Why Your Company Needs Modern Business Intelligence in 2023?

In 2023, the international business intelligence market size is aimed to register a value of US $28,216.8 million. It is aimed at growing to $56,200.9 million by 2023. 

The market value of mobile BI is predicted to reach a CAGR of 22.43% between the forecast period of 2021 and 2026.

Business Intelligence Definition

Business intelligence is a combination of architectures, technologies, and approaches that transform raw data into actionable insights that inform tactical and intelligent business decisions. 

It is a technology-oriented procedure used by businesses to drive relevant information by analyzing data to help managers and other professionals make operational business decisions. 

Business intelligence refers to the list of tools that offer immediate and easy access to actionable insights related to a company’s present state according to the available data. 

Business Intelligence tools analyze sets of data and showcase existing analytics results in dashboards, graphs, charts, reports, and maps to offer end users complete information regarding the condition of a business.

Although 40% of organizations don’t report major issues, business analytics can be tough in some cases.

The statistics from BI the survey indicated that 12% of companies struggle with poor governance and bad data quality issues, and 10% of respondents mention insufficient field training.  

Why Do Organizations Need BI Consulting Services?

To achieve consistent growth and stay in the market, organizations need BI consulting services.

Here are the reasons that demonstrate the need for Business intelligence consulting services:

a) Address their weakness

b) Monitor marketing 

c) Better visibility into different business functions

d) Strategic thinking

e) Value addition

What are the 5 Stages of Business Intelligence?

Business Intelligence includes the following five different stages:

Data Collection: This stage involves improving decision-making by collecting past and present data.

Data Storage: Data storage involves storing data effectively for future use, i.e., reporting and analysis.

Data Analysis: In this stage, both quantitative and qualitative approaches are followed to analyze data, and different trends and patterns are discovered to offer insights for the future.

Situation Awareness: The objective of this technology-oriented process is to offer the respective users in the company knowledge that assists in situational awareness.

This stage involves the generation of corporate reports and presentations and sharing them with the decision-makers to give hints about what’s happening inside and outside the organization.

This information is useful to understand the upcoming market trends and government regulations. 

Offering data access: Offering access to data enables the end user to conduct an analysis and look at the outcomes through numerous dashboards and reporting tools.

What is the Main Role of Business Intelligence?

Modern business intelligence is an integration of both data analytics and business analytics, using them wherever necessary but not fully.

With the use of next-generation Business Intelligence, users can produce conclusions from data analysis. Using predictive analytics and advanced statistics, data scientists look into data to identify and predict patterns related to the future. 

Let’s take a deeper look at how BI helps businesses streamline their processes:

More perfect data results in better decisions. Perfectness leads to better business forecasting. 

Proper planning and analysis can be done to strengthen the process, concentrate more on business operations, and make data-driven decisions.

Advancement in the sales forecasting procedure helps organizations with marketing and budgeting. In short, more accurate sales forecasting means better budget planning for the organization.

Advancements made to prices associated with the marketplace and product offerings can assist in more sales, resulting in more revenue. 

With the use of BI, employees can understand key performance indicators (KPIs). Knowledge of KPIs via dashboards and reports helps employees focus more on achieving their goals. 

What is the Importance of Business Intelligence in Big Data?

The term “Big data” has become a hot topic now. Data professionals simplify it by Volume, Value, Variety, and Velocity.

Big data is defined by these four “Vs”. Volume, which is something people usually assume is the critical defining feature, as the amount of data points is continuously changing and not hard to retain for a longer time. 

Both Big data and BI are different, but they have a few common goals. The objective of both BI and big data is to help in analyzing the data to obtain valuable insights and view the applicable data. 

How Business Intelligence Works?

Business intelligence brings together a series of data sources on one platform. Details, including marketing analytics, financial reports, customer surveys, sales performance, etc., are gathered and added to a single view.

This process has three actions: Extract, Transform, and Load. 

The “Extract” and “Transform” processes are related to finding and gathering data from suitable sources, and the “Load” process refers to uploading the data.

Once such data has been gathered into one, unified data store, companies can create reports for their users. 

Let’s dig deeper into an example that describes how businesses benefit from business intelligence services:

If your company started losing customers as a result of less quality customer service, this might be because they’re not happy with their experience when purchasing services or products online or from stores.

In this scenario, BI tools would offer management evidence in the form of statistics showing the percentage of people who complained about particular issues during every single transaction over a while, so that they could identify the root cause of their unhappiness. 

It is just a data-oriented process. Soon after collecting data from several sources, you can use algorithms and statistical models to discover insights into what does not work and what does. 

Let’s illustrate another scenario. Looking at sales data associated with you, you might identify that users who make purchases after visiting your site make more than those who purchase in-store.

This could allow for the development of fresh products or coming up with advertising options targeting online shoppers. 

Furthermore, business intelligence and data analytics services work well with crucial tools such as Tableau, Azure Synapse, Power BI, and Google Cloud. 

What are the Key Features of Business Intelligence?

Here are 10 features of business intelligence solutions:

Reporting:

This technology gives you a chance to schedule custom reports automatically to make sure they’re sent to clients on time. 

Adding amazing machine-readable style reports will help you explore data using pivots, rows, resizing columns, and filters. 

Advanced Analytics:

You can analyze the link between independent and dependent variables through the regression analysis option provided by this feature.

Also, you can use modern relations OLAP to explore data from a wide variety of sources. 

You can effortlessly compare business performance over customer sectors, geolocations, time, and groups of products.

Relying on self-service BI tools in advanced analytics makes the process human-friendly and accessible.

Data Visualization:

Visualizing data according to data charts and structural elements allows companies to look into their operations from various angles.

Simultaneously, BI offers numerous graphical cues to indicate major facts or statistics and trends. 

Location Intelligence:

Location intelligence maps and visualizes data in geographical ways.

The real-time overview and customer geographic location provided by this feature can act as a powerful weapon for businesses. 

BI users can use location intelligence to understand both trends and patterns in consumer behavior and make faster decisions related to sales and marketing. 

Customized alerts:

By default, BI software has an in-built automated alert feature.

Based on the client’s request, customized alerts can be set that will schedule emails to the management and employees concerning different reports on a daily, weekly, or monthly basis.

Data Management:

This process has various steps, such as developing, blending, examining, and cleansing data for investigation.

Inspect data to uncover characteristics, trends, and views while indicating them using tools like Power BI, Tableau, and Qlik Sense.

Self-service Analytics:

Making a smarter business decision requires access to relevant data; a business intelligence solution has to offer self-service analytics expertise that lets users access such data effortlessly and get a meaningful explanation to get started. 

Integration with different systems:

In order to analyze and share data at the business level, a BI solution needs to be combined with different systems.

Predictive Analytics:

In the dynamic world of business, you need to be competent enough to make error-free predictions.

Predictive analytics is used by firms to detect and exploit patterns composed within data to spot opportunities and threats.

Mobile business intelligence:

All companies work with huge quantities of data. In this competitive world, everyone wants to have access and control to real-time data to make decisions.

Many companies have adopted mobile applications and SaaS applications for major business operations.

No matter whether you’re the president, an owner, or a member of any team, mobile business intelligence provides you with a chance to enhance productivity and decision-making.

Types of Decisions Supported by Business Intelligence

Different types of decisions supported by Business Intelligence include:

1. Tactical Decisions
2. Strategic Decisions
3. Operational Decisions
4. Financial Decisions
5. Risk Management Decisions
6. Competitive Decisions

Tactical Decisions: Organizations are making tactical decisions to concentrate on day-to-day operations and enhance efficiency.

Managers are using BI to analyze real-time data to streamline workflows, allocate resources, and optimize processes.

These decisions will lead to departmental reorganization, proper work schedules, and improved profitability.

These are medium-term decisions that are less complex and are made by managers at the mid-level.

Strategic Decisions: Business decisions of a higher level are considered strategic decisions and these are normally less frequent and made by the business’s executives. 

Few types of strategic decisions involve hiring additional staff, acquiring a company, or choosing a specific market to penetrate.

Significant expenditure is required to make decisions at this level. Moreover, they are usually non-repetitive and can be taken only after thorough analysis.

These are long-term decisions made by managers at higher levels.

Operational Decisions: Operational or structural decisions generally happen on a daily or hourly basis and are made by managers at the junior level.

They are related to day-to-day operations and don’t have a greater effect on the company.  

Examples of operational decisions include answering questions related to sales, calculating the performance bonus of an employee, approving a business quotation, etc. 

Financial Decisions: Businesses use BI to get updated, perfect data analytics related to finance.

Financial managers use this technology to track major KPIs, monitor expenses and revenues, predict financial outcomes related to the future, and discover cost-saving probabilities.

This in turn results in budgeting and financial planning, decisions related to investment, and financial stability.   

Risk Management: Business intelligence is used by organizations to make decisions related to risk management by analyzing past data and discovering possibilities for risks and dangers.   

By keeping an eye on key risk indicators, companies can proactively minimize risks, follow regulations, and ensure continuity of operations. 

Competitive Decisions: These involve the collection of huge quantities of data related to the competitors to create perfect business strategies that beat the competition.

Furthermore, it doesn’t include getting information in unethical ways.

Applications of Business Intelligence

Sales Intelligence: The sales department of every business focuses more on customer negotiation skills.

Sometimes it’s very hard to convince potential clients to buy a product or service. This process has become more predictable and smoother through business intelligence and analytics consulting services. 

Initially, BI collects data on various KPIs such as sales metrics, customer demographics, conversions, and so on.

Later, this data is well organized into structured visualizations such as scattergrams, graphs, and pie charts. 

Both the sales and marketing teams can implement BI to find out trends in customer interests, allowing the company to increase sales with their perfect client bases.

This makes them shift their focus to converting targeted leads and improving both conversion rates and complete profit margins. 

Visualization: Business intelligence software makes use of various data analytics tools to understand and manage data relevant to business operations.

Organizations present such data in visualized formats to keep an eye on sales, productivity, and logistics. 

Custom reporting capabilities will be provided by some business intelligence platforms that allow end users to highlight their parameters.

Whereas, ready-made reporting templates with built-in standard metrics will be provided by others. 

Reporting: It is the activity of organizing data in the synopsis to track overall business performance.

It translates data into simple, plain information and gives a clear idea of what’s happening. 

Performance Management: Companies can use BI applications to track goal progress using customizable or pre-set timeframes.

Target delivery time, project delivery deadlines, and sales goals come under data-driven goals. 

Users can monitor how much of the goal has been completed and use progress information to measure the complete productivity of the company. 

What are the Advantages of Business Intelligence?

Here are the different advantages of BI:

Fast and Accurate Reporting:

Employees use business intelligence to measure major KPIs using customized templates, producing real-time reports, and offering the latest and most suitable information to assist businesses in responding immediately and enhancing the perfection of their reporting.  

Increased collaboration:

The centralized platform provided by BI tools can allow teams to access and share information, collaborate on analysis, and generate action items.

It enhances cross-functional collaboration by breaking down silos within the company. 

Better ROI:

Both CX and sales efficiency can be improved by the in-built CRM feature present in the business intelligence system.

This leads to smoother handling of both current and after-sales services. Business intelligence enables organizations to eliminate underperforming products, optimize their marketing approaches, and increase ROI. 

Minimized risks:

Companies use it to make data-oriented decisions, reduce guesswork in making business decisions, and effectively allocate resources.

It becomes very easy to inspect both the success ratio and the performance of different programs. That assists in tackling various organizational challenges before they arise. 

Enhanced productivity:

Business intelligence assists companies in automating day-to-day tasks, categorizing processes without human efforts, refining processes, and enhancing productivity and CX.

Business Intelligence Examples

Let’s take a look at some real-world examples of business intelligence from leading international brands that use these tools:

Netflix: Everyone is familiar with the OTT platform Netflix, which uses both data science and business intelligence to acquire fresh subscribers and enhance the user experience.

Business intelligence solutions produce customized watch lists and delightful artwork while convincing subscribers to watch their preferred genres.  

It uses recommendation systems for content promotion to reach the right audience at the right time. 

Starbucks: Starbucks uses BI to analyze data according to traffic patterns, population density, customer demographics, average income level, and public transport centers.

By providing the best deals and loyalty card programs, it tracks individual purchase information through a mobile app.

This information will be used later to predict purchases and send customized offers through email or apps to encourage customers and improve sales. 

Tesla: It is a reputed automotive company that uses BI to connect its vehicles wirelessly to corporate offices to collect data.

Later, that data can be analyzed to prevent issues such as traffic hazards and equipment damage. 

This technology helps this automotive giant increase user satisfaction and inform decisions about upcoming upgrades. 

Uber: This is a transportation company based out of California that tracks conditions of traffic, journey duration and times, availability of drivers, and customer demand using business intelligence.

It uses a rating system and surge pricing in its business model to control fares and maintain trust between customers and drivers. 

Walmart: Based on client purchases, Walmart makes use of business intelligence to measure client behavior in-store and online.

They can use it to make smarter decisions around varieties, resources, promotions, merchandising, and inventory to generate traffic.

Business Intelligence vs. Business Analytics

Both processes use data to enhance business, but let’s explore further to understand the differences between business analytics and business intelligence:

The focus of business intelligence is on descriptive analytics

Business intelligence gives more importance to descriptive analytics, which involves a synopsis of past and current data to display what has occurred or is occurring at present.

BI provides the “what” and “how” answers so you can duplicate what is effective and modify what is ineffective. 

The focus of business analytics is on predictive analytics 

Business analytics gives more importance to predictive analytics, which makes use of modeling, ML, and data mining to find out the possibility of upcoming results.

Business analytics provides a solution for the “why” to predict upcoming events more perfectly.  

Business intelligence is less expensive than Business Analytics

Many parameters are used to conduct data visualization and growth analysis. Business analytics gives high priority to past and current data and analyzes the needs of customers.

The report does not simply include a synopsis of what it found. 

Business Analytics has a much wider perspective

Business intelligence relies more on data collection, whereas Business analytics concentrates on making instant progress.

Business analytics is necessary and mandatory to form a strategy and aims to reprogram the upcoming operations of a company’s future to make it profitable. 

Business intelligence aims to adopt and translate received data into useful insights. Business analytics is future-driven, as it assists in understanding future difficulties. 

Reporting vs. Applying

BI is more simplified and has data systematically organized into reports that are simple to understand and inform the viewer of what is happening.

With BI outcomes, charts, simple-to-understand reports, and interactive dashboards are frequently used. 

Business Analytics goes a step further and moves further to explain why things are occurring by using both statistical analysis and data applications. 

Structured vs. Semi-structured data

Business intelligence applications are better suited for structured data from business applications such as financial software systems and ERP.

It assists in getting insights from previous financial transactions. 

Business analytics applications are better suited for semi-structured and unstructured data, convert them into useful data before analysis, and later receive insights from that data with in-depth predictive analytics.

Disadvantages of Self-Service BI

Incorrect analytics outcomes:

As a result of incomplete sets of data or data issues that aren’t identified and addressed, self-service questions might lead to incorrect outputs.

In the case of numerous users working with different versions of the same data and organizing it for analysis in various ways, there is a possibility of irregularity. These challenges can result in ineffective decision-making. 

Issues related to privacy, ethics, and data security:

When reliable data security measures and effective information governance are in different places, the increased data accessibility that self-service BI allows might raise issues.

Unauthorized people might get access to confidential data that breaks laws related to data privacy and ethical standards in business. 

Deployments without supervision:

Self-service BI settings may become disorganized when there is no centralized monitoring and supervision by the BI team.

Irregular data silos, different BI tools, and rising costs can make extending self-service capabilities productive and efficient in cases where business divisions implement BI systems independently.

Business Intelligence Trends 2023

Connected Cloud:

The working approach of many companies has changed after the COVID-19 pandemic. During this period, many companies started changing their current BI strategies. 

Organizations realigned their expenses to make room for the transition to Cloud BI and analytics platforms, as on-premise solutions weren’t able to handle the hurdles of a largely remote workforce. 

According to Gartner’s reports, 40% of all enterprise workloads have already been transferred to the cloud. Organizations are now slowly implementing data solutions after realizing the importance of analytics.

Leading industry brands like SAP, Amazon Web Services, and Oracle offer industry-oriented BI solutions with ready-to-move automation and personalization. 

You don’t need to build workflows from the start; personalization gives you more control over how the application functions and appears.     

Artificial Intelligence: 

In 2023, companies will progressively integrate both AI and BI to obtain detailed insights and make intelligent decisions.

The integration of these two technologies will facilitate their ability to randomly discover and automate IT operations while maintaining high volumes of agility and scalability, thus analyzing extensive datasets with less human involvement. 

These capabilities can make the data analysis process error-free and faster and minimize the stress on people.

Predictive and Real-time Analytics:

In the upcoming year, companies will combine real-time and predictive analytics to inspect data.

This two-extended strategy will enable companies to tackle unwarranted threats immediately and change reactions based on circumstances in real time. 

This will enable them to optimize their present processes and drive innovation by gaining better insights, adopting better procedures, and discovering fresh opportunities for organizational growth. 

Augmented Analytics:

Combining AI and ML makes it easier for companies to let non-technical employees access the importance of business intelligence.

With the help of augmented analytics, the whole team can quickly produce powerful data analytics models and gain useful insights from them. 

One of the key features of any platform for business intelligence is data analytics, which has become more accessible by asking relevant questions and offering contextual feedback for related insights. 

In 2023, it will continue to influence organizations because it helps them manage the complexity and volume of data through flawless data collection, cleaning, and insight creation. 

Natural Language Processing (NLP):

Because of NLP, self-service BI has become a hot trend in analysis. A few language tools, such as Bard and ChatGPT, have become popular for driving insights from unorganized data.

These language tools could accelerate the extensive development of NLP in analysis. 

Developing a platform to respond in major spoken languages requires patience and time, but technology is growing.

In 2023, it is expected that there will be major developments in the application of NLP.

Data Discovery or Visualization:

For a larger audience, visual data discovery provides fresh insights. It will expand over time with rising frequency.

Both employees and companies need to understand the impact of data. In this case, data discovery or visualization comes into the picture. 

Data analytics dashboards increase data transparency and accessibility by analyzing and disclosing sensitive information.

Embedded Analytics:

Allied Market Research states that the international embedded analytics market is projected to hit $60,281 million by 2023.

Embedded analytics enable rapid data analysis without shifting any information between software environments by becoming close to local apps. 

Data Automation:

Automation plays a critical role in large-scale analytics projects in which manual efforts will result in inaccurate results and a waste of time.

In such cases, data-driven decision-makers prefer data automation using BI for many tasks.

The Role of BI in the Present Business Environment

In the present business environment, business intelligence plays a major role in many key areas, including:

Faster decision-making:

At the organizational level, BI establishes business goals. The tools offered by BI examine and validate raw data to help in better decision-making. 

Consider an example: a retail firm takes advantage of BI and analytics services to predict product purchases and offer customized solutions to its customers via email.

This approach forces customers to land on their site repeatedly, which leads to improved revenue.

Goal and ROI Enhancement:

For instance, reporting operations are automated by a consolidated business intelligence implementation and solution.

It lets the marketing team generate tailored marketing campaigns for particular regions. They can react to consumer behaviors and improve marketing efforts if they keep track of and monitor real-time data. 

Improved Productivity:

It is possible to increase labor productivity by consolidating business information. The major advantage of business intelligence analytics tools and management is automated report creation and real-time updating.

Therefore, the employees may concentrate on more productive tasks. 

Sales and Market Intelligence:

Customer Relationship Management (CRM) software is used by both sales and marketing teams to monitor their customers.

As they include customer interactions and contacts, enormous amounts of data can be assessed for strategic efforts. 

Businesses can leverage business intelligence systems to conduct sales loss/win analysis, find fresh clients, maintain and monitor present clients, and provide after-sale support. 

Planning the Business for a Brighter Future:

Investing in experienced business intelligence consultants allows firms to speed up their ability to predict market trends and implement changes at the corporate level to stay competitive.

How can Business Intelligence Enable Better Conversions in Digital Marketing?

Target Demographics:

Business intelligence for marketing enables organizing information into multi-channel sources, empowering businesses to make perfect marketing action plans.

Marketers use this technology to collect data related to customers from many sources and highlight it in a dashboard view regarding their buying habits, demographic stats, preferred products, and pain points. 

Marketers will go through this information thoroughly and start sending campaigns to their niche audiences using the relevant channels to produce results.   

Optimize the company website for more conversions:

Firms are using business intelligence for CRO (conversion rate optimization) – periodically updating websites to acquire more visitors who subscribe to newsletters, purchase a product, etc.

By making use of business intelligence tools for marketing, firms can get valuable details related to the journey of visitors who converted. 

Customer journey analysis:

Business intelligence tools provide a complete client journey to marketers. 

These tools ensure marketers have a clear understanding of the different factors that lead to conversions and address pain points throughout the client lifecycle. 

A/B testing:

Business intelligence eases A/B testing and optimization by offering statistical analysis and insights to decide the winning variation.

By testing various versions of ads, email content, and landing pages, marketers can track the performance of changes and find out the elements that lead to more conversions.

How can Business Intelligence help in eCommerce Reporting?

Listed below are some important reports that business intelligence tools can provide to help eCommerce companies understand their business and attract the right prospects:

Inventory Reports:

For the success of eCommerce businesses, inventory management plays a key role.

eCommerce business intelligence tools can track real-time inventory data, minimize stockouts, ensure maximum stock levels, and reduce holding costs.

By combining sales data with inventory data, eCommerce companies can discover highly selling products, predict demand, and make wise business decisions regarding the supply chain of inventory.

Sales and Revenue Reports:

When it comes to sales, data collection comes to mind. Business intelligence in eCommerce helps track the overall performance of all sales professionals.

This involves the number of leads generated and the total number of qualified leads converted by each employee in the sales team.

Moreover, business intelligence reporting involves a clear understanding of the origin of leads and the month with the highest sales. 

Marketing Reports:

In eCommerce, business intelligence is used for business planning, forecasting, and visualizations. Marketing is important for the success and development of eCommerce companies.

So, marketing strategies like SEO and PPC can generate enough data to analyze. Hence, BI helps companies centralize all data together so it can be perfectly leveraged. 

Customer Data Reports:

eCommerce companies take complete advantage of business intelligence and analytics services to monitor the touchpoints of their customers.

These reports involve a 360-degree view of clients’ behavior across various levels, along with the tasks carried out by resellers and distributors. 

eCommerce firms can improve profitability using the insights provided by this customer intelligence tool, which covers which product has been searched for by which user, which user has ordered a specific product, etc.    

Conclusion:

Business intelligence is the best option for organizations to collect data from countless sources. They can choose from numerous options to perform this. Still, the most powerful method includes using tools that let them simply visualize data so that their decision-makers can make better and more intelligent decisions.

If you are in search of a reliable BI services company, you are in the right location.

Express Analytics is a trusted organization that assists you maximize profits and productivity through data-driven insights.   

References:

The Role of Business Intelligence: What it is and Why it Matters

Business Intelligence Trends to Know in 2023

Why is Business Intelligence Important for Your Organization?