Before we get into the kinds of business intelligence systems, let us understand “business intelligence”.
Business Intelligence refers to the policies, infrastructure and processes that guide a company in collecting, storing and analysing data generated by its business activities. “Business intelligence” can cover data mining, analysis, performance benchmarks and descriptive analytics.
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What are Business Intelligence Systems?
A “Business Intelligence System” is a network of software programs (or a standalone program) that collate, analyse and present data required by a company. The data can be specific to the company (sales, production, marketing, financials) and can also be extended to cover macro areas such as competitors, market information and distribution channels.
What is the objective of a Business Intelligence System?
The primary objective is to present data in a manner that enables organisations to enhance their strategic decision-making capabilities and to offer a competitive advantage to help companies forecast trends and react to situations faster and better.
Types of Business Intelligence Systems
Business Intelligence systems can vary in complexity from a simple spreadsheet (yes – Microsoft Excel is one of the earliest business intelligence systems!) to massive systems that integrate multiple functions -data collection, analysis and visual representation.
Systems for Business Intelligence
Business Intelligence systems need to have certain “must-have” features:
Source: https://www.selecthub.com/business-intelligence/key-types-business-intelligence-tools/
Business Intelligence Systems Examples
Business Intelligence Systems can be simple spreadsheets, independent tools, integrated suites of tools or as parts of a meta industry system. Many systems are open source or free to use. The main examples of Business Intelligence Systems are:
1. Excel spreadsheets
2. Reporting and Querying software
3. OLAP or OnLine Analytical Processing
4. Decision Engineering / Data Mining
6. Digital Dashboards
7. Local Information Systems
8. Process Mining
9. Business Performance Systems
The Business Intelligence ecosystem
A standard business intelligence ecosystem will be structured as below:
However, business intelligence today is a much more complex dataset and requires a far bigger and more robust architecture. A multi-point, data-based business intelligence system in use today will have the following main segments:
1. Data warehouse: to store company and external information in a central, secure and easily accessible location
2. Data management: tools that mine and analyse the data from the warehouse
3. Business Performance Management (BPM): tools that monitor achievement of business goals
4. User interface: an interactive (on-screen) dashboard that helps access information quickly through reporting tools and data visualisation
We can present a modern Business Intelligence Systems ecosystem as follows:
Source: https://www.passionned.com/bi/systems/
How do companies host their Business Intelligence systems?
Business intelligence systems can be deployed in three ways:
1. Cloud based
2. Premise based
3. Hybrid
The chart below shows the preference for deployment among a set of users:
Source: https://www.selecthub.com/business-intelligence/key-types-business-intelligence-tools/
It is clear that though there is no clear preference for a particular type of deployment, users prefer a system that can be accessed easily at any time.
Advantages of Business Intelligence Systems
A business intelligence system that is designed properly and functions well allows companies to move from descriptive situations (what is happening now) to predictive situations (what’s going to happen). There are several tangible and intangible benefits of using a business intelligence system:
1. Facilitates data-driven business decisions
2. Presents data that is trusted and reliable
3. Helps improve organisational efficiency
4. Provides faster analysis through dynamic dashboards
5. Allows greater collaboration between different company departments
6. Better data visualisation for a 360-degree view of the company
7. Enables a multi-platform, multi-user exploitation facility
8. Scalability to provide advanced reporting and analyses
9. Helps identify new business opportunities and trends
10. Improves employee satisfaction through effective KPI tracking
Companies Using Business Intelligence Systems
Companies use business intelligence systems to drive customer loyalty, build revenue, improve operational effectiveness, customer behaviour prediction and create new opportunities for business. Some examples include:
1. Netflix: data from 148 million customers is a mouth-watering scenario for business intelligence system developers! Netflix uses this data to drive viewer engagement with its content and develop recommendations for streamed content and original programming
2. Tesla: uses business intelligence to connect its cars to the office for data collection and analysis. This enables granular engagement to drive customer satisfaction scores higher and use data-informed decisions for new product development
3. Expedia: uses BI to build greater customer satisfaction by aggregating various objectives that allow it to analyse customer feedback
4. SKF (Sweden based global major in seals and bearings): streamlined its manufacturing process using business intelligence systems to centralise its data and improve demand forecast and planning
5. New York Shipping Exchange: NYSHEX used business intelligence systems and processes to improve the entire shipping process through data centralization and analysis at multiple levels
6. American Express: uses business intelligence systems to develop new payment products and engage and retain customers
7. Coca-Cola: uses business intelligence and AI-powered image recognition technology to generate insights into its customers – who they are, where and why they are drinking Coca-Cola. This has helped the company plan and promote its products better through targeted advertising
8. Starbucks: uses data from its loyalty program and mobile app to develop and broadcast individual offers to customers, draw existing customers more frequently into its physical stores and push sales volumes
9. Delta Airlines: Business Intelligence systems are helping Delta improve its customer service and the overall “Delta Experience”. The airline uses data to identify and reward high value corporate travellers individually, develop programs to enhance the Delta experience and build customer loyalty
10. Walmart: the world’s largest retail organisation uses business intelligence systems to design simulations to decode customer buying behaviour and patterns. This helps understand how in-store and online purchase activities are influenced by browsing behaviour and it can then identify the busiest times for any product or category
What are the success factors for Business Intelligence Systems?
Why do companies need a dedicated Business Intelligence System? Business intelligence applications are not restricted just to IT professionals today; the tools available today have evolved to enable more employees in a company to use the data available. Business Intelligence has also moved from the classic format of using in-house data to generate and analyse reports to interactions with intuitive, agile and transformational systems that analyse data at great speed.
However, over 60% of companies report that their business intelligence systems do not live up to expectations or deliver the expected results. So, what are the success factors for a business intelligence system?
1. Performance: Speed, accuracy and ability to crunch huge amount of data are important factors for a successful business intelligence system
2. Ease of use: Business intelligence systems today are meant for non-IT professionals to use also, and should be easy to use by non-technical staff
3. Focus on the key business area: It is tempting to integrate a system that covers all business areas, whether required or not. The risk here is time lags for implementation, unnecessary expense and obsolescence. Choose the business area that will benefit the most from the improved reporting and analysis, and which has the biggest analysis problem.
4. Be clear about cost: Any business intelligence system has fixed and variable costs which are not always visible at the time of evaluation and / or purchase. Be sure to get the total cost outflow so that there are no surprises
5. Choose wisely: Evaluate as many options as possible and choose the technology that best fits the requirements
6. Accuracy and robust reports: The technology implemented should ensure that the users receive analysis that makes sense to them. Faulty output will lead to loss of trust in the system
What are the challenges Of Business Intelligence Systems?
Business intelligence systems are today a much-needed and integral part of a company’s processes. However, there could be certain challenges in implementing and using a B I system effectively:
1. Complexity of data: Not everyone in the organisation knows how to analyse the data effectively and this could lead to blind spots in adoption of the system
2. Time deficiency: Data mining and analysis takes time, even with superfast systems. If these tasks are assigned to only a few company-wide resources, it will fight for priority with other tasks of the team members
3. Multiple systems: Use of multiple and non-compatible business intelligence systems will hinder the organisation’s ability to use the data effectively.
4. Lack of access: A business information system works best when multiple users are able to access it at any time. Confining the system to a “select few” employees (key business managers for example) leads to imperfect decisions.
Conclusion
Business intelligence manipulates data into actionable insights that determine how a company can maximise its business success through data-led decisions. A robust, flexible and integrated business information system is a vital piece of the company’s processes and should be at the centre of every level of decision making within the company.
Developments such as the growth of artificial intelligence, ERP and CRM functionalities and machine learning capabilities are poised to drive business information systems into many more applications to make the business of running companies much more efficient.