Competitive advantage in today’s tech-enabled business environment comes through innovation and differentiation. Business intelligence (BI) is the key to achieving such ends. Here are the top trends in BI for 2021 and beyond.

1. The Rise of Augmented Business Intelligence

Artificial Intelligence and Machine Learning enable augmented Business Intelligence.

BI tools, powered by machine learning algorithms, are now embedded into enterprise systems. The most common adoptions are in CRM, ERP, field management suite, and collaborative tools. As a case in point, Salesforce acquired Tableau in 2019 and integrated the software into its cloud-based CRM platform. With such integration, BI becomes a part of the core business workflow, rather than a separate, disconnected process. The AI-powered BI tool works in the background and analyzes data sets automatically. Users get real-time alerts that unlock new possibilities or enable creative problem-solving. Use cases include:

• Smart assistant tasks, such as tracking the progress of meetings, follow up on emails, and generating automated reports.
• Anomaly detection. An AI algorithm on a neural network learns from historical trends and patterns and detects anomalies. The system notifies the user immediately.
• Identifying new opportunities. Embedding BI into applications enables Operational BI and facilitates real-time decisions making. The conventional BI practice of delivering weekly or monthly reports and charts no longer suffice. The entire scenario might have changed by the time the report comes. Operational BI collates data from the supply chain, consumer touch points, and other sources. The tool analyzes the data in real-time and provides live recommendations. The insights include growth trends, correlations, what-if analysis, and more.

Augmented BI turns an average business user into a citizen data scientist. It paves the way for self-service BI. Users get insights with a few clicks. They no longer need the support of the IT team to access, interpret, and understand the data.

It is still early days for Augmented BI though. It will take a while before the entry barriers for Augmented AI become low enough for casual users to adopt it in mainstream use.

Meanwhile, the opportunities for innovation and unlocking new use cases are endless.

2. Increasing Use of Business Intelligence for Predictive Analytics

Businesses now use predictive BI in a big way.

A big stumbling block with data analytics is its reactive nature. The analytics engine deals with information that has already come to pass. Such past data will not guarantee what will unfold in the future. Predictive analytics goes beyond making sense of what the data reveals. It uses the data to forecast probabilities and co-opts alternative scenarios. The tool generates several eventualities, the probability of each eventuality, and risk assessments.

Use cases abound. Airlines deploy predictive BI to decide how many tickets to sell at each price band. Hotels deploy predictive BI to forecast demand and predict the number of rooms they can expect to sell at different price points. Marketers may predict customer responses and identify cross-sell opportunities. The opportunities are endless.

The rise of predictive analytics coincides with the rise of prescriptive analytics. This involves the application of advanced techniques, such as neural networks, simulation, complex event processing, heuristics, recommendation engines, and more. It visualizes the effect of each possible future decision and adjusts the recommendation. Use cases include optimizing scheduling, right-sizing inventory, and improving the supply chain design.

3. Increased Cloud Adoption

In the age of Big Data and remote work, the cloud has become the strategic enabler of BI.

The cloud offers easy scale-up of resources, suiting the needs of BI software perfectly. The cloud also offers easy accessibility, elasticity, and speed. But many enterprises viewed BI as a legacy technology before the COVID-19 pandemic. They were reluctant to undertake the hassles of moving data to the cloud, to facilitate big scale BI analytics.

With the pandemic forcing work-from-home, cloud migration became inevitable. Enterprise IT had no workaround to making available remote access to key business applications. They became habituated to move large data sets to the cloud, to run such applications. This mitigates the problem posed by data silos and makes running data analytics in the cloud easier.

Side-by-side, the pandemic forced enterprises to understand their business processes, customer behaviour, and supply chain dynamics in a better way. This has put the focus back on BI.

This technology blog discusses six ways the cloud enhances the capabilities of Business Intelligence tools.

In 2021, more than half of the new BI deployments are in the cloud. Cloud deployments also trigger the rise of mobile BI. Users access cloud-based BI solutions through convenient smartphone apps.

4. The rise of Natural Language Processing

Any BI software is only as powerful as the query and the data fed into it.

Formulating the right query is difficult for the lay user. But BI systems capable of natural language processing will solve the problem. The lay user may ask a question in a normal conversational mode and get the answer. Natural language processing makes BI popular and eliminates the role of data scientists as an intermediary.

But it is early days for Natural language processing. Natural language systems still need tuning.

5. Use of Storytelling

The traditional BI way of stale reports and dashboards is passe. Colourful charts look slick but do not present information in the best way to non-tech users. Leading BI vendors toy with storytelling as a solution. The software walks the user through the problem and offers recommendations. Textual narrative, and even voice, accompany slick and glitzy graphs and charts.

The latest BI tools also offer customized solutions, set to the user’s preferences.

6. Entrenchment of Data-Driven Culture

Enterprises have realized that successful BI depends not only on the tools but on the culture. A data-driven culture is an essential prerequisite. Without the free flow of data and a culture of open sharing of information, BI systems will generate results based on incomplete or flawed data.

Most enterprises now realize the importance of analytics to make informed decisions and drive competitive advantage. They seek to collect good quality data and make such data accessible. A 2021 BARC survey reveals data quality management and data discovery as top priorities.

IDC pegs the global business intelligence and analytics market at $19.2 billion in 2020, with a CAGR of 5.2%. This is despite the pandemic-related economic upheavals. As companies focus on digital transformation and smarter uses for their data, the focus on BI will rise further.