“Without data, you’re just another person with an opinion.” – W. Edwards Deming
These words perfectly illustrate the power of data insight, and how people and organizations that make decisions based on gut instinct or intuition often make biased and incorrectdecisions. But how do you get from raw data to business insights?
If we take this one step further, there’s a critical step between gathering business data and using that data to make informed decisions – business intelligence.
Business intelligence or BI envelopes the technologies and strategies that organizations use to analyze and manage data. It’s all about the data.
BI has been increasingly growing in popularity due to the significant benefits it offers to businesses, such as improved decision-making, increased operational efficiency, enhanced customer experiences, refined financial performance, and a competitive advantage in the market. However, the key reason why so many companies are seeking business intelligence is to significantly improve their bottom line, by leveraging BI to provide real-time, data-driven insights, and decision-making tools.
In this article, we’re going to look at how business intelligence can transform your bottom line.
The Evolution of Business Intelligence
In the 1960s and 70s, BI was all about creating reports and visually-led dashboards to provide a summary of data from various internal and external sources. This data was typically stored in legacy systems or mainframes and was notoriously difficult to access, let alone analyze and make real use of.
However, the rise of desktop computing and data warehousing in the 1980s and 90s changed all of that. The BI landscape went from something that was notoriously barren and difficult to navigate, to something that was growing small seeds of possibility, all within the space of just a few years. Data warehousing made it possible to store and manage huge volumes of data, while desktop computing provided the necessary tools to easily access and analyze data for business use.
And it gets better…
With the growth of the Internet and the rise of social media channels, came the emergence of big data and cloud computing. That landscape that showed potential is now flourishing into lush green foliage. Big data become a huge catalyst and critical factor in the evolution of business intelligence. It opened the world up to new methods of handling and processing big volumes of data. Alongside, the advent of cloud computing provided simpler storage systems and easier analysis of almost-unimaginable quantities of data.
Then came advanced analytics and data visualization. The BI landscape is now an oasis. The increased processing power of computers and the accessibility and availability of intuitive and innovative cloud computing solutions made it possible to perform advanced analytics and create interactive data visualizations. This completely revolutionized the way in which organizations can use their data to make informed decisions, by clearly showing data in a visual manner that’s easier for stakeholders to understand and back.
Organizations now have access to a wide range of business intelligence tools, techniques, and technologies, including artificial intelligence (AI) and machine learning (ML). These tools make it possible to analyze near-infinite volumes of data in real-time, providing organizations with near-real-time insights into things like business operations, performance, customer satisfaction, and changing market conditions and trends.
The market has changed so significantly over the last fifty-plus years. BI tools and technologies have evolved beyond recognition since their advent. Organizations no longer need a whole team of data scientists to navigate complicated workflows and data sets – anyone can do it. Making use of data for business improvement is more accessible and beneficial than ever before.
The Benefits of Business Intelligence
As shown, business intelligence has evolved remarkably over the years, and these developments have resulted in a shift in benefits.
Today, organizations can expect to experience benefits such as:
Providing access to real-time data and advanced analytics, BI helps organizations make informed decisions that are based on actual facts and trends instead of relying on intuition and expertise. This means better, data-driven decision-making, which can result in improved performance, increase competitiveness, and generally enhance overall business success.
Increased operational efficiency
Organizations have the tools necessary to identify areas of improvement in their operations – so, by analyzing data and identifying inefficiencies, companies can then streamline processes and reduce waste, increasing efficiency and cost savings.
Refined financial performance
With real-time insights into sales, revenue, costs, and other financial metrics, BI enables organizations to make better decisions that don’t negatively impact their bottom line, but instead, protects, supports and boosts it. With improved financial performance comes increased profitability and ultimately, greater business success.
Enhanced customer experiences
Greater insights into customer behavior, preferences, and feedback, enable companies to deliver better customer experiences, which equals increased customer satisfaction and loyalty.
Businesses have an advantage over their competitors by leveraging real-time insights and enabling data-driven decision-making, this helps companies stay ahead of the curve and the competition and achieve their goals more effectively and efficiently, and stand out in what may be overcrowded and competitive markets.
Key Components of a Business Intelligence Solution
For organizations that want to reap the benefits of modern BI, there is a huge pool of technologies, solutions, and tools available to choose from. However, they should all envelope five key components; data warehousing, data integration and management, dashboards and reporting, data visualization, and performance management and predictive analytics.
1. Data Warehousing
This is the process of collecting, integrating, and storing large amounts of data from multiple sources into a centralized repository, specifically designed to support BI activities. Its purpose is to provide a single, comprehensive, and integrated view of the data, making it easier for organizations to access, analyze, and make informed decisions based on the data
Data warehousing enables organizations to overcome the challenges posed by disparate and siloed data sources and provides a base for advanced analytics and business intelligence applications to launch from. Data is organized and stored in a way that is optimized for querying and analysis, allowing organizations to gain insights into their business operations and make data-driven decisions based on output.
2. Data Integration and Data Management
This component is about acquiring and integrating data from various sources, such as ERP (Enterprise Resource Planning), and CRM (Customer Relationship Management) systems, alongside marketing channels, PIM (Product Information Management), DAM (Digital Asset Management) tools, and flat files (e.g. spreadsheets, csv, xml), plus external sources (e.g. customer data enrichment), and feeding that into the data warehouse.
3. Dashboards and Reporting
Dashboards and reporting provide real-time insights into business data.
Dashboards are graphical displays that provide real-time data insights, they are interactive and allow users to quickly see and understand the status of key metrics. They are highly customizable, so organizations can tailor them to meet their specific business requirements.
Reporting enables organizations to present and communicate information in a structured and categorized way. They can be generated in various formats such as tables, charts, and graphs, providing a greater granularity and detailed view of data compared to dashboards.
4. Data Visualization
Data visualization makes complex data more understandable and accessible. It’s a way of representing data in a graphical or pictorial format to facilitate better understanding and communication, especially with relevant stakeholders.
5. Performance Management and Predictive Analytics
Using insights into business data, combined with KPIs, performance management enables organizations to quickly identify and improve their business operations to meet changing market and industry demand, alongside shifting customer expectations.
Predictive analytics is a branch of analytics that uses data, statistical algorithms, and machine-learning techniques to identify the likelihood of future events, trends, patterns, and outcomes based on historical data to improve forecasting. It is an essential component for organizations looking to drive better business outcomes, stay ahead of the curve, and make data-driven decisions.
How to Implement Business Intelligence in Your Organization
Now you know everything you need to know about business intelligence, it’s time to look at how you can actually implement it and start reaping the rewards.
First things first, you need to assess your current data landscape. You need to ask the following questions:
What data do you have?
Is the data you have useful?
What data don’t you have?
What data do you actually need?
Is the data you have structured in a way that’s easy to understand, analyze and share?
Assessing your data landscape can be a daunting task, especially if you have disparate systems that hold various versions of data, and that data is unstructured. But assessment is the first step to making improvements, so embrace it and keep the benefits front of mind.
Once you’ve successfully assessed your data, you need to define your business intelligence goals and objectives:
What do you want to achieve with BI – think about the benefits outlined earlier on, and ensure the goals you do decide to pursue, align with your overall business objectives
Now, you need to select the right BI tools and technologies that will enable you to achieve those goals:
Think about budget allocation, resource availability, IT accessibility, and infrastructure
As mentioned before, there are loads of business intelligence and data platform tools available on the market:
Power BI: a powerful and widely-used data visualization and analytics tool from Microsoft that allows users to create interactive dashboards and reports
Tableau: a popular data visualization tool that enables users to create interactive dashboards and reports using simple drag-and-drop functionalities
QlikView: a data discovery and visualization tool that provides users with the ability to create dashboards and reports using a variety of data sources
IBM Cognos Analytics: this is a business intelligence and performance management tool that offers a range of capabilities, including reporting, dashboarding, and data visualization
SAP BusinessObjects: a comprehensive BI platform that provides reporting, dashboarding, and data visualization capabilities, alongside advanced analytics and predictive modeling
The following data platform tools provide organizations with a range of capabilities for managing and analyzing their data and are often used in combination with other BI tools – such as those mentioned above – to create comprehensive and effective data solutions.
Azure Synapse: another Microsoft service, this time offering a cloud-based analytics solution that combines big data and data warehousing capabilities into a single platform
Azure Data Factory: a cloud-based data integration service from Microsoft that allows users to create, schedule, and manage data pipelines that move and transform data across on-premise and cloud environments
Microsoft SQL Server: a relational database management system from Microsoft that offers a range of data management and analysis capabilities, including reporting, analytics, and data warehousing
SSIS (SQL Server Integration Services): this data integration tool from Microsoft allows users to create, deploy, and manage data integration packages that move and transform data across various data sources
TimeXtender: a low-code data integration tool that allows users to easily create and manage data warehouses and data models, with automated data integration and transformation capabilities
Microsoft SQL Server MDS (Master Data Services): this data management tool from Microsoft enables users to create and manage master data entities, such as customers, products, and suppliers
Lastly, you need to build and drive a data-driven culture.
Stakeholders, teams, and employees need to get on board with BI or a new initiative simply won’t work. Organizations need the buy-in and involvement of everyone to drive the level of change management required – everyone needs to see and understand the benefits, why the organization is taking the approach, what will change, what help they will receive and what technology will be put in place to support it. Complete transparency is needed. Only then, can organizations hope to see success and encourage employees to drive BI across the board and experience the advantages.
There are numerous benefits associated with business intelligence, from increased sales and intuitive marketing to saving time, effort, and resources and protecting the bottom line. The key thing to remember is that different organizations seek BI for different reasons, to align with and bolster their overarching business goals.
The future of business intelligence looks promising, as companies continue to rely on data-driven decision-making to remain competitive. Here are some trends and developments to look out for:
Increased adoption of AI and ML: as these technologies become more accessible and affordable, businesses will increasingly use them to extract insights from large sets of data
Integration with other business systems: BI tools will continue to integrate with other business systems such as CRM and ERP systems to provide a more comprehensive view of business performance.
Greater emphasis on self-service BI: this will become more common as companies seek to empower their employees to make data-driven decisions via intuitive dashboards and user-friendly interfaces.
Focus on real-time analytics: with the increasing speed of data generation, businesses will demand real-time analytics capabilities to make timely decisions.
Increased use of cloud-based BI: cloud-based BI tools will continue to gain popularity as they offer greater flexibility, scalability, and cost-effectiveness compared to more traditional on-premises solutions.
Improved data security: with the increasing importance of data privacy and security, BI solutions will need to provide robust security features to protect sensitive data.
Overall, the future of BI looks bright, with increasing adoption and integration with other business systems, as well as the use of advanced technologies.
Learn more about business intelligence and how technology can support your BI goals by booking a demonstration with exMon, here.
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