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Improving BI Content and Improving its Accessibility

1 September 2012
Mila Pavlock
A person using a tablet

Organizations invest resources in business intelligence, but despite its enormous potential to improve decision-making and achieve business goals, only a few succeed in extracting the added value from the information and data that BI systems provide. In this article, I will touch on two principles that can help extract more value from BI solutions.


Content

Description of the situation: We are tempted to display every possible data point.


The proposed principle: Less is more.

  1. It is very important to define the metrics that will help us manage the team/activity effectively. You may think this is trivial, but many of us do not invest enough thought into it. We must decide what metrics are essential and influential in decision-making and where they can improve future operations.

  2. We need to decide what is suitable to manage and know about these metrics:

    1. We need to define what is more important for understanding the data: the trend or the exact value.

  3. We need to determine whether it is essential to see the change compared to the past or compared to the goal.

  4. We need to analyze whether aggregated/sorted information is required or whether individual data is more meaningful to provide the best overview of the situation.


These will determine the data that is most appropriate and important to display.


Accessibility

Description of the situation: When it comes to creating BI reports, we often talk about complex tables and graphs loaded with information. The user is supposed to read the data and make decisions, but they may get lost, waste a lot of time decoding, and sometimes miss what is essential to know.


Most BI tools tempt us to use various design and animation applications, which improve the appearance of presentations/reports but distract the reader.


The proposed principle: Accessibility focused on simplicity. In the world of knowledge management in business intelligence, too, the issue of displaying and presenting information correctly is critical for the desired success in the task, especially when dealing with complex information.

Once we understand how the data can serve us, we will be in an ideal position to plan the clearest possible display of metrics. Here are two examples of the most commonly used graphs: Line/bar charts are the best and most widely used charts for displaying most types of data. Line charts are better for displaying trends over time, and bar charts are more suitable for comparisons between categories.




For more on charts, click here.


To summarize in one sentence: Less and simpler creates added value; it is essential to analyze and plan the data and report display well and present them simply and in a simple and user-friendly way.

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