TDWI | Training & Research | Business Intelligence, Analytics, Big Data, Data Warehousing

Does the Analytics Tool Matter?

As data analysis becomes increasingly important, the debate over which tools to use also increases. However, the most important factor is the actual analytics value a tool provides to the business.

• By Mark Worthen
• September 14, 2017

I have been involved in data, reporting, and data analysis/BI for years, and I will admit there have been times when I have been a tool bigot. I would see someone performing analysis in Excel, Access, or some other tool and think to myself, "Get a real analytics tool!"

I believe anyone who has worked in data analysis understands the importance of good data. I have seen (and unfortunately helped create) some beautiful dashboards and analytics applications that proved to be nothing more than "lipstick on the pig" due to the poor quality of the data. For this article, I assume you have well-structured data of good quality.

For Further Reading: Making Peace with the Venerable Old Spreadsheet Q&A: Advanced Business Analytics Tools Promote Pervasive BI Four Keys to Achieving Value Faster from BI and Analytics

Does Excel Cause Errors?

An article from a few years ago on newstatesman.com titled "Is Excel the Most Dangerous Piece of Software in the World?" points out that Excel was the software JPMorgan used to track the "value-at-risk (VaR) model for the synthetic portfolio." The risk model was "operated through a series of Excel spreadsheets, which had to be completed manually, by a process of copying and pasting data from one spreadsheet to another."

In the process of creating the spreadsheets, Morgan employees had "divided by their sum instead of their average." In essence, the author blames Excel for a human error.

I doubt there is any tool more used and loved by the masses for tracking, analyzing, and massaging data than Excel. It is ubiquitous. However, as the article points out, and as I have seen many times, Excel can easily result in errors that lead to poor business decisions, but that certainly doesn't make Excel a bad choice as a tool for doing analysis.

After all, I have also seen BI dashboards or applications from different vendors that have invalid calculations that, in turn, also led to poor business decisions.

Rather than questioning the validity of the tool, we should question the validity (or, in some cases, the existence) of the process and/or standards used to create analytics.

How Does the Analytics Tool Matter?

Does Excel or any of the myriad of other options matter?

More than the tool, what matters is the result of the analysis. Does the analysis provide useful information to the business? Getting to the point of finding that useful information can be time-consuming and require patience. Sometimes as we work to achieve the desired analysis, our activities may feel akin to Thomas Edison's efforts to create the light bulb: "I have not failed. I've just found 10,000 ways that won't work."

Does the tool matter? Only in that it is required to achieve a desired goal. Does the specific tool choice matter? Yes and no.

Yes, the tool matters because you need to match the right tool to each individual. You shouldn't tell someone who doesn't understand databases or programming to use R to perform their analysis. At the same time, the tool does not matter because all the business really needs is the analytics output. The business does not care what tool is used to generate the output. It only cares that the analysis is correct.

In matching tools to users, there will likely be some training involved no matter what product is used. However, matching the tool to the user will minimize the time required to generate usable analysis and lead to continued usage and value to the organization.

Evaluate the Bottom Line

Data analysis is a service provided to the business. As with any service, the organization is looking to get the greatest return on investment.

Does the analytics service (whether IT generated or self-service) provide a good value? If a tool is adopted, used, and its output provides value to the business, then the tool provides value. A different tool may provide greater functionality or a more intuitive interface, but if the tool is not adopted and used, it provides little or no value.

The value equation for your analytics service includes cost, usage, time-to-results, and accuracy. As a BI professional, you are a service provider. Increase the success of your BI projects by focusing on providing the best value.