As a company gets larger and wins more business, they naturally start to collect more data. One challenge that businesses face as they grow is how to put this data to work. Adapting to new data implementations, however, isn’t an easy task.
Businesses that haven’t used data at all in the past now need to develop data-driven strategies for all parts of their operations. That’s not something that can happen overnight. Businesses need to build a data culture, often from scratch, to stay competitive.
One BI feature that can help businesses build their data culture is ad-hoc analytics. Ad-hoc analytics allows employees to analyze and visualize their data without relying on pre-built dashboards or static reports.
What are ad-hoc analytics?
Ad-hoc analytics is the name for a collection of BI features and strategies that allow users to edit, reconfigure, and adapt their current analytics and visualizations toward novel, self-guided analysis.
That explanation is kind of academic—it may be easier to understand ad-hoc analytics through an example.
Say a marketer is trying to analyze their campaign data. They want to analyze their social media campaigns against their banner ad data, but they only have visualizations that compare social media against search ad data.
In tools that don’t have ad-hoc analytics, they’d be stuck with their current visualizations, meaning they couldn’t answer their novel business questions. With ad-hoc analytics, though, they can edit the visualizations they have access to.
They could edit their current visualization to compare banner ad data instead of search ad data, or they could even build a completely new visualization to answer their new business question.
The key to all of this is that it’s self-led; at no point in the ad-hoc analytics process does the user have to reach out to a visualization designer or data expert to do the analysis for them. They can answer their own business questions with the tools they already have access to.
Ad-hoc analytics allows for things that more static, inflexible tools could never enable. They’re an important element of self-service BI tools since they allow users to solve their own business problems without referring back to an expert.
Businesses that want to build an employee-driven data culture need ad-hoc analytics. Ad-hoc reporting has various benefits that make it essential for businesses that want to survive and thrive.
How ad-hoc analytics can benefit your business
Ad-hoc analytics helps teams collaborate
Ad hoc reporting and analysis tools promote teamwork by making it simple to create reports and visualizations. From there, it’s easy to share that ad-hoc work with other employees, teams, and departments.
It also allows for greater flexibility in how teams incorporate their data into other departments’ data strategies. If two departments want to build collaborative dashboards that combine their data streams, they can just do that instead of having to wait for a data professional to do it for them.
Ad-hoc analytics offer flexibility
Designers like to think of their dashboards as one-size-fits-all solutions, but that’s not always the truth. Some people want to edit or reconfigure the dashboards they have access to so that they can understand those dashboards better. Ad-hoc analytics allows users to edit and personalize their dashboards, without impacting the underlying data analytics.
Sometimes, though, dashboard users do want to impact the underlying data analytics. With ad-hoc analytics, they can build personalized data analyses, visualizations, and data flows that can drive more specific, personalized insights.
Ad-hoc analytics speeds up reporting
A well-designed dashboard is very useful, but it takes a lot of time to make a dashboard really shine. Businesses don’t always have the time to design a whole new dashboard when they want an answer to a new business problem. Rather than building new dashboards and reports from scratch, they can just rely on ad-hoc analytics.
Ad-hoc analytics is the ‘quick and dirty’ approach to answering business questions. They might not be as visually effective as a purposefully designed dashboard, but they get you an answer, which is all you need.
If the ad-hoc question becomes a common problem, then it can be useful to build a dashboard to solve it. But for one-time questions that need one-time answers, you can’t beat ad-hoc analytics.
Ad-hoc analytics frees up your data experts
With ad-hoc reporting, your employees can design their own visualizations and solve their own business questions. They don’t need to go to data experts for technical support for every little visualization.
No one will be happier about this than your data team. Since they don’t have to respond to every data request in your business, they have the time to focus on things that actually require their expertise.
Ad-hoc analytics empowers your employees
With ad-hoc analytics, your employees are empowered to design their own visualizations, build their own dashboards, perform their own analyses, and solve their own business problems. This means that they’re in charge of their own data experience.
Many businesses can’t manage to build a data culture because their employees don’t have the tools they need to succeed. If you give your employees the opportunity to build their own data culture ad-hoc, they’ll make it happen.
Ad-hoc analytics offer new perspectives
When a team or department keeps using the same metrics and visualizations over and over again, they can start to become blind to new trends and fail to spot new opportunities.
Every team has blind spots, but if they’re using the same visualizations day in and day out, there’s no way that they can ever notice them. This is where ad-hoc analytics is especially valuable.
Ad-hoc analytics allows teams to change things up, remix and reconfigure their data, and hopefully, discover their blind spots and biases. It allows for new data perspectives, changing the ways that teams look at their analytics.
Ad-hoc analytics saves money
With all the time saved, trends spotted, and insight gained with ad-hoc analytics, not only can it save money, it can also open up completely new sources of revenue and boost your overall profits.
Businesses don’t just build data cultures because they like data. They make data such a priority because data analytics is valuable. Ad-hoc analytics, with its speed and flexibility, is an even better value proposition.
Ad-hoc analytics vs. self-service analytics
Ad-hoc analytics are related to another fairly recent concept in BI design—self-service analytics. When explaining the two approaches, they can seem very similar, but they have some key differences that set them apart.
This approach is similar to ad-hoc analytics, which lets any user build their own dashboards and visualizations and adapt existing ones without any sort of oversight. Ad-hoc analytics are a central component of many self-service BI strategies, but the presence of ad-hoc analytics doesn’t automatically mean a tool is self-service.
Ad-hoc analytics just offers users the flexibility to build their own content; it doesn’t assume that users won’t know how to. In fact, users often need more BI knowledge and expertise with their specific tool to make good use of ad-hoc features.
Ad-hoc analytics—empower your employees with data
The best way for businesses to build an effective data strategy is from the bottom up. By empowering the average employee to use data to make their own decisions and drive insight, businesses can leverage their data more easily.
When a rapidly growing business starts looking for a BI tool, they need to keep this in mind. Ad-hoc analytics may seem like a simple feature, but it’s essential for implementing effective data strategies and making your tool work for you.
Check out some related resources:
Nucleus Research: Domo’s ROI as a Data Platform
POV: Next-Generation Banking
Domo for Financial Services Playbook
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