Don’t get us wrong, we love Excel as much as the next person; it’s versatile, familiar, and comes bundled with a suite of tools (Office 365) that almost every business has.
However, it’s important to recognise where Excel performs, and where it comes up short.
If you’re collecting one off data, working on quick mock-ups or building simple models then there isn’t much reason to look further – but if your organisation relies on business reporting, insights, and management information, then it’s time to consider the benefits of a ‘built-for-purpose’ platform.
How did Excel come to be used for business reporting in the first place?
For many, Excel has been part of the business ecosystem for decades. It’s ubiquitous and, if you have the right skills, it can be customised to serve a wide range of functions it was never originally made for. Additionally, since it comes bundles with Microsoft Office suite, many companies view it as a ‘free’ resource and find it hard to justify investing in a new reporting tool. This often leads small and medium-sized businesses (SMBs) to stick with Excel long past the point where it is practical or efficient.
The role that data and analytics plays in modern business is changing, fast. What started as a reactive service, used on a case-by-case basis, has become a coveted resource and a key driver of business value for SMB’s and Enterprises alike.
As data and analytics grows in importance within a business, using an ad hoc tool becomes less and less productive. Simply put, Excel imposes a ceiling on what you can achieve when extracting value from your data – moving to a modern business intelligence (BI) platform gives you room to expand.
So, let’s take a look at five key areas where dedicated BI tools can bring new value to your data and analytics programs.
A skilled Excel veteran can probably manipulate the software to do just about anything, but this doesn’t change the fact that the program is not optimised to handle large volumes of data, not to mention the fact it’s difficult to employ a whole team of Excel veterans.
‘Work arounds’ that may have performed well to begin with, start to become extremely inefficient once you’re dealing with data at scale. This is especially true if you’re trying to run more complex Excel operations such as automation or front-end features on large volumes.
Furthermore, Excel has a functional limit on the number of rows and columns it can handle. While you might not be working yet with truly large volumes of data, it’s best to deal with this issue before it becomes a problem. Bumping up against these limits results in truncated data, this can lead to costly errors or even to businesses diluting the power of their data and analytics. To get around the limits of Excel, it’s not uncommon for organisations to self-impose limits on the data they collect: storing only top-line, aggregated, simplified categories.
Needless to say, constraining your ambitions to fit within the limitations of a software platform is the exact opposite of what you should be doing.
2. Sharing and security
An essential part of business reporting is the ability to safely and easily share data across your organisation without creating new risks and vulnerabilities.
As a file-based platform, Excel was not built with cloud-based sharing and collaboration in mind. While using a separate sharing platform is certainly an option, this in turn creates a new dependency.
Beyond difficulties in sharing reports, there is perhaps the even larger issue of security. An Excel file can be locked down with a single password, but this is simply not sufficient to safeguard sensitive internal data. The lack of any user-based password system allows a workbook password to easily be shared in an unrestricted manner – rendering this method of security largely meaningless. User or role based security is difficult to achieve unless you have the right infrastructure in place, which often leads to an ‘everyone can see everything’ approach, or worse, countless versions of the same file with different cuts of data within them.
In a world where data security and data integrity are becoming ever more crucial, taking risks with your data is not something that any business should do lightly.
Hand in hand with sharing and security is the issue of governance. Providing easy access to essential data can provide new insights across the business – however, what you certainly don’t want is multiple users creating unauthorised edits or duplicates which conflict and contradict one another.
Excel is not a governed platform, and while it is possible to impose a form of data governance on individual Excel workbooks, this is, once again, a ‘work around’ and not a core feature of the platform.
This is not only an issue of data security but also of data integrity. Business reports play a critical role in supporting information-based decision making – and the accuracy and integrity of the data must be paramount.
4. Ease of use
Ease of use, both for developers and for end users is an essential prerequisite for a modern BI tool and often drives total cost of ownership and an organisations ability to self serve.
It’s true that in Excel there is almost always some form of ‘make-shift’ solution that can get you the features you want. However, easy-to-use development and end-user tools aren’t part of the software because they were never meant to be.
A skilled Excel veteran may be able to manipulate the software to suite a range of scenarios, but is far less likely to comprehensively document this process. Laying ad hoc, atop make-do, atop workaround eventually results in a platform that does not follow best practices and is hugely dependant on key specialist personnel. If that specialist decides to leave the company or becomes unavailable, then simply maintaining the system can become a challenge.
Specialist dependency can also lead to serious bottlenecks around how data can be accessed and used. Ideally you want to empower as many workers as possible to engage with data and analytics to facilitate information-based insights. This is near impossible, when the tools they use are hard to update, hard to build upon, overly complex and non-user friendly.
5. Repeatability and Automation
While we’ve established that a seasoned Excel developer could generally build a model capable of most things with the use of VBA, including automation of processes, there are number of limits in this space. Automated processes built in Excel are normally very rigid and require inputs to be just so, exactly as they were prescribed. For example, if automatically importing data from csv files in a given folder, columns will need to be in the correct position and order for all files. Additional development may be able to allow adaptability in some cases, but this will be at a cost across time, performance and lack of robustness.
With this considered, the rigidity of these solutions also poses a potential problem down the line when changes are required. What might be a small change for the stakeholder (e.g. swap the order of output columns in the final report of your model) might result in the need for a mass of time-consuming upstream coding changes that could risk the functionality of your model.
With purpose-built BI platforms these changes can be adapted for automatically, or a simple change (a single “drag and drop” or change of a setting) could cater for the change in seconds in many cases. In addition, these platforms are designed for large quantities of data. They will handle multiple millions of rows comfortably if best practices are followed, thus the possibility an automated process growing beyond its mean is much less of a concern.
In summary, pushing Excel to full roles it is not best suited for may work for a time. However, over the longer term it can creates restrictive limitations, vulnerabilities and inefficiencies.
Our advice – let Excel do what it does best and take advantage of powerful modern BI tools to expand your data maturity.
This article is part of our Data-Driven SMB series. For more information, advice and resources on how to accelerate your organisation’s data and analytics maturity, click here or contact us today.
Tim lives, sleeps and breathes analytics. A Chartered Management Accountant by trade, Tim has been with TrueCue for over a decade, having previously enjoyed roles as a Finance Analyst at Walt Disney and Auto Trader.