Best Practices for Discussing Data Insights

Best Practices & How-To’s

The ultimate goal for Business Intelligence solutions is to reveal data insights so better actions can be taken. In most cases, the process of understanding insights and taking actions involves more than one person, which means that collaboration in some form needs to take place to best put the data to use.

In many organizations, collaboration is done through traditional methods such as sending emails, which either occurs manually or based on pre-defined schedules or threshold driven alerts. Other companies may use internal chat tools or team collaboration tools with real-time messaging capabilities. While these methods are great for different use cases, they are limited when it comes to ensuring the collaboration is done in the context of the data at hand. Emails and chats tools are introducing yet another system to share and store insights around the data that lives in your BI system. This makes it harder for people to understand where/why the original discussions began, and even harder to sustain a shared dialogue on the insights found within the BI system, particularly when the data is revisited again in the future. With these methods, insights simply get lost.


Rethinking Collaboration in BI Tools

To get away from side discussions occurring in 3rd party tools, the conversations need to move directly into the BI tool – right next to the data. In practical terms, users should have the ability to add their notes or annotations to the data, and have group discussions by placing their comments, thoughts, questions and answers within their dashboards and reports. Anyone that is looking at the data for the first time or after 6 months (for example), and is curious about a data point, should be able to go through the discussion thread and get answers immediately or ask new questions and participate in the discussion.


What's Unique about Dundas BI's Collaboration with Notes?

While some modern BI tools have adopted the concept of having collaboration done within the tool, with Dundas BI, we took it one step further and were even awarded a patent for our approach. Instead of having comments displayed in a side panel within the BI tool, the Dundas BI collaboration experience is unique in that it takes place directly on top of your visualization. There is no need to look at your dashboard and then go through comments on the side and have your eyes wander to try and relate the two. In Dundas BI, the comments are displayed right on top of the exact data point (for example, at the ‘spike point’ in your chart, or on a ‘poorly performing location’ within your map visualization.

The chart below shows a similar discussion taking place, and anyone looking at this thread can easily understand that this specific discussion is about the dip in Sales for Q4, comparing to the previous year:

There are a few others factors that make Dundas BI’s notes more valuable and better for collaboration:

Figure 1: Portion of Notes Visible in Dundas BI

Notes 2.0

So far, we’ve discussed the concept of adding notes on data points and how to use them to communicate with other users. But what if the data point value itself was incorrect or you wanted to change it to implement a what-if scenario on the data? This is where data annotation (i.e. data correction) comes in and is considered the next generation of notes. Using this feature, users can go beyond just adding a comment on a data point, but can actually change its value to correct it or to perform their own analysis by changing the data.

A use case for this might occur if the data was entered incorrectly in the system and the business user wants to see the visual with the right data, or if the system has not been updated yet with the latest data, which the user wants on the visual at that time. For example, you may be the Sales Manager and are looking at the number of units sold for different product categories only to realize that one of the categories is showing a very low number incorrectly. You know that the issue is due to an error in the system that failed to record a major consignment. You can correct this right away by right-clicking on the data point and changing its value to the right one, along with placing a comment on why the change was made.

Figure 2: Data Annotation

As you can see, when you make the change, it adds an annotation on the data point to let the users know exactly what changes were made and why. It is important to mention that this type of annotation can never be hidden as it is important to notify others about this data change and of course, with great power comes great responsibility, so by default the permission to correct a value isn’t available to all users unless granted by the administrator explicitly.

As mentioned here are other use cases for data corrections, such as for conducting what-if-analysis. To learn more about those, check out this webinar on actionable analytics.


Next Steps

Try out these collaboration methods yourself! Start using them in your favorite Dundas BI dashboards and encourage others to join the discussion.

Have any comments for us? We’d love to start new discussions with you! Please leave comments below or in Dundas BI’s user forums.

New to Dundas BI? Want to see the notes in action on your data? Talk to us or try it for yourself.