The Universal Language for Data: Excel
The rise of sophisticated enterprise tools for data analytics has empowered businesses to derive more complex insights and do incredible things with data but this also creates a challenge: How do we standardise communication between tech-savvy data professionals and less technical stakeholders?
A better question is: how do we bridge the data literacy gap?
The answer, surprisingly, remains rooted in a tool that has been around since the '80s—Microsoft Excel.
Enterprise Tools Aren't Universal
Complex enterprise tools may offer powerful capabilities, from data mining to predictive analytics, but they often require specialised training. For data engineers and scientists, this is a non-issue. However, non-technical stakeholders, like marketers, HR professionals, and even C-level executives, may find these tools inaccessible. Consequently, sharing insights generated from these platforms can become a bottleneck.
The most generic of visualisation tools is Excel followed by only slightly more complex business intelligence tools like Tableau and Power BI. However, even tools like Tableau and Power BI get a push back sometimes (and yes even though you can export data to Excel from Power BI dashboards!).
Excel: A Common Language
In contrast, Excel serves as a universal currency for data exchange. It's a tool that almost everyone has at least a basic understanding of. When insights are translated into Excel sheets, the barrier to comprehension is dramatically lowered. Anyone with a basic understanding of Excel can open a workbook and immediately grasp the data points and visualisations presented, thereby making informed decisions more quickly.
Whilst not a general observations, anecdotally I've heard stories of executives rejecting Power BI reports and requesting Excel. Why? It's because that's what they know and they can therefore make more informed decisions.
Data Democratisation
Enterprise tools are undoubtedly effective at data crunching and detailed analytics. Still, their outputs often need to be democratised for broader consumption. Excel excels at this— pun intended. By making data easily understandable, Excel democratises information, enabling more people in an organisation to engage with the data, draw conclusions, and contribute to data-driven decision-making processes.
Seamlessness in Data Transfer
Excel's compatibility features also deserve mention here. Most enterprise tools have options to export data to Excel formats. This makes it easy for data professionals to transfer complex analytics into a universally readable format without losing data integrity. In essence, Excel becomes the bridge between data generation and data consumption.
Not Tied to the Cloud
The cloud is great - there is scalability, accessibility, reliability and security. But that accessibility piece comes with the need for an internet connection. The use case for on prem reports is for travelling leaders who want to review reports while on a plane.
Business Decisions Still Happen in Excel
Let's face it: Despite the allure of high-tech dashboards and real-time analytics, many critical business decisions are still made based on Excel sheets. Budgets are often drafted in Excel, performance metrics are tracked in spreadsheets, and forecasts are frequently modeled using Excel's array of functions. Excel provides a level of tangibility that other tools sometimes cannot, making it indispensable in decision-making processes.
Conclusion
As the landscape of data analytics tools continues to expand and specialise, Excel's role becomes even more crucial. It acts as the universal currency for data exchange, facilitating seamless communication between those deeply entrenched in data analytics and those who are not. In this way, Excel doesn't diminish in value in a world full of advanced enterprise tools; rather, it becomes the essential connector, enabling everyone in an organisation to participate in data-driven decision-making.
Last remarks - I leave you with this photo which is very real at some institutions!
