What is needed to operationalize business intelligence | cullen4congress

What is needed to operationalize business intelligence?

As marathon runners near the finish line, well-meaning sideline supporters often clap with words of encouragement: “Great job. Keep going. You’re almost there. » That last stretch can seem like an eternity, though, perhaps the most mentally and physically challenging part of the race. When it comes to leveraging business intelligence and artificial intelligence (AI) insights across the organization at scale, the marathon analogy rings true, with companies struggling to conquer the elusive “last mile.” Too often, the data, results, and even insights are there, but delivering the right intelligence to the right people at the right time adequate to inform decision making is where organizations get stuck.


Let’s explore what it takes to put business intelligence insights to work, driving more value from data to create business efficiencies and better results.


Put data in context to create business intelligence

Data alone is far from intelligent and can quickly become a burden for organizations overwhelmed by too much data, data without context, or poor data quality. A recent Gartner survey found that 31 percent of executives say « lacking the right kind of data » is a « very challenging » data and analytics problem.[1]

Without the right kind of data, delivering valuable business intelligence, business insights, and real-time analytics to support decision-making becomes nearly impossible. The same survey revealed five signs that your business users are missing rich context, if:

  1. Switch frequently between screens to perform the analysis necessary to decide.
  2. Consider that 99 percent of the information presented is irrelevant to your decision.
  3. Comment that the risks and impacts of the decision are invisible or unclear.
  4. He blames the lack of information provided for the negative impact on business results.
  5. Describe business opportunities lost due to lack of decision support.

To help understand your content, text mining is an essential business insight as it provides much-needed functionality to acquire data from a wide variety of structured and unstructured sources, including social media feeds and siled documents. of content. As content from multiple sources is ingested, natural language processing and AI are applied to make sense of millions of documents at once, helping support contextual decisions.

Discover the feeling, emotion and intention.

When it’s done right, text extraction It doesn’t stop there, relying on algorithms to extract additional actionable business information from unstructured user-generated content. According to Gartner, by 2025, AI for video, audio, vibration, text, emotion, and other content analytics will spark major innovation and transformation in 75 percent of the global Fortune 500 companies.[2]

Separating subjective and objective statements, understanding the reasons behind positive or negative tonality, and detecting underlying emotions, intentions, and concerns is a game changer for organizations. As a result of gaining insights and intelligence from customers, employees can deliver more personalized and empathetic experiences, supported by intelligent routing and escalation and rapid identification of service trends and issues.

Switch to autonomous analysis

Another way to deliver business insights at scale is to address gaps in consumer-friendly analytics by making AI learnings accessible to business users in a self-service fashion. This allows companies to use advanced and predictive analytics techniques without the need for teams of analytics developers and data scientists.

Data discovery tools Providing drag-and-drop experiences, they give employees the ability to explore, interact, and analyze business intelligence. By eliminating the need to convene a data scientist, organizations push business intelligence to the finish line, amplifying the benefits of AI-enriched insights to help drive critical decisions. Additionally, by shifting the reporting and analysis workload away from IT and engineering, organizations generate significant time savings and efficiency gains.

Turn business insights into visual insights

Without easy-to-use data discovery tools, it can be challenging to get advanced intelligence from your data and into the hands of business users, posing an obstacle to widespread scalability. Another way to put business intelligence insights to work is to turn big data into interactive visualizations.

By integrating and incorporating rich, interactive business intelligence reports and dashboards in legacy and cloud applications, users can take advantage of self-service reporting, with quick access from any device within their workflows.

Also, with advanced data exploration tools, users can focus only on the data that supports their function, choosing to apply advanced analytics techniques for the desired visualizations or select from recommended smart visualizations. Without any coding, people can gain insights based on selected data, using diagrams, bubble charts, pattern mining, decision trees, and other visual assets.

Rely on a foundation for value-driven intelligence

A final hurdle to putting business intelligence to work is the use of multiple, siled tools to carry out various AI and analytics processes. Being able to support rich, collaborative decision-making processes across an organization requires users to have access to data, knowledge, and tools to navigate information, regardless of skill set or role.

With a unique artificial intelligence and analytics platform, organizations can reduce the complexity of business intelligence information, benefiting from comprehensive capabilities to scale securely across the enterprise. Relying on a single source for text mining, data discovery, and business intelligence and reporting means organizations can minimize the effort and expertise required to deliver value from AI and put big data insights to work faster. .


Ready to take your business insights and analysis through the last mile for widespread business benefit? find out how master modern work with open text.



[1] Gartner® Use Multi-Structured Analytics for Complex Business Decisions, David Pidsley, Nov 10, 2022
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the US and internationally and is used herein with permission. All rights reserved.

[2] Ibid.