Why you should Embed contextual BI directly into your operational applications

Adoption of BI software continues to increase at a rapid pace - not surprising given that workloads are increasingly migrating to the cloud. And the potential they offer in identifying actionable information from raw data, making way for data-driven decisions across industries, is unrivaled. However, analysts have pointed out that standalone BI solutions require users to exit operational applications to access reports, then reopen operational applications to take action based on the information received from the BI tool. A direct result of this is a reduction in operational productivity. Simply put, tasks take longer, opportunities are lost, and productivity takes a dive.

Embedded BI is the way forward.

In his Transforming Data With Intelligence paper titled Embedded Analytics: Closing the Loop Between Operational and Analytical Applications, analyst and researcher Wayne Eckerson writes that the best way to simplify and operationalize BI is to embed it directly into operational applications and processes that drive business.

The solution to this can be found with embedded BI, which integrates BI solutions within business software. It provides the existing software with data visualization, dashboards, and reporting capabilities.

This argument is supported by the Aberdeen Group’s report titled Embedding BI in Enterprise Applications: Magnifying the Analytical Impact, which found that organizations that used embedded BI saw notable benefits. These include a 20% year-over-year increase in operating profit, a 19% year-over-year increase in organic revenue, and a 16% year-over-year increase in operating cash flow.

One of the critical benefits of embedded BI is that it allows for in-the-moment decision-making with real-time or near real-time data. The proximity of real-time or near real-time data and decision makes improves the immediacy and relevancy with which urgent business-driving decisions can be taken. By incorporating BI into existing applications via dashboards, users can make more accurate decisions without switching between platforms.

Embedded BI simplifies user adoption as it can be plugged into an existing application without significant interruption. It also effectively eliminates the need for setup and training that a standalone BI tool often demands. Furthermore, it fosters agility and constant iteration as it is easy to access and use and allows for real-time changes to be made, as anyone with access to the dashboard can implement them.

Streamlining data with context

More often than not, BI tools with embedded visualizations that summarize important data do offer insights into the cause for a change or trends. If the user lacks the expertise for delf-service analysis, this puts an added burden on the developer to explain the report’s results. Contextual BI alleviates this by providing insights into the data amassed. These insights are generated by analyzing data from multiple sources and building data modules, thereby improving the relevancy of data. It takes embedded BI a step further, enabling a more universal use of reporting and analytics. It allows users to gain instant, dynamic, and guided insights with a single click, significantly reducing the “gut” requirement from the decision-making process. For example, manufacturing departments can avail alerts of key performance indicators; retailers can access weekly demand forecasts and find appropriate options to act in the moment, like automatically creating shift schedules. Similarly, inventory managers can assess the changes in stock and make decisions on replenishing orders based on trends in buyer behavior.

Embedding contextual capabilities into existing processes is an effective way to deliver relevant data to different departments and meet the requirements of each group. The analytical components are synchronized with the rest of the page so that when the context changes, so does the data. For example, if an operator chooses to filter a list of transactions on a page, the analytics will be updated to reflect that particular set of data.

The next level of operational productivity

For an organization to make the most effective use of BI data, visualization and actions need to work harmoniously, providing deeper insight and driving productive action. Dashboards allow for summarizing essential data at a glance and enable monitoring overall performance, letting the user control analysis. Adding contextual analytics to the equation makes the process more dynamic and supports decisions with a transaction or becomes the trigger for a decision. It also offers potential for automated actions or alerts that can help improve specific functions.

They are offering BI capabilities in a single application, which results in increased user adoption and productivity compared to using multiple applications for the same purpose. Combining contextual BI with embedded BI allows analytical and operational functions to be taken to the next level. It also gives users the insight and guidance they need better to understand the relationship between operational processes and business data. This in turn, allows them to react faster to emergent opportunities and evade or nullify potential threats.

You can find more information on how BI tools can help productivity and boost effectiveness at https://www.airquery.com/

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