Making the right decisions in an aggressive market is crucial for your business growth and that’s where decision intelligence (DI) comes to play. As each choice can steer the trajectory of an organization, propelling it towards remarkable growth or leaving it struggling to keep pace. In this era of information overload, utilizing the power of data and technology has become paramount to drive effective decision-making.

Decision intelligence is an innovative approach that blends the realms of data analysis, artificial intelligence, and human judgment to empower businesses with actionable insights. Decision intelligence is not just about crunching numbers or relying on algorithms; it is about unlocking the true potential of data to make smarter choices and fuel business success.

Imagine a world where every decision is infused with the wisdom of data, where complex problems are unraveled and transformed into opportunities, and where the path to growth is paved with confidence and foresight. Decision intelligence opens the doors to such a world, providing organizations with a holistic framework to optimize their decision-making processes.

At its core, decision intelligence harnesses the power of advanced technologies to collect, integrate, and analyze vast amounts of data. This data becomes the lifeblood of the decision-making process, unveiling hidden patterns, trends, and correlations that shape business landscapes. But decision intelligence goes beyond the realm of data analysis; it embraces the insights gleaned from behavioral science, acknowledging the critical role human judgment plays in the decision-making journey.

Think of decision intelligence as a synergy between the human mind and cutting-edge algorithms. It combines the cognitive capabilities of humans with the precision and efficiency of artificial intelligence, resulting in a harmonious collaboration that brings forth actionable recommendations and strategic insights.

From optimizing resource allocation to mitigating risks, from uncovering untapped market opportunities to delivering personalized customer experiences, decision intelligence is a guiding compass that empowers businesses to navigate the complexities of today’s competitive world. It enables organizations to make informed choices, capitalize on emerging trends, and seize growth opportunities with confidence.

What is decision intelligence?

Decision intelligence is an advanced approach that combines data analysis, artificial intelligence algorithms, and human judgment to enhance decision-making processes. It leverages the power of technology to provide actionable insights and recommendations that support effective decision-making in complex business scenarios.

At its core, decision intelligence involves collecting and integrating relevant data from various sources, such as databases, text documents, and APIs. This data is then analyzed using statistical methods, machine learning algorithms, and data mining techniques to uncover meaningful patterns and relationships.

In addition to data analysis, decision intelligence integrates principles from behavioral science to understand how human behavior influences decision-making. By incorporating insights from psychology, cognitive science, and economics, decision models can better account for biases, preferences, and heuristics that impact decision outcomes.

AI algorithms play a crucial role in decision intelligence. These algorithms are carefully selected based on the specific decision problem and are trained using the prepared data. Machine learning algorithms, such as neural networks or decision trees, learn from the data to make predictions or generate recommendations.

The development of decision models is an essential step in decision intelligence. These models capture the relationships between input variables, decision options, and desired outcomes. Rule-based systems, optimization techniques, or probabilistic frameworks are employed to guide decision-making based on the insights gained from data analysis and AI algorithms.

Human judgment is integrated into the decision-making process to provide context, validate recommendations, and ensure ethical considerations. Decision intelligence systems provide interfaces or interactive tools that enable human decision-makers to interact with the models, incorporate their expertise, and assess the impact of different decision options.

Continuous learning and improvement are fundamental to decision intelligence. The system adapts and improves over time as new data becomes available or new insights are gained. Decision models can be updated and refined to reflect changing circumstances and improve decision accuracy.

At the end of the day, decision intelligence empowers businesses to make informed decisions by leveraging data, AI algorithms, and human judgment. It optimizes decision-making processes, drives growth, and enables organizations to navigate complex business environments with confidence.

How does decision intelligence work?

Decision intelligence operates by combining advanced data analysis techniques, artificial intelligence algorithms, and human judgment to drive effective decision-making processes.

Let’s delve into the technical aspects of how decision intelligence works.

Data collection and integration

The process begins with collecting and integrating relevant data from various sources. This includes structured data from databases, unstructured data from text documents or images, and external data from APIs or web scraping. The collected data is then organized and prepared for analysis.

Data analysis and modeling

Decision intelligence relies on data analysis techniques to uncover patterns, trends, and relationships within the data. Statistical methods, machine learning algorithms, and data mining techniques are employed to extract meaningful insights from the collected data.

This analysis may involve feature engineering, dimensionality reduction, clustering, classification, regression, or other statistical modeling approaches.

Behavioral science integration

Decision intelligence incorporates principles from behavioral science to understand and model human decision-making processes. Insights from psychology, cognitive science, and economics are utilized to capture the nuances of human behavior and incorporate them into decision models.

This integration helps to address biases, preferences, and heuristics that influence decision-making.

AI algorithm selection and training

Depending on the nature of the decision problem, appropriate artificial intelligence algorithms are selected. These may include machine learning algorithms like neural networks, decision trees, support vector machines, or reinforcement learning.

The chosen algorithms are then trained using the prepared data to learn patterns, make predictions, or generate recommendations.

Decision model development

Based on the insights gained from data analysis and AI algorithms, decision models are developed. These models capture the relationships between input variables, decision options, and desired outcomes.

The models may employ rule-based systems, optimization techniques, or probabilistic frameworks to guide decision-making.

Human judgment integration

Decision intelligence recognizes the importance of human judgment in the decision-making process. It provides interfaces or interactive tools that enable human decision-makers to interact with the models, incorporate their expertise, and assess the impact of different decision options. Human judgment is integrated to provide context, validate recommendations, and ensure ethical considerations are accounted for.

Continuous learning and improvement

Decision intelligence systems often incorporate mechanisms for continuous learning and improvement. As new data becomes available or new insights are gained, the models can be updated and refined.

This allows decision intelligence systems to adapt to changing circumstances and improve decision accuracy over time.

Decision execution and monitoring

Once decisions are made based on the recommendations provided by the decision intelligence system, they are executed in the operational environment. The outcomes of these decisions are monitored and feedback is collected to assess the effectiveness of the decisions and refine the decision models if necessary.

How is decision intelligence different from artificial intelligence?

AI, standing for artificial intelligence, encompasses the theory and development of algorithms that aim to replicate human cognitive capabilities. These algorithms are designed to perform tasks that were traditionally exclusive to humans, such as decision-making, language processing, and visual perception. AI has witnessed remarkable advancements in recent years, enabling machines to analyze vast amounts of data, recognize patterns, and make predictions with increasing accuracy.

On the other hand, Decision intelligence takes AI a step further by applying it in the practical realm of commercial decision-making. It leverages the capabilities of AI algorithms to provide recommended actions that specifically address business needs or solve complex business problems. The focus of Decision intelligence is always on achieving commercial objectives and driving effective decision-making processes within organizations across various industries.

To illustrate this distinction, let’s consider an example. Suppose there is an AI algorithm that has been trained to predict future demand for a specific set of products based on historical data and market trends. This AI algorithm alone is capable of generating accurate demand forecasts. However, Decision intelligence comes into play when this initial AI-powered prediction is translated into tangible business decisions.

In the context of our example, Decision intelligence would involve providing a user-friendly interface or platform that allows a merchandising team to access and interpret the AI-generated demand forecasts. The team can then utilize these insights to make informed buying and stock management decisions. This integration of AI algorithms and user-friendly interfaces transforms the raw power of AI into practical Decision intelligence, empowering businesses to make strategic decisions based on data-driven insights.

By utilizing Decision intelligence, organizations can unlock new possibilities for growth and efficiency. The ability to leverage AI algorithms in the decision-making process enables businesses to optimize their operations, minimize risks, and capitalize on emerging opportunities. Moreover, Decision intelligence facilitates decision-making at scale, allowing businesses to handle complex and dynamic business environments more effectively.

Below we have prepared a table summarizing the difference between decision intelligence and artificial intelligence:

How can decision intelligence help with your business growth?

Decision intelligence is a powerful tool that can drive business growth. By leveraging data-driven insights and incorporating artificial intelligence techniques, decision intelligence empowers businesses to make informed decisions and optimize their operations.

Strategic decision-making is enhanced through the use of decision intelligence. By analyzing market trends, customer behavior, and competitor activities, businesses can make well-informed choices that align with their growth goals and capitalize on market opportunities.

From zero to BI hero: Launching your business intelligence career

Optimal resource allocation is another key aspect of decision intelligence. By analyzing data and using optimization techniques, businesses can identify the most efficient use of resources, improving operational efficiency and cost-effectiveness. This optimized resource allocation enables businesses to allocate their finances, personnel, and time effectively, contributing to business growth.

Risk management is critical for sustained growth, and decision intelligence plays a role in mitigating risks. Through data analysis and risk assessment, decision intelligence helps businesses identify potential risks and develop strategies to minimize their impact. This proactive approach to risk management safeguards business growth and ensures continuity.

Market insights are invaluable for driving business growth, and decision intelligence help businesses uncover those insights. By analyzing data, customer behavior, and competitor activities, businesses can gain a deep understanding of their target market, identify emerging trends, and seize growth opportunities. These market insights inform strategic decisions and provide a competitive edge.

Personalized customer experiences are increasingly important for driving growth, and decision intelligence enable businesses to deliver tailored experiences. By analyzing customer data and preferences, businesses can personalize their products, services, and marketing efforts, enhancing customer satisfaction and fostering loyalty, which in turn drives business growth.

Agility is crucial in a rapidly changing business landscape, and decision intelligence supports businesses in adapting quickly. By continuously monitoring data, performance indicators, and market trends, businesses can make timely adjustments to their strategies and operations. This agility enables businesses to seize growth opportunities, address challenges, and stay ahead in competitive markets.

There are great companies that offer decision intelligence solutions your business need

There are several companies that offer decision intelligence solutions. These companies specialize in developing platforms, software, and services that enable businesses to leverage data, analytics, and AI algorithms for improved decision-making.

Below, we present you with the best decision intelligence companies out there.

• Qlik
• ThoughtSpot
• DataRobot
• IBM Watson
• Microsoft Power BI
• Salesforce Einstein Analytics

Qlik

Qlik offers a range of decision intelligence solutions that enable businesses to explore, analyze, and visualize data to uncover insights and make informed decisions. Their platform combines data integration, AI-powered analytics, and collaborative features to drive data-driven decision-making.

ThoughtSpot

ThoughtSpot provides an AI-driven analytics platform that enables users to search and analyze data intuitively, without the need for complex queries or programming. Their solution empowers decision-makers to explore data, derive insights, and make informed decisions with speed and simplicity.

DataRobot

DataRobot offers an automated machine learning platform that helps organizations build, deploy, and manage AI models for decision-making. Their solution enables businesses to leverage the power of AI algorithms to automate and optimize decision processes across various domains.

IBM Watson

IBM Watson provides a suite of decision intelligence solutions that leverage AI, natural language processing, and machine learning to enhance decision-making capabilities. Their portfolio includes tools for data exploration, predictive analytics, and decision optimization to support a wide range of business applications.

Microsoft Power BI

Microsoft Power BI is a business intelligence and analytics platform that enables businesses to visualize data, create interactive dashboards, and derive insights for decision-making. It integrates with other Microsoft products and offers AI-powered features for advanced analytics.

While you can access Power BI for a fixed fee, with the giant company’s latest announcement, Microsoft Fabric, you can access all the support your business needs with this service in a pay-as-you-go pricing form.

Salesforce Einstein Analytics

Salesforce Einstein Analytics is an AI-powered analytics platform that helps businesses uncover insights from their customer data. It provides predictive analytics, AI-driven recommendations, and interactive visualizations to support data-driven decision-making in sales, marketing, and customer service.

These are just a few examples of companies offering decision intelligence solutions. The decision intelligence market is continuously evolving, with new players entering the field and existing companies expanding their offerings.

Organizations can explore these solutions to find the one that best aligns with their specific needs and objectives to achieve business growth waiting for them on the horizon.

Certified Business Analysis Professionals, equipped with the necessary skills and expertise, play a pivotal role in the ever-changing world of business. In order to remain relevant and seize opportunities, organizations must make well-timed, informed decisions. This is precisely where the proficiency of business examiners, commonly known as business analysts, becomes invaluable. Certified Business Analysis Professionals specialize in evaluating multiple factors within a company, thereby fostering its growth.

To thrive in the role of a business analyst, it is imperative to stay updated with the latest industry developments. And what better way to achieve this than by obtaining the prestigious CBAP certification? Offered by the International Institute of Business Analysis, headquartered in Canada, this certification carries immense value.

It signifies a level 3 certification, serving as a testament to the individual’s experience and prowess in the field. Armed with this distinguished certificate, professionals can anticipate securing positions at the intermediate or senior level, aligning with their exceptional abilities.

Who is a Certified Business Analysis Professional?

A Certified Business Analysis Professional (CBAP) refers to an individual who has successfully acquired the CBAP certification, a prestigious credential bestowed by the International Institute of Business Analysis (IIBA). These professionals specialize in the field of business analysis and showcase a remarkable level of knowledge, expertise, and experience in this particular domain.

The CBAP certification serves as a testament to the extensive expertise and comprehensive understanding of business analysis possessed by individuals who have earned this prestigious designation. It is specifically designed for seasoned business analysts who have demonstrated proficiency across various facets of the discipline. These include requirements planning and management, enterprise analysis, elicitation and collaboration, requirements analysis, solution assessment, and validation, as well as business analysis planning and monitoring.

By attaining the CBAP certification, professionals validate their proficiency and commitment to excellence in the field of business analysis, thereby distinguishing themselves as highly skilled practitioners. This prestigious credential enhances their credibility, opens up new career opportunities, and sets them apart as recognized leaders in the realm of business analysis.

Working areas of Certified Business Analysis Professional

Certified Business Analysis Professionals (CBAPs) are highly versatile and can be found working in various areas within the field of business analysis. Their expertise and knowledge equip them to handle diverse roles and responsibilities. Here are some common working areas where CBAPs make a significant impact:

Elicitation and analysis: Certified Business Analysis Professionals excel in gathering and comprehending business requirements from stakeholders. They employ techniques such as interviews, workshops, and surveys to extract requirements and analyze them to ensure alignment with organizational objectives.

Planning and management: CBAPs possess the skills to develop strategies and plans for effectively managing requirements throughout the project lifecycle. They establish processes for change management, prioritize requirements, and create requirements traceability matrices.

Business process analysis: CBAPs evaluate existing business processes to identify areas for improvement. They collaborate with stakeholders to streamline workflows, enhance operational efficiency, and boost productivity.

Solution assessment and validation: CBAPs play a crucial role in evaluating and validating proposed solutions to ensure they meet desired business objectives. They conduct impact analyses, assess risks, and perform user acceptance testing to verify solution effectiveness.

Business analysis planning and monitoring: CBAPs contribute to defining the scope and objectives of business analysis initiatives. They develop comprehensive plans, set realistic timelines, allocate resources, and monitor progress to ensure successful project delivery.

Stakeholder engagement and communication: CBAPs possess excellent communication and interpersonal skills, enabling them to engage with stakeholders effectively. They facilitate workshops, conduct presentations, and foster clear communication between business units and project teams.

Enterprise analysis: CBAPs possess a holistic understanding of the organization and conduct enterprise analysis. They assess strategic goals, perform feasibility studies, and identify opportunities for business improvement and innovation.

Data analysis and modeling: Certified Business Analysis Professionals have a solid grasp of data analysis techniques and can create data models to support business analysis activities. They identify data requirements, develop data dictionaries, and collaborate with data management teams.

Business case development: CBAPs contribute to the development of business cases by evaluating costs, benefits, and risks associated with proposed projects. They provide recommendations for investment decisions and assist in justifying initiatives.

Continuous improvement: Certified Business Analysis Professionals actively contribute to the continuous improvement of business analysis practices within organizations. They identify areas for process enhancement, propose new methodologies, and mentor other business analysts.

These examples illustrate the wide range of working areas where Certified Business Analysis Professionals thrive, leveraging their versatile skill set to drive effective analysis and strategic decision-making. Their contributions are instrumental in helping organizations achieve their business goals.

Is CBAP certification recognized?

The CBAP certification is widely recognized and highly regarded in the business analysis industry. It holds international recognition and carries significant value among employers, industry professionals, and organizations.

Employers often prioritize candidates with CBAP certification when hiring for business analysis positions. This certification serves as tangible evidence of a candidate’s proficiency and commitment to the field. It validates their expertise in business analysis principles, techniques, and methodologies.

How to get certified as a business analyst

The CBAP certification is acknowledged as a significant milestone in professional development within the business analysis domain. It can substantially broaden career prospects, open doors to new opportunities, and distinguish individuals in a competitive job market.

The International Institute of Business Analysis (IIBA), the governing body responsible for granting the CBAP certification, is globally acknowledged as a leading authority in the field of business analysis. The IIBA upholds rigorous standards for the certification process, ensuring that Certified Business Analysis Professionals meet the necessary requirements and possess the skills and knowledge essential for success in their roles.

Benefits of becoming a Certified Business Analysis Professional

CBAP certification offers several compelling benefits that can significantly impact your career trajectory. Let’s explore some of the key advantages that can propel your professional growth to new heights.

Undergoing CBAP certification training can greatly enhance your chances of passing the certification exam on your first attempt. Additionally, you can find more detailed information about CBAP benefits here.

Credibility: The CBAP certification holds wide acceptance, which translates to increased credibility in the eyes of employers. It serves as tangible proof of your expertise and competence as a skilled business analyst, making you a desirable candidate for job opportunities.

Job satisfaction: Attaining CBAP certification grants you access to a wealth of valuable tools and resources that streamline your job responsibilities. This means you can work on critical and impactful projects, instilling a sense of importance and confidence in your role. In reputable organizations, knowledge is highly valued, enabling you to apply your expertise and derive job satisfaction from making a meaningful impact.

Skill development: Becoming a Certified Business Analysis Professional equips you with a diverse range of techniques that further develop your skills and enhance your problem-solving abilities. The comprehensive curriculum provides valuable insights and practical knowledge to excel in your business analysis endeavors.

Salary advancement: CBAP certification opens doors to potential salary increases and career advancement opportunities. With this prestigious certification, you demonstrate your proficiency in handling complex programs and projects, positioning yourself for higher-paying roles within the industry.

Industry recognition: Certified Business Analysis Professionals are held in high regard within the business analysis domain. Their commitment to continuous learning and professional development makes them highly sought after by top industries and organizations.

Networking opportunities: Effective networking plays a pivotal role in the business analysis field. CBAP certification provides you with the opportunity to tap into the untapped potential of the industry and connect with like-minded peers, expanding your professional network and fostering valuable collaborations.

By utilizing the benefits of CBAP certification, you can elevate your career prospects, gain industry recognition, and unlock new opportunities for growth and success.

How much does a Certified Business Analysis Professional earn?

In recent years, companies have increasingly sought out professionals with CBAP certifications due to their specialized skill sets and expertise in business analysis. As a result, individuals holding the CBAP designation enjoy several advantages, including better job opportunities, higher income potential, and global recognition.

One of the key benefits of CBAP certification is the improved job prospects it offers. Companies value the comprehensive knowledge and advanced competencies that CBAP recipients possess, making Certified Business Analysis Professionals highly desirable candidates for business analysis roles. With a CBAP certification, you have a competitive edge in the job market, opening doors to a wider range of career opportunities.

The global recognition of CBAP certification further enhances its value. Certified Business Analysis Professionals are acknowledged internationally for their proficiency in business analysis and their adherence to globally recognized standards. This recognition not only adds prestige to your professional profile but also facilitates career advancement on a global scale.

According to data from Indeed, a Certified Business Analysis Professional earn an average salary of $83,000 per year. This figure showcases the financial benefits that come with attaining the CBAP certification, solidifying its reputation as a valuable credential in the field of business analysis.

Alternative certifications to CBAP certification

The CBAP is not the only certification available for professionals who want to demonstrate their skills as business analysts. The Professional in Business Analysis (PBA) certification offered by the Project Management Institute (PMI) is also popular among industry professionals.

Here is a quick overview of the key differences between the two certifications to help you determine which one aligns better with your goals:

CBAP certification

• Requirements: Complete a minimum of 7,500 hours of business analysis work experience within the past ten years, with at least 3,600 hours dedicated to combined areas outlined in the BABOK (Business Analysis Body of Knowledge); 35 hours of professional development within the last four years
• Exam: Consists of 120 multiple-choice questions to be answered within a time frame of 3.5 hours

PBA certification

• Requirements: With a secondary degree, complete 7,500 hours of work experience as a business analysis practitioner, earned within the last eight years, with at least 2,000 hours focused on working on project teams. With a Bachelor’s degree or higher, complete 4,500 hours of work experience as a business analysis practitioner, with at least 2,000 hours dedicated to working on project teams. Both secondary degree and Bachelor’s degree holders require 35 hours of training in business analysis
• Exam: Consists of 200 multiple-choice questions to be answered within a time frame of over 4 hours

The choice of certification will depend on personal preferences. PMI has been established for a longer time than IIBA, but CBAP has been around longer than PBA. Consequently, some employers may be more familiar with one organization or certification than the other. Nevertheless, both certifications are highly regarded. In 2020, for instance, CIO, a notable tech publication, listed CBAP and PBA among the top ten business analyst certifications.

The role of Certified Business Analysis Professionals (CBAPs) in the field of business analysis cannot be overstated. These highly skilled individuals have demonstrated their expertise, knowledge, and commitment to the profession through the rigorous CBAP certification process. The CBAP designation not only signifies credibility and recognition on a global scale but also opens doors to better job opportunities and higher income potential.

In a world of evolving business landscapes and increasing demand for effective decision-making, CBAPs play a crucial role in driving organizational success. Their expertise, coupled with their commitment to excellence, makes them instrumental in delivering impactful business solutions and fostering innovation. With their invaluable contributions to the field of business analysis, CBAPs shape the future of organizations and drive success in an ever-changing business world.

Why business intelligence is a must in the modern business? Business intelligence (BI) solutions can help organizations maintain their competitiveness by giving them a comprehensive view of all of their data. But it can also be challenging to comprehend exactly what BI is for individuals who haven’t adopted a tool yet or are just curious. Is it a fortune-teller? Let’s take a closer look.

Why business intelligence (BI) is needed?

The age of technological advancement is upon us. Our daily lives have undergone a complete revolution thanks to technological improvements, and the business world has been particularly affected. Businesses today have access to data-driven tools and tactics that enable them to understand more than ever about their customers and themselves. Still, not all of them are making use of them.

Businesses can benefit from business intelligence solutions to maintain a competitive edge and increase income streams. Organizations of all sizes and stages employ BI software to manage, analyze, and visualize corporate data.

Business Intelligence services are essential for modern businesses due to the numerous benefits they offer. Here are some of them:

Companies can use data analytics to define their operations, examine causes for good or bad events, produce knowledge they may not have, and receive advice on a potential course of action. These kinds of analyses, including tracking key performance indicators (KPIs) and creating precise reports, may all be done by businesses using business intelligence tools.

Analysts can put their insights into practice by using these tools to share their findings with stakeholders. As you can see, this is a crucial step for every business. Because of that, business intelligence analysts are in high demand.

A brief reminder of business intelligence will help us better understand the subject.

What is business intelligence and analytics?

To assist businesses in making more data-driven decisions, business intelligence integrates business analytics, data mining, data visualization, data tools and infrastructure, and best practices.

You can determine if your organization has modern business intelligence when you thoroughly understand its data and use it to drive change, eliminate inefficiencies, and react swiftly to supply or market changes. Flexible self-service analysis, controlled data on reliable platforms, empowered business users, and speed to insight are prioritized by modern BI solutions.

What is the purpose of business intelligence?

Business intelligence’s purpose is to use pertinent data to enhance an organization’s business operations. Businesses that use BI tools and methodologies properly can turn their gathered data into insightful information about their operational procedures and business plans.

Incorporating corporate data into user-friendly representations like reports, dashboards, charts, and graphs is what business intelligence (BI) software does. Business users can access various data types using BI technologies, including semi-structured and unstructured data like social media, historical and current data, internal and external data, and third-party and internal data. Users can examine this data to learn more about the company’s performance and make predictions. So, is it a fortune-teller? Not exactly.

How business intelligence works?

Data warehouses have always served as the foundational source of information for BI tools.

A data warehouse combines information from various sources into one main database to facilitate reporting and business analytics. The warehouse is queried by business intelligence software, which then displays the findings to the user as reports, charts, and maps.

Online analytical processing (OLAP) engines can handle multidimensional queries in data warehouses. For instance, if you wonder how are sales in our eastern and western regions compared to last year, BI is here to help you.

Some business intelligence (BI) software can link with solutions for particular industry verticals, like retail, travel, and media services. Using dashboards, intricate analytical processing, and potent visualizations, BI reporting and BI analytics may be able to assist these users in finding answers to guide their daily business. Because it enables executives to make prompt, data-supported decisions,

BI reporting is a crucial component of business intelligence.

But how exactly does business intelligence work efficiently? Most businesses have data scattered across several locations, but they cannot manage this data or combine these various data sources.

BI systems can use many data sources to quickly and accurately present information to decision-makers, eliminating the need for an IT department to run intricate reports. These data sources could come from supply chain information, marketing or sales analytics, operational performance, or customer relationship management software (such as Salesforce).

Typically, BI software can combine all of these sources to offer historical, present-day, and future perspectives that support corporate planning. Businesses should think carefully about their operations and strategies, particularly their current data integration, reporting, and information sharing procedures.

Are you looking for the best way to build your business intelligence strategies? We explain techniques, roadmap, and examples of BI strategies in this article.

Importance of business intelligence

Why is business intelligence crucial for firms in the modern era? A strong BI strategy and system should be adopted for the following primary reasons:

New customer insights

Businesses invest time, money, and resources into business intelligence since it improves their capacity to watch and assess the most recent client purchasing trends.

Your business’s bottom line will increase after you use BI to comprehend what and why your customers are buying from you. With this knowledge, you can develop new goods and improve existing ones to fulfill their wants and expectations better. It is one of the reasons why business intelligence is needed.

Better data quality

Data is rarely perfect, and there are numerous ways for discrepancies and mistakes to surface, especially when using a poorly constructed “database”.

Businesses that care about gathering, maintaining, and producing high-quality data often have greater success. 

Businesses can use BI software to combine data from many sources to get a more comprehensive picture of their operations.

Visibility

Due to a BI system’s increased visibility of these functions, business intelligent enterprises have more control over their processes and standard operating procedures. The days of reading quickly through annual reports with hundreds of pages are long gone.

Business intelligence illuminates every aspect of your company, making it easier to spot areas that need development and enabling you to take a proactive rather than a reactionary approach.

Actionable information

A powerful business intelligence system can spot important organizational trends and patterns. A BI system also enables you to comprehend the effects of different organizational processes and changes, make wise decisions, and take the appropriate action.

Efficiency improvements

BI systems contribute to increasing organizational effectiveness, which in turn raises production and potentially boosts income. Businesses may readily exchange important information across departments thanks to business intelligence platforms, reducing the time spent on reporting, data extraction, and analysis.

Organizations can minimize redundant roles and responsibilities by facilitating information sharing more effectively. This frees up employees’ time to concentrate on their work rather than processing data.

Check out how business intelligence creates collaboration in the workforce

Sales insight

Both sales and marketing teams use the Customer Relationship Management (CRM) program to keep track of their customers. CRMs are made to handle all customer interactions.

Check out the best CRM software for small businesses in 2022

There is a plethora of data and information that can be evaluated and applied to strategic goals because they house all consumer contacts and interactions. BI systems assist businesses with various tasks, including finding new customers, keeping track of and retaining existing ones, and offering post-sale services. It is one of the reasons why business intelligence is required.

Real-time data

The data is vulnerable to human mistakes and runs the risk of being out of date before it is even presented for evaluation because executives and decision-makers must wait for reports to be assembled by several departments.

Spreadsheets, visual dashboards, and scheduled emails are a few ways BI systems give customers access to data in real-time. Utilizing Business Intelligence solutions allows for large volumes’ swift and accurate assimilation, interpretation, and distribution.

Competitive advantage

In addition to all of these wonderful advantages, business intelligence may help you learn what your rivals are doing, enabling your company to prepare for the future and make informed decisions. It is one of the reasons why business intelligence is important.

Importance of business intelligence in decision-making

All the advantages mentioned above contribute to the decision-making process. Making judgments based on assumptions rather than facts is one of a business’s biggest blunders.

Businesses can use business intelligence to gather the information they need to make critical decisions, such as which goods to promote more aggressively and which to phase out. All business-related information can be gathered, including financial, production, and customer satisfaction data.

Real-world BI use cases

By giving teams the freedom to analyze their own data and come to better conclusions, BI may improve business processes by giving them a comprehensive perspective on their objectives. Now that we are aware of BI’s significance. Now let’s examine some BI real-world applications.

Amazon

Amazon employs BI technology and tools to sell things, personalize product recommendations, and make logistical business decisions. In-depth data analysis ensures the smooth operation of Amazon’s massive supply chain.

Amazon’s supply chain is significantly impacted by data and business intelligence technologies ranging from inventory allocation to delivery route optimization.

Coca-Cola

Coca-Cola gains from its social media information, which includes 105 million Facebook likes and 35 million Twitter followers. The company uses AI-driven picture recognition technology to track down when images of its drinks are shared online. This data, together with the prevalence of BI, enables the business to understand more about who is consuming its beverages, where they are, and why they are making online mentions of the brand.

Personalized advertising, which is four times more likely to be clicked on than generic advertising, is given to consumers using the data.

Netflix

This online entertainment company has a sizable BI advantage thanks to its 148 million customers. 

Netflix uses data in several different ways. The company’s method of creating and evaluating new programming concepts based on previously watched shows is the most well-known business intelligence application. Netflix uses BI to get users or customers to engage with its content.

Over 80% of all streamed content comes from the service’s recommendation algorithm since it pushes targeted content effectively.

How business intelligence systems are implemented?

Business intelligence implementation is not difficult, but it does require careful planning and strict adherence.

It is recommended that you do not neglect these steps:

• Create a plan for implementing business intelligence.
• Identify and appoint the BI implementation team.
• Define KPIs.
• Find a reliable software provider.
• Choose appropriate BI tools.
• Consider the infrastructure.
• Execute data migration (if needed).
• Create a feedback loop.
• Implement BI on a larger scale.

It is also crucial for the implementation process to distinguish between business analytics and business intelligence.

Comparison: Business intelligence vs business analytics

Business analytics, commonly known as BA, and business intelligence are closely related.

Some people think the primary distinction lies in the passage of time: business analytics aids in business planning for the future, such as by using predictive analytics to determine why things are happening and how they will develop in the future, whereas business intelligence assists in day-to-day operations and how things appear in the present.

Most people who work with business analytics have a background in math or statistics or have completed an online master’s program in the field. Experts in business intelligence should also have a strong mathematical foundation and analytical thinking.

Business analytics and business intelligence frequently function effectively together. Business analytics may continue where BI left off and find methods to enhance a company’s performance in the future because BI helps businesses manage and optimize their daily operations.

Why business intelligence is the future?

Since its inception, the business intelligence sector has advanced significantly. From its inception in the 19th century, when data-driven judgments replaced gut instincts, to on-premises databases and difficult IT reporting projects that only experts could translate in the 20th century, to the present-day self-service models we are familiar with and use.

Technology, applications, and trends in business intelligence are getting easier and easier to access.

Business intelligence is projected to become considerably more automated and aggressively used in the future, with fewer interface restrictions and barriers to the free flow of data. Future BI trends are part of a rapidly changing framework necessary for the development of contemporary businesses.

Some of the most anticipated BI trends for the future include:

• Augmented analytics,
• Natural Language Processing (NLP),
• Data cognition,
• Auditable AI, and more.

Did you notice these are all related to AI? If you wonder how AI transforming business intelligence, we have already explained it.

According to Mordor Intelligence, the Business Intelligence Market was estimated to be worth USD 20.516 billion in 2020 and is projected to increase at a CAGR of 12.5 percent over the forecast period to reach USD 40.50 billion by 2026. (2021-2026).

Is business intelligence a good career?

Like data scientists and analysts, business intelligence analysts are one of the most sought-after positions globally and sweep both the business and technology markets. The success of a company and the development of an enterprise both depend on a skilled business intelligence analyst.

Check out the most wanted business intelligence analyst skills in 2022

According to PayScale statistics, the yearly pay for a business intelligence analyst ranges from $48,701 to $93,243 in the United States, with a standard salary of $66,645 per year. We can easily assume the demand continues to rise, and business intelligence is one of the best career options in the world.

Other highly sought-after positions include some of the following:

• Blockchain engineers
• Artificial intelligence careers
• Data architect
• Cloud computing jobs
• Data engineer jobs, 
• Machine learning engineers 

Conclusion

BI enables the combination of data from various sources, analysis of the information, and dissemination of the information to pertinent stakeholders. Because of this, businesses can view the big picture and make wise business decisions.

Making every business decision always comes with certain inherent risks, but those risks aren’t as noticeable or concerning when using a solid BI system. Business Intelligent firms can advance with confidence in a world that is becoming more data-driven because they are ready to meet any challenge that may come their way. So it is not a fortune-teller; it is a fortune-maker!

More and more companies are seeking to implement innovative ways to improve business efficiency. As data is constantly expanding, BI software draws meaningful insights from the raw data to provide a deeper impact for businesses. If you’re in this place and evaluating BI software consider checking out some of these popular systems

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Journey Science, being derived from connected data from different customer activities, has become pivotal for the telecommunications industry, providing the means to drastically improve the customer experience and retention. It has the ability to link together scattered pieces of data, and enhance a telco business’ objectives. Siloed approaches are becoming obsolete – take call centers as an example – there is only so much that you can do with data from only one system.

By using insights from customer journey analytics, telco businesses can better measure the user experience, and make informed decision for refining it. The data not only allow them to take proactive approach towards customer satisfaction, but enable the prediction of future failures as well. With customer journey analytics, you can evaluate the touchpoints to journeys, and revamp your strategies to better cater to customers’ needs.

In the telecom industry, it is difficult for a business to effectively manage the massive volume of data with the existing systems and technology. There are several aspects where telecom companies need to make improvements, such as reduce costs, improve customer experience, increase conversion rates, and many more. To do so, they need to derive meaning from the collected data by finding connections among them. This linked data is also known as journeys. Journeys provide you with relevant data that enable you to make well-grounded business decisions by looking at customer transactions as a whole, and determining where direct improvements are needed.

Customer Journey Analytics is Transforming Telecommunications

Many leading telco businesses are embracing the Journey Science concept, and deem it to be the best way to make greater impact on the target audience. One good way to better understand digital journeys is through a multi-channel, end-2-end, view. Journey Sciences, at its best, provides enhanced data accessibility and increased analytics agility, and helps in weaving together disparate pieces of data. This makes it possible for telco businesses to link together structured and unstructured data back to their strategic objectives, and quickly modify them to ensure they cope with the evolving customer demands. However, in order to get insight into customer experience through journey analytics, it is critical to focus not only on the individual moments but the customers’ end-to-end experiences as well.

Customer Experience Boost

The main benefit of customer journey analytics for telco companies is that it enables them to better recognize customer needs, and assess their satisfaction level. While most people think Journey Science is all about marketing, it mainly focuses on the services domain. For example, a customer seeking technical support for their device has multiple paths to resolution. Journey Science enables businesses to evaluate each step of the journey experience, and figure out the critical points that could negatively impact customer experience. With this kind of information, businesses can develop strategies to overcome hurdles customers face on all such touchpoints, resulting in improved customer experience.

Improving Customer Journeys through Transparency

Connecting the Dots

For improving customer experience, it is essential to connect all the data down to the individual customer level to fully understand the required changes. For telco businesses to completely understand customer journeys, they must gather data from many different channels, and track the individual journey the customer experiences. Typically, more than 50 percent of customers make multi-channel journeys; meaning, in order to understand their behavior, establishing connection among all the data is extremely important. Because of the deep roots of technology in today’s common lifestyle, many journeys start from digital channels, but eventually go into a human channel for completion.

Utilizing Aggregate and Raw Data

Apart from giving a complete picture of customer journeys, the analytics let you tap into different levels of aggregation, allowing you to view raw data as well. With journey mapping, telco businesses can benefit from both in-depth data points and aggregated data sets. Since a single customer journey can compile hundreds of thousands of data points, having aggregated views makes it much easier to pinpoint and prioritize the problematic areas. On the other hand, some journeys may yield unclear results, for example, unusual behavior of a customer on a webpage. In such a case, having access into the raw data renders the ability to focus on one key area and get invaluable insights.

Making Changes through Data Availability

Effective utilization of data from customer journey analytics allows telco to revamp their strategy as well as make smaller improvements on a continuous basis. Getting immediate feedback regarding a certain change is critical for understanding its impact. You can determine whether the intended results will be realized, or should you scale-up or sustain the change. However, a manual, project-based approach that only provides an overview of the required data will not be enough to transform journeys successfully. Instead, you should opt for an agile, iterative, analytic approach that uses continuous data availability.

It won’t be wrong to say that all those ad-hoc, manual, project-based approaches using snapshots of data have severe limitations.

How the Customer Journey differs in both Fixed and Mobile Telco

Mobile (mobile data usage, subscriptions, charges, and mobile data access)

Several small customer journeys can be linked together to make improvements to a mobile telco operation. One great way is through customer engagement, i.e. moving down to individualized journeys of each customer instead of mass-segmentation. Journey Science opens doors for mobile telco companies to take personalization up a notch, and provide customized recommendations based on the journeys of each customer. You should also utilize real-time context to enhance customer engagement for better results.

Mobile customer experience comprises of several touchpoints where a subscriber interacts with a service provide agent – it can be during retail, billing, customer support, visible marketing campaigns, and others. Consider three customers below that have 3 different journeys to perform the same action.

Fixed line providers have an additional interaction channel with field technicians being deployed to customers’ homes for service. These field service appointments are a major part of customer experience and often have significant variability for different customers. Consider the following journey which involves multiple appointments, agent phone calls, and delays:

Journey Science is Moving towards Predictive Analytics

The Journey Science concept is increasingly becoming popular across the telco industry, as it greatly benefits by assessing journeys of individual customers and allow them to develop customized strategies. Moreover, it allows telco businesses to anticipate the potential pitfalls leading to negative customer experience and prevent it altogether. By tapping into the data from customer journey, telco can streamline their operations and provide a better, more satisfying experience to their customers.

In today’s world, customer satisfaction is the keystone for success in every industry, including telco. Businesses should turn to the Journey Science movement, and optimize their processes by carefully analyzing customer journeys and making improvements accordingly. Effective utilization of customer journey analytics leads to better redesigning efforts, ultimately reducing costs, enhancing customer experience, and stretching bottom-line.

Want to talk more about Journey Sciences? Join the JourneyScience movement on Twitter by following @journey_science and the Journey Sciences Linkedin group today.

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