The future of business intelligence: It is about interaction rather than visuals

• Business Intelligence

Data is the most valuable resource for business leaders of today. Robust analytics tools offer deep insights into brand data, and help with effective decision making, efficiency in business processes and improving ROI.

In this article we’ll be exploring key trends for the future of Business Intelligence, and the benefits you can experience from a new breed of Augmented Analytics tools delivering critical BI. But first, let’s take a look at the advancement of BI over the years, the key drivers of BI adoption, and the state of the market.

Transformation of Business Intelligence

About a decade back, we witnessed the adoption of Gen One BI. Business Intelligence was established as the cornerstone for business growth. With the lack of proper BI analytics tools, businesses mostly conducted reporting projects dependent on on-premises data and were driven by IT personnel. This was an extremely time and resource-intensive process, but some large enterprises were able to mitigate the challenges, benefit from the BI studies, and paved the way for analytics.

The year 2016 saw Gen Two BI develop from an end-user perspective, and is being widely used till date. The rise of data democratization, self-service analytics, mobile analytics, use of HTML5, and the integration of dashboard software; changed the way information is accessed by the end-user. The data is not just easier to access, but easy to consume, empowering end-users with the analytics capabilities. Data democratization catalyzed by the evolution of analytics capabilities and the focus on interactive dashboards, led to large scale adoption of second-generation BI tools and platforms, by even small to medium enterprises (SME).

Improved data processing performance, machine learning, cognitive computing, elastic cloud architecture, and the internet of things (IoT) are changing the way data is analyzed and business insights are derived.

The trend is clearly towards the demand for easier and more accessible ways of accessing data-driven insights by the end-users to drive business value. In a 2020 study, 54% of organizations agreed that cloud business intelligence is critical to their current and future initiatives.

Factors Driving Adoption of Business Intelligence

Data-driven decision making

One of the primary reasons behind the extensive adoption of BI, is its ability to enhance decision-making. BI can be leveraged across business units by the enterprise as a whole, helping stakeholders take more effective decisions, and elevate the entire enterprise from end to end.

Increased Accessibility

Just as analytics capabilities and BI tools have evolved for greater efficiency, they have also become more accessible and affordable. SMEs can afford to employ BI tools and easily integrate them into their operations. This change has come about due to the increasing adoption of cloud platforms offering software-as-a-service. Cloud-based SaaS solutions have made it possible for small and medium enterprises to employ scalable BI solutions, without investing in on-premise servers and skilled personnel for handling the technology.

Barriers to becoming a data-driven organization

Even with the above mentioned factors improving BI offerings and BI adoption, analytics as the precursor to insights, has not matured at the same rate. And this is especially true for SMEs. A study by New Vantage found that in 2020, only about 27% of businesses surveyed had a data-driven approach to their work.

While enterprises understand the value that BI tools can offer their business, and have been increasingly integrating these tools into their work environment; they are just scratching the surface of what the tools are capable of.

‘People and process challenges’ are cited as the primary barrier to becoming a data-driven company. But user-friendly solutions shall continue to drive investment in analytics and insights.

Having said that, here’s how the BI market has been shaping up with various factors influencing adoption of BI tools.

The Business Intelligence Marketplace

When the COVID-19 pandemic hit and crisis was at full-swing, businesses were faced with huge challenges. The impact was hard, and business leaders had to know how much revenue was being generated at both the local and the global level. They had to keenly inspect their operations, revenue from sales, and the costs they were bearing.

The crisis acted as a catalyst, and propelled the need for companies to analyze their data for gathering critical business information and carrying out effective decision-making. Even though the economy was crashing, BI tools experienced increased adoption. Organizations can integrate data from multiple sources, automate their analytics process, get unique and curated insights in near real-time, and make crucial decisions that impact overall brand health and drive ROI.

With 2020 and 2021 having a major impact on the augmented analytics market, the landscape is still evolving at a rapid pace. Trends in BI analytics tools in 2022 suggest that we will witness a shift in focus from dashboards and data visualizations, to secure data presented through simple yet powerful presentations. Increased access to valuable insights through embedded analytics, and a step toward collaborative decision-making.

Factors Influencing Business Intelligence Trends

Artificial Intelligence

The rapid evolution of AI technology is enabling engineering and hyper-automation to gather business intelligence with ease.

Machine Learning (ML) and AI are changing the way we interact with data analytics, how we leverage insights, and ensure data security through superior data management. Gen 3 BI will be supported by scalable AI technology, focused on gathering curated insights.

With the COVID-19 crisis altering the entire business landscape, AI and ML will no longer focus on historical data, but sift through small data segments, while complying with changing privacy regulations. This ensures that companies manage the data securely, respect data privacy regulations.

Advancements in AI technology can also empower end users with accurate and timely anomaly detection, based on existing historical data and trends. The end user gets an immediate notification and can optimize strategies to adapt with the anomaly.

AI-powered Augmented Analytics will also enhance BI solutions with new and improved capabilities for the entire process, from data discovery to delivering actionable insights. Your data analytics will be completely automated. You select the dataset to be analyzed, and the variables that the query is about.

AI will do the calculations and present you with varied insights on business growth, market trends and forecasts, customer segments, anomalies and brand health. Real-time access to critical insights, offers a massive time advantage to decision makers and stakeholders.

NLP-powered AI assistants will also aid the querying process, by enabling the user to simply type or even talk to the software. The AI processes the question, runs the algorithm and offers the business intelligence. This only gets better with the solution’s Predictive and Prescriptive Analytics capabilities.

Predictive and Prescriptive Analytics

With IoT pervading every aspect of our lives, more data is being created now than ever before. These two analytics models vastly upscale the decision-making capabilities of enterprises and are at the heart of business intelligence.

Predictive Analytics refers to the analysis of historical data and current data, attempting to predict future trends with reasonable reliability. It also offers risk assessment for strategies, and alternative scenarios for possible future trends and market conditions.

The AI and ML driven solution processes large volumes of data and gets more intuitive and efficient with time. It can help your enterprise to understand your products, customers, vendors, and partners, while identifying new opportunities, and possible risks.

If you are operating in the retail sector, Predictive Analytics can help you identify potential upselling or cross-selling opportunities which may be demographic or location specific, or dependent on other factors. You get to adapt your strategies, increase production if needed and remain prepared for all possibilities.

With self-service analytics becoming the in-demand feature for BI solutions, predictive analytics methods are being increasing employed. The two most prevalent being Autoregressive Integrated Moving Average (ARIMA), and Artificial Neural Networks (ANN).

Prescriptive Analytics is the order of the day. This model of analytics suggests the best routes to success and the steps to be take, for achieving the target set by the decision-maker. It leverages several analytical techniques and tools such as event processing, graph analysis, neural networks, ML and even creates simulations for testing potential opportunities.

Being able to consider possible scenarios and the how different decisions can affect the situation, is a crucial factor when the future of outcomes has to be considered. This is business intelligence gold, as it can help your enterprise optimize everything from production and inventory, to supply chain and revenue.

Data Discovery and Management

Gen 3 BI solutions will have a greater focus on data discovery. We will witness advancements in the seamless integration of data from both internal and external sources. Assisted by advanced analytical capabilities, the solution will offer deep insights through powerful data visualizations.

The data discovery tools that will come into play, shall be really simple to handle, offering greater flexibility and agility. With a massive reduction in time to insights even for large volumes of data, stakeholders will be able to set-up a sustainable and data-backed decision-making process.

The effectiveness of the decisions being made by stakeholders, is directly dependent on the quality of the data quality management. Accessing the right data for analysis, while adhering to stricter data security regulations, is of prime importance. If data is at the foundation of BI, consistent management of the data is fundamental to optimal BI utilization.

Data Security

Security and management of data and sensitive information has always been a key element of business intelligence best practices. Privacy regulations such as the California Consumer Privacy Act (CCPA) in the US, and the General Data protection Regulation (GDPR) in the EU, are aimed at protecting both businesses and consumers.

You have to consider implementing optimal data security measures as cybercrime is also on the rise, and data is your most valuable asset. The shift to online or hybrid models of business after the COVID-19 crisis hit, saw a surge in the demand for SaaS BI solutions. This presented another opportunity for cybersecurity vulnerabilities to be tested.

BI tools will be increasingly adopting a mesh architecture, which offers a scalable solution to protecting data on the cloud, application data, IoT data and more.

Gartner suggests that enterprises enabling the cybersecurity mesh architecture by 2024, will be able to protect themselves from breaches and minimize the financial impact of data leaks by 90%.

Data Literacy

This has always been a barrier to efficient utilization of data and the insights it offers. With self-service analytics becoming prevalent, you need to empower your employees with the right training and tools, so that they may better understand and utilize the data they are presented with.

With continual effort and improvements, end users will be able to leverage the right tools, understand the data with ease and communicate the findings lucidly.

Data experts will no longer be needed as extensively, and advanced analytics will be carried out by unskilled personnel accessing the solutions. Predictive and prescriptive analytics will aid the decision-making process, and elevate data literacy.

Automation

We will see a greater migration to automated BI systems than we have witnessed in the past few years. Automation will take over most tasks from data discovery and management, to analysis and the presentation of insights through automated data storytelling.

The rise of hyper-automation will enable your business to automate most business processes, with AI, ML and NLG tools transforming the way you interact with data. With low to no-code tools increasing in popularity and adoption, the roadblock of requiring skilled data scientists for analytics and insights will be eliminated.

BI solutions will become the central hub for gathering, monitoring and analyzing data, and for subsequently reporting on it, sharing insights, and collaborative decision-making.

Collaborative BI

Self-service BI solutions have removed the necessity for skilled IT personnel to handle data and offer their understanding of the same. They facilitate easy communication and data sharing capabilities, even through integrated social media platforms.

The solutions will be tracking not just data and documents, but the progression of various interactions with your business ranging from calls and emails to social data and internal communications. With easy access to insights and simplified sharing capabilities, stakeholders and heads of business units will be able to promote intra-organization collaboration and improve efficiency and effectiveness of decision-making processes. This in turn will boost productivity and revenue margins.

Cloud-based architectures of BI solutions will help in fostering collaboration even further, removing all restrictions for time and space.

Cloud-based BI

Upscaling of cloud services is one of the overarching trends that BI solutions will witness in the next few years. It paves the way for software and applications to be accessed at anytime and from anywhere, and supported on any device.

Everything from data collection to analytics and insights will be available at the click of a button, right on the end-users deice. This will create a higher demand for SaaS BI solutions, and will promote data management and collaboration across enterprises and industries.

Natural Language Generation (NLG)

Natural Language Generation capabilities will reach new heights, and one of the most popular ways end-users will interact with machines is through speech. Advanced voice recognition capabilities and cognitive computing enabled by Microsoft Cortana, Google Speech, and Amazon Alexa enable people to interact with their devices using voice. These can be easily integrated into a BI system to make its interface more intuitive and voice-enabled.

This will enable business users to engage and access any information they need by simply talking to their devices and requesting for specific answers. Voice-enabled BI system will enable seamless interaction of end-users with their organizational data and make decisions instantly.

Impact of Advanced BI Solutions

There are several ways that these drastic improvements in the capabilities of BI solutions will impact your business.

There will be greater integration of your existing analytics tools and solutions with your Business Intelligence solution, providing a more uniform approach to all your brand data and the analysis of the same.

The collaboration feature of the BI tools will foster inter-departmental communication and a free flow of idea, leading to new approaches to business problems, data, analytics and insights. Disparate business units will have an opportunity to work in closer proximity and have a free flow of ideas on how to optimize the insights gained for the achieving their individual targets.

Collaboration within and outside the organization will expand your tech infrastructure, and offer you newer opportunities and avenues for expanding your business. Data proactivity will also be supporting your expansion efforts with timely insights on new revenue streams and business opportunities, which will be revealed through your data analysis.

AI, ML and NLG technologies will revolutionize the way you approach data. And with self-service models being increasingly adopted, your entire business will soon be driven by data and analytics. Embrace this culture of being powered by data-backed decisions, and witness your entire organization being enhanced from the ground up.

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