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In the modern world, reporting is an essential part of running a company. But reporting only allows management to react to what has happened. There’s no outlook for the future. If our business only does reporting, we are already lagging behind.
Business Intelligence can help us have smart reporting that gives insights about decisions that can positively influence the future. BI is a mix of technology and strategy within the company, which aids the data analysis of business information.
Business Intelligence uses the power of automation to transform your data into insights to support your decision-making process. It aims to support the strategic decisions within the company.
BI tools provide detailed intelligence about the business by analyzing our data. They show us financial analytics, summary dashboards, and data visualizations. The primary purpose of such tools is to provide quick access to easy-to-read reports.
Dashboards are the most widespread representation of Business Intelligence, showing us the business’s current state with meaningful scorecards, charts, maps, and more.
BI won’t tell us what to do but will tremendously improve our ability to aggregate data and analyze it in a way, allowing us to draw insights for better business management.
Business Intelligence supports a fact-based decision-making process by following historical performance instead of assumptions.
Business Intelligence vs. Business Analytics
We can interpret Business Analytics as a subset of Business Intelligence, looking at statistics, prediction, and forecasting.
If we look at a more specific view on Business Intelligence, it gives us an overview of the company’s current state. BI helps answer questions like what happened with inventory this month, how many sales orders we received this week, or how much claims and returns cost us for the quarter.
BI is descriptive of the current situation, and it can give insights into what happened to get us to this situation. Business Intelligence strives to give users easy to understand snapshots of various states of affairs in the business, to support managers’ decision-making process.
Business Analytics aims to be predictive and give us an idea of what might happen in the future. It guides what we can do for a better outcome. BA is generally less accessible than BI, as it requires data science professionals to model, analyze, and interpret the results.
Business Intelligence tries to be more accessible to non-technical users, providing simple tools so even non-IT employees can build reports and perform analysis.
Development of BI
Back in the day, Business Intelligence involved some massive IT resources that would process and analyze the data and provide a static report out of it. This made it hard to ask follow-up questions, as this meant going back to the IT people and starting the process all over again, which was time-consuming and costly. Companies were mostly unable to leverage current (live) data to enhance their decision-making process. However, this is still quite a typical situation, especially in reporting, where most businesses don’t prioritize future outlook.
Modern BI systems are more interactive and dynamic. Making them more approachable also makes it easier to train non-technical users to visualize data and create reports and dashboards to answer their own questions ad hoc.
With modern Business Intelligence solutions, IT can focus on data governance and access control. They can leave data analysis and interpretation to the people directly involved in the relevant business operations.
Business Intelligence Tools
Dashboards and Visualizations are the two most common BI tools, by far. Some other options include:
- Data Mining;
- ETL (Extract – Transfer – Load) tools – transferring from one data store to another;
- Process Mining.
Processes in BI
- Descriptive analytics – using data to identify sources of different developments (what happened);
- Querying – asking specific questions that can be answered directly from the data;
- Preparation of data – compiling data from multiple sources, preparing it for further analysis;
- Visual analysis – employ visual storytelling to facilitate data exploration
Business Intelligence Software
BI platforms can gather and process vast amounts of data to give structured insights into the business operations, supporting the entity’s strategic planning and decision-making process.
Leveraging a Business Intelligence system properly can give us a competitive advantage and ensure long-term stability. Such solutions provide a way to interpret big data, which is otherwise too large for people to comprehend.
BI can help with both operational and strategic decisions. The platform combines different external (like market and benchmarking data) with internal data sources (performance data like sales) to give us the ‘big picture,’ which we cannot derive from a single set of data.
There are many software solutions giving companies ample options to implement BI functionality within their organization. Some of the most popular solutions available are:
These software modules combine technology and data to support modern-day businesses in making more data-driven decisions. Successful implementation of BI means to have an overview of company data that we use to drive optimizations, support decisions, and eliminate inefficiencies.
Steps to Implement BI
In broad outlines, the process of implementing a Business Intelligence solution has three main steps:
- Gather the raw data from all relevant systems;
- Process, clean, and make the data homogenous so that we can store it in a data warehouse that will reload it automatically;
- Use the BI system to access the data and prepare dashboards and reports with which users can interact.
Uses for Business Intelligence
We can apply BI in any aspect of the business. To analyze the business’s progress, we can track key performance metrics and compare them against targets. Utilizing the power of statistics and business analytics, we can identify trends and support predictive and prescriptive analysis. We can also use BI software to do all kinds of business reporting to help strategic decisions via dashboards and data visualizations.
Here’s a summary of the ways that Business Intelligence can help us make smart decisions:
- Customer behavior analysis;
- Competitor/industry benchmarking;
- Performance tracking;
- Market trends analysis;
- Operations optimizations;
- Identify areas for improvement.
One of BI’s most significant benefits is that it makes data visualizations more approachable and more straightforward. Humans are visual beings, and we are good at recognizing visual cues, patterns, and color differences. Representing our data with visualizations makes it more accessible and readable. A dashboard with visual analytics is more comfortable to interpret and spurs more discussion between users.
Companies use BI platforms more and more as a front-end (user interface) for big data systems. Their flexible connectivity options enable such tools to connect to a vast range of data sources.
Use cases and Business Intelligence applications vary between industries, the common thing being the need for fast analytical tools to support operations.
- In finance, we can use BI to assess risk or to identify investments that will complement a client’s portfolio;
- In retail, BI helps with marketing campaigns management, inventory management, and others;
- Manufacturers use BI to track facilities’ operations to better plan production, procurement, and distribution;
- Hotels can track bed capacity;
- Healthcare uses BI to diagnose disease and track the spread of viruses;
- Schools can monitor student’s performance and identify those in need of assistance.
As businesses realize the benefits Business Intelligence can provide, there’s an ever-increasing demand for professionals well versed in the field. People engaged in this role will focus on finding areas for improvement for the business. The ultimate goal is to either cut expenses or increase profits. They maintain the BI tools and design the reports managers use by leveraging the company’s data. They also ensure data consistency and correct transfer between the raw data and the data processing pipeline, which often requires pre-processing and cleaning up.
Advantages and Disadvantages of BI
When you consider the prospect of implementing a Business Intelligence solution in your company, it is crucial to consider the following benefits and drawbacks.
- Boost productivity – once reports are set within a BI system, generating them is a matter of selecting a date range and clicking a button, which saves much time;
- Accountability – BI makes it easy to track performance against goals and thus enforces accountability to people responsible for the operations;
- Increased Visibility – BI makes processes more visible and helps managers in identifying areas for improvement for the business;
- Overview of the Business – BI gives decision-makers an overall view of the business through dashboards and KPI scorecards;
- Allows Easy Analytics – allowing non-technical people to use BI makes analytics more approachable and easy to generate insights out of data.
- Complexity – BI systems and data warehouses can be hard to implement, and understanding the data and how to link it in a meaningful way may prove tedious;
- Cost – BI can become quite costly to small and medium companies, mainly if they only use it for routine transactions, which will diminish the benefit;
- Time-consuming – some ERP’s have tens of thousands of data tables behind them; processing and setting up these can take much time;
- Limited Use – often, companies start to implement a BI system and invest a lot of money and hours to ultimately abandon the project because they don’t have the technical resources to utilize the system.
Future of Business Intelligence
In recent years there has been a rise in self-service BI tools. These aim to reduce the reliance on IT specialists. Non-technical users have a larger role to play, as self-servicing Business Intelligence gives simple ways to aggregate, drill-down, and analyze data.
The future of Business Intelligence will see Artificial Intelligence (AI) and Machine Learning (ML) algorithms become a more prominent part of the available BI tools. This will allow a merge between the descriptive part of BI and the prescriptive part of BA, each one making the other one better over time. Bringing more of Business Analytics in Business Intelligence tools will also provide users with much more accessible techniques for predictive analysis.
Such advancements will also tremendously improve software packages’ what-if analysis capabilities, making it easy to look at different future scenarios based on live data. Doing so will provide valuable insights into the business in support of management’s decision-making process.
As AI and ML start to play an increasing role in BI, efforts to share data, and collaborate on such projects will also increase. Visual data will make sharing insights much more comfortable as there will be no necessity to have a deep understanding of the underlying data.
Business Intelligence is a term that covers the processes and methods to gather, store, and analyze business performance data to identify areas for improvement.
BI helps us present our data within the right business context. Companies rely on it to track performance against goals and to find answers to their questions.
Business Intelligence is not a linear process, as finding the answer to one question usually leads to follow-up questions and actions. It’s a cycle of data gathering, exploration, and sharing. In the modern sense, BI prioritizes self-service analytics and a quick and approachable way to get valuable, actionable insights from data.
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FCCA, FMVA, Founder of Magnimetrics
Hi! I am a finance professional with 10+ years of experience in audit, controlling, reporting, financial analysis and modeling. I am excited to delve deep into specifics of various industries, where I can identify the best solutions for clients I work with.
In my spare time, I am into skiing, hiking and running. I am also active on Instagram and YouTube, where I try different ways to express my creative side.
The information and views set out in this publication are those of the author(s) and do not necessarily reflect the official opinion of Magnimetrics. Neither Magnimetrics nor any person acting on their behalf may be held responsible for the use which may be made of the information contained herein. The information in this article is for educational purposes only and should not be treated as professional advice. Magnimetrics accepts no responsibility for any damages or losses sustained in the result of using the information presented in the publication.