Ad Hoc Analysis Best Practices

by | May 12, 2021 | Technology Featured

There are many ways to analyze data. Ad hoc analysis, however, is unique in that it’s about answering a one-time question, versus tracking something over time. The ability to perform ad hoc analysis allows enterprises to gain insights into things that would have been overlooked in the past.

Here are some ad hoc analysis best practices.

Invest in Employee Training

Your company can only be as good as the people working at it. Without great employees, even the best ideas and products can languish. This is why investing time and resources in employee training is such an important thing.

There are many areas in which it makes sense to spend significant time educating a workforce. Cybersecurity training is one of the most obvious examples of this. Phishing attacks are a prolific threat to enterprises, which is why keeping employees current is such an essential task. While the risks related to ad hoc analysis are different than cyber threats, both require employee training. Without it, enterprises are putting their critical operations, data and finances at risk.

Ad hoc analysis allows individuals with lower levels of data expertise to glean insights on their own. There’s a clear incentive for doing this, as it allows busines decisions to be made faster. It can backfire, however, if employees are using incorrect analyses to inform their decisions. Employees need to understand how to use ad hoc analysis tools, as well as how to manipulate and interpret data on a basic level. Without meeting these prerequisites, enterprises are setting themselves up for the risk of incorrect analysis, which can create massive headaches and potentially waste tons of resources.

The best ad hoc analysis tools will be intuitive and easy to use for individuals without deep data knowledge. Regardless, your organization needs to be proactive in ensuring all individuals using these tools are apt and understand them.

Build a Data-Driven Culture

When thinking about best practices, there are lower- and higher-level considerations that can affect your organization. One of the highest levels is being able to foster a data-driven culture within your organization.

A data culture is a massive asset in today’s world. With the ability to quantify and analyze more than ever, organizations can get ahead of their competition. This is only going to happen, however, if you can get the team on board. This is where ad hoc analysis comes into play.

Opening up data analytics to your whole team can be a tenuous process. There are certainly going to be risks involved in the process. Some individuals will see it as having to do more work that doesn’t interest them. Others will be excited, but get themselves in too deep too fast with their candor. It’s the role of leadership to guide this process by showing everyone how all can benefit from greater adoption of ad hoc analysis.

Analytics platform providers such as ThoughtSpot make a strong case for how ad hoc analysis can help foster a data-driven corporate culture. Search-based analytics, for example, make it easier than ever for employees without a data background to gain insights. With an arsenal of embeddable visualizations, it’s not hard to see how these tools can make workflows smoother.

Delineate What Needs Redundancy

Due to some of the issues already raised here, it should be clear that some things need to be double-checked before full implementation. While ad hoc analysis is a powerful tool, it can’t be used for absolutely everything. This is why it’s essential to have protocols for what kind of data and analysis needs to go through a redundancy process before being considered actionable. Having this procedure in place will make ad hoc analysis even more powerful, as it will increase confidence in results.

While there are incredible use cases for ad hoc reporting, best practice means understanding limitations. Ad hoc analysis needs to be verified by deeper expertise and methodology before being implemented into far-reaching corporate systems. It’s important to remember there needs to be a balance between speed and depth. Regardless, ad hoc analysis still helps enterprises get to where they’re asking the right questions sooner, even if some of the answers require a second pair of eyes.

Ad hoc analysis has many implications for enterprises today. Implementing these tools into employee workflows allows organizations to extract far more data insights than with more traditional methods.

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