/ Why ad-hoc analytics is essential to BI innovation
Why ad-hoc analytics is essential to BI innovation
Businesses need to take full advantage of their collected data to drive insight and make decisions. However, many organizations are still using the same old strategies that don’t produce valuable results.
Data strategies don’t always succeed in the same ways for different businesses, and gauging the effectiveness of a given data strategy can be difficult. Still, many business leaders can just ‘feel’ that something is off.
When a business uses the same data strategy for a long time, the benefits of that strategy start to decline and stagnate. To really make the most of their business data, businesses need to innovate and use their data in new ways from time to time.
This is hard, because many businesses limit the sorts of people who can access, edit, and analyze business data. Their data strategies are top-down, with business leaders and senior staff doing the bulk of the data work.
If the same group of people keep performing data analytics, they’re more likely than not going to keep finding the same sort of insight. If a business wants to build fresh insight, they need new perspectives.
To build effective data strategies and find novel insights, businesses need to introduce more people to their business intelligence tools. They need to allow the average employee to perform data analytics.
Ad-hoc analytics is essential for driving this sort of employee-focused data strategy. Businesses that adopt ad-hoc analytics can draw insight from every level of their organization.
In short, it means that users can utilize pre-existing BI content as a jumping-off point for performing their own analysis. Employees can do things like reconfigure a visualization or swap out the data sets that power a dashboard.
For example, imagine a marketing employee wants to analyze the data related to a campaign that they recently launched. However, they don’t have a dashboard that can provide that information.
Instead of having to build a whole new dashboard from scratch, this employee can use pre-existing dashboards and visualizations to answer their business questions. They can take a dashboard from a previous campaign and edit it to show information about their new one.
They could switch out data sets while keeping others where they are. For instance, they could plug in their new campaign data into the visualizations while leaving their financial data where it is.
This way, they can calculate things like cost per conversion without having to power completely new dashboards or re-find relevant financial information.
The key to ad-hoc analytics is that all of this is employee-led. Employees don’t need to ask permission or wait for a supervisor to perform this analysis; they can just do it when the need arises.
Ad-hoc analytics allows average employees to perform analytics and find insight in a completely self-driven, agile way. It’s the perfect solution for businesses that have found their data strategies to be stale or outdated.
How can ad-hoc analytics help my business?
It can be hard to see how something as simple as allowing employees to edit BI content can be valuable to businesses. However, ad-hoc analytics is the real deal.
In recent years, it’s become clear that businesses that innovate with fresh digital strategies are better poised to win business. It’s not enough just to use data for a few insights in key departments; data needs to drive every level of an organization.
This has made building an employee-driven data strategy all the more crucial for businesses that want to win business and succeed against the competition.
It also brings more discrete and clear benefits to the businesses that choose to invest in it. Here are just a few ways in which an ad-hoc analytics strategy can bring clear benefit to an organization.
More agile decision-making
Ad-hoc analytics allows businesses to make decisions and react to changes much quicker than compared to top-down data strategies.
When a user has a business question they need an answer to, they can use ad-hoc analytics to get that answer quickly. They can cobble together a fresh visualization based on pre-existing data streams, allowing them to see new perspectives.
For example, a sales team member might want to see how supply chain disruptions will affect their product sales. They already have a dashboard that shows how the supply chain translates to product success, but it can’t perform any predictive analytics.
With ad-hoc analytics, this employee can use their pre-existing dashboard to perform new analysis. By updating their supply chain data, then performing some predictive analytics, they can see how supply chain disruptions impact sales success.
Ad-hoc analytics isn’t just for reactive data analytics. Businesses can use the agility it affords them to become more proactive.
Now, businesses don’t have to wait for data experts to design and implement BI content. They can just make new dashboards and visualizations when the need arises, letting data experts focus on more important things.
This dramatically lowers the time between someone asking a business question and getting a data-driven response. With a lower activation cost for dashboard use, businesses can bring BI to more of their operations.
New insights and fresh perspectives
Ad-hoc analytics helps businesses see their data in new ways. It also helps them to effectively integrate new data sources into their pre-existing analytics.
With the technology, businesses can allow all of their employees to become part of the data process. When someone has a business question that isn’t answered by a pre-existing dashboard, they can build an answer themselves.
This allows the average employee to ask questions about their data and get answers all on their own. If they want to perform an analysis that isn’t built into a dashboard or visualization, they can create a new visualization to do it.
When people use the same dashboards day in and day out, they start to get the same few data implications from them. Over time, a dashboard loses its ability to provide fresh value to a business.
This way, businesses can still use their reliable, incumbent dashboards to report on KPIs and track goal attainment, but also use new analysis to drive new growth.
Better data ingestion
Not every employee learns information in the same way. Some people are visual learners who can easily understand data at a glance. Other people need to put more effort in to understand their data.
At the most basic level, ad-hoc analytics can help employees customize and reconfigure their dashboards and visualizations to understand them better.
Often, this is more for accessibility than anything else. For example, someone who’s color-blind might not be able to gain effective insight from a color-heavy dashboard. With ad-hoc analytics, they can edit their dashboard to make it more effective for them.
Ad-hoc analytics can go beyond this and help every employee understand their data on a deeper level. Beyond just basic visualization, ad-hoc analytics encourages data curiosity.
With the ability to edit and change analytics based on the data they have access to, employees can form a more personal connection with their data. They can play around with it, seeing where different metrics trend and intersect for themselves.
This allows workers to go beyond surface-level analytics and really delve deep into what their data means. By encouraging this data curiosity, businesses can gain much deeper insight.
Ad-hoc analytics—essential to BI success
To compete in today’s markets, businesses need to constantly innovate their data strategy. It’s not enough to use the same old dashboards and visualizations you always do—everyone needs to look for fresh insight.
Ad-hoc analytics is a crucial part of this formula. It allows businesses to build bottom-up data strategies, where every employee can contribute their insight.
By implementing ad-hoc analytics, businesses can encourage data curiosity, make more agile decisions, and use fresh perspectives to find fresh insight.
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