Analysis of Data Visualization Individual Assignment

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There is an abundant amount of data that organizations gather each year however, the data itself is meaningless to most organizational leaders as it does not provide valuable insights on its own. Data visualization is needed to properly interpret data so that strategic business decisions can be made. Additionally, it is essential for any annual report because it allows those who are investing in these organizations to grasp information that is hidden in the data and to understand how well these companies are performing. Another major benefit of data visualization is that it allows a company to tell a story to their reader to get them engaged and emotionally invested in the content. Visuals can help the reader see difficult concepts and new patterns in simple form, as well as reveal problem areas that could be focused on. The reason for this is because images are processed 60,000x faster than text and 90% of information transmitted to the brain is visual (Thermopylae Sciences + Technology, 2014). This paper will analyze the annual reports of L’Oreal and Estee Lauder, two of the largest cosmetic brands in the world.

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Although they are both successful companies and fall within the same industry, the visualizations within their report differ significantly. L’Oreal & Estee Lauder Background L’Oreal was founded in 1909 and is now the largest cosmetics company in the world with 34 brands in 150 countries (L’Oreal, 2018). In 2017, L’Oreal achieved sales of €26.02 billion and €4.68 billion in operating profit (L’Oreal Finance, 2018). This is a result of acquisitions, major launches and the opening of new subsidiaries over the last 100 years. L’Oreal currently has a goal to embrace diversity and share beauty with everyone and they are achieving this goal with their strategy of universalisation. Their products are affordable to the general population and they focus on beauty differences around the globe. Estee Lauder was founded in 1946 and is an international cosmetics company that specializes in high-end products and has a diverse portfolio of brands (Estee Lauder Companies, 2018). They use the best ingredients and latest technology to create prestige products and the ultimate customer experience. In 2017, they had net sales of $11.82 billion and net earnings of $1.25 billion (Estee Lauder Companies, 2018). Estee Lauder’s mission is to be the best in everything they do and to help women look and feel their most beautiful. Analysis of L’Oreal & Estee Lauder Annual Reports It is evident that both L’Oreal and Estee Lauder put in a lot of time and effort to determine how to effectively present their quantitative information in their annual reports. When determining which visualizations to use, L’Oreal and Estee Lauder needed to consider four main categories.

These categories include comparison to compare datasets, relationships to show a correlation between variables, composition to show parts of a whole, and distribution to look for trends over time (Gulbis, 2016). L’Oreal and Estee Lauder needed to first determine what they wanted to show with the data in order to select the correct type of graph to use. Both companies have an overview pages near the beginning of their reports highlighting their wins for the year. This is a good page to have at the beginning as it gets the reader excited to read the rest of the report and it shows stakeholders the company’s success. With so much data that these companies gather, it is important to give an immediate overview of the most important information in order to make it simple for the reader to know how the company is doing. Although both pages provide important information about their companies, Estee Lauder’s page is more visually pleasing and at first glance can tell that it is a more prestige company that L’Oreal. This further demonstrates how visuals tell a story and how important they are for an annual report. Estee Lauder’s Overview L’Oreal’s Overview L’Oreal and Estee Lauder both have line graphs in their annual reports to display changes over time. Line graphs are useful as they provide a clear image of past trends and they can help make predictions about the future (Oetting, 2018). L’Oreal used a line graph to show the growth of the worldwide cosmetics market over the last 10 years and they also used a line graph to show operating profit over the last five years. Estee Lauder on the other hand used a line graph for total stockholder return over the last six years and compared it to the S&P 500 and S&P Consumer Staples. Both companies used simple titles that were to the point which made it clear to the reader what they were looking at. Also, they both zoomed in on the y-axis as their dataset started higher than zero, which makes it easier for the reader to see the trends (French, 2018). Both companies compared less than five lines which is a good practice because more than that could be too cluttered for the reader.

Additionally, the graphs had the appropriate height in order for the lines to take up most of the y-axis, leaving little white space. Although both companies made good use of these graphs for trends, there are some areas for improvement. Neither L’Oreal nor Estee Lauder clearly labelled their axes which is very important even if the axes appear to be obvious. As well, L’Oreal did not mark their y-axis, but rather put the actual value next to each point. This could be distracting to the reader from wanting to see the overall trend quickly. Although line graphs are sufficient on their own, perhaps both companies could have combined their line graphs with another type of data visualization to tell more of a compelling story. They could have also added a line graph that, for example, that shows revenue versus what was spent in marketing to see the correlation (Dunn, 2018). L’Oreal’s Line Graph L’Oreal and Estee Lauder both have pie graphs in their annual reports to display the breakdown of different categories and to see how they contribute to the total. Pie graphs are a good visual to use when the categories vary in size in order to easily interpret the data (Gulbis, 2016). L’Oreal used a pie graph to show the breakdown of 2017 sales by operational division, geographic zone and by business segment. This was a good way to demonstrate how categories represent parts of total sales. Estee Lauder on the other hand, used a pie chart to show the breakdown of its different channels. Neither organization had too many categories which is important to ensure so that the differences between the categories can be seen. As well, the values add up to 100% and the categories are ordered based on their size. Estee Lauder put the “other” category at the end even though it was not the smallest category so that it does not detract from the other relevant categories. Both companies used appropriate colour tones throughout the pie charts and they ensured the colours were different enough to distinguish between the categories.

Both companies avoided using 3D effects for their pie charts which was well thought out as 3D imagery could detract from what the company is trying to show, or it could produce optical effects (French, 2018). L’Oreal and Estee Lauder could have also considered using Treemaps as another way to demonstrate parts of a whole in order to not have an overload of pie graphs. Estee Lauder’s Pie Graphs L’Oreal’s Pie Graphs L’Oreal and Estee Lauder both have column graphs in their annual reports to compare values for different categories and to show how chronological data has changed over time. Column graphs are good to use when specific values are important and in order to show a comparison of items over time. L’Oreal used a column graph for their consolidated sales to compare the growth each year and they also used a column graph to look at the performance of the luxury cosmetic market compared to the total market. Similarly, Estee Lauder used a column graph to look at net sales and they used a column chart to look at category growth in 2017 compared to 2012.

Both companies used horizontal labels and at most five categories which are good practices to ensure that the graphs provide maximum value to the reader (Oetting, 2018). As well, the graphs have clearly visible values and they have set time dimensions. Both companies made wise choices using column charts rather than bar charts because bar charts should be used when the category names are long or when there are more than seven categories (Gulbis, 2016). However, L’Oreal could have used a consistent colour throughout and use a different colour to highlight a meaningful data point while Estee Lauder could have used solid colours rather than different shades. Although both companies have clear titles illustrating what the graphs represent, neither company has clearly stated their axes. L’Oreal could make the width of the columns wider to reduce the white space between them to make it more visually pleasing to the reader. Estee Lauder should have started their y axis for the net sales graph at 0 as this is important to do for this type of graph. Conclusion Overall both L’Oreal and Estee Lauder selected appropriate data to visualize and kept it simple for their readers to understand. They did not have any graphs that were meaningless or that were too difficult to comprehend. When comparing the two annual reports, L’Oreal used many more visuals that Estee Lauder did, and it is clear that Estee Lauder should be including more visuals in their future reports. Even though there were some areas for improvement, their graphs were well executed and provided a good story for their readers to follow.

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