Just as finding the right product-market-fit is important for enterprises, so is data mining for business intelligence for a future-ready, self-sustaining venture. It helps in future road mapping, product development, and umpteen business processes that keep the profit-wheel rolling. Therefore, in this article, we’ll be articulating topics that relate to data mining and business intelligence, the importance of data mining, and how it is carried out to ensure seamless revenue flows. 

What is Data Mining in Business?

The importance of data mining in business is that it is used to turn raw data into meaningful, consumable, actionable insights. Data engineers employ software to look up patterns that aid in analyzing consumers. Data sets are compared to unearth relevant metrics having an impact on revenue lines to follow up with strategies, sales improvement measures, and optimizing marketing campaigns. 

Due to the overlapping nature of the subject between data operations, data mining is often confused and used interchangeably with data analysis and business intelligence. But each term is different from one another. 

Data mining refers to the process of extracting information from large data sets whereas data analysis is the process used to find patterns from the extracted information. Data analysis involves stages such as inspecting, cleaning, transforming, and modeling data. The objective is to find information, draw inferences, and act on them. Moving on, let us look at the differences between data mining and business intelligence. 

Processes like data mining and data analysis converge into business intelligence helping organizations generate usable and demonstrable information on products and services. 

How is Data Mining Used in Business Intelligence?

The way we use data mining for business analytics and intelligence varies from one business to another. But there is a structure to this business process management that remains pretty much iron clad. Here’s a look at it. 

Business Understanding

If you are undertaking data mining for business analytics and want it to be successful then begin by identifying the purpose of data mining. Subsequent steps in the plan could tackle how to use the newfound data bits. Ideating your data mining algorithm would be a far-fetched task lest you underline the purpose of data mining concisely. 

Data Understanding 

After getting to know the purpose of data mining it is time to get a touch and feel for your data. There could be just as many ways to store and monetize data as there are businesses. How you create, curate, categorize, and commercialize your data is upto your enterprise IT strategy and practices. 

Data Preparation 

Considered one of the most important stages in the course of nurturing data mining for business intelligence, company data needs expert handling. Data engineers convert data into a readable format that non-IT professionals can interpret in addition to cleansing and modeling it as per specific attributes. 

Data Modeling 

Statistical algorithms are deployed to decipher hidden patterns in data. A lot of trial and error goes into finding relevant trends that can enhance revenue metrics. 

Data Evaluation 

The steps involved in data modeling should be evaluated microscopically for inconsistencies. Remember, all roads (must) lead to streamlining operations and augmenting profits. 

Implementation

The final step is to act on the findings in an observable way. Field trials of the recommendations should be piloted at a smaller scale and then expanded onto branch outlets upon validation. 

Now you know how the build-up of milestones distills into ground reality. Let us explore some of the technicalities of data mining for business intelligence.  

An Overview of Data Mining Techniques 

In this section, we will look over each rung of the data mining ladder and how they act as stepping stones for future growth. 

Classification 

This is a complex procedure that uses data attributes to compartmentalize information to draw understandable collusions. As a reference to this, an example of data mining in business could be using supermarket data to group information into categories such as groceries, dairy products, etc. Tagging and studying this data can help users understand customer preferences for each line item. 

Clustering 

Although it may sound similar to the previous step yet there are differences. Cluster groups are not as defined in structure as Classification groups. An example could be edible items, non-edible items, perishable products, etc. instead of specific groceries, dairy products in the earlier case. 

Association Rules 

Here, we use link variables to track patterns. Continuing on our supermarket example, this could mean customers who purchase a grocery item (edible), are more likely to purchase fruits (perishable) as well. Upon validating this fact, store owners can itemize the shelves in accordance with customer choices. 

Regression Analysis 

Regression helps miners determine the relationship between different variables in a set. It is used to foresee the probability of a future event. In the case of a supermarket store, business owners can set price points based on seasonal demand, competition, and supply chain issues. 

Anomaly Detection 

The last of the data mining techniques includes identifying outliers. There will always be anomalies in the data which have to be accounted for. For instance, the majority of buyers in the supermarket happen to be females but for a week in (say) January they are displaced by men. Why? Such outliers have to be studied for a balanced approach. 

The aforementioned techniques make clear how data mining is used in business operations. Drawing this piece to an end, we can conclude that data mining and business intelligence go hand in hand and that one compliments another. 

Explore Enterprise BI like Never Before

Appinventiv is a leading business intelligence service organization that offers end-to-end BI services that are second to none. With almost a decade of industry expertise, we’ve successfully launched many projects implementing business intelligence techniques with a client satisfaction rating of over 70%. Some of the services that we offer in this field include: 

• BI consulting
• Enterprise BI solutions 
• BI implementation 
• BI support & maintenance  

Our portfolio of work includes successful partnerships with several global brands.  

For one of the leading telecom companies in the US, we deployed an effective data mining and BI solution that led to achieving results such as 100% processing of customer data and 85% increase in data quality and accessibility. Don’t worry, we don’t bite if you call and enquire about how we can help you up your game We’ll be waiting to hear from you (if you find our pitch interesting)!

A robust BI solution for a financial services business helps convert a large amount of data into actionable insights. These insights are further used by organizations to make better strategic and tactical business decisions.

However, in order to leverage BI for maximum benefits, it’s important for financial companies to have a well-defined business intelligence strategy. A BI strategy is basically a blueprint for deciding how an organization will use data in its business.

A business intelligence strategy enables finance companies to organize, analyze, and contextualize business data from around the company. It addresses all the problems related to data and helps develop a unified system.  

Today, in this article, we will dive deep to understand the benefits of a BI strategy and how to build a successful BI strategy for your banking and finance business.

Why do you need a BI strategy for your financial business?

A business intelligence strategy is essentially a roadmap that enables financial services businesses to measure their performance, identify competitive advantages, and make informed data-driven decisions using data mining and statistics. It also helps the company reap the rewards of having actionable insights. 

On that note, here are a few perks of having a BI strategy in place for your financial business. So, let’s dive in!

Saves time: A good business intelligence strategy helps you choose, purchase and implement a software solution in the shortest, smoothest way possible. By having an established plan, budget, and training outline, you’ll save time that would otherwise be spent determining all these factors. 

Boosts customer retention: Business intelligence in banking and finance institutions can keep marketing and sales teams armed with the most current information on customers. It can help identify an organization’s most loyal and profitable clients to market relevant products and services and enhance customer experience.

Offers competitive edge: BI strategy is helpful in comparing product or service offerings with your competitors to uncover ways of strengthening your competitive position in the market. It also helps you shortlist vendors that deliver the best BI solution for your finance business integrated with top-notch features. You can even test the BI solution and ensure it meets the requirements.  

Saves money: A good business intelligence strategy helps save money in several ways. Firstly, determining the exact features you’ll use is one of the main ways to save money. BI strategy also helps prepare for the training offerings and associated costs. This will help you budget accordingly and reduce unforeseen expenditures. 

Now that we have discussed what is business intelligence strategy in banking and financial services and how BI is useful for organizations, it’s time to look into the steps to build a successful BI strategy for your organization. 

How to build a successful BI strategy for financial services business?

It’s vital that your BI strategy aligns with your business goals and vision. This initiative will place trusted, relevant data in the hands of the company and employees so that they can make informed decisions every day. 

So, here are a few steps to follow when building a successful business intelligence implementation plan. Let’s get started!

Assess your current BI ecosystem

To know where you’re headed, you must set a baseline. Say, for instance, you know that several departments have been using analytics, but the data has been mostly siloed – customer support is tracking user feedback for their own internal purposes, the marketing team doesn’t have access to sales information, or maybe there is no analytics at all – basically, all seems to work but how effectively is not clear. 

So, the first step is to talk to all the key players involved in the current BI processes. As a result, you should be able to answer the following questions:

• What’s your BI vision? How is that vision aligned with your finance and corporate strategy?
• How do you handle data management and data governance? 
• How do you support BI users?
• What solutions are you using and how? Which of them brings value?

Knowing where you stand enables you to take additional first steps toward a formal BI strategy without disrupting good work that’s already being done in your financial business.

Chart a BI roadmap

You are not going to get far with business intelligence in financial services’ initiative if you don’t have a unified vision and a clear agreement between stakeholders. So, it’s crucial to build a BI roadmap. 

This is your overall strategy document highlighting your goals, vision, and the path you’ll take to reach there. It explains the scope of your vision and the overall hierarchy of responsibility. This, in turn, helps employees to stay on the same page, be aware of what’s been done and what’s coming up, and enable them to adapt to changes.

The BI for finance roadmap should focus on the following:

a) Corporate strategy

The main objective of business intelligence for financial services is to give an insight into your financial business operations. But in order to implement a successful BI strategy, you must first know what direction your business is going towards. 

Else, you might end up tracking analytics that has no real impact on your business’s long-term goals. 

For example, you might build a detailed market intelligence dashboard. But corporate might want to focus on the direct sales and partnerships model, rendering your marketing dashboard useless. So, it’s important to align the BI initiative with your corporate strategy. 

b) KPIs and metrics

You can have great financial data and substantial buy-in from stakeholders. But your BI for finance initiative will still be a failure if you’re measuring the wrong metrics. This is particularly challenging if your financial business has countless seemingly similar metrics.

So, look at your data sources and divide them into the following categories:

Tracked metrics – This includes data that you will track on a regular basis, but won’t use to measure performance.

Untracked metrics – This includes data that you won’t track. But this data should be available for future analysis.

KPIs (Key Performance Indicators) – This is a subset of your tracked metrics and will be used to measure your business’s performance.

In addition to your own data, you can also keep track of industry-wide metrics to benchmark your performance.

c) Vision document

Finally, include everything you’ve discovered so far into a vision document. This is a short document outlining the broad goals of the BI strategy, what metrics you need to track, and how you will measure the performance.

You can use this document to evaluate the success or failure of business intelligence for financial services. 

[Also Read: A complete guide on Data Science & Analytics for businesses]

Present BI to stakeholders

Before implementing a business intelligence plan into your financial company, set the terms and share the objective of BI with all your stakeholders. 

As several employees and other stakeholders are involved in the data processing, make sure that everyone is on the same page and has a mutual perception of what business intelligence development strategy is.

Choose a sponsor

While a BI strategy should include multiple stakeholders, it is imperative to have a sponsor to spearhead the implementation of the BI strategy. Chief financial officers or chief marketing officers are usually appointed for heading the BI strategy initiatives.

They can govern the implementation with a documented business case and be responsible for changes in scope. CMOs and CFOs also understand the organization’s strategy and goals and know how to scale the BI platform. 

Build your BI team

A BI team is responsible for implementing the BI strategy. Since BI draws data from different departments of an organization, it is important that your BI team includes all the necessary stakeholders from all the relevant departments such as finance, sales, and HR. 

To give you an idea, here are some individuals that are typically needed in a business intelligence team:

• Business analyst
• Head of BI
• BI Infrastructure architect
• Data administrator
• Data mining expert
• Data quality analyst
• Database administrator
• Metadata administrator
• Project manager
• Subject matter expert
• Developers
• Executive sponsor
• Steering committee
• Data scientist

Once you have your team, the next step is to put together your data.

Gather and organize data

Data is the lifeline for any business intelligence strategy. You need to figure out a way to capture data and turn it into insight. A sound data plan should be a part of your BI strategy. It should include the following:

Identify data sources: As a financial service business, you’ll have data from countless sources – clients, projects, sales, marketing, finance, etc. So, the first step is to identify all these data sources and their importance. While there is no fixed process to organize data, you can segregate them by department (finance, sales, etc.), function, or business impact.

This will help identify the most crucial metrics for your banking business and figure out how you will track them. 

Create a visualization strategy: Data should always be presented in the right format, else it’s not useful. Therefore, your data plan should include a data visualization strategy. The strategy will focus on two important things – What metrics you’ll prioritize in your BI dashboard, and how will you visualize them? 

The answers to the above questions will majorly depend on stakeholder preferences and your company’s vision. You can even create multiple dashboards for different stakeholders, depending on their choices. For instance, one stakeholder might prefer scatter graphs, while another might favor textual data. 

However, it’s advisable to work with a designer to ensure your visualization strategy is easy to follow. Also, make sure your BI tool supports your visualization choices.

Create a budget for implementation of BI in financial services

Developing an accurate budget is key to successful BI implementation. You can ask for a quote directly from the vendors you are shortlisting to get an accurate estimate of BI platforms. Don’t go for the expensive version with features that you are not likely to use. Also, underbuying is likely to result in an underdeveloped system that doesn’t provide what you need. Stay realistic and moderate when planning a budget.

Choose the right BI software partner

Choosing the right BI partner is important if you want to create a successful BI strategy. You can compare different business intelligence software development partners on how well they are rated for different features. Combining this comparison report with reviews and eventual demos will help you choose the right partner for your financial business.

Plan user training

Once you choose the right software development partner, it’s time to plan your training program. Usually, vendors offer video training, live classes, and in-person seminars to get you set up and comfortable with the software. These offerings vary by vendor and come at different costs based on the platform but are pretty standard. 

Training will also help employees learn about the best features and stay on top of data insights. It will also help overcome any challenges in business intelligence in the banking sector. 

Refine your data

Another part of your process should be cleaning your data on a regular basis. Every year low-quality data costs over $9.7 million to American businesses as it results in low productivity and ultimately reduces the overall ROI.

Therefore, it has become crucial to maintain the cleanest data possible for better operational activities and decision-making processes. The ROI and the quality of insights you get will also depend on the quality of data you feed to power BI.

How Appinventiv can help in creating a BI strategy

A sound business intelligence strategy makes it much easier to gather your data and make it accessible to your company’s decision-makers. You can follow the above steps to chart your BI strategy and bring clarity to your operations.

You can also make the process much easier by hiring our team of experts. At Appinventiv, our highly-skilled team of professionals will help design an effective BI strategy that will help accelerate business operations, monitor key metrics, and focus on specific customer data. 

We also offer top-notch business intelligence services that utilize big data opportunities to grow revenue, reduce risks and optimize costs across the business. Additionally, our business intelligence capabilities can offer embedded analytics that is tightly integrated into your existing systems. This can, in turn, help introduce new targeted information to support additional awareness and decision-making. 

If you want to know more about BI strategy and solutions, kindly contact us. We will be happy to help! 

[Also Read: Business Intelligence vs Business Analytics: Which Platform is Right for Your Organization]

FAQs

Q. What is a BI strategy?

A. A BI strategy is a roadmap that enables businesses to address all their data problems and needs, develop a cohesive system, and maintain it.

Q. What are the applications of business intelligence in the banking industry?

A. Some of the applications of BI in the banking industry are as follows:

• Improved marketing
• Developing new investment strategies
• Improved marketing
• Increased customer retention
• Reduced risks

Q. How would the banking industry use business intelligence strategy?

A. Business intelligence for financial services turns data into actionable insights. The banking and finance industries use these insights to understand customer behavior, analyze and improve operational performance, and gain a competitive advantage.

BI helps retailers organize, analyze, and contextualize business data from around the company. It also provides reports, performance measures, and company trends that help businesses make informed decisions in the present day. 

With the worldwide business intelligence and business analytics software market expected to reach 17.6 billion dollars in 2024, it goes without saying that BI can certainly benefit the retail industry specifically.

Business intelligence allows retailers to take advantage of new opportunities to predict sales and see the market potential and understand customers on a deeper level. 

While you might have got a brief idea about why BI in retail is necessary, in the following sections, let us discuss in detail the role of BI in the retail sector and its countless benefits for your business. 

Role of business intelligence in the retail industry

The retail industry is more competitive and fast-paced than ever, and when it comes to staying ahead of the competition, there’s no such thing as having too much information. 

Business intelligence in the retail industry helps track how customers interact with eCommerce stores, and this information can be used to enhance the customers’ shopping experience. For instance, a customer gets suggestions based on previously viewed items. 

With business intelligence, retailers can also make smart and efficient decisions based on customer behavior. Data can be viewed in real-time, allowing businesses to make changes in merchandise offerings or adjust prices quickly. 

This information can be also used by brick-and-mortar stores. They can use BI to balance inventory between online and in-store stock and provide cost-effective shipping options such as picking up in-store or buying online. 

For instance, many brick-and-mortar stores such as Home Depot, Walmart, and more are using BI to offer shipping options that are cost-effective and manage their inventory effectively. 

Expanded access to valuable operational and customer data also helps businesses create a consistent experience across all channels. Additionally, BI also helps to predict when the stock will run out so that retailers can get ahead of ordering and make better-merchandising decisions. 

Key benefits of BI in the retail industry

Brands that can tap into good customer service and personalization in today’s market can deliver 5.7 times more revenue than competitors. 

But how can you know about your target customers and what they desire? This is where business intelligence comes to play. It allows companies to absorb mass amounts of data about their business – from sales to market trends, customer behaviors and needs, and more. This, in turn, helps you to connect with your customers. 

Here are a few additional benefits of business intelligence in the retail industry. So, let’s dive in!

Improves business operations

Using BI tools allows retail businesses to have greater control over their operations. It helps them keep track of what’s going on in the company. This allows making rapid corrections in case of any errors. 

For instance, a retail company can use the BI tool to deal with late deliveries and know why delays occur. This kind of information in their operations could help the company vastly improve its services.

Enhances customer experience

Excellent customer service is the key to success for any business. It adds business value, helps retain customers, reduces employee turnover, and increases brand loyalty. 

However, offering exceptional customer services can be challenging, especially if a business has a large customer base and fewer employees. It can be a quite difficult task for a retailer to engage employees and keep customers happy while running a profitable business. 

Businesses can mitigate these problems as well as keep their customers happy by automating customer service the right way using BI tools. Automation offers valuable data to businesses to make informed decisions.

For example, retailers can use customer analytics from a BI tool to understand the needs of their customers, meet their expectations, and identify opportunities for improvement. These analytics can also help marketers create a data-driven customer journey map by giving insights about how customers interact with products, websites, or businesses.

Helps optimize inventory management

Inventory management is the foundation of any well-functioning retail business. It encompasses all activities related to stock handling – from sourcing to storing to selling inventory and finished goods. 

Any retail company that holds stocks is faced with several inventory challenges. From inefficient tracking to overstocking issues, managing inventory can be quite challenging for retailers. 

However, investing in a BI and data analytics solution can help in inventory management and solve most of the stock-related challenges that retailers face. With a BI system in place, retailers can maintain optimal stock levels, reduce inventory costs, and improve order management and order processing. 

BI allows retailers to classify their merchandise based on Selective Inventory Control (SIC), also known as ABC analysis. Using this approach, retailers can identify the items that have a high impact on inventory costs. It divides the inventory into three categories A, B, and C. While A is the most valuable, C is the least important.

Organizations can also predict overstocking situations before they become a significant problem by using BI analytics. 

Identifies emerging consumer trends

BI has become crucial for identifying new and emerging consumer trends.

Take Covid-19, for example. The pandemic outbreak caused a shift in consumer behavior with an increased focus on health-related products and services. Increased consumption of healthy foods like eggs and dairy was seen as a perfect opportunity for retailers to rework their offerings to ride the changing consumer demands. 

Another perfect example is clothing brands that have hopped onto the consumer trend of branded face masks and started creating more hygienic products after receiving large demand from consumers. 

BI in retail allows identifying patterns in their consumer purchasing behavior, allowing marketing teams to rework pricing strategies and inventory to increase revenues and maximize margins. 

Helps to optimize store floor plans

One of the main reasons retailers opt for BI is to design a floor plan that can tempt consumers to shop for longer. Businesses should choose a floor plan that allows customers to shop without hassle. 

With the help of BI software, retailers can determine whether the selected floor plan is sufficient for the floor size and product types. They can analyze various data sets using BI solutions (number of stops, visits’ duration, etc.) and recommend a floor plan that will help consumers to find products with ease. 

Takes marketing to the next level

With many social media tools and marketing platforms available, marketing has become an increasingly data-driven industry. However, to get the best result from a marketing strategy, organizations need to have a system in place that can provide useful insights and analyze data into the consumers buying behavior. And this is where BI tools come to play. They make a company’s marketing strategies more effective.

By using BI analytics for marketing, companies gain in-depth insights into their customers’ preferences, interests, and attitudes. These insights help them design marketing campaigns and advertise on the right platforms. 

For example, if a retailer wants to capitalize on Facebook ads, a BI solution will provide relevant metrics such as page views, likes, on-page actions, etc. Moreover, a BI tool can identify trends and data patterns that can help to increase Facebook likes and click-through rates (CTR).

Boosts efficiency in the supply chain

Supply chains become more complex as retailers involve more merchants and sell more of their products. The sourcing of merchandise, as well as the different distribution channels, make the supply chain in retail ripe with inefficiencies and underperforming departments.

However, with the help of BI in retail key insights can be gained from day-to-day operations. This allows retailers to create better forecast models as well as identify key logistical bottlenecks that should be addressed by the supply team to meet their organizational KPIs. 

[Also Read: How mobile apps can add value to your retail business?]

Real-world examples of retail businesses using BI

By now, you might be clear on how business intelligence enables retail businesses to organize and analyze business data from around the company and make informed decisions. 

Further, let us go through some business intelligence examples of real companies to see how this business solution is becoming a game-changer for the retail industry:

Amazon and BI go hand-in-hand: The company uses business intelligence to personalize product recommendations, market products, and make logistical business decisions. In fact, in-depth data analysis is the key reason for the smooth functioning of Amazon’s massive supply chain.  

From allocating inventory among warehouses to optimizing shipping routes, BI tools influence practically every step of Amazon’s supply process.

[Also Read: How much it costs to build a marketplace like Amazon?]

Starbucks leverages BI: Using the retail business intelligence software, Starbucks predicts what purchases and offers a customer is likely interested in. The company informs customers of the offers it believes they will want to take advantage of. This system lets Starbucks draw existing customers into its stores more frequently and increase its sales volume. 

Lowe’s is big on BI, too: The home improvement company uses BI to optimize their supply chain, analyze products to identify potential frauds, and solve problems. They also use BI to discover deeper insights that lead to better product assortment and staffing at specific store locations. For instance, Lowe’s uses BI tools to load trucks specific to individual zip codes, so the right store gets the right amount and type of product.

Walmart gets in on BI: The retail giant uses BI tools to understand how online behavior influences in-store and online activities. Walmart can understand customers’ purchasing patterns using BI tools. For instance, how many people searched for a particular product and then bought it from the Walmart app/website on the same day. This way, they are able to pinpoint the busy days and the exit points in their users’ journey. 

How can Appinventiv help you in your BI journey?

The advantages of utilizing business intelligence in the retail industry are endless. From offering clear insights into business trends to improving customer experiences, the implementation of BI can enhance your business’s proficiency. 

At Appinventiv, our highly-experienced team of professionals will help you implement the retail business intelligence software for your business while taking care of all your data challenges at the same time. 

So, in case you are looking for top-notch business intelligence services, you can consult and hire our experts. We will have all your needs covered! 

FAQs

Q. What is retail business intelligence?

A. It is a technology-driven process of translating raw data into meaningful insights to improve productivity and support better decision-making in the retail sector. 

Q.  How does the retail industry use business intelligence?

A. BI is used to collect, analyze, and present pertinent business information. It also helps to generate personalized communication for customers using their past purchase histories and area of interest.  

Q.  What are the benefits of using BI in the retail sector?

A.  Some of the key benefits of using BI in the retail industry are identifying customer trends, optimizing store floor plans, and enhancing customer experience. 

Over 50% of the organizations today are already convinced that BI is essential to survive in today’s technical environment. As per Market Watch’s latest report, the BI market will register a magnificent spike in CAGR in terms of revenue. 

Another study states that various factors such as rising investments in analytics, increased demand for dashboards, growing focus on digital transformation, and increase in cloud adoption, IoT in supply chain and other industries has driven the growth of Business Intelligence. It is expected to reach 33.3 billion USD by 2025, offering new opportunities to every sector.

If we talk about the adoption of Business Intelligence in a specific sector, the supply chain and on-demand logistics development domain has played a massive role in embracing BI solutions. logistics domain has played a massive role in embracing BI solutions. Industrial experts state that to stay competitive in the supply chain management business, you need to recognize the potential weakness of your organization and form ideas to overcome them. Modern solutions such as Artificial Intelligence and Analytics and business intelligence help you identify potential risks associated with your business and take timely actions.

In simple words, you can gain insights based on real-time actionable data, get automated recommendations, and evaluate the production process with the transactions. So whether it’s about transferring inventory, arranging shipments, or releasing orders, BI is going to keep every data just a click away from you. 

Now, coming to our point of discussion, why is supply chain and operations massively adopting Business Intelligence solutions? 

The increased adoption is probably due to the supply chain digital transformation where BI plays a remarkable role in its varied sectors. 

Impact of Business Intelligence in the supply chain process

The amount of data that flows within the supply chain sector is infinite. BI essentially means converting this sea of data into knowledge for practical business use. If you ask what kind of data in the supply chain is driven by Business Intelligence? 

Data such as repair cost, transportation cost, KPIs (key performance indicators) on carriers and suppliers, strategic planning, and trend analysis is heavily managed by Business Intelligence. 

Further, this data needs to be drilled down into required information to perform research and analytics. The final figures tell you how the company needs to act according to the performance and business objectives.

BI supply chain tools such as dashboards and scoreboards also provide you with a detailed breakdown of a company’s performance (daily, weekly and monthly) to help you keep the progress in check. This is how critical Business Intelligence is in the supply chain cycle.

Four sectors of the supply chain that run on the BI model

Talking about BI’s influence on the supply chain process, there are four significant sectors of the supply chain highly influenced by the Business Intelligence model. Let’s take a quick glance at them.

Business Intelligence for product distribution

 The most prominent role of BI is ensuring that the product reaches its customer in a considerable amount of time. Business Intelligence software helps track the fleeting services that follow area deliveries. If the deliveries take longer than expected, the concerned manager can take timely actions to fix the challenge. 

BI is not just a master in product tracking; it also tracks external factors such as fuel cost, delivery estimation cost, and other business expenses. In simple words, you get every tiny detail to capture to maximize profits. 

Business Intelligence for demand planning 

Another aspect in supply chain management that depends highly on Business Intelligence is demand planning. Demand management is critical since it tells you how much production is required for your business to reach profits. Business Intelligence solutions help forecast demand needs. The tools combine both sales pipeline and historical figures with market segments and estimate the time and resources needed to meet customer demands.

Think of it; if a company under or overproduces, it directly affects its profit margins; therefore, demand planning is a critical aspect in the supply chain. 

Business Intelligence for IoT machinery 

Supply chains have massively adapted to the smart industry trend. IoT in manufacturing is a concept where various machines and devices are interconnected with the Internet of Things, running in a data-driven cycle. The data gained by IoT provides information on machine uptime, so the product remains consistent. BI in return utilizes this data to produce monthly reports stating the area of improvements. 

On top of that, these interconnected devices can alert businesses when they require routine maintenance. This helps cut outages and regulate expenses.

Business Intelligence for inventory management

With BI tools accessing inventory data, you can easily optimize volume numbers for higher profits. Most BI inventory solutions track sales, purchase numbers, and supplier data. You can leverage all this data on one platform, ensuring your business’s optimal inventory volume at all times. 

Similarly, many such aspects feed into the supply chain BI model, where every data can be molded into insights. However, the usability and applicability of the Business Intelligence model don’t end here. Wait till you hear about embedded BI. 

What is Embedded Business Intelligence (BI)?

Embedded BI refers to integrating Business Intelligence solutions within business portals or applications. Suppose you have a mobile application that requires Business Intelligence solutions and features to track your supply chain business. All you need is embedded BI that gives your application BI features such as reports, interactive dashboards, data analysis, predictive analytics, etc. 

This differs from traditional BI since it puts all the capabilities of BI into your business application. 

Some of the primary reasons why supply chain business needs embedded BI are:

• It constitutes revenue growth 
• It has over 40% adoption rate in the supply and manufacturing industry.
• It enhances the user experience and customer satisfaction
• It adds value to the business application
• It also helps with customer engagement (increases the time spent within the application) 

Supply chain management with embedded BI 

When you are all set to integrate Business Intelligence solutions in your supply chain, you are able to spot potential challenges before they become an issue. 

Here’s how to leverage embedded Business Intelligence in your everyday product cycle. Below are a few routine supply chain cycles that you can easily track with your embedded BI application.

• Track cash to cycle time- It refers to the time between paying for materials and getting paid for sales. 
• Track customer order cycle – It refers to the time between receiving an order and delivery. 
• Track fill rates- It is the percentage of lines, orders, and units shipped on the first attempt. 
• Track days of supply- This refers to the time you can work without restocking or reordering. 
• Track outstanding payments- This is how timely you collect payments from your customers
• Track turnover- This tells how efficiently you turn working capital invested in inventory into profits. 
• Track inventory velocity- This tells you about underperformers and best sellers.
• Track gross ROI (Return on investment)- This is the total profitability from inventory investments. 

One additional challenge that supply chain enterprises and manufacturers face is tracking inventory across multiple vendors. Seeking innovative BI supply chain solutions can help you build a collective dashboard software that allows you to merge data from numerous sources, creating interactive tracking reports for comparison. 

Three Business Intelligence aspects that every supply chain enterprise needs

Now that we know that Business Intelligence is all about using data to improve strategies and decisions, here are three essential categories in BI every supply chain enterprise must utilize to drive productivity and efficiency. 

Reporting tools 

Currently, supply chain enterprises rely more on scorecards that help managers and decision-makers to improve the workflow. Predictive analysis and deep insights into data help generate a detailed analysis of everyday events that can give you the pain points. You can further use these shortcomings to modify supply chain strategies. 

Dashboards 

Real-time actionable dashboard visibility is one of the biggest highlights of Business Intelligence. It gives a quick view of what’s happening in the supply chain cycle and generates immediate reactions. The BI dashboards have customizable features that give you a hassle-free scroll and navigation advantage. For better data visualization, you can utilize dashboard features like data tables and filters and catch a better review of your internal operations. 

Benchmarking 

Benchmarking gives an upper hand to any enterprise into supply chain competition. This includes comparing your supply chain operation by the industry standards to help you come up with better performance. BI-directed data benchmark is specifically designed to improve operations and identify growth opportunities.

Key benefits of BI solutions in supply chain management

Here are some of the key functionalities and benefits of Business Intelligence tools that enable enterprise data sharing across multiple functional units for uniform decision-making.

1. Supply chain BI solutions help drill down data layers into any format for analysis purposes. Formats such as charts, spreadsheets, and hyperlinks help monitor the everyday workflow of the enterprise. 

2. Balanced scorecards under BI solutions can be used to aggregate databases for performance evaluation. This also helps create relevant data views to bring clarity to critical information. 

3. BI also provides built-in integrated reporting and dynamic query generation features that extract intermediate data and perform analysis for all possible adverse outcomes. 

4. Through the additional BI features, enterprises can identify a baseline against specific metrics to figure out what they need to measure on a daily, weekly, monthly, and yearly basis. 

5. BI also allows customization where your dashboard can provide more contextual information that helps in gaining deeper insights. 

How can Appinventiv fuel your supply chain with Business Intelligence?

If you want to strengthen your supply chain process, integrating Business Intelligence is more than a necessary step for you. BI is a holistic approach to collecting, processing, and distributing data to improve business performance and customer satisfaction. Allow us to be a part of your supply chain growth by connecting with us for Business Intelligence solutions. 

Appinventiv provides BI services and solutions that help enterprises not only adapt but also master new advancements in technology. We are there for you right from the BI consulting to making a full fledged BI solution till it’s maintenance. 

FAQs on Business Intelligence in Supply Chain

Q. What is the future of business intelligence in the supply chain industry? 

A. BI is an established technology driven process that converts available business data into knowledge. This knowledge is further delivered to managers, vendors, operations team and suppliers to analyze and make appropriate decisions. With this massive involvement of big data in BI process, there are no signs of slowing down in the coming years. Infact, BI solutions and tools are becoming more proactive, collaborative  and insightful to manage. 

Q. How BI is used in supply chain management and logistics?

A.  BI solutions provide engaged data in the form of reports and dashboards that help vendors, production managers and distributors track machinery and shipments. 

Moreover, the operations highly rely on supply chain reporting  to control costs and optimize resources. 

BI also helps monitoring the logistics by analyzing timely returned orders and the reason for returns. This helps in identifying the order patterns and can serve a way in personalizing products. 

Q. What is the difference between Business Intelligence (BI) and Business Analytics (BA)?

A.  As BI becomes more prominent, there has been a rising confusion between Business Intelligence and Business Analytics. 

In simple words, BI utilizes present and past data to drive current business decisions whereas BA analyses only historical data to drive current business needs. For detailed insights, you can also refer to Business Intelligence vs Business Analytics.

Q. What is the process of implementing BI software? 

A.  Reliable BI solutions and services can support your enterprise through a structured process. A generic implementation process involves design, shaping, modeling and visualization. However,  BI solutions are integrated according to the business needs and requirements. In every way, the end goal must be making the data accessible. 

By utilizing these two digital solutions, organizations gain valuable insights into industry trends and enable a strategic decision-making approach.

Here are a few stats that show the increasing use of Business Intelligence and Business Analytics:

• As per Statista, the market size for business intelligence and analytics software applications is expected to increase from 14.9 billion U.S. dollars in 2019 to 17.6 billion in 2024. 

• According to a survey by Forbes, 48% of organizations consider cloud BI either ‘critical’ or ‘very important’ to their operations.
• As per PR News Wire, North America is predicted to have the largest business intelligence and analytics market share due to the presence of key industry players in the area.

Now that we have seen important stats related to BI and BA, let’s understand the concepts in detail and know how and why Business Analytics and Business Intelligence solutions are important for your organization. Let us also understand the difference between Business Analytics and Business Intelligence to know which of the solutions is more viable for your organization.

What is Business Intelligence?

Business intelligence (BI) is a technology that enables businesses to organize, analyze, and contextualize business data from around the company. BI provides reports, performance measures, and company trends that help businesses make informed decisions in the present day. It is mostly used as a way to generate a detailed overview either on business or product metrics. 

Here are some real-world examples that show how BI is making a difference for companies around the world:

1. Uber

The company uses Business Intelligence to determine multiple core aspects of its business. For instance, Uber uses BI for surge pricing. Algorithms monitor the time of journey, traffic conditions, and customer’s demand in real-time. So, prices adjust as demand rises and traffic conditions change.

2. Netflix

Netflix uses data in multiple ways. One example is how the company offers suggestions to users based on previously viewed programs. Netflix also uses Business Intelligence to get people to engage with its content. 

[Also Read: Revealed – The Actual Netflix-like App Development Cost]

3. Coca Cola Bottling Company

Coca-Cola previously had issues with its daily manual reporting processes. But by replacing the process with an automated BI system, the company completely streamlined the process and saved 260 hours a year. Now, the company can quickly check metrics related to budget, delivery, and profitability with just a few clicks.

4. Lowe’s Corp

The home improvement company is one of the earliest adopters of BI tools. They have used this technology to optimize their supply chain, analyze products to identify potential fraud, and solve problems.

5. American Express

American Express has been using BI to develop new payment service products and market offers to customers. BI also helps the company to detect any financial fraud and protect customers whose card data may be compromised. 

What is Business Analytics?

Business Analytics (BA) is used to interpret and analyze historical data to identify trends and patterns in the business. BA helps companies to improve or change their current operations and make better decisions for the future. It can be used to recognize market opportunities, improve relationships with customers and better indicate potential risks.

Let’s understand this better with the help of some real-world examples:

1. Microsoft

Microsoft used Business Analytics in 2015 when their engineering groups’ offices moved. Microsoft’s Workplace Analytics team hypothesized that moving the 1,200-person group from five buildings to four could improve collaboration by cutting down on the number of employees per building and reducing the distance that staff needed to travel for meetings. This move saved 100 hours of work per week and they gained a net saving of 520,000 USD per year in terms of employee time.

2. Starbucks

Starbucks uses BA to predict the purchases and offers a customer is likely to be interested in. Using BA tools, the company is able to identify the pattern in a customer’s purchase and then suggest offers through mobile devices.

[Also Read: A 10 Minute Guide on Using Predictive Analytics for Mobile Apps]

3. Amazon

The most popular on-demand app, Amazon has successfully used Business Analytics to personalize product recommendations and make logistical business decisions. Amazon’s massive supply chain runs smoothly due to in-depth data analysis.

Now that we know what is Business Analytics and what is Business Intelligence, let’s move on to the next part of this article where we will compare BI and BA to see which is a better fit for your organization. 

Business Intelligence vs Business Analytics – A Comparative View

While choosing between Business Intelligence and Business Analytics, business leaders must do a comparative analysis of these solutions. Here are a few comparison points that will help you choose the right solution for your business. 

1. Present vs Future Focus: Business Intelligence uses past and current data to make decisions about how a company should run in the present day. Business Analytics, on the other hand, uses historical data to predict what might happen in the future or how an organization can move forward. 

A present focus using BI is generally more useful for entrepreneurs who are satisfied with current business operations but want to identify ‘pain points’, increase productivity and streamline processes. But for those, who want to change any major functioning or business model, Business Analytics is a better choice to get useful insights. 

2. Reporting and Analysis: Business Intelligence mainly focuses on collecting and reporting relevant data. The trend in analytics has been instead to provide people with the tools to get their own answers. BA lets people get in the flow of analysis, explore their data, and ask their own questions.

3. Maintaining vs Revolutionizing: BI is needed to run the business while BA is needed to drive a change in the business. 

BI focuses on creating operational efficiency via real-time data enabling individuals to most effectively perform their job functions. BI also includes analysis of historical data from multiple sources enabling problem identification and resolution. 

Business Analytics relates to the exploration of historical data to identify trends and understand the information that can drive business change and support sustained successful business practices.

4. Ease in Decision Making: Large-scale businesses depend almost entirely on their skilled team of analysts who can predict challenges or market fluctuations. While an analyst is able to access all the information with the help of business intelligence tools, translating this intelligence into a useful resource is not possible without analytics. 

Business analytics help identify growth patterns, economic shifts, and future market trends on the basis of historical data and the current functionality of the business. So, when it comes to forming major decisions, the analytical perspective is most crucial because it doesn’t just tell you about an enterprise’s current state but can also see ahead.

5. Applications: Business Intelligence is used by most of the companies to run current business operations. For example, if you’d like to reach a certain sales goal, your BI system can analyze previous months of data and suggest a reasonable goal based on past performance.

Business Analytics applies to companies that see future growth and productivity as their main goals. BA gives you the tools to process data, answer the question to ‘why’, and create future actionable items. You can apply business analytics across all verticals of a business. It can be applied to marketing, finance, CRM, Human Resource Management, and even manufacturing.

Advantages of BI & BA for Businesses

Business Intelligence is useful for companies to stay competitive and maximize revenue streams. Here are the key benefits that BI offers to organizations:

•  Improves business operations: Organizations that use BI have greater control over their operations. They have a better understanding of what’s going on in the company. Maintaining active monitoring over processes and standard procedures aids in the rapid correction of any errors.
  For instance, a logistics company can use BI to deal with late deliveries and know why the delays are occurring. This kind of knowledge in their operations could help the company vastly improve their services.
• Valuable customer insights: Businesses can better understand their clients by evaluating their purchasing behaviors and establishing user profiles using effective business intelligence systems. Many organizations are looking for custom software development solutions to help them with BI systems and management. This enables them to provide their customers with better products and experiences.
  
  
• Improved productivity: One of the major benefits of Business Intelligence tools is the automation of processes such as report generation and real-time updation. As a result, the employees can focus on more productive tasks.
• Increased revenue: Data from BI tools can help businesses to identify sales weaknesses and identify other problems. When organizations are listening to their customers, watching their competitors, and improving their operations, revenue is more likely to increase.
  
  
• Competitive advantage: Another significant advantage of having a BI solution is competitive advantage. Business intelligence platform allows companies to see what their competitors are up to and make informed and educated judgments about their plans.
  
  For example, in the fashion industry, the most important benefit of business intelligence is to identify important trends. Companies can use business intelligence tools to figure out what kind of audience they need to appeal to.

Business Analytics can help organizations to increase overall efficiency and mitigate and identify potential risks. Let’s look at the key benefits of Business Analytics:

• Keeps businesses on a budget: Most startups and small-scale companies have tight marketing budgets. The use of Business Analytics helps you maximize every dollar by helping you understand your customers better, anticipating their ever-changing needs, and bringing innovative solutions to the marketplace.
  
  
• Informed decision-making: Enterprises can use business analytics to make informed business decisions and minimize financial losses. Predictive analytics can be used to close business gaps and respond to changes.
  For instance, businesses can model changes to pricing or product offerings to determine how those changes would affect customer demand. Additionally, businesses can also leverage location intelligence to create a powerful system that can assist them in discovering effective business solutions. Know more details on the subject in our latest blog post on Multiple Ways Location Intelligence Benefits Your Enterprise.
  
  
• Increased efficiency: Nowadays, businesses can collect data at lightning-fast speed. With the help of business analytics, you can identify any breakdown in the process or performance in almost real-time, thus saving time, money, and resources.
  
  
• Staying in the know: Business owners use BA to track customer behavior, changes in customers’ needs, and market shifts. This data helps to keep you on top of things and make changes dynamically when and if supporting data indicates it’s time. 

Determine your Organization’s BI and BA Needs

Well, if you are deciding to choose between BA and BI, I would say that a business needs both technologies to succeed. So when choosing the technologies and tools you want to invest in, you should focus less on Business Intelligence vs Business Analytics and more on what you need the data system to do and who will be using it. 

If you are satisfied with your business model and just want to improve operations, increase efficiency and meet your organizational goals, BI may be an optimal choice for you. On the other hand, if you want to change your business processes – or even your entire business model – but don’t have the necessary insights, BA might be the best option. It’s better to start with BI and then move towards BA to improve efficiency and generate more revenue. In short, business analytics and business intelligence solutions can help you take your business where you want it to go.

FAQs

Q1. What is Business Intelligence used for?

BI refers to technologies, strategies, and practices used to collect, analyze, and present pertinent business information. The entire purpose of Business Intelligence is to help businesses in better business decision-making. 

Q2. What are some Business Intelligence use cases?

Some business intelligence use cases are:

• Analytics
• Dashboard development
• Data mining
• Process mining
• Business performance management
• Text mining
• Predictive analytics
• Prescriptive analytics
• Data visualization

Q3. What are the three types of business analytics?

The three types of business analytics are:

• Descriptive analytics
• Predictive analytics
• Prescriptive analytics

Conclusion

There’s no doubt that the future of Business Analytics and Business Intelligence is bright. Both BA and BI help companies to analyze data in order to make better and informed decisions. While BI tools are getting more powerful and providing advanced capabilities, data professionals are still needed for predictive business analytics. The best strategy is to first focus on business intelligence and then incorporate business analytics to improve efficiency, revenue generation, and productivity moving forward.

In case you still have any questions regarding BI and BA or want to know which platform you should invest in, feel free to contact us.

Business intelligence refers to the ability of an organization to make informed judgments, choose measured actions, and implement proficient business progressions.  By utilizing BI effectively, the organization gets access to actionable data, gains valuable insights into industry trends, and enables a strategic decision-making approach.

Below are a few stats that tell the increasing use of Business Intelligence.

• As per Mordor Intelligence, the Business Intelligence Market was valued at USD 20.516 billion in 2020 and is expected to reach USD 40.50 billion by 2026 to grow at a CAGR of 12% over the forecast period (2021-2026). 

• According to the same report, North America is predicted to have the largest market share in BI from 2020-2025, due to the presence of key industry players in the area. Factors such as rising competition, intense technological R&D, and a growing trend of data proliferation are aiding the market’s expansion in the country.

• According to Datanyze, the global market size of the Business Intelligence industry is 236,320 companies, and there are 273 companies producing Business Intelligence technologies.

Organizations must be flexible in today’s business environment to keep ahead of the competition and cater to a constantly changing consumer base. In both of these critical tasks, BI is a valuable asset, that’s why we have provided the answer to the much-hyped question – why is business intelligence important for your organization? Before answering the why, let’s quickly understand what is BI all about.

What is Business Intelligence?

Business Intelligence is a technology-driven process that helps transform data into actionable insights, thereby allowing companies to make more strategic business decisions..

Business Intelligence enables firms to swiftly extract meaningful insights from old and current data. This is made feasible via business intelligence tools, which process big data sets from many sources and deliver insights in visually appealing ways that are easy to grasp and distribute.

This method is perfect to ensure that company managers, corporate leaders, and even startup owners make informed business decisions. BI is mostly used for generating and producing new prospects that will aid in the expansion of the firm, as well as enhance profits and overall turnover. Below are some departments where the use of BI has increased.

Marketing

A business intelligence (BI) solution allows your organization’s marketing team to develop better marketing campaigns with a higher return on investment (ROI) through easy access to data from current and previous campaigns. BI solution also provides essential campaign metrics like customer acquisition cost (CAC), cost per lead (CPL), and campaign click-through rates (CTR) required for a successful marketing campaign.

Sales

BI helps increase your organization’s sales by predicting the sales cycle and analyzing the conversion rates and total income. BI can assist your sales team by recognizing what’s working and what’s not, resulting in drastically enhanced sales performance.

By keeping track of your customers’ data, BI provides you a better understanding of how they interact with your company on a deeper level. This further gives you the opportunity to resolve consumer issues and reach out to them with tailored messages to drive sales.

Finance  

Finance departments can benefit from BI by having crucial and in-depth insights into financial data. BI can also be used to track quarterly and annual budgets, identify possible issues before they have severe consequences, and improve the overall business health and financial stability of a firm.

Why Business Intelligence Matters to Your Organization

By displaying current and historical data business intelligence assists firms in making better decisions. Analysts use BI to provide performance and competitive benchmarks, which helps the company to run smoothly and efficiently. Below are a few of the reasons why BI is used in organizations.

Rapid Decision Making

The most crucial factor to consider when making any business decision is having sufficient evidence to support the conclusion. 

BI helps in establishing business goals for the benefit of the organization. The various uses of BI tools such as examining and evaluating raw data  (with comprehensive representation) help in making quick and better decisions.

For example, a retail company using business intelligence and analytics can forecast purchases and deliver personalized offers to customers via their app and email. This strategy encourages existing consumers to visit the store more frequently, resulting in increased revenue. This results in higher consumer satisfaction and positive brand connotations.

ROI and Goal Improvement

For example, a centralized business intelligence implementation and solution automates reporting operations. It also allows the broader marketing team to create tailored digital marketing efforts for specific regions. The team can react to customer behaviors and optimize marketing campaigns if they monitor and track real-time data. The end result is improved conversion rates and customer retention.

Improvement in Business Operations

Traditional reports are static and become outdated in no time. Yet, companies have to depend on monthly and annual reports to make key business decisions. BI reporting, on the other hand, allows everyone to access data, conduct analysis and create personalized reports. The BI reporting is also dynamic, allowing users to select a specific metric and analyse the data.  

For instance, if we talk about online purchases, then the data insights on percentage of clients that abandon their carts, rather than the number of transactions, can lead to an actionable measure. The company can see where customers are leaving and take the required steps to lower the cart abandonment rate.

Another business intelligence example is the problem that the pharmaceutical industry is currently facing, which is keeping track of the expiration dates of the pharmaceuticals they store. BI software can assist in reducing the danger of expired products being sold to clients unintentionally. 

Enhanced Productivity

Employee productivity can be boosted by centralizing company data. One of the benefits of Business Intelligence management and analytics tools is the automation of processes such as report generation and real-time updation. As a result, the personnel may focus on more productive tasks.

For example, the use of a business intelligence platform is a vital concern in the energy industry, particularly in the fossil fuel environment, such as the oil market. Many businesses utilize their business intelligence systems to analyze geological data quickly. Had it been a manual task, a lot of time and effort would have gone just to analyze the data. Businesses can utilize predictive analytics to find where the largest oil discoveries are expected to be through trend analysis and the utilization of diverse sources of information.

Improved Efficiency

Having a good business intelligence system in place greatly enhances the overall efficiency of the company. This, in turn, has a favorable impact on the organization’s overall revenue. Making useful data available to various teams within the organization minimizes report request wait time and boosts the productivity of all teams within the organization. Data should not be restricted to a few privileged teams but should be available to all. This keeps everyone in the company informed and allows them to make informed decisions.

For example, telecom companies lookout for measures to improve quality assurance. After using BI, the companies can maintain data processing and gain significant insights from the raw data they collect. Companies can even concentrate on predicting client requirements and developing innovative retention techniques.

Sales & Market Intelligence

Most of the sales and marketing teams use Customer Relationship Management (CRM) software to keep a track of their customers. There is a lot of data that can be evaluated and applied for strategic efforts as they incorporate all customer contacts and interactions. BI systems assist businesses in a variety of ways, including discovering new clients, tracking and maintaining existing customers, and offering after-sale services.

For example, companies can leverage BI tactics to undertake sales win/loss analysis. Business intelligence implementation can help you identify new income prospects and deliver actionable insights by analyzing your internal and external processes. For example, having a better understanding of current market trends may enable you to spot a previously unnoticed sales opportunity.

Competitive Advantage

Another significant advantage of having a BI solution is competitive advantage. Business intelligence platform allows companies to see what their competitors are up to and make informed and educated decisions about their plans. Furthermore, a corporation that keeps a constant watch on its internal systems stays ahead of a company that does not.

For example, the capacity to follow and identify key trends is the most important benefit of business intelligence in the fashion industry. When it comes to selecting a design that has the potential to become a global trend, making informed decisions is critical. Another sought-after component of BI is Location Intelligence. The technology allows the integration of geographical data with business intelligence and creates a powerful system that assists organizations in discovering effective business solutions. Check out our latest blog on Multiple Ways Location Intelligence Benefits Your Enterprise to get complete details on how to leverage the technology for your business.

Real World BI Use Cases

BI can enhance business processes by providing a broad perspective about their goals and empowering teams to evaluate their own data and make better decisions. Now that we have known the importance of BI. Let’s now have a look at the real-world examples of BI.

Amazon

Amazon uses BI tools and technologies to personalize product recommendations and sell products, as well as to make logistical business decisions. Amazon’s huge supply chain runs smoothly thanks to in-depth data analysis.

Data and business intelligence technologies have a major impact on Amazon’s supply chain, i.e. from optimizing shipping routes to allocating inventory.

Coca-Cola

Coca-Cola benefits from its social media data, which includes 35 million Twitter followers and 105 million Facebook likes. The corporation can detect when images of its drinks are posted online using AI-powered image recognition technology. This information, combined with the dominance of BI, allows the company to learn more about who are drinking their beverages, where they are, and why they are mentioning the brand online.

The data is used to provide consumers with personalized advertising, which is four times more likely to result in a click than a generic ad.

Netflix

With 148 million customers, this online entertainment company has a significant BI advantage. The question that arises is, what is Netflix’s approach to business intelligence?

Netflix employs data in a variety of ways. The most popular business intelligence example is how the organization develops and tests new programming concepts based on previously seen shows. BI used by Netflix encourages the customers or users to interact with its content. The service is so good at promoting targeted content that its recommendation system is responsible for over 80% of all streamed content.

American Express

The fintech industry is the one where BI has proven to be most effective. In this industry, American Express has been a forerunner in using BI to produce innovative payment service solutions and sell offers to clients. American Express makes use of BI to take effective actions to retain customers who are otherwise thinking of closing their accounts.

Frequently Asked Questions

Q1. What is BI?

Ans. Business intelligence (BI) is a technology-driven process for assessing data and supplying actionable information to leaders, managers, and employees to help them make better business decisions.

Q2. Why is business intelligence important?

Ans. Since BI involves collection and distribution of information, thus, it provides a large amount of measurable data to make decisions and build new products.

The reason why BI is important is because businesses leverage business intelligence to identify major events and monitor company trends in order to promptly respond to their changing environment. You can enhance decision-making and tactical strategic management processes in your organization if you implement great business intelligence strategies.

Business intelligence provides the tools to metricize both what’s going on in your company and what might happen in the future.

Q3. How to use business intelligence?

Ans. There are numerous business intelligence solutions available today that can assist you in tracking important KPIs. Data analytics and business analytics are included in business intelligence, however, they are only used as part of the overall process. Here are some ways in which you can implement business intelligence in your organization:

• Collect business information quickly and efficiently 
• Align performance indicators with business strategies
• Achieve meaningful customer insights 
• Track sales information
• Increase employee productivity

Q4. What are some business intelligence use cases?

Ans. Some business intelligence use cases are:

• Analytics
• Dashboard development
• Data mining
• Process mining
• Business performance management
• Text mining
• Predictive analytics
• Prescriptive analytics
• Data visualization

The Future Role of Business Intelligence

As business intelligence is constantly growing in response to changing corporate needs and technological advancements, we, as an AI development company, keep the development trends up to date. You should also know that artificial intelligence and machine learning will continue to advance and that firms may include AI-derived technologies and insights into a larger business intelligence and analytics strategy. 

Companies’ efforts to exchange data and collaborate will grow as they strive to become more data-driven. Data visualization will become even more important as teams and departments collaborate. This article is merely a primer on the subject of business intelligence and analytics. If you want to know how BI can help your business, then kindly contact us. We are happy to help!