/ Why embedded ad-hoc analytics is essential

Why embedded ad-hoc analytics is essential

Embedded analytics and reporting are extremely popular with both BI vendors and buyers. Businesses that are interested in a fresh style of implementation want to embed content right into their already existing sites and apps, and BI vendors are all too happy to sell them that capability.

While many businesses have started to implement embedded BI solutions, it’s very rare to see businesses actually making the most out of their embedded content. All too often, businesses only choose to implement static reports and baked-in visualizations, which prevents their solution from being as effective as it could be.

With modern embedded implementations, it’s possible to do so much more. One way businesses can improve the success of their embedded implementation is through embedded ad hoc analytics.

Embedded ad-hoc analytics turns basic, static embedded dashboards into flexible tools that can be used by any employee to perform novel analysis and drive fresh insight. It’s one of the most powerful ways that businesses can democratize their data.

Businesses that have already implemented embedded solutions should look seriously at upgrading their solution to focus on ad-hoc analysis. Businesses that don’t already have embedded tools should discuss next steps with their vendor to bring embedded ad-hoc tools to their operation.

 
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What is embedded analytics?

Embedded analytics are analytics that are ’embedded’, or built into, external websites and apps. They differ from regular, first-party analytics because they can be viewed by anyone with access to the page they’re presented on.

Regular, non-embedded data analytics produced by a BI tool can only be viewed and edited within that tool. In some ways, this is good; it allows businesses to limit access to their data only to people with the credentials to view it.

But as businesses grow and their data priorities shift, it can be very limiting to have every analytic, dataset, and visualization that a company produces trapped within their BI tool.

For instance, most BI tools charge their customers by the number of people that they have using the tool. For smaller companies, this cost is manageable, but as companies grow, it quickly becomes cost-prohibitive to let everyone have access to their tools.

This means that, to manage their costs, businesses that don’t use embedded analytics need to make careful choices about who has access to data and who gets shut out. These sorts of limitations make it very difficult to maintain a data-driven organization.

With embedded analytics, though, businesses can give freer access to their data to all levels of their organization. This way, even low-level and frontline workers can view the data that determines their day-to-day tasks and their business’s strategic goals.

Embedded analytics have use cases beyond internal data access. They’re especially popular with client-facing businesses that want to give the organizations that work with them more access to their data.

For example, a marketing firm might work with different external businesses to improve those businesses’ marketing efforts. That marketing firm will collect data on the success of their client’s campaigns and store that data within their BI tool.

Their clients will want to view that data, but it’s very difficult for the marketing firm to give access to that data in a meaningful way without letting the client into their BI tool. In these situations, both the provider and the client need a better solution.

By using embedded analytics, in conjunction with other tools like customer portals, providers can let clients access their data in a freer, more client-led way. Even better, providers can limit data visibility so that each client can only see their own data.

Embedded analytics is a powerful tool for improving data access, but it has some limitations. Until recently, embedded content could only be viewed, which meant that users accessing embedded content were very limited in what sort of conclusions they could draw.

With embedded ad-hoc analytics, this is changing. Businesses can embed much more freely now, and employees at all levels of an organization can do their own analytical work through their embedded solution. This helps to drive a more effective data environment, which leads to better insight overall.

 
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What is embedded ad-hoc analytics?

Embedded ad-hoc analytics is an approach to building and deploying embedded content that prioritizes ad-hoc utility. Simply, it’s embedded content that allows for ad-hoc analysis of the data it presents.

For those that don’t know, ad-hoc analytics is the opposite of static, pre-built reports and visualizations. With an ad-hoc approach to analytics, rather than users having to use the pre-built content in front of them, users can build their own analytics and visualizations based on the underlying data.

Most data-driven businesses prefer to use ad-hoc analytics over static reports and visualizations. It allows for deeper and more novel insights into data, while also helping every BI user to pick up important data analysis and investigation skills.

Think of a static report, like an earnings report, generated by financial software. This report might contain important information that people need to know, but it can’t be edited or changed in any way. This limits its utility beyond answering its core question.

With an ad-hoc approach, the data that powers this report can be fed into a BI tool. Instead of getting just one report about earnings, users can analyze every data stream that powers the report, allowing them to build all sorts of visualizations that give further context and insight into the data.

Even better, users can then also add data from other pieces of software, allowing the data from the report to meet needs in many other situations. Repeat this example across every data source across an organization, and it’s clear that ad-hoc analytics is an extremely powerful and extremely useful approach to data analysis.

Embedded ad-hoc analysis blends this freer, less rigid approach to data analysis with the power and flexibility of embedded content. With this approach, users can see their content on external sites and apps, and also edit and reconfigure that content to build new analyses and visualize other relationships.

 

How can embedded ad-hoc analytics help my business?

Many businesses have already moved away from static, pre-built embedded content towards embedded ad-hoc content that can be filtered and customized.

Every stakeholder in the embedded data, from low-level employees who have more context into company operations, to managers and executives who can do more unique analysis on their important business data, to clients who can analyze and visualize their data in ways that are specific to them.

 

Embedded ad-hoc analytics for frontline workers

Low-level and frontline workers often lack context for their position that can lead to fundamental problems. With static reports, these employees can’t get information that would otherwise allow them to do their jobs more effectively.

For example, a production line foreman might have access to an embedded dashboard on company-wide quality control issues. This dashboard allows the foreman to access company-wide statistics on production errors, but lacks further information about the issues.

Based on this report, the foreman knows that there are quality control issues on their production line that need to be fixed, but they don’t know where the issues are, and they don’t know how to fix them in a timely manner.

If the foreman had the ability to drill down into the company-wide data, by filtering it just to their production line’s data or analyzing production issues by cause, they’d be able to solve their quality control issue much faster. With embedded ad-hoc reporting, they could do all that, and more.

With more context about broader company goals and the goals of their position and the ability to track and customize their KPIs more closely, low-level and line-level employees can perform much better. They have more latitude to do their jobs correctly and can let data drive their day-to-day decisions.

 
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Embedded ad-hoc analytics for managers and executives

At the mid and high levels of an organization, the demand for data is the strongest. Managers and executives need actionable data to do their jobs effectively. With static reports and visualizations, even embedded ones, they’re stuck in the past and can’t get answers to the questions that they have.

Static visualizations and pre-built reports can be useful for meeting expected day-to-day data needs, but when new business problems crop up, pre-existing data analyses are often insufficient.

For instance, a business might be preparing for the launch of a new product when a major competitor launches a product that fills a similar product niche, blindsiding all the senior staff involved and forcing them to rethink the strategy for their product launch.

To build out a new strategy quickly and ensure that their own product launch isn’t a disaster, the managers and executives for the launch need data. However, all of their pre-built reports and visualizations don’t take their competitor’s launch into account.

These users need to be able to quickly build out new data analyses that accurately represent the situation. Otherwise, they’ll have to use outdated information to make their decisions. With static embeds, they’ll have to wait until their data scientists and IT specialists come up with something. Until then, the senior staff will be working in the dark.

With embedded ad-hoc analytics, the product launch team would be able to hit the ground running. They’d have the ability to start building out new dashboards and visualizations as soon as they heard the news, which would allow them to figure out their new strategy as soon as possible.

Businesses often have a hard time reacting to new, unforeseen business problems. Embedded ad-hoc analytics can’t completely solve the problem of being unprepared when a disaster occurs, but it can help businesses react to problems in an intelligent, data-driven way.

 

Embedded ad-hoc analytics for clients

Client-facing businesses often have issues with properly communicating data to their customers. Automated reports and Excel spreadsheets can only go so far. In today’s business world, clients expect much more than that.

Embedded analytics is a good first step. With regular embedded analytics, clients have much more flexibility in how they can access their data. Instead of relying on weekly reports or having to beg their account executive for data, they can access it anytime, in a context they’re already familiar with.

Regular embedded analytics can be limited, however. Clients expect to have ownership over their data; they won’t be happy with static analytics. They want to be able to drill down, reconfigure it, do fresh analysis, and see it in other contexts. In short, they want to be able to edit it in an ad-hoc way.

Of course, embedded ad-hoc analytics allow them to do just that. For client-facing businesses, embedded ad-hoc analytics is a good business choice. By allowing clients to have more ownership over their own data, they can easily win new business and keep the clients they do have happy.

 

Embedded ad-hoc analytics—greater flexibility, more insight

Embedded analytics revolutionized the BI space when BI vendors first introduced the technology. Businesses no longer needed to visit their tool to see their data, which streamlined their workflows and saved them money.

Now, embedded ad-hoc analytics is about to revolutionize it again. The technology completely unchains BI users from their tools, leading to even greater productivity gains and allowing more businesses to use data to drive insight.

For more information on how embedded ad-hoc analytics can help your business or if you want to know which BI tool is best for your situation, contact us today. Our team can connect you with the tool that will meet your needs, and help you to implement any sort of implementation you can come up with.

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