Why Ad Hoc Analysis Matters for Your Business
In today’s fast-paced business world, companies need to make informed decisions quickly to stay ahead of the competition. The ability to extract insights from vast amounts of data has become a necessity for businesses of all sizes. Ad hoc analysis is a valuable tool that enables companies to make data-driven decisions by quickly answering specific questions with relevant data. By conducting ad hoc analysis, businesses can gain insights into customer behavior, identify areas for improvement, and make informed decisions in real-time. In this article, we will explore what ad hoc analysis is, how it differs from other types of business intelligence, and the benefits and drawbacks of this approach.
What is Ad Hoc Analysis?
Ad hoc analysis refers to the process of conducting analysis on a specific set of data to answer a particular business question that may arise unexpectedly. It involves creating a custom report or visualization that provides quick and meaningful insights to stakeholders who require an immediate answer to a specific problem. Ad hoc analysis is different from routine or regular reporting, which may not always provide the specific insights or answers that stakeholders require.
Understanding Ad Hoc Analysis
In order to better appreciate ad hoc analysis, it is important to understand what it does not entail. Constructing an interactive dashboard or a Microsoft Excel report, is not ad hoc because it is something designed for the user to use over and over again for a long period of time. A report released for a company at the end of each year is also not an ad hoc report because that is something that analysts spend a lot of time putting together, is not usually customized and is not a one-time dive into the data.
Ad hoc data analysis includes certain characteristics. For instance, an ad hoc report generally:
- Contains only one or a couple of questions that an analyst answers one time, or that a user answers for themselves with a self-service BI tool
- Provides fairly quick-to-produce answers, especially when compared to other tasks that data scientists perform, such as managing a data warehouse for an institution, building a dashboard, or creating an in-depth data visualization for end-users
- Produces metrics that represent a snapshot of one particular moment in time, on an as-needed basis
- Contrasts with a canned report, which answers questions people think of ahead of time
One of the main ways that ad hoc data analysis differs from other types of analysis is that people who aren’t experts on ad hoc reporting tools (or who aren’t even familiar with data management in general) can still be empowered to delve into company data themselves. With the increasing integration of machine learning into self-service business intelligence tools, ad hoc analysis can become even more powerful and insightful, as algorithms can help identify trends and patterns that may not be easily discernible to human analysts. Understanding what ad hoc data analysis is and how it works is important when deciding when to best use this method of reporting.
How is Ad Hoc Analysis Different From Other Types of Business Intelligence?
Ad hoc analysis differs from other types of business intelligence in that it is designed to answer a specific question or set of questions quickly. Other types of business intelligence—such as regular reporting, static reports, spreadsheets, or interactive dashboards—tend to be more standardized and ongoing.
Ad hoc analysis is also often conducted by end-users who may not be familiar with data management and analysis tools, whereas other types of BI solutions may be created and managed by data analysts or IT professionals. Additionally, ad hoc analysis is usually a one-time pull of data that may not be requested again, while other types of business intelligence are often regularly produced and used to track trends and performance over time.
The use of KPIs is also more common in other types of business intelligence, as they are often used to track and measure ongoing performance against established targets or goals. In contrast, ad hoc analysis is typically used to gain insight into a specific issue or question and may not be directly tied to established KPIs.
Benefits of Using Ad Hoc Analysis to Explore Data
Once you are aware of how ad hoc analysis works, you might begin to explore some of its benefits. Some of the benefits of ad hoc reporting include:
- Giving end users the ability to find answers to a specific business question that regular reporting may not answer
- Granting other teams—such as the financial reporting and IT departments—the freedom to continue working on their own projects rather than responding to multiple requests for data exploration
- Acknowledging the need for business users to have access to data sources in order to make decisions for the company at any time
- Making use of custom visualizations such as graphs to understand the story behind big data
- Drill down to underlying data to answer questions in real-time
- By incorporating segmentation, ad hoc analysis can provide targeted insights into different customer groups or business areas
There are many advantages that make this type of analysis attractive to a wide variety of businesses.
Disadvantages of Using Ad Hoc Analysis to Explore Data
It is important to keep in mind that ad hoc analysis comes with some disadvantages as well. A few of the cons of this type of analysis compared to others include:
- The risk that users who are unfamiliar with the data or with analysis tools will make incorrect business decisions from the data they pull and examine
- The potential for companies with sensitive data to still require users to go through data analysts or the IT department for each ad hoc request, which can be time-consuming
- The chance that one single data pull will not give the full story and leave out crucial details for decision making
- The risk that data becomes compromised behind the scenes, with ordinary users having no way to tell that something is amiss
Although there are many advantages to ad hoc reporting, always consider the downsides before incorporating any new methodology into your company.
Ad Hoc Reporting Examples and Use Cases
Another way that managers can help decide whether an ad hoc data pull or another type of data analysis service is best for them is by examining some real-life cases of ad hoc reporting. Although most companies can benefit from many kinds of analysis, there are some industries that lend themselves especially well to ad hoc analysis.
Sales and Retail
Whether your business conducts sales online, in a brick-and-mortar location, or a combination of both, you know that best practices involving the exchange of goods and services are something that evolves rapidly. Because of this, managers do not want to have to wait for yearly, quarterly, or monthly reports every time they have a question regarding the performance of their business.
One example of ad hoc analysis in the sales industry is looking at how well a product performed after the company spent a large amount of money promoting that product for a week. The sales team could, for instance, pull up their profits for the week before, during, and after the promotion to see if the extra advertising cost was worth it.
Employee turnover and satisfaction are big issues in most lines of work, since hiring and training new employees is time-consuming and a large financial expense. Due to this, most businesses have practices in place to help ensure that employees stay with the company for more than just a few months, barring extenuating circumstances such as a family emergency that causes an employee to move out of town.
If there is a sudden increase in employee turnover, managers can run an ad hoc report to look at any factors that may be contributing to the turnover. Sometimes, there are things that managers might not consider until they drill into the data. For example, they may find that employees who work for one specific manager are leaving, rather than the cause being employees being dissatisfied with the company as a whole.
As an industry that relies on timely good decision-making, it is imperative that people working in the healthcare field be able to examine data quickly. For example, if there is a recent outbreak of an illness in a community, a medical facility should be able to quickly examine the demographics of anyone who recently entered their facility with symptoms of the illness. This can be important when it comes to tracing and containing the spread of disease.
How to Conduct Ad Hoc Analysis
It is important for both business intelligence professionals and anyone who has a stake in the business to know how to perform their own ad hoc analysis. Some steps to follow when attempting to answer an ad hoc data question include:
- Pinpointing the data source that you wish to use
- Taking a look at the data source and determining whether or not there are any other questions to answer
- Using business intelligence tools to produce visualizations that tell a story
- Interpreting the results of your analysis and making suggestions for best business practices going forward
Keep in mind that it might take some trial and error to figure out the best way to go about examining the data specific to your company.
Best Practices for Ad Hoc Reports
Once you have a good routine in place for ad hoc reporting, it is wise to implement some best practices.
Firstly, it is essential to ensure that the data you are using is up-to-date and free of errors. You do not want to base your decisions on outdated or inaccurate information. To prevent this from happening, you might enlist the help of your company’s IT department or data analysts to clean the data before you perform any analysis. They can check for any inconsistencies, duplicates, or missing values, and correct them. This will help you save time and prevent you from drawing incorrect conclusions.
Secondly, it is crucial to use the correct BI tool for the job. There are various BI tools available in the market, and each one has its strengths and weaknesses. For example, if you work with sensitive data, you should check to see if the tool you want to use provides fine-grained security permissions. This can help you make sure you get the right data to the right people at the right time. Similarly, if you are dealing with large datasets, you’ll need a tool that is designed to handle that volume of data. Choosing the right tool can make a significant difference in the accuracy, efficiency, and reliability of your ad hoc reporting.
Finally, when it comes to explaining your findings to others, it is essential to communicate your insights in a way that people across your organization can understand. Avoid using technical jargon or complex terminology that may be unfamiliar to your audience. Instead, use simple language, visual aids, and clear examples to demonstrate your findings. This will make it easier for others to grasp the key takeaways and make informed decisions based on your insights.
Leveraging Ad Hoc Analysis for Better Business Decisions
Ad hoc reporting of business data is a great way to quickly enable everyone in your organization to make better decisions. This method allows everyone on your team to get involved with examining the data, rather than only the employees who are specifically trained in data science. It also allows people to learn the answer to very specific questions that a dedicated data analyst might not know to include in their regular reports.
Companies wishing to take advantage of the pros of ad hoc data analysis should consider using a tool like Spider Impact from Spider Strategies. With its powerful BI capabilities, Spider Impact makes it easy for users to perform ad hoc analysis and gain valuable insights from their data. Whether you’re looking to improve your decision-making processes, gain a competitive edge, or drive business growth, Spider Impact can help.
If you’re interested in seeing what Spider Impact can do for your business, we encourage you to sign up for a free test drive or demo today. With its user-friendly interface and powerful features, Spider Impact is the ideal tool for businesses looking to leverage ad hoc analysis to make better decisions and achieve their goals.
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