Why You Can’t Be Successful with Your Sales & Operations Analysis Using Excel or Power BI Alone

There’s no doubt. Power BI is powerful. It’s highly visual. And on a self-service level, it packs a real punch in letting business analysts and other advanced users build simple reports and visually appealing dashboards from live data sources. Excel’s a real powerhouse, too, and not surprisingly the most widely adopted reporting application today for number-crunching aficionados. Unfortunately, though, no business can be successful using either Power BI or Excel alone to effectively analyze and report on sales and operational performance.

In scenarios where information is used across departments and groups and/or multiple data sources, you run into the problem of having no synchronization or consistent reporting across the enterprise. Common links between the data that make sense to report on don’t exist. Users need to be confident in the fact that they are all grabbing the same data … and that the data (whether it be product groups, geographical groups or other logical groupings) is consistently defined and aligned. This makes the need for a modern data hub more inevitable than ever.

There’s No Escaping Inconsistent Data

Usually the data in traditional data sources like ERPs or CRMs contain data that needs to be checked, corrected and stored in a structured manner. If these systems are not integrated, changes made to one does not automatically update the respective tables in the other. As a result, you end up with two different pieces of data carrying the same transactions that need to be cleaned up and made consistent to provide for proper and accurate reporting. If you additionally connect to point-of-sale and other third-party sources with tools like Power BI and Excel, that data needs to be checked and corrected in a repeatable manner to ensure optimum data quality, too. A modern data hub is perfectly suited to handle such data management requirements.

Multiple Data Silos End Up Losing Control

Connecting directly to data sources from a visualization tool does not allow for consistent sets of data that are optimized for analysis like they are in a data hub. Scores of disjointed datasets often end up being created and used autonomously by analysts. No single “version of the truth” exists to ensure that everyone is working with the same data while gaining the insights needed to drive enterprise performance in the most effective manner.

Data Becomes Unruly to Manage

On the flipside, Excel requires a ton of manual effort to compile data, especially if it’s coming from multiple systems and sources. And as the volume of data to be analyzed grows, there’s a lot of room for both human and formula errors because of the manual process of copying and pasting data. In the end, that compromises data integrity.

Plus, if you’re using Excel as your main data dashboard and are sharing it, it’s challenging to manage the version of the spreadsheet that everyone is seeing. This makes it more difficult to collaborate around the data, because stakeholders may be looking at different reports with different numbers.

No Real-Time, Deep-Dive Analysis is Possible

Beyond the data-related issues that can occur using Power BI or Excel as a primary hub for business intelligence and reporting, there are a few other challenges to consider. With both, it is difficult – if not impossible – to drill down and get to very fine levels of actionable information. Also, neither offers advanced ways to view data based on “time” (for example, you can’t analyze data this season vs. this season last year, by rolling time periods, etc.).

If you’re an Excel user, the data in your spreadsheet is not going to be in current unless someone is working behind the scenes to create macros and scripts that update the data regularly. Plus, using Excel can be fraught with security issues particularly when sensitive information is shared both internally and externally with no totally secure way to protect the data.

Both Power BI and Excel offer a myriad of great features and are perfectly suited for higher levels of analysis involving lower volumes of data. But relying on either one to completely run the business in a secure, efficient and accurate manner requires more. And that’s a modern data hub that organizes, manages and stores information together with key performance metrics and visualization capabilities that can drive the type of insights needed to effectively manage business performance.

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