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3 reasons your business needs Ad Hoc analytics in 2021

Ad hoc analysis can make decisions more relevant and faster by empowering regular users to get answers from data

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As more companies move toward becoming data-driven in their decision-making, the question inevitably arises what tech and tools are necessary to facilitate this level of analysis. After all, enterprises driven by data are 58 percent more likely to exceed their revenue goals than businesses not yet driven by data, as CIO Dive reports. But before companies invest in new or updated data analysis systems, leaders inevitably want to know what value this tech can provide through its capabilities.

One such example is self-service analytics. A company with existing legacy business intelligence (BI) infrastructure might wonder whether it’s really worth it to upgrade, as it will require an up-front investment. But what the company must also measure is the cost of reporting lags and backlogs in terms of how much it can hinder effective decision-making.

Here’s more on the value of providing ad hoc analysis in an organization — which is an important consideration for companies aiming to drive decision-making processes with data.

What Is Ad Hoc Data Analysis?

For a long time, organizations had to depend on static reports produced by BI power users with access to siloed data. While this approach did provide decision-makers with some data insights, the static nature of the reports and the amount of time it’d take to create them left little room for users to ask important questions in the moment. Depending on the demand for BI reports and the legacy tech in play, the “average” employee could find themselves waiting days, weeks or even months for insights.

Ad hoc analysis, on the other hand, empowers users to ask their own questions, query data and receive insights as needed. As TechTarget notes, ad hoc analytics answer specific business questions — like a user creating a report that does not currently exist, or digging deeper into a static report for additional useful context.

Here’s just one example of ad hoc reporting in action from Vents Magazine: Although physicians have specialized knowledge about how to treat patients, they may not be especially tech-savvy — nor have the time to request specific patient reports from a data specialist throughout the course of a day and wait on the results.

Ad hoc analytics allows physicians to ask questions, get answers and configure the data into easy-to-understand formats like charts and graphs. So, this medical expert can get a quick, personalized, data-driven view into patient care results to aid decision-making.

Benefits of Ad Hoc Analysis 

What benefits does conducting ad hoc data analysis unlock for organizations?

Faster business decision-making: In a high-speed business environment where time is quite literally money, the speed (or lack thereof) of a decision can affect its outcome just as much as the actual content of the decision itself. In other words, making the right decision too late can nullify its positive outcomes. So, enterprises benefit when front-line employees have access at their fingertips to key data insights they can incorporate into timely decision-making.

More relevant decision-making: Self-service analytics platforms powering ad hoc reporting provide interactive data visualizations to users as opposed to static reports. This enables users to zoom in and out — to look at the data insight from different angles — and ask addition questions as needed. Rather than dealing with the limitations of a static report, users can access the most relevant insights to the decisions at hand before proceeding.

Streamlined IT workflows: When IT/data teams are tasks with querying data and compiling reports at the behest of every other team within an organization, they can become bogged down with endless requests — necessitating they devote much of their time to report generation and delivery. Introducing self-service, ad hoc analytics tends to reduce this backlogged workload, freeing up IT specialists to work on higher-order projects.

Ad hoc analysis can make decisions more relevant and faster by empowering regular users to get answers from data — leading to benefits such as an improved customer experience and better products and services both of which feed into improved customer satisfaction – all while reducing the burden on the IT team. 

3 Reasons Your Business Needs Ad Hoc Analytics in 2021

As more companies move toward becoming data-driven in their decision-making, the question inevitably arises what tech and tools are necessary to facilitate this level of analysis. After all, enterprises driven by data are 58 percent more likely to exceed their revenue goals than businesses not yet driven by data, as CIO Dive reports. But before companies invest in new or updated data analysis systems, leaders inevitably want to know what value this tech can provide through its capabilities.

One such example is self-service analytics. A company with existing legacy business intelligence (BI) infrastructure might wonder whether it’s really worth it to upgrade, as it will require an up-front investment. But what the company must also measure is the cost of reporting lags and backlogs in terms of how much it can hinder effective decision-making.

Here’s more on the value of providing ad hoc analysis in an organization — which is an important consideration for companies aiming to drive decision-making processes with data.

What Is Ad Hoc Data Analysis?

For a long time, organizations had to depend on static reports produced by BI power users with access to siloed data. While this approach did provide decision-makers with some data insights, the static nature of the reports and the amount of time it’d take to create them left little room for users to ask important questions in the moment. Depending on the demand for BI reports and the legacy tech in play, the “average” employee could find themselves waiting days, weeks or even months for insights.

Ad hoc analysis, on the other hand, empowers users to ask their own questions, query data and receive insights as needed. As TechTarget notes, ad hoc analytics answer specific business questions — like a user creating a report that does not currently exist, or digging deeper into a static report for additional useful context.

Here’s just one example of ad hoc reporting in action from Vents Magazine: Although physicians have specialized knowledge about how to treat patients, they may not be especially tech-savvy — nor have the time to request specific patient reports from a data specialist throughout the course of a day and wait on the results.

Ad hoc analytics allows physicians to ask questions, get answers and configure the data into easy-to-understand formats like charts and graphs. So, this medical expert can get a quick, personalized, data-driven view into patient care results to aid decision-making.

Benefits of Ad Hoc Analysis 

What benefits does conducting ad hoc data analysis unlock for organizations?

Faster business decision-making: In a high-speed business environment where time is quite literally money, the speed (or lack thereof) of a decision can affect its outcome just as much as the actual content of the decision itself. In other words, making the right decision too late can nullify its positive outcomes. So, enterprises benefit when front-line employees have access at their fingertips to key data insights they can incorporate into timely decision-making.

More relevant decision-making: Self-service analytics platforms powering ad hoc reporting provide interactive data visualizations to users as opposed to static reports. This enables users to zoom in and out — to look at the data insight from different angles — and ask addition questions as needed. Rather than dealing with the limitations of a static report, users can access the most relevant insights to the decisions at hand before proceeding.

Streamlined IT workflows: When IT/data teams are tasks with querying data and compiling reports at the behest of every other team within an organization, they can become bogged down with endless requests — necessitating they devote much of their time to report generation and delivery. Introducing self-service, ad hoc analytics tends to reduce this backlogged workload, freeing up IT specialists to work on higher-order projects.

Ad hoc analysis can make decisions more relevant and faster by empowering regular users to get answers from data — leading to benefits such as an improved customer experience and better products and services both of which feed into improved customer satisfaction – all while reducing the burden on the IT team. 

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