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The joys and perils of Data Visualization and Analytics

28th Dec 2022
Brought to you by
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Konsolidator is a Scandinavian SaaS company that delivers a 100 % cloud-based consolidation tool.

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Showing business stakeholders data in long-winded tables with lots of numbers is a no-go. You will not find many finance professionals that have not yet understood that point. Similarly, most finance professionals know that we must develop insights through analytics to get a seat at the table. However, doing this does not come without challenges…

We can rarely take data straight from the ERP or accounting system and throw it into the visualization tool. Therefore, we often must extract the data to Excel or another tool to arrange it neatly and analyze it to understand what insights we can draw from it.

These manual interventions bring about several challenges, such as:

  • Increase the risk of making errors.
  • Make it difficult to track data back to the source.
  • Complicate having a qualified dialogue about what happened and why it happened.
  • Slow down the data-to-insights process, which makes executives wait too long for their numbers.

This article will look at ways to tackle each of these challenges. We will also point to a desired future state when using the data created in the ERP or other operational systems.

You need proper data and model governance

Ideally, all data is correct and usable from the source, but even in that case, it is rarely ready to be shown immediately. That is why we must process it through other tools. We do that to develop insights through analytics and to visualize them in an appealing and digestible way. However, it does not come without challenges. Let us look at how you can tackle at least four of them.

Increase the risk of making errors

The challenge in most cases is that data is extracted in free form to Excel, allowing the user to make any modification (s)he desires. With every additional modification, the risk increases. Hence, you can build a data model to prevent this and ensure that data is always processed similarly. However, the model should be documented and agreed upon with stakeholders and clearly stated if a true ad hoc analysis is needed. This way, you can ensure alignment with stakeholders about the risk of errors.

The difficulty of tracking data to the source

For every single number you show to your stakeholders, you must be able to state what the source is. In addition, you should be able to show what processing has been done to it to arrive at its current form. If you are looking at inventory numbers, for instance, you should be able to go to the warehouse and point at the physical item. One way to ensure you can do this is to create a simple flow- or process chart that shows the flow of data from sources to uses.

The complications of having a dialogue about the numbers

It must be transparent to all stakeholders where numbers come from and how they have been processed. The easiest way to do this is by having an audit trail from aggregated numbers to the source. You cannot do this if all you have is flat data in Excel (or even PDF). In this case, each sheet must contain a link that leads the user to the source data. Doing this makes your dialogue with stakeholders straightforward when looking into what and why something happened.

The slow data-to-insights process

Your stakeholders want their numbers to be relevant for decision-making as soon as possible. However, every step you take to prepare the data will slow down the process. The best way to go around this is to build automatic interfaces between systems. If all you have is Excel, this is clearly a challenge, although not impossible, if you create macros that can replicate your manual steps.

Regardless of how you choose to solve these challenges, it is crucial that you use a proper data model and adhere to strict governance around using it. This might feel limiting to the flexibility of how you can use the data. However, if you clearly distinguish between standard and ad hoc analysis, you can at least set the right expectations with your stakeholders.

Is excel the right tool for you?

To truly enjoy the upside of proper analytics and data visualization, you must re-evaluate if you are using the right tools. As you can see above, using standard functions in Excel will, in most cases, come with many challenges.

With Power Pivot and Power Query, you can do many types of analysis to better connect to and visualize data from other sources. However, the ability to slice, dice, and double-click on numbers to better understand the details is more sophisticated in BI systems.

With Power BI or similar tools, you can better visualize the numbers and connect the same tools directly to the source.

data visualization

Image above: In Konsolidator®, customers have access to Konsolidator Konnect. Here, they can connect their numbers directly to their Excel or BI systems. This enables them to use the different systems for what they are good for – making documentation and working papers in Excel and presenting and analyzing in a BI system. And they can easily track their numbers down to the original source.

Maybe this is a good time to consider what tool(s) could enhance your data visualization and analytics capabilities. Similarly, these tools would likely help you tackle the challenges highlighted in this article. Explore what is possible and escape your current perils of trying to do too many calculations in Excel and manual interventions. Find tools that allow you to focus on the important things, such as discussing how to improve business performance.

What are you waiting for?