacks a proper title and only shows when the data was generated, it has no well-labelled axes, and the Y-axis does not begin at 0. However a trend can be identified as a glance, and the peaks and falls can clearly be observed in the visualization. The lack of legend in this graph is however justified since only one data element id being presented.
Figure 4: Candlestick Chart
Based on the analysis a Candlestick chart is suitable for depicting price changes over time; therefore, the current implementation is suitable, the graphing also utilizes several colour codes for distinction; the bar graph also provides extra information regarding the sales volume at any given period. However, the presentation could be improved by starting the Y-axis at 0, using appropriate legends and effectively titling and labelling the axes appropriately; these are missing in the current implementation.
Figure 5, 6 and 7: Bar graphs 2
The bar graphs below represent trading volume, the income, revenue, net income and the dividends over different periods of time. In figure 7 (far left), the graph appears simple and has a title which should be the case for every graph but lacks appropriate labels to the axes, the use of numbers like 2K,4K, 6K and 8K could be more meaningful if zeros were used instead. However, a comparison and a trend can be clearly observed within the period presented. The colouring, size and spacing of the bars are also consistent; the use of a different colour for average is also useful for distinction.
In figure 6 (the middle graph), similar mistakes have been propagated; even though the legends are present for proper distinction, the bars appear consistent in terms of colouring size and spacing and the values are labelled at the top of each bar, the axes still lack proper labelling in addition to the use of values like 50M, or 7.77M which are not suitable. Further, the use of gridlines is also not necessary in this case.
In figure 7 (far right); the chart has a title, size, spaces and colouring of the bars are also consistent. It is easy to observe the trend and also identify the performance of each presentation over time. Therefore with proper labelling, the figure will attain the threshold of being considered “a good presentation.”
Figure 8: Area Chart between 2014 and 2020
The area chart depicts revenues and warming of 1300 Smiles Limites, the bar colouring is appropriate to ensure a proper distinction and also making it easy to understand the trends of each data element. The chart has a title, appropriate legends with well-labelled axes. Further, the chart has a source at the end of the presentation. The choice of this method to represent data is valid since an area chart is primarily used to compare data sets over a period of time. It can also be used particularly with data elements with a big range as the case of the current implementation. Thus, this is considered a good representation.
(ASX: ONT Income Statement, April 21st 2020)
Figure 9: Line Graph
The below represents the rate of earning per hour vs. dividend per share for ESP and DPS for 1300 Smiles Limited Company between. Even though the graph has a title, proper legend, and different colour codes for the two distinct line graphs, one axis is not labelled making it difficult to understand what is being represented. The choice of a line graph is appropriate for this analysis since it compares performance over a given period of time for two elements. With a proper label of the X-axis and a source, it will be considered a good visual presentation.
Figure 10: Gar graph
Bar graph 9, below is a representation of the Annual Report for 1300 Smiles (ASX: ONT). At a glance the comparisons can be made effectively since the bars are consistent in terms of size spacing and colouring, the bars are also appropriately labelled. However, the graph lacks an appropriate title and source.
Conclusion
Based on the criteria, there are good elements of the visualizations presented, the charts and graphs meet some criteria, however, the evaluation has shown that several aspects have been left out, particularly, the labelling of the axes, and the labelling of the titles. The visualizations, however, demonstrate a good understanding of the data set since in all cases they were chosen appropriately. This report, therefore, concludes that particular attention should be put on proper labelling and titling of the graphs. Thus, the only figure that appeared to meet all the criteria was figure 8. The remaining figures including 1,2,3,4,5,6,7,9 and 10 showed some positive elements but require further improvements to meet the criteria of being considered “good visual representations”
References
Chai, C., Li, G., Fan, J., & Luo, Y. (2020). CrowdChart: Crowdsourced Data Extraction from Visualization Charts. IEEE Transactions on Knowledge and Data Engineering.
Ho, P., Zhang, H., & Singh, P. (2018). U.S. Patent No. 10,163,235. Washington, DC: U.S. Patent and Trademark Office.
Mansour, T., & Shabani, A. S. (2019). Enumerations on bar graphs. Discrete Math. Lett, 2, 65-94.
Mansour, T., & Shattuck, M. (2020). Statistics on bar graphs of inversion sequences of permutations.
MEMORANDUM, E. (2014). 1300SMILES LIMITED ACN 094 508 166.
Wang, W. B., Huang, M. L., & Nguyen, Q. V. (2016, October). A space-optimized scatter plot matrix visualization. In International Conference on Cooperative Design, Visualization and Engineering (pp. 382-385). Springer, Cham.
