8 real-world business intelligence examples sorted by industry

By harnessing the power of BI, organizations can unlock a wealth of opportunities to enhance operational efficiency, improve customer experiences, and gain a competitive edge in their respective markets. One study has even suggested that organizations employing BI tools have the potential to reach decisions five times faster than those that don’t. Accurately interpreting and extracting insights from these huge volumes of operational data is making BI an increasingly business-critical option.

Historically, the expense and resource drain of BI software implementation meant early adopters tended to be larger organizations. It’s estimated that around 80% of businesses with over 5,000 employees use some form of business intelligence system. With the advent of cloud BI solutions, however, business intelligence reporting has become far more accessible to smaller businesses. Cloud business intelligence tends to offer lower upfront costs and infrastructure managed by service providers, leveling the BI playing field for organizations of all sizes.

In addition, many organizations are supplementing BI systems with Process Intelligence. This is because while business intelligence deployments provide important information, they don’t possess the mechanisms to suggest solutions nor the means to action them. But Process Intelligence does.

The Celonis Process Intelligence Graph creates a digital twin of business workflows. It acts as an organization’s connective tissue, linking people, processes and systems – unlocking value opportunities hidden within business processes and enabling BI insights to be addressed in real time. Using standardized process knowledge and AI, Process Intelligence can identify optimal approaches to process improvement and even orchestrate intelligence process automations to make these enhancements.

In this article we’ll look at some real-world business intelligence examples from across a range of different industries.

Business intelligence in banking

Business intelligence is crucial in the banking industry for gaining insights that drive strategic decision-making. Applications of business intelligence systems include:

• Customer targeting and customer experience: BI tools help banks analyze customer data, creating segments based on demographics, behaviors, preferences and transactions. This enables the creation of targeted campaigns and personalized offerings, allowing banks to reach new audiences, enhance customer experience and boost loyalty.
• Risk management: By enabling the analysis of historical data, credit data and market risk trends, banks can make more informed decisions around, for example, customer creditworthiness. They can limit their financial exposure and strengthen their risk management frameworks.
• Fraud detection and prevention: Advanced, augmented analytics powered by machine learning algorithms allow banks to detect and flag potentially fraudulent activity in real time. Business intelligence software analyzes transaction patterns and account behaviors to identify anomalous transactions and block potentially illegal activity.
• Operational efficiency: BI reporting enables banks to track and visualize financial KPIs, enhance budgeting and forecasting, evaluate the performance of individual branches and all digital channels, helping identify opportunities to enhance operational efficiency.

Real-world impact of Process Intelligence in Banking and Finance

Process Intelligence has enabled some of the biggest names in the financial services industry to deliver outcomes such as:

• A 50% reduction in waiting time of credit approval
• A 34% reduction in wait time for customers
• 100 days saved in credit recovery
• 15% increase in automation rate

For a more in-depth study, see how Celonis used process intelligence to enhance customer onboarding and compliance at Degussa Bank.

Business intelligence in the consumer packaged goods sector

In the hyper-competitive CPG industry, business intelligence tools enable organizations to gain detailed insights into sales data, consumer behavior, market trends, and supply chain performance. Business intelligence examples from the CPG sector include:

• Demand forecasting: Close monitoring and analysis of sales data, market trends, and buyer behaviors, consolidated into BI dashboards and reports, enables the business user to forecast demand for products accurately.
• Supply chain optimization: With effective data analytics and data visualization, a BI tool enables a CPG business to fine tune its supply chain performance. Real-time reporting of KPIs such as on-time in full (OTIF) rates, out-of-stock levels, and inventory turnover help identify opportunities to drive supplier performance, optimize logistics, eradicate bottlenecks and improve customer satisfaction.
• Leverage distribution / shelf space: Accurate reporting of market trends, product sales data and segmented customer profiles helps CPG brands to convince retail buyers and category managers that their products are worthy of online distribution or store shelf space.
• Brand performance monitoring: BI provides real-time monitoring and data analysis of brand performance metrics including market share, brand sentiment, and brand perception. By tracking these metrics, companies can spot emerging trends, assess marketing effectiveness (ROI), and update brand strategies and promotional activities proactively.
• Market basket analysis: This is a data-mining technique via which BI software identifies patterns and correlations in consumer purchasing behavior – such as which items they frequently buy at the same time. With these insights, CPG companies can optimize product placement, cross-selling strategies, and promotional campaigns.

See how process intelligence helped drive a digital transformation at PepsiCo.

Business intelligence in the energy sector

The energy industry forms part of the critical infrastructure for all aspects of society – heat, light, power and transportation. BI helps energy businesses manage often complex operations that combine high tech with heavy industry, multiple sites, major infrastructure and large teams. Examples of business intelligence in the energy sector include:

• Demand forecasting: BI enables energy companies to forecast energy demand by analyzing factors such as historical demand data, weather patterns, and even economic indicators (e.g. industrial activity levels and energy prices). Accurate demand predictions create actionable insights to optimize production, pricing, and distribution strategies.
• Customer behavior and energy consumption analysis: By consolidating energy usage information and segmenting it by customer type, industry, or geography within data visualizations, BI analysis helps pinpoint areas of consumption. This can be used for optimizing energy distribution and designing targeted energy-saving programs.
• Equipment health and asset management: BI reporting provides real-time reporting on the operational performance of energy equipment and infrastructure. It enables downtime alerts and even predictive maintenance schedules to help energy companies optimize their assets, from power plants to pipelines.
• Compliance and regulatory reporting: Business intelligence data collection, analysis, and reporting help ensure adherence to environmental and safety standards.

See how process intelligence helped transform energy giant Hydro.

Business intelligence in the healthcare sector

The valuable insight deriving from a BI solution takes on a whole other dimension when the information under analysis is healthcare data. Every data driven decision that optimizes healthcare provision, has the potential to save lives as well as money. Some healthcare applications of BI include:

• Population health management: The capacity of a BI system to aggregate and analyze large, diverse data sets helps healthcare professionals identify high-risk populations, track health trends, and target interventions for health promotion or disease prevention.
• Optimize patient experience: BI dashboards and visualizations provide the ideal forum to aggregate and analyze patient feedback on the quality of their care. This provides healthcare leaders the ability to track trends in patient preferences, identify areas to enhance care coordination, personalize care delivery and improve overall patient experience.
• Revenue Cycle Management (RCM): Business intelligence enhances revenue cycle management in healthcare by offering data-driven insights into claims processing, denial management, patient payment patterns, and operational bottlenecks. This empowers healthcare professionals to streamline billing processes, diminish denials, and optimize revenue capture.
• Operational efficiency and improved service delivery: Healthcare professionals leverage business intelligence reporting to track operational KPIs within their facilities. From total patient numbers, patient numbers by department, waiting times, treatment costs and staff coverage, BI reporting helps identify potential risks like service shortfalls, as well as opportunities to optimize service delivery.

Learn how Celonis helped transform Cardinal Health’s digital processes at scale.

Business intelligence in the life sciences and pharma sector

This highly regulated sector leverages business intelligence insights to underpin both clinical and commercial strategies with data-driven insights. Applications in this sector include:

• Optimizing clinical trials: Clinical trials form a crucial part of the research and development pipeline. Leaders in this sector can maximize the impact of such trials by using BI analytics to analyze and correlate patient recruitment information, specific trial protocols and trial outcomes. This analysis can help identify potential inefficiencies, and unnecessary costs, while predictive analytics can be applied to predict the likely success of trial candidates.
• Accelerating product development: BI analytics can serve as an accelerator for the development of new drugs or therapies. Organizations can leverage their business intelligence tool to identify trends and insights in clinical trial data and focus new product development initiatives.
• Regulatory compliance: By automating data collection, analysis, and reporting processes, BI tools help ensure that life science and pharmaceutical companies adhere to regulatory requirements throughout their product development cycle.
• Pricing strategies and market access: Business intelligence platforms enable pharmaceutical companies to analyze data on insurance providers, payer data, reimbursement trends, and changes in healthcare policies. This analysis allows them to develop better strategies for price optimization, gaining access to markets, and getting their products covered and paid for by insurance plans.

See the impact process mining made to process efficiency at Bayer AG.

Business intelligence in the manufacturing sector

There are so many moving parts in manufacturing, so many workflows and processes, that making optimum use of available business data is essential. Some of the key uses of business intelligence tools in manufacturing include:

• Production orchestration: A BI application can transform a manufacturer’s production planning and scheduling processes. By drawing together and analyzing demand forecasts, production capacity and resource availability, manufacturers can leverage BI solutions to identify and eradicate production bottlenecks, optimize schedules and reduce production lead times.
• Inventory management: Business intelligence helps manufacturers improve inventory management by providing real-time visibility into inventory levels and analyzing demand patterns to optimize stock levels. By identifying slow-moving products and streamlining ordering processes they can reduce costs associated with overstocking or stockouts.
• Predictive maintenance: BI tools that employ predictive analytics help manufacturers minimize machine downtime. By analyzing machine sensor data to predict equipment failures and schedule maintenance proactively, BI optimizes production efficiency.
• Supply chain optimization: By analyzing KPIs such as supplier lead times, inventory turnover rates, transportation costs, and on-time delivery metrics, BI software helps to identify inefficiencies, minimize disruptions, and streamline logistics for improved efficiency and cost savings.

Learn how Celonis delivered supply chain transparency for Freudenberg FST.

Business intelligence in the public sector

While public sector organizations aren’t typically considered to be ‘businesses’, they are every bit as swamped by data as those in the private sector. Consequently they derive a great deal of benefit from business intelligence platforms. These include:

• Crisis management and emergency response: BI enables government agencies to analyze real-time data from multiple disparate sources to optimize government agency response to a crisis. It can draw on data sources such as sensors (weather, seismic, air quality, or traffic sensors for example), emergency service resource data, social media, and geographic information systems. Using this data, BI analytics help leaders analyze and optimize emergency responses, disaster preparedness and public safety.
• Improving public services: By integrating data from multiple government systems and agencies (such as highways or social care) – cross referenced with analysis of citizen needs, preferences and behaviors – government agencies can tailor services to better meet citizen needs.
• Budgetary control and financial management: BI tools enable public sector leaders to ensure that people are getting the most from their taxes. BI platforms allow them to analyze financial data, expenditure patterns, supplier costs and revenue streams to improve financial planning, budget allocation and resource management within government agencies.

Learn how the State of Oklahoma was able to save tens of millions of tax-payer dollars with process intelligence.

Business intelligence in the retail sector

The retail industry is the engine-room of many economies, with multi-channel businesses battling for the hearts, minds and wallets of consumers. Business intelligence analysis is a major influence on this battle, with BI tools allowing retailers to track sales data, interrogate inventory levels, optimize supply chains, personalize marketing campaigns, and forecast demand. Some specific applications of BI include:

• Managing inventory: BI helps retailers optimize inventory levels by analyzing sales patterns, lead times, supplier performance and returns processing to ensure adequate stock levels while minimizing excess stock costs or stockouts.
• Merchandising and product mix: By combining customer buying behavior data, customer intention data and market trends in a single model, BI systems allow retailers to optimize their merchandising and product mix planning – getting the right products to the right stores in the right volumes.
• Customer segmentation and customer experience: People expect personalized engagement from retailers – particularly in the online and social spaces. BI enables retail leaders to identify customer segments based on demographic data, purchasing behaviors, intent data and preferences. These detailed profiles form the basis of personalized customer marketing activity.
• Loss prevention: Business intelligence tools aid retailers in identifying and averting theft, fraud and shrinkage. They do this by examining transactional data, discrepancies in inventory, and surveillance footage (integrating with video analytics software), to enable the detection of suspicious activities and the reduction of associated risks.

Real-world impact of Process Intelligence in Retail

Using Process Intelligence, Celonis has helped multiple retailers drive significant business improvements, including:

• A 75% reduction in maverick buying at an online fashion, footwear and beauty retailer
• A 20% decrease in customer cancellation rate at a major luxury retailer
• A 90% perfect invoice ratio at a large grocery retailer

For a more in-depth study, read how Celonis helped Globus gain full visibility into their shipping and eCommerce processes.