Business Intelligence – A Complete Guide

  • What is Business Intelligence?

    Size of business intelligence and analytics software

    Business intelligence or BI as it’s usually called, uses services and software to convert data into actionable insights. These insights are used by the organization to make better tactical and strategic decisions. 

    Use cases of BI in corporate setup can be seen in how a company which wishes to manage the supply chain better uses BI to identify the cause of delays and where variabilities exist in the shipping journey. Moreover, the technology can be used for keeping track of member retention, generating sales reports, and showing the status of prospects to customers’ journey. 

    There are several BI tools like Tableau, Microsoft Power BI, etc. that gather and analyze data sets to then present the analytic findings in summary, report, dashboard, chart, map, etc.

    Now even though business intelligence has established itself as a key part of attaining business objectives, there is still some confusion around the meaning of BI and business analysis. Let us answer that for you today. 

    Business Intelligence vs Business Analytics

    The biggest difference in business intelligence and business analytics lies in the questions that they answer. BI focuses more on the descriptive analytics that provide gist of present and historical data to show what is happening now and what has happened earlier. It answers the how and what side of a business so that the managers can replicate what works and change what doesn’t.

    Business intelligence vs Business analytics

    Business analytics, on the other hand, looks into predictive analysis. It makes use of data mining, machine learning, and modeling etc. to know the likelihood of any future outcomes. It answers the why side of the business queries, helping managers make sound predictions and anticipate the outcome of a new business decision. 

  • The Two Primary Types of Business Intelligence

    Strategic Business Intelligence

    Also known as auto-delivered intelligence, it is a type of business intelligence which is related to generating reports from the data warehouse or data source. It betters the business processes by analyzing predetermined datasets which are relevant to the specific process and offers a historical outlook of data. Additionally, the strategic intelligence model offers a base for planning, goal setting, and forecasting, etc.  

    Strategic BI emphasizes on showing the output in graphs and charts to show the opportunities, trends, and the problem areas. It runs on four key parameters:

    • Gathering and storing the data 
    • Optimizing data for analysis 
    • Identifying key business drivers
    • Seeking answers to crucial business questions

    Operational Business Intelligence

    This type of business intelligence is related to the operational and transactional data source. One way to identify this type is to see if data that is generated from the analysis directly helps finish an operational task. Operational BI offers relevant, time-sensitive information to the operation managers and front-line customer-facing employees to aid them in their everyday processes.

    Since the operational BI is heavily task focused there is less need for graphs and charts. An example of this can be seen in if someone in the operational domain wants to inform a member of the clients over dues, a graph won’t work well. What they would need is a brief message. 

    This is the reason why communication devices like instant message, email, and dashboard etc. play a key role in operational BI. The output which one gets from operational business intelligence consists of schedules, invoices, shipping documents, and financial statements.

  • How Business Intelligence Works?

    Even though business intelligence gets used in multiple ways for multiple objectives by businesses, the process is more or less same for all the industries – 

    1. Data is gathered from different sources – consisting of internal company data and external market data – is integrated and stored in a data warehouse.
    2. Data sets are made and set up for analysis by creating robust data analysis models.  
    3. The data analysts then run queries against the models and the data sets.
    4. The query results are used for creating visualizations in the form of graphs, charts, and histograms, etc. in addition to BI dashboards and reports.
    5. The decision makers use the reports to make key business decisions in terms of what is working and what needs to change.
  • Core BI Components for Enterprises

    Business intelligence tools

    Enterprises can deploy various types of BI tools depending on the BI use cases for their business. Some such tools include:

    • Data mining software
    • Online analytical processing (OLAP)
    • Reporting software
    • Data warehousing software
    • Business performance management tools  

    Dashboards

    A dashboard is a simple digital interface that provides graphical representation of data. Dashboards are an effective way to distribute BI information to business users to enable effective decision-making. 

    Data sources

    These primarily include an organization’s operational systems such as Customer Relationship Management (CRM), Enterprise Resource Planning (ERP), and Supply Chain Management (SCM) applications. 

    Data integration

    Extract, Transform and Load (ETL) tools are the primary means of integrating data for business intelligence uses. Other integration methods that can be used include data virtualization, data profiling and data cleansing.

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  • What are the Different Business Intelligence Benefits?

    The benefits of BI in business are widespread. Every domain comes with a use case for the technology. Let us dive into them. 

    Speedy and correct reporting: Through BI, the employees can use customized reports or templates to monitor the KPIs through a  variety of data sources, which includes operational, sales, and financial data. These reports can be generated in real time and be used for businesses to act quickly.

    Gathering business insights: Businesses can easily measure their revenue, employee productivity, and the department-specific performances through BI tools. It can help reveal the weaknesses and strengths of the business while giving them insights into what is working and what’s not. In the BI platforms, businesses can even set notifications to keep on top of the movement in KPIs which matter to them. 

    Better customer satisfaction: Business intelligence tools can provide enterprises an inside out view into their customers patterns and behaviors. Since the tools are designed to track customers’ feedback in real time, they can help them retain the existing customers and reach new ones by taking timely actions and anticipating the needs of the customers.

    Identifying new opportunities: Identifying trends and creating strategies backed by data can give businesses a competitive edge. The employees can merge the external market data with their internal sales journey to identify the trends in both customer experience and market conditions. 

    Better operational efficiency: Business intelligence platforms merge multiple data, which helps the complete organization across domains. What this leads to is that the managers spend less time in tracking down the information and focusing on creating timely and accurate reports. 

    For the employees this means that they can focus on how their performance is impacting the  short and long term business goals.

    Better revenue: High revenue is the end goal for any enterprise or startup. The data gathered from BI tools can help the businesses ask better questions and identify weaknesses in a timely manner. The BI tools can help with analyzing the gaps in revenue while highlighting the ways to expand the margins. All of this together can help businesses make better strategies around where the budgets should be spent to get the biggest revenue.

  • How are Enterprises Using BI Capabilities to Grow?

    Twitter

    The leading social media company is using BI along with Artificial Intelligence (AI) to counter potentially dangerous and inappropriate content on the platform. The algorithms together have proved to identify 95% terrorism-related accounts. 

    The technology is also used by them for fine-tuning the overall user experience of the application. The business intelligence tools see the live feeds and categorize them on the basis of their subject matter. They also use this data for bettering their search capabilities and identifying the videos/content the users will be interested in. 

    Uber

    The company makes use of business intelligence to identify the different vital aspects of the business. An example of which can be seen in surge pricing. The BI-led algorithms track the traffic conditions, time of journey, availability of the driver, and customer demand – all in real-time. This feature of dynamic pricing is also used by hotels and airlines to adjust the price on the basis of the customers’ needs. 

    Walmart

    The retail giant makes use of BI technology to understand the impact of online behavior on in-store and online activity. Through the analysis of simulations, Walmart is able to understand customers’ purchase patterns, for example, how many people searched for a piece of furniture 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. 

    Starbucks

    Through a mix of its mobile app and the famous loyalty card program, Starbucks gets purchase data of millions of customers around the world. Using that information and the BI tools, the company then predicts purchase trends and sends personalized offers of what a customer would prefer through email or application.

    This system helps in drawing the existing customers in the stores more frequently, thus leading to high sales volumes.

    Lowe’s

    The home improvement company makes use of business intelligence for merging what customers tell them with the actual online and in-store behavior. They use the data for discovering insights that lead to staffing and product assortments in stores. The technology helps with driving sales and also with serving the customer. For example, Lowe’s uses predictive analytics for loading the trucks specific to the different zip codes, this way the right store gets the correct type and amount of the product. 

     Netflix

    The 209.18 million active users of Netflix give the brand a huge BI benefit. The company uses the technology in several ways:

    – formulation and validation of the programming ideas on the basis of previously seen programs.

    – increase the in-app time. The recommendation system that the Netflix app is built on drives more than 80% of the streamed content.

    Coca-Cola

    With over 35 million Twitter followers and 105 million Facebook fans, Coca-Cola uses BI to benefit from the social media data. Using AI-driven image-identification technology, the brand notices when the photos of its drinks are posted online.

    This information when merged with BI gives the brand insights into who is drinking Coca-Cola and in what context they are mentioning the brand. This information helps the brand hit their user base through targeted advertising, which results in a lot more clicks than a generic advertisement.

    Delta Airlines

    Delta Airlines has created a memorable “Delta Experience” feature by merging BI and big data to support customer service. The flight attendants get the BI tools to recognize and thank valued travelers.

    The positive customer experiences blended with well-thought programs help position the airline as a market leader in the business travel sector.

    American Express

    Business intelligence is crucial for the finance domain. American Express has been using the BI technology to build new payment-based services and products to its customers. The company, through BI capabilities, found that 24% of the Australian users were closing their accounts in under 4 months. To solve the issue, the bank took steps to retain customers. The technology also helps them detect fraud and protect the customers whose card data might have been compromised.

    These are just a few examples of the adoption of BI capabilities in the business world. The one takeaway that you can take from here is how the technology has a use case across a range of different industries. Let us look into the ways you can implement the capabilities in your business.

  • How to Implement BI into Your Business Model?

    1. Build a business intelligence strategy

    A business intelligence strategy is a roadmap that enables a company to measure its performance, know the shortcomings, better the competitive advantage, and use analytics to make well thought of business decisions.

    In order to build a sound business intelligence strategy, it is important to get answer to these questions:

    – What is the business objective?

    – What resources do you have to meet that objective?

    – What do you require to meet the objective?

    2. Set up the key performance indicators

    Once you have enough information and a strategy in place, the next step would be to set the KPIs that you are going to track the company’s growth against. The KPIs have to be measurable, should match the objectives, and must be crucial to achieve the business goals.

    Some examples of KPIs in the business intelligence can be –

    – Financial: Liquidity ratio, net income vs net earnings

    – Marketing: Customer Acquisition Cost, conversion rate

    – Project management: Returns on investment, productivity

    – Customer service: Customer effort score, net promoter score

    – Human resources: net income per employee, cost per hire

    3. Build a BI team

    When you are out to build a business intelligence team, you get two options: hire an in-house team or outsource the BI project. Either ways, here are the different professionals who will be involved in implementing your BI project- Application developer

    – BI Infrastructure architect

    – Business representative

    – Data administrator

    – Data mining expert

    – Data quality analyst

    – Database administrator

    – Meta data administrator

    – Project manager

    – Subject matter expert

    4. Know the BI software requirement

    The choice of best BI software tool will depend on the budget and the business requirement. However, there are some key considerations to consider when buying a software solution:

    – Do you have a simplified view of the data?

    – Does the software offer integration with the existing system?

    – Can you collaborate with others on the data analysis part?

    – Will you be able to discover insights on your own?

    5. Pick data storage, platform, and environment

    If you do not have an infrastructure, it will be a good start to look for data storage options. Usually, a data warehouse is seen as the best choice for business intelligence implementation since it offers analysis of data coming in from both business apps and online transaction processing. Once you fix the best data storage platform for your BI project, the next step would be to fix an environment – in-cloud, on-premise, or hybrid.

    6. Prepare your data for quality business analytics

    The success of a good business intelligence and analytics project is dependent heavily on the quality of the data.

    But how do you know your data is prepared for analysis? Well, it should pass through this checklist:

    – Complete

    – Valid

    – Unique/non-duplicated

    – Consistent

    – Timely

    – Accurate

    7. Implement a pilot project

    Once all the processes are in place and the data has been vetted, the last step that remains is to run a pilot test. And while it can be enticing to launch the project across the entire organization, we recommend testing it across a small group of users to see how receptive they are towards it.

    After the pilot project is live, review the results and measure them against the KPIs we had set up in step 2. If you don’t see them supporting the expectations, revisit the architecture.

    Up until this point, you must have gathered how complex it can get to integrate BI capabilities in an enterprise or a startup. While when you outsource the project to a team of expert business intelligence engineers, they handle the complexities and deliver you a product that is personalized according to your business needs, you have to go through all the complexities of BI project development if you choose to build it in-house.

    Let us look into what those organizational challenges are.

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  • The Business Intelligence Challenges that Enterprises Face

    The Business Intelligence Challenges that Enterprises Face

    1. Gathering and refining of data

    A business data is spread across a range of platforms and systems both on-premise and in-cloud. The growth in data sources means that the businesses have to plan out a system to get all the data in one place. Now, you can make use of BI tools and deploy a data warehouse in a common place for the BI data.

    The next phase of data-related business intelligence lies in refining the data, ensuring that quality wise, it is good enough to base key business decisions on. It is extremely important to not just run data through a checklist of key considerations but also categorize them into right groups, so that every team knows which data is of what use.

    2. Training the end users

    Failed company-wide adoption of business intelligence capabilities is one of the biggest challenges of BI integration. It is crucial to get a buy-in from every stakeholder and the people who are responsible for maintaining them.

    Right from the beginning of the development process, it is important to loop in all the team-wise key people. A set of clear objectives and KPIs that come from them will help with the development of a well-thought of BI product which is built for success.

    While on one-hand, it is important to get buy-in from key people in the organization, on the other hand, it is equally important to train the staff.

    3. Not using the right performance indicators

    One of the biggest BI adoption challenges lies in the fact that after putting in a lot of time and money behind the entire BI development cycle, entrepreneurs fail to see any real value coming out of it. This situation majorly arises out of the reason that there is a lack of correct key performance indicators in place.

    It is necessary to understand the capabilities of your BI project and what it can achieve. Only when you know the exact processes it can impact, will you be able to measure it against.

    With this, you now know everything there is to know to get started with the implementation of BI capabilities in your business and things that you should have a lookout on. The only thing left to understand is what the technology has planned in store for itself in the coming years. Knowing this would help you set your BI project off the right grounds.

  • The Key Business Intelligence Trends in 2022

    Data governance

    It is the process of creating a blueprint for managing the corporate data asset which includes architecture, processes, and operational infrastructure. It forms a base on which business-wide data management occurs. The creation of data governance, while having been seen as a nice-to-have process, will grow on to become a must-have element in a BI architecture in order for a company to be compliant with the laws.

    Connected cloud

    It is an undeniable fact that the future of a business, especially in terms of data, lies in the cloud. In the time to come, we will see all the BI elements ranging from data source, data models, computing power, etc. moving to the cloud. Another facet of this would be that businesses will find it difficult to get a one size fit all solution for their variety of BI needs. This is where the concept of connected cloud strategy will come into the forefront.

    A connected cloud strategy will become a great approach to introduce flexibility and lower the risks involved in business analytics.

    Self-service BI interfaces

    Business stakeholders have always raised their discomfort against rigid, complex BI analytics tools and the high operational cost of hiring an expert BI expert. This concern has led to the advent of self-service BI interfaces. These platforms enable businesses to manage the BI tasks without any additional technical help.

    With more businesses planning to use the BI features for promoting data-driven culture, the self-service BI trend is only poised to grow in the years to come.

    Data Quality Management

    Data is the livelihood of any business and a key component of business intelligence efforts’ success. However, in order to truly make it work for you, the quality of data is crucial. With data sources getting interwoven every passing minute, it is important to have a good data quality management process in place. An effort in this direction is what we can expect to become a trend in the coming time.

    Now that we have reached the end of the guide, it is only understood that you would be having a lot of questions. Let us try to answer them in the last segment of our guide.

  • Frequently Asked Questions about Business Intelligence

    Q. What is BI and where is it used?

    A. BI is a tech-driven process for analyzing data and delivering actionable insights to the executives, managers, and workers. The use cases of BI can range anywhere from customer retention to product improvement and identifying the cost per hire, along with a range of other benefits.

    Q. How does business intelligence collect data?

    A. Organizations can collect data from social media, POS systems, websites, apps, surveys, etc. to build their business intelligence project upon.

    Q. Who are the target users of BI in any organization?

    A. The target users can be anyone from analysts and lineworkers to the top management and the customers or suppliers.

    Q. What are some of the key success factors of a BI project?

    A. There are quite a few success factors of a BI project:

    • A well-defined business case to get the best solution
    •  An ROI plan
    • Definition of all the KPIs
    • Proper end-user training
    • Availability of latest technologies

    Q. What parameters should I see when choosing a BI solution?

    A number of parameters should be kept in mind while choosing a BI solution: 

    •       Product acquisition cost
    •       Scalability
    •       Returns on investment
    •       Agile BI support
    •       Ease of integration with third-party solutions
    •       Data blending support

    The next steps? Initiate your BI journey by understanding the true capabilities of the technology in your business space.

    Appinventiv is a data science and business intelligence company offering services and solutions in the form of consulting, implementation and support. Reach out to us to get all your BI needs covered. 


  • https://appinventiv.com/guide/business-intelligence-for-enterprises/

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