You must have heard that data is the new oil, but the truth is that unstructured data alone cannot help you drive success. What really moves the needle is your ability to turn that data into clear, actionable insights. That’s where Business Intelligence (BI) comes into the picture.

BI isn’t just a competitive advantage; it’s a necessity for businesses today. But implementing and managing BI tools in-house can be complex, time-consuming, and costly, especially for businesses without technical bandwidth or resources. This is why business intelligence outsourcing has rapidly become a go-to solution for companies seeking both efficiency and expertise without overhead.

So, whether you are a growing startup or an established enterprise, this guide will walk you through what, why, and how of business intelligence, including how outsourcing can unlock its full potential for your business. So, let’s begin.

What is business intelligence?

Business intelligence (BI) is the collection of strategies and tools business uses to gather information from different sources. Companies use BI to enhance their decision-making processes, minimize operating costs, and identify new areas of opportunity.

BI is not a new concept. In fact, BI tools and techniques have been reshaping the world for more than a decade. There has been a recent spike in interest around BI due to the significant amount of data that is available to businesses today.

The role of data in business intelligence

Data is possibly the most important component of any BI project, serving as its foundation. Businesses collect data from sources like internal databases and real-time feeds, data undergoes processing, cleaning, and transformation before analytical tools uncover valuable insights.

There are two main types of data used in business intelligence solutions, structured and unstructured. Here’s the role they play in BI projects.

Steps involved in the BI process

BI projects can sometime be time consuming as there are multiple phases involved in the process. Here’s how businesses transform raw data into actionable insights for effective decision-making.

1. Data sources: Here, businesses determine what data is to be evaluated and analyzed. Data from a data warehouse or data lake, the cloud, industry statistics, supply chain, pricing, sales and marketing, CRM, inventory, website, or social media can be used in the BI projects.
2. Data collection: Raw and unstructured data is collected from various sources and then segregated and cleaned using different filters. This data preparation could involve manually gathering data into a spreadsheet or using automated Extract, Transform, and Load software (ETL).
3. Data analysis: Here, companies try to find patterns or unexpected results in the data. This could be included in data mining, search, or modelling techniques.
4. Data visualization: After collecting and analyzing data, experts create data visualizations, graphs, and dashboards with BI tools like Power BI and Tableau. This visualization should contain drill-down, drill-through, and drill-up tools that help the users to analyze data at multiple levels.
5. Decision-making: In this phase, decision-makers gather actionable insights based on a comparison of historical data to key performance indicators. Actions could include more efficient procedures, marketing customizations, supply chain risks, or responding to customer experience issues.

For the successful completion of any BI project, it is highly essential to follow all the above-mentioned steps. But still, some new BI solutions can extract and load raw data directly using different technologies.

Key functions of business intelligence

Understanding the key functions of BI is very important for any business aiming to harness the full potential of its data. Here are some key functions BI businesses use to make informed decisions.

1. Enterprise reporting: One of the key functions of BI is enterprise reporting. Here, reports can take many forms and are produced using several methods. However, BI software can automate the report generation process. BI tools can bring enterprise-level scalability in report production and enable collaboration between the various stakeholders.

2. Business analytics: Business Analytics is the process of examining data and figuring out patterns or trends to make key business decisions. Analytics can be descriptive, prescriptive, or predictive.

• Descriptive analytics describe a dataset through measures of central tendency (mean, median, mode) and spread (range, standard deviation, etc.).
• Prescriptive analytics is a subset of BI that prescribes specific actions to optimize outcomes. It is situation-dependent, and it helps to determine a prudent course of action based on data.
• Predictive analytics, also known as predictive modeling, is the use of statistical techniques to create models that can predict future or unknown events. It is used to forecast trends in any industry, at a macro level.

3. Benchmarking: Benchmarking is the use of industry-recognized KPIs to measure the success of a business, a project, or a business process. It is a very important activity in the BI ecosystem and widely used to make incremental improvements to a business.

Common business intelligence mistakes

Even the best tools and platforms for BI projects can fail if not used correctly. Many organizations dive into BI expecting instant insights, only to find themselves overwhelmed, misled by poor data, or struggling with user adoption. To unlock the power of BI, it’s crucial to know what not to do.

Here are the common mistakes business owners make while implementing any BI project.

1. Focusing on data without clear goals

Mistake: Collecting and analyzing excessive data without aligning it to specific business objectives.

How to avoid:

• Start with clearly defined KPIs and business questions.
• Align BI efforts with organizational goals.
• Use a data governance strategy to filter out irrelevant data.

2. Poor data quality

Mistake: Using inaccurate, outdated, or inconsistent data which leads to faulty insights.

How to avoid:

• Implement data validation and cleansing processes regularly.
• Establish data ownership so someone is responsible for maintaining quality.
• Use automated data quality tools to detect and fix issues early.

3. Ignoring user training and adoption

Mistake: Assuming BI tools are intuitive, and everyone will know how to use them.

How to avoid:

• Offer ongoing training and user support.
• Create user-friendly dashboards tailored to different roles.
• Promote a data-driven culture where employees feel confident using BI tools.

4. Overcomplicating dashboards and reports

Mistake: Creating cluttered dashboards that overwhelm users with too much information.

How to avoid:

• Keep dashboards clean and focused—less is more.
• Prioritize visual hierarchy: use charts and graphs that are easy to interpret.
• Build role-specific reports to serve different team needs.

5. Failing to act on BI insights

Mistake: Treating BI as a reporting tool only, without integrating insights into decision-making.

How to avoid:

• Encourage leadership to regularly review BI reports and incorporate them into strategy meetings.
• Set up automated alerts for critical changes or anomalies.
• Tie BI outcomes to business actions and measurable results.

Challenges businesses face during BI implementation

If your company is going through any major organizational change, several challenges are bound to tag along. Overcoming these challenges is not difficult but you need expert supervision to sail through them. Some challenges that business owners face while implementing BI are:

1. Data integration: For companies gathering data from multiple sources, integration becomes a huge problem. It forms the foundation of every BI project as inaccurate data can bring inconsistencies along with it.
2. Data quality: The success of any project depends on the quality of data BI applications are built on. The root cause of poor data quality can be a lack of understanding about the importance of proper data management and the absence of a data management strategy.
3. Data security: As data breaches and unauthorized access pose significant threats to data, companies need to take robust security measures and adhere to all the compliance regulations in order to safeguard themselves.
4. Self-service BI tools: Uncontrolled self-service BI deployments in different business units can lead to a chaotic data environment with silos and conflicting analytics results that create confusion in the minds of business executives and other decision-makers.
5. Resistance to change: Even after a successful BI implementation, there is a fear of losing control or changing established practices. Therefore, management should get engaged early in the process, demonstrating how BI can support decision-making and improve outcomes.
6. Scalability: As businesses grow, their data volume and user demand increase, requiring BI systems to scale efficiently to accommodate future needs.

Real-world applications of BI

Business intelligence offers valuable functions in multiple industries. Some real-world applications of BI are:

1. Customer service: With both customer and product data available from a single data source. Customer care reps immediately answer customer questions or start to resolve their issues or complaints.
2. Finance and banking: By combining customer histories and market conditions, financial businesses can assess current business health and hazards, as well as predict future success.
3. Healthcare: Patients can easily get answers to a considerable number of critical healthcare questions without having to ask lengthy questions from medical personnel. Internal processes, including inventories, are easier to monitor and track within minutes.
4. Retail: Retailers may cut costs by comparing performance and benchmarks across stores, channels, and regions. With more visibility into the claims process, insurers can identify areas where they are falling short of service targets and use that data to improve results.
5. Sales and marketing: By combining data on promotions, pricing, sales, consumer activities and market trends. Marketers can make better future market decisions and campaigns. Detailed targeting or segmentation can hike sales.
6. Security and compliance: Centralized data and unified dashboards can help increase accuracy and identify the underlying causes of security issues. Compliance with rules can be assisted by using a single system to collect reporting data.

Strategy to implement business intelligence solutions

BI strategy is a blueprint for how you use the data generated by a company. This data can come from different sources, including human resources, supply chain, manufacturing, finance, customer relationship management and more. A successful BI strategy involves people, processes and technology.

1. Assess your current BI ecosystem: Review your company’s data needs at every level. Some companies will have analysts who require powerful tools for modeling, statistics, and data visualization. If you have sales staff, they may need real-time customer data. Consider using the BI maturity model to set a starting point for your BI strategy.
2. Determine your BI objectives: Whether your BI objectives include cutting costs, building new opportunities or cutting out inefficiencies, document the reasons for the improvement.
3. Define the vision and scope of BI: You know where your company exists with its current BI strategy. Now, figure out where it needs to go. You should align the vision and scope with your organization’s vision. To define the achievable scope, ensure you specify the KPIs that the project addresses. Scope all projects within the lens of the larger initiative. In other words, how does each project lead to a greater goal?
4. Identify key stakeholders: Determine everyone affected by the BI strategy you are developing. These are people who can influence or have an interest in the plan, especially customers.
5. Build a data map: Data maps reveal the supporting data landscape and what it means within a BI strategy. When you integrate data from multiple sources, build a map that shows the schema changes and the resulting data model. Be sure to include the data type.
6. Choose your BI platform and tools: BI platforms provide users with analysis, reporting and the ability to integrate software systems and datasets. When selecting a new system, consider technical compatibility in relation to your current plans. Determine the capabilities that you need, such as reporting and custom dashboards.
7. Prepare your data infrastructure: The data infrastructure consists of three main pieces: the business intelligence architecture, prepared data, and a data integration plan. Modern BI enables the user to bring together data from many sources, not just data warehouses. Develop the architecture based on business data sources. Make decisions about how you want this data to come together. This knowledge will help you prepare and integrate the various systems and data sets.
8. End-user training: The main end-users of a business intelligence strategy are decision-makers and anyone who needs to use business intelligence data to guide their actions. Train end users on the program, process and documentation locations.

Benefits of BI

An effective BI process can bring numerous benefits to the business. For example, BI enables businesses to continuously monitor and track business performance. Analyzing customer data improves marketing, distribution, sales, customer service and supply chain processes can be identified before they create economic loss. HR managers can track employee productivity, labor expenses and other workforce metrics.

Overall, the main advantages of BI solutions for businesses are the ability to do the following functions:

• Accelerate and improve decision-making.
• Optimize internal business operations.
• Improve operational efficiency and productivity.
• Identify business issues that need to be addressed.
• Identify new business and market trends.
• Create new business strategies.
• Drive up sales and new revenue.
• Gain a competitive advantage over the enterprises.

Most effective tools for BI projects

When looking to leverage BI, there are dozens of tools to choose from. Here, we review some of the top options on the market.

Factors influencing the success of BI in an organization

BI implementation in an organization can only succeed if the organization is committed and executes it effectively. The critical factors that influence the success of BI implementation include:

1. Business sponsorship: Business sponsorship is the most important success factor because even the best BI implementation cannot overcome a lack of commitment from the business leadership. If there is a lack of budget or motivation with the executives, BI cannot be adapted to its full potential.
2. Business needs: It’s critical to understand the business needs to properly implement business intelligence software. This understanding extends to both the end-users’ needs and the IT departments’ needs, and often they may differ. To estimate the BI requirements, organizations must analyze all the needs of its various stakeholders.
3. Amount and quality of the data: A BI initiative can only be successful if it incorporates high-quality data on a scale. Common data sources include customer relationship management (CRM) software, marketing platforms, customer support software, and enterprise resource planning (ERP) tools. Poor quality data will lead to poor decisions. By using data profiling techniques, the data is examined, and statistics are collected for improved data governance. This helps in maintaining consistency, reducing risk, and optimizing search through metadata.
4. Data gathering and cleansing: Data may be gathered from many sources, and this can easily overwhelm an organization’s decision-making capabilities. To prevent this and to create value with the BI software, organizations must identify their critical data sources. Business intelligence data often includes CRM data, competitor data, industry data, and more.
5. User experience: Intuitive user experience is critical when it comes to business intelligence in order to promote user adoption and to drive more value from BI tools. End-user adoption will be hard without simple and usable interfaces.
6. User training: User Training drives end-user adoption. If the end-users of the BI software aren’t properly trained, adoption and value creation become much slower and difficult to achieve.
7. Monitoring and improving: BI tools can end up becoming a black box to many users, so it’s important to continually validate their outputs. Setting up a feedback system for requesting and implementing user-requested changes is important for driving continuous improvement in business intelligence.

Future of BI

Recent innovations in BI have focused on self-service BI tools, which allow non-technical users to perform automatic analysis and reporting. The IT team remains responsible for managing corporate data, including accuracy and security, but multiple teams can now have direct access to data and oversee their own analysis, rather than having the job wait in queue for IT to run.

Machine learning and artificial intelligence are expected to be integrated into modern business intelligence and analytics systems as technology improves. With today’s focus on self-service, these capabilities can also help the company analyze data more quickly and generate deeper insights. Al-based systems may read from various sources automatically, capturing the most important data to lead decision-making.

Natural language queries, which are user-friendly than non- SQL specialists, are among the latest technologies in enterprise BI systems. Some BI systems include low-code or non-code development capabilities allowing users to design their own tools, apps, and reporting interfaces to speed up answers and time-to market.

Optimize your workflow with BI solutions

After learning about the intricacies of BI, business can now make an informed decision of how to utilize BI to help your business grow. BI is much more than a support for decision-making, if used correctly, BI has the potential to transform organizations.

At FBSPL, our experts have years of experience in providing the most efficient BI services that help you gather data specific to your business needs. With BI, you can create your own drilldowns to plunge into help desk data, customize the visualizations and share it with the people who can make a difference. Contact us today for more info.