Business intelligence is critical in today’s companies for helping leaders make smart decisions. For example, using data from a variety of sources, an organization might be able to determine what products or services customers would most like, how to market them most effectively, and where to make them available for optimal customer convenience.
Sophisticated analytics drive these decisions, which can help companies optimize resources and give them an edge over the competition. Business intelligence tools are available for companies of all sizes across industries. Given the power of this technology, it’s not a stretch to say that business intelligence can make or break a company’s success.
In the following sections, we explore business intelligence trends for the next couple of years. But first, let’s take a closer look at exactly what business intelligence is.
What Is Business Intelligence?
Business intelligence is a combination of technologies that enables companies to incorporate and analyze data from a variety of sources to generate valuable insights. The technologies include data mining and other data tools, business analytics, and artificial intelligence (AI). Data sources include internal company information from databases, anonymized customer information, and other sources, as well as external information from social media platforms, websites, and other sources.
According to business intelligence platform provider Tableau, business intelligence methods include data mining, reporting, performance metrics and benchmarking, descriptive analysis, querying, and statistical analysis. Each of these methods is a specialized way of “collecting, storing, and analyzing data from business operations or activities to optimize performance.”
The following video offers helpful explanations to understand business intelligence:
The Latest Technologies for Business Intelligence
The latest technology in business intelligence includes cloud-based systems, automation, AI, machine learning (ML), and predictive analytics. Cloud-based business intelligence enables companies to store and analyze massive data sets without the need for hardware to house them. Cloud-based systems are secure and can be modified as needs change. These applications have the added benefit of being accessible from anywhere, making them useful for remote teams and enabling employees to get answers to critical questions at any time.
Automation allows companies to run business intelligence tasks with minimal human involvement through the use of robotic process automation (RPA). This method frees up staff time to focus on higher-value work, yet another benefit that can help organizations move more effectively toward their goals. Automation can be used for a wide range of tasks including evaluating customer sentiment, making sales projections, and predicting market trends.
Predictive analytics plays a large role in business decision-making by providing professionals with clues as to customers’, clients’, and competitors’ next moves. This technology analyzes patterns in consumer behavior, industry trends, market and societal shifts, and governmental actions to arrive at conclusions that can keep companies one step ahead.
AI and ML provide the backbone for all these technologies, as their purpose is to replicate functions that could formerly only be performed by humans and to provide automated operations.
The Future of Business Intelligence
As with many technologies, the nature of business is constantly shifting. So, what is the future of business intelligence?
Self-service. Business intelligence is becoming more widespread throughout organizations. Past systems required specialized knowledge by trained professionals to create reports and draw conclusions. New systems enable “data democratization” in which professionals of all types on any team can use tools to efficiently get the information they need.
Collaboration. Collaborative business intelligence, otherwise known as social business intelligence, enables employees to easily share information, including reports and insights, with co-workers or external stakeholders. This method, which includes the use of wiki and blogging platforms, allows teams to work together to solve challenging business problems. Its use continues to support companies in their pursuits.
Augmented analytics. Augmented analytics is the use of AI and ML to support data analysis activities, including data preparation, insight generation, and story development. This technology helps professionals at all levels and across all departments at companies to generate data stories, which are insights presented in a narrative format. With it, more people continue to gain more critical knowledge based on raw data.
Embedded Business Intelligence
A recent BRANDVOICE article appearing on Forbes discusses another emerging trend, the notion of embedded business intelligence. The article recognizes the time-consuming nature of developing insights from data—even with the help of automated tools—and suggests that companies are poised to supplement self-service options with methods like embedded analytics “that won’t require [business professionals] to learn new skills or invest additional time.”
The article suggests that organizations are looking for applications that have built-in analytics tools. “In this environment,” states the article, “workers can make data-driven decisions without thinking twice and without any disruptions.” Insights gleaned from this approach may go “beyond descriptive analytics (what happened) and predictive analytics (what will happen) to prescriptive guidance (what to do about it).”
Use cases for such guidance include reaching out to customers based on certain signals—such as a late package delivery—rather than waiting for them to call in with complaints, or proactively adjusting inventories based on buying trends.
Business Intelligence Trends for 2023
Some challenges with business intelligence remain, including data quality. With data as the foundation of business intelligence, it must be trustworthy to deliver the most accurate results. Companies recognize the potentially huge costs of making poor decisions based on erroneous data. Therefore, many are implementing data quality management (DQM) policies and continued data tracking to ensure they are starting in the right place and reducing operational risk.
The outlook for additional business intelligence trends in the coming year includes a continuation of the developments mentioned above. Workers across professions, departments, and seniority levels will be able to run more tasks autonomously, make better sense of data insights, and gain insights that will help them to not just react, but proactively move forward with valuable initiatives. In other words, business intelligence is getting smarter all the time.