Why Data Analysis in Excel Could Be Hampering Your Data Analytics Strategy

Conducting data analysis in Excel is a popular way to examine and interpret large datasets. While Excel is a powerful tool, it can be limiting when implementing a comprehensive data analytics strategy.

Business leaders must leverage data to remain competitive and drive growth. Data — particularly insights and analytics derived from it — is critical for businesses to understand their customers, remain profitable, drive efficiency, and identify weaknesses competitors can exploit.

Explore why data analysis in Excel may not be the ideal option for most organizations looking to implement a data analytics strategy and how a new approach could bring new opportunities.

Why Microsoft Excel for data analysis could be limiting

While Microsoft Excel have many uses — and their capabilities continue to expand every year — they may not be the answer to all data analysis needs. Some of the strengths of Excel — such as the ability to quickly add new data to a sheet — can without proper controls lead to inaccuracies and misinformed decisions.

Spreadsheets also tend to proliferate data silos. If data needed for analysis is in a spreadsheet, it’s difficult to reuse across an organization. Excel is great for one-off analysis of small data sets, but when trying to define an enterprise data analytics strategy, Excel could be a component part but not the foundational tool.

Exploring advanced data analytics benefits

Data analytics is the process of examining datasets to draw conclusions about the information they contain. The more complex the data, the greater your needs. Consider the advantages of a more robust data analytics platform:

• Eliminating data silos
• Effectively handle large, complex datasets
• Enhance data accuracy and integrity by removing manual data entry and formula creation
• Foster collaboration, allowing multiple users to work with the same information simultaneously
• Go beyond basic analytical capabilities to explore opportunities to incorporate machine learning and advanced digital options
• Create interactive and dynamic data visualization
• Access data analysis in real time
• Personalized views of information

By using scalable data analytics tools, you can gain insights into operations, customers, and markets. A sound data analytics strategy can improve accuracy and efficiency, leading to better decision-making and a competitive advantage.

Looking to move beyond Microsoft Excel for data analysis? There are several options that can grow with your data analytics strategy.

How to get started with a data analytics strategy

To build scalable data analytics, assess your current state, develop a data strategy, invest in the right tools and technology, and build a data-driven culture.

Assess your current data state

The first step is assessing your current data state. This involves understanding your current data capabilities, identifying gaps, and recognizing opportunities.

Develop a data strategy

Once you’ve reviewed your current state, you need to develop a data strategy. This involves defining your data goals, prioritizing use cases and desired business outcomes, identifying the data you need to achieve those goals, and determining how you will collect, store, and analyze that data. Consider these questions:

• Do you have trusted data and systems to drive your data analytics strategy?
• How can you maintain a connected data ecosystem?
• What are the most important key performance indicators your business would like to track?
• What are the ideal outcomes your business is looking to achieve through data?
• What processes might new insights streamline?
• How can data be used to learn more about your customers?
• How might data help in fraud prevention?
• What reporting would you like connected with your data analytics?

Invest in the right data analytics tools and technology

To make the most of your data, evaluate what tools and technology you might need to help you achieve your organization’s goals. This includes data analytics software, data visualization tools, and data management systems. What is the right amount of money to spend on your company’s data strategy?

Build a data-driven culture

To succeed with a data analytics strategy, build a data-driven culture. Educate your employees on the importance of data, provide training on data analytics tools, and create a culture of data-driven decision-making.

Increasing efficiency by 20% — a data case study

CLA has worked with businesses to successfully transition from using spreadsheets in Microsoft Excel for data analysis to creating a more advanced data analytics strategy.

A manufacturing client struggled to keep up with demand due to inefficient production processes. By implementing a data analytics solution, they identified bottlenecks in their production line and increased efficiency by 20%.