Over the last ten years or so, many organizations have acquired very large and complex data, creating a Rush Industry we refer to as Big Data. Doing reporting which has an impact to take better decision is crucial for your business.
Today, the biggest challenge in data reporting is being able to use the available data. One big problem is that we don’t know how to extract information or make our data operational.
In most organizations, data reporting is nonexistent or in embryonic states at best. This is because Business Intelligence tools are mostly intended for data analyst or experts. That said, there isn’t much training available to learn these skills, and most of the data reporting has been self-taught.
This is where this article on data visualization can become handy. Knowing how to present the information, opens up the possibility of your team to understand the complex concepts by just visualizing them.
It could be for performance measurements, communication or presentation. This way you give all of your team access to the same data, whether they are specialists, decision makers or technicians.
It doesn’t matter what tool you use to present your data. We want to share with you our past experiences and expertise. In this article we will expound on two questions:
What makes up a good data reporting?
What graphical display is best for your data?
How to build an appropriate data reporting system?
Choosing the right graph type to present your company’s data isn’t supposed to be a difficult task. On the other hand, choosing the wrong graphical display can cause confusion for your team and can lead to a bad interpretation of your message.
Here are 5 steps that you need to keep in mind while building your graphical displays:
1. Prioritize your indicators
Your data reporting must have a direction and be clear to read. Exhausting your audience with confusion is the worst thing you can do. Often when we do not know where to start, we end up building multiple complex graphs using all the data that we have at hand.
Unfortunately, the audience is lost by looking at complex graphs, and he/she will be the one to choose what message to take away from your work. You therefore can’t be certain of relaying the correct message.
Define who your audience is and their needs in order to choose the most important indicators. Once you have done that you must retain that notion for the entire data reporting notion. Any idea that doesn’t concern these key indicators should be kept for another data reporting concept.
2. Plan and test your graphs
For this next step, do not put all of your efforts into the end product. Draw out your indicators on paper. Discuss them with your audience, and find out what you can do better. Ask them if all the indicators are useful, as you don’t want to have too many indicators on the same page.
Repeat this for all your indicators until you have created a clear reporting schema. Remember that when you are creating a dashboard there is one key rule: One graph = One message.
3. Integrate your data
After you have finished defining your message, it is time to plug your data in. At the beginning, you might be surprised by the results. Your audience can also be surprised. They might even ask for clarification. If they do, you must continue working with their feedback to make the presentation better.
4. Tell a story
You must keep in mind the very important rule mentioned earlier : one graph per message. Data visualization shouldn’t be just looking at bars and lines. It is what we like to call data storytelling. It is the ability to tell a story with data in order to make it easier to understand.
This is done through giving context to the data by : adding a legend, comments, captions, a good choice of contrasting colors, a glossary, etc.…
Give your audience the best option to better understand the information you want to convey.
5. A good report should be operational
Whether it is tracking sales performance or financial performance, presentation of your department’s KPIs should lead to taking action.
Lets imagine the sales department didn’t meet their goals. How can you help them with that? What was their performance for the last period? Was this dip in performance a seasonal decline? Or was it due to the departure of one of the top salesmen? Study the case carefully and offer them an actionable solution.
Data Reporting: use case
Main goal: Brings together 3 indicators to show correlations. This is the perfect tool for comparing complex data.
Usage: Bubble charts are generally used to compare and show relationships between labels and categories. This is done by changing the positions and proportions of your bubbles. Bubble charts can therefore be used to analyze models and correlations.
Too many bubbles will make your chart hard to read. This type of chart therefore has limited capacity in terms of data volume. You can also use the bubbles interactively. If you hover over each bubble, additional hidden details become available.
Force Directed Graph
Main goal: This graph is ideal for analyzing networks or links between many entities.
Usage: This particular graph involves complex algorithms and is hard to put together. Force directed graphs are quite unique; they allow you to display and compare relationships between 2 entities in either volume or fluctuation.
Bar and line chart
Main goal: Allows you to correlate volume and variation.
Usage: This type of chart is ideal for correlating volume or quantity and change over time. This chart has 2 layers. The line chart shows trend or progression over time. Line graphs can be used to show temporal trends in different data categories. Line graphs are used with continuous data.
This graphical display is ideal for showing two quantitative variables with different scales. For example 3% and 3,000k€.
Main goal: with this graphical display, you can illustrate many indicators that are not related to each other.
Usage: theoretically, you should only use a scorecard when you do not have other options.
For dataviz purists, this graphical display carries no added value in terms of readability
You should use this graph to present different data types even if they have different units.
2. How to compare data ?
Main goal: This chart is used as a classic comparison between quantities or fluctuations. The dimension can also be temporal.
Usage: Use several indicators in the same group to make comparisons. Keep it simple though, don’t compare more than 3 indicators at a time.
Main goal: this graphical display allows you to compare multiple different entities. For example, you can compare your company’s performance with another company’s performance over a given period of time.
Usage: A horizontal histogram can be used when there are more than 10 labels to compare. This visualization tool can compare up to 3 different data types at a time.
Centered average leaderboard
Main goal: This tool is ideal for comparing indicators of quantity or fluctuation represented as averages.
Usage: Use a reference average with which to compare your performance data. This way you can compare your data to one single objective.
Main goal: This graphical display shows changes in tendencies between a certain date t and t+1 for each entity.
Usage: It studies the progress under two different conditions. The more the lines on this graph cross, the more changes have taken place as compared to the initial recording.
This graphical display is used to track a variety of data types. This graph is perfect for comparing many different types of variables and finding relationships between them. For example, if you need to compare the sales performance of a large scale of products over two years.
Main goal: A bullet chart is a graphical display that allows you to compare objectives.
Usage: Use the vertical yellow bar for objectives and the horizontal bar for current performance.
This graph shows an indicator’s progression towards its goal. It allows you to compare the rate of progression of different indicators.
Main goal: To show an overall view of a selection of entities and indicators. It is ideal for cross-checking transversal data.
Usage: A heat-map distinguishes your data through color variation. This graph is most useful for comparing diverse data. This is done by adding data variables on the x and y axes and adding color to the cells in the table.
The heat models are useful to describe variation across multiple variables. A heat map shows all the models. Through color variation it is easy to detect similarities and differences as well as correlations that may exist between variables.
Main Goal: To look at your data from a geographical standpoint.
Usage: This graphical presentation is perfect for displaying the geolocalization of performance data. Maps allow you to show geographical zones, specific regions or even company locations through color patterns. You can geographically show data tends and variations.
3. How to display temporal data ?
Main Goal: This graphical display is principally used for temporal data.
Usage: line charts are used to present a quantitative value over a time interval or a given time period. Most often it is used to show tends and relationships. You get a global view of trends over time interval. It can also be useful to select custom intervals.
Line charts are great for viewing performance over time.Limit your trend lines to 3 per graph, for better clarity.
Main Goal: This is to be used to show milestones or a notable change for the company or an individual.
Usage: To display graphically an individual’s biography or a company’s history. Make sure that you are selecting the most important data for your chart to keep it simple and understandable.
Stacked Bar Chart
Main Goal: To categorize the total value of an entity or indicator.
Usage: This graphical display is used to compare all the categories that a single entity might have, allowing you to easily spot the strong and weak points as well as each categories impact on the entity. For example, Stacked Bar Charts can be used to monitor various contributors to a department’s results.
Main Goal: sometimes referred to as a Mario Chart because of its floating rectangular bricks, a Waterfall graph is ideal for illustrating fluctuation.
Usage: A Waterfall display allows you to visualize all of the positive and negative values of your data over a given period of time. It can also be used to show how an initial value is affected by intermediate values, either positive or negative, resulting in a final value. This graph simplifies complex results.
A good example of this is if you want to evaluate the impact of sales from various stores on the total company sales results.
Main Goal: To visualize data hierarchy and complex data structures.
Usage: A Tree-map is a way to visualize a large array of data without taking-up too much computer screen space. It is a very compact option for looking through your data’s hierarchy and for taking a quick glance at your data’s general structure. Another good way to use it is to compare multiple entities.
Main goal: To illustrate your performance data with clients’ comments and to explore your data through a qualitative format.
Usage: Show the comments for each category within the graphical display.
DATA STORYTELLING : Tell a story through your data reporting
Your reporting can be great, but it isn’t much without context. Add comments, sources, the units that you are using, legends, captions and glossaries.
2. Enrich your contents
An image is worth a thousand words. This is the logic that you should keep in mind when building a rich dashboard. Add images and videos to contextualize the information that you want to share with your team or audience.
3. Highlight the most important data
A successful data visualization is seen when the most essential information is highlighted. The graphical display should tell a story while presenting your data with colors and context. Choosing what data to present is key to reporting, and will help make the report operational.
You must understand that building a high-quality data reporting system isn’t about cramming a lot of condensed data on a single page. Rather, it is about making your data comprehensible to all of your readers.
You must select the most relevant data and question your work as if you were a member of your audience. Your dashboard must speak for itself. If you can send it to your team without having to explain anything. It is only then, that you have successfully created a complete and successful data reporting system!
Kilian Bazin, co-founder and general director at Toucan Toco.
The Mission Statement at Toucan Toco is to teach you how to transform your data into Dataviz with interactive stories.