Crafting a Business Intelligence Strategy

A business intelligence (BI) strategy is a roadmap or blueprint designed to help businesses determine how to best use data. It aims to make more informed, data-driven decisions that help organizations achieve business goals. 

Business intelligence involves gathering, analyzing, and applying data to guide strategic decisions, refine operations, and build competitive advantage. Originating from the management information systems of the late 20th century, BI has transformed, harnessing advanced technology to deliver valuable, actionable insights. Today, BI is essential across industries, driving benefits like increased operational efficiency, deeper customer understanding, and new pathways for strategic growth.

Components of a business intelligence strategy

Understanding the core components is essential for developing an effective business intelligence strategy and roadmap. A successful business intelligence (BI) strategy relies on multiple components that transform raw data into valuable insights. These elements create the foundation of a BI strategy by enabling data collection, management, and analysis to support informed decision-making and drive growth. Each component is vital, from setting clear goals to establishing robust data governance, choosing the right technology, and fostering a data-driven culture. 

Goals and objectives 

Clearly defining your BI strategy’s specific business goals and objectives aligns all BI efforts with the organization's overall strategic goals. Establishing data-driven goals creates a more focused approach to leveraging data for business growth and improved decision-making. For instance, a business intelligence strategy example of precise goal setting might increase customer retention by 15 percent. When you set clear objectives, your organization can more easily identify improvement areas, whether revenue, growth, or customer acquisition. 

Data governance 

Data governance encompasses the processes, policies, and procedures that dictate how organizations collect, store, and maintain data. It’s an essential component of a BI strategy because it helps maximize the value of organizational data so it can best meet your organization’s needs. Effective data governance ensures that data is accurate, clean, secure, and compliant with regulations.

To implement data governance policies and procedures, it’s critical to inform all stakeholders, work as a team to establish roles and responsibilities, clearly define the processes and procedures (i.e. data security, data collection, etc.), and maintain high-quality and accurate data.

Organizations rely on data governance to help implement and manage these policies. These tools convert high-quality data into actionable insights, improving efficiency and supporting informed decision-making with consistent and accurate information to guide strategic business decisions. 

Analytics and reporting

Analytics and reporting are essential components of a BI strategy. They turn raw data into actionable insights and support continuous improvement and strategic growth. 

Through analytics, organizations can process and examine data to uncover trends, patterns, and correlations that provide a deeper understanding of their operations, customers, and markets. Reporting organizes these data insights into more straightforward and visually appealing formats like dashboards, reports, and visualizations, making it easier for organizations to interpret data and make informed decisions. 

With clearer, data-driven information, analytics and reporting help guide strategic choices. For example, the marketing department within an organization can better create tailored marketing strategies for allocating resources more effectively. Tracking key metrics over time allows businesses to monitor performance, identify improvement areas, and proactively react to market changes when needed. 

Tools and technology 

Tools and technology provide the necessary infrastructure to store, organize, and analyze data, which is foundational for any BI strategy. These tools support data integration from multiple sources, allow for complex analysis, and generate more reliable insights for organizational decision-making. 

When crafting and implementing a BI strategy, BI tools help create a solid infrastructure for it, helping to transform raw data into actionable insights. These tools work together to collect, store, and analyze data in valuable and meaningful ways: 

• Data sourcing tools: Data sourcing is the process of data collection. Organizations use data sourcing tools to identify and set up the sources from which they will gather data (i.e. sales, customer service, and marketing) to achieve a specific objective. 

  • Examples: Excel, Google Analytics (marketing), SQL

• Data collection tools [extract, transform, load (ETL) tools]: After defining data sources, ETL tools help merge data from multiple sources into a cohesive format. These tools automate the ETL process, simplifying the movement and preparation of data for storage in the warehouse. 

  • Examples: Apache NiFi, Informatica, Talend

• Data storage tools (data warehouses): A data warehouse allows organizations to store and organize the cleansed data from ETL processes in a centralized data warehouse, allowing for more organized and efficient analysis. 

  • Examples: Amazon Redshift, Snowflake, Google BigQuery 

• Data governance tools: Once data is stored, organizations apply governance tools to ensure quality, security, and regulatory compliance. This step helps maintain data integrity in the BI processes.

  • Examples: Azure Governance, Microsoft Purview Data Lifecycle Management 

• Data visualization and analysis tools: Organizations can generate insights through BI platforms and visualizations to make data more accessible to analyze and visualize. Data mining tools, data discovery tools, or data modeling tools help organizations look for trends in data, build reports, and generate insights based on business needs. 

  • Examples: Power BI, Tableau, Cognos Analytics

User adoption

User adoption is critical for maximizing the impact and implementation of a BI strategy. It ensures stakeholders and employees within the organization can effectively use BI tools to make informed, data-driven decisions. 

To encourage adoption, consider holding training tailored to users' roles and technical abilities, providing active sessions, tutorials, and other forms of ongoing support. Creating a user-friendly interface with intuitive dashboards and visualizations helps make BI tools accessible, even to those with limited technical experience. Conducting regular feedback sessions with users helps identify any challenges so you can address them quickly.

The role of business intelligence strategy

A well-crafted business intelligence (BI) strategy is pivotal in enabling organizations to leverage data effectively for competitive advantage. By allowing for real-time data analysis, a strong BI strategy supports quick, informed decision-making that can respond to market shifts to maintain a competitive advantage. 

A core benefit of BI strategies is that they help identify trends and patterns, which can provide valuable insights for strategic planning that aligns with long-term goals. A BI strategy also deepens customer understanding, offering insights into customer behavior and preferences that can improve market positioning. 

Who benefits from a business intelligence strategy?

By harnessing data insights, BI strategies enhance decision-making, streamline operations, and support customer understanding in nearly every sector. These strategies extend beyond IT departments; they empower the following professionals:

1. Business analysts

Business analysts leverage data analysis to streamline business processes and enhance productivity, efficiency, and profitability. They collaborate with internal teams to identify needs, address issues affecting the company’s bottom line, and uncover opportunities for growth as market conditions shift. By identifying areas for improvement and potential advantages, business analysts can help an organization stay competitive.

How does a BI strategy help?

An effective BI strategy improves a business analyst's ability to make informed decisions and boost organizational success. Analysts rely on BI strategies to identify trends, monitor performance, and uncover insights that inform strategic planning.  Business analysts can use BI tools to boost productivity by quickly retrieving, storing, and organizing data, streamlining business operations. BI strategies enhance visibility with interactive reports, graphs, and charts that track KPIs and reveal trends, leading to better insights into company performance, customer demographics, and market conditions. 

2. Marketing managers

Marketing managers create and implement marketing campaigns for organizations or specific products. They establish marketing policies, monitor market trends, devise pricing strategies, and identify target customer markets to increase demand and sales. These marketing professionals collaborate with other marketing and advertising professionals, work closely with product managers, and oversee teams to ensure proper campaign development. Marketing managers must know how, when, and why to change marketing strategies to align with organizational goals.  

How does a BI strategy help?

Finance departments can benefit from high-quality data when a BI strategy is in place. With BI tools and a solid BI strategy, finance departments can track revenue in real time, which then trickles down to improved decision-making in other areas like marketing. With an effective BI strategy, financial professionals can achieve more accurate budgeting and forecasting with data on key performance metrics such as sales, financial, and operations KPIs. In short, organizations can optimize their supply chain with more detailed financial data in hand.  

3. Executive leadership positions

Those who hold executive positions (also known as C-level titles) manage and supervise other positions and/or projects within an organization. Roles vary widely based on the size of the company, the department in which you work, and your specific C-level position. Standard executive titles include: 

• Executive director (ED)

• Chief executive officer (CEO)

• Chief information officer (CIO)

• Chief operating officer (COO)

• Vice president (VP)

• Chief marketing officer (CMO)

• Chief financial officer (CFO)

How does a BI strategy help?

Finance departments can benefit from high-quality data when a BI strategy is in place. With BI tools and a solid BI strategy, finance departments can track revenue in real time, which then trickles down to improved decision-making in other areas like marketing. With an effective BI strategy, financial professionals can achieve more accurate budgeting and forecasting with data on key performance metrics such as sales, financial, and operations KPIs. In short, organizations can optimize their supply chain with more detailed financial data in hand.  

4. Finance departments

An organization’s finance department makes helps make financial decisions for the organization. Some responsibilities of a finance department include running payroll, controlling income and expenses, creating and forecasting budgets, and making strategic financial moves on the company’s behalf based on economic and market data. A company’s financial department typically includes the following roles: 

• Auditor 

• Accountant 

• Finance administrator 

• Budget analyst 

• Payroll officer 

• Finance controller 

• Treasury analyst  

How does a BI strategy help?

Finance departments can benefit from high-quality data when a BI strategy is in place. With BI tools and a solid BI strategy, finance departments can track revenue in real time, which then trickles down to improved decision-making in other areas like marketing. With an effective BI strategy, financial professionals can achieve more accurate budgeting and forecasting with data on key performance metrics such as sales, financial, and operations KPIs. In short, organizations can optimize their supply chain with more detailed financial data in hand.  

Pros and cons of implementing a BI strategy

As with any business strategy, both benefits and drawbacks are to be considered. Implementing a BI strategy takes intentional time, effort, and resources with the right people to develop the appropriate strategy for your organization. It requires careful planning, skilled personnel, and tools tailored to your organization’s needs. But when you get it right, a well-crafted BI strategy with the right BI tools can transform raw data into actionable insights, enabling better decision-making, improved operational efficiency, and a competitive edge.

Advantages

An effective BI strategy with the right tools enhances data accessibility, provides real-time reporting, and empowers teams across the organization to make informed choices based on data-driven analytics. Some of the advantages of implementing a BI strategy include: 

• Data-driven insights improve decision-making

• Enhanced operational efficiency and productivity

• More transparent reporting and more consolidated data 

Disadvantages

Initial setup costs can be high when first implementing your BI strategy, and without proper training, user adoption may suffer, limiting the strategy’s effectiveness. Some of the disadvantages to consider when building a BI strategy include: 

• High initial setup and implementation costs

• Data quality issues like inaccuracy or duplication 

• Contradictions in data analysis 

• Low user adoption rates 

• Security concerns 

Despite these challenges, the benefits of a robust BI strategy often outweigh the drawbacks when aligned with organizational goals. By investing in the right technology, building a data-driven culture, and involving key stakeholders, you can better maximize the value of your BI efforts. 

Launching your career in business intelligence

Starting a career in BI requires a blend of education, practical experience, and professional certifications to set a solid foundation in the field. Most careers in BI require a degree. Experience and skill building are other essential steps in launching a successful long-term career in the field. Many continuing education opportunities exist if you want to demonstrate proficiency in key BI skills and tools further. 

Education

Most BI roles, such as data analyst, business analyst, BI developer, and data visualization specialist, require at least a bachelor's degree in relevant fields like data science, computer science, business, or information systems. A master’s degree offers advanced training in machine learning, big data technologies, and data mining that can lead to more advanced positions, especially in data analytics and BI management. 

Professional and practical experience

Gaining experience with BI tools and software is critical for aspiring data analysts and anyone who wants to launch a successful career in BI. You can seek out experience through real-world data internships, entry-level positions, and opportunities like open-source data analysis projects.

Some skills you’ll want to build include: 

• Expertise in programming languages 

• Proficiency in data analysis tools

• Understanding of data warehousing and ETL processes 

• Data retrieval and analysis

• Knowledge of machine learning algorithms

• Ability to work with BI tools such as Tableau and Microsoft Power BI

• Predictive modeling 

Certifications and certificates 

Beyond earning a degree and building practical and professional experience, consider enrolling in boot camps, online courses, or certification programs on data analytics or specific programming languages. These additional credentials add essential technical skills to your resume and demonstrate dedication and proficiency in essential BI skills with popular BI platforms. For anyone transferring into BI from another field, certifications, and certificates are beneficial for transitioning into a new profession. 

Some certifications and certificates to consider in the field of BI include: 

• Microsoft Power BI Data Analyst Professional Certificate is an online professional certificate program offered on Coursera that is designed to equip you with the necessary skills to gain proficiency in data analysis using Microsoft Power BI. The program consists of eight courses that cover topics such as connecting to data sources, transforming data, creating reports and dashboards, and preparing for the PL-300 certification exam.

• Microsoft Certified: Data Analyst Associate certification formally validates proficiency in using Microsoft Power BI to design and build data models, clean and transform data, and create meaningful data visualizations. To earn this certification, you must pass Exam PL-300: Microsoft Power BI Data Analyst, which assesses skills in preparing, modeling, visualizing, and analyzing data, as well as managing and deploying Power BI assets. 

• Tableau Desktop Specialist: This entry-level credential validates foundational skills and knowledge in Tableau Desktop. It assesses a candidate's ability to connect to data sources, prepare data, explore and analyze data, and share insights through visualizations. The exam consists of 45 multiple-choice and multiple-response questions and has a 60-minute time limit. 

Getting started with business intelligence on Coursera

Developing a robust BI strategy takes dedication, time, and effort. Get started building your business intelligence strategy online with an online course on BI essentials and fundamentals. Online courses offer an efficient and effective means of learning more about BI and the benefits of implementing a robust BI strategy for your organization. 

Consider enrolling in the Google Business Intelligence Professional Certificate, a helpful and highly insightful course designed for anyone wanting to learn basic strategies for building an effective BI strategy. This program covers topics like business intelligence, data models, and pipelines.