What is business intelligence? A newbie’s guide

Business intelligence. For years, it has existed in an odd space between business analytics and artificial intelligence, and in some people’s eyes, is as buzzwordy as both combined.

But recently there’s been an uptick in the number of companies interested in the idea. In a world where dealing with data has become a greater issue for companies than collecting volumes of data, business intelligence stands out as a cost-effective, adaptive approach to data use.

For those unconvinced or unsure, below is a brief primer on business intelligence, its relevance and its use.

How business intelligence (BI) differs from business analytics (BA)

The line is often blurred between BI and BA, and some people even use the terms interchangeably. However, others see the difference between the two as delineating a sharp divide in approaches to data use. This view has been steadily gaining in popularity as companies dive further into more effective and nuanced ways of considering data.

The general gist is this:

Business analytics is about using historical data and predicting and preparing for future business climates. It is especially useful for analysing very specific business problems.

Business intelligence, on the other hand, uses current and actionable data to provide insights for business strategy settings. This primarily suits continuous improvements in decision making, operational efficiency and productivity.

Why BI is still valuable in the age of AI and big data

AI and big data are trendy right now, but they typically remain novel tools accessible only by multinational enterprises with extensive resources and data facilities.

Small-to-medium businesses with a much smaller client base and market influence simply do not have the luxury to afford usable and business-friendly AI. Business intelligence remains the most cost-effective option for helping smaller businesses improve their decision making.

What business intelligence is doing for businesses

In general, organisations use data visualisation features to generate real-time reports that contain relevant and actionable data for daily decision making on various business disciplines.

A good example of this is in the fast-moving consumer goods sector, which has pioneered BI application to analyse consumer preferences and market trends and ultimately to optimise pricing and marketing strategies.

Questions that can be answered with BI in this scenario include:

  • Which product/s should be discounted?
  • Where and how long does a product need to be on the shelf during the promotional period?
  • Which package will drive the most impact in achieving the campaign target?

All these decisions are supported by analysis of current sales data, consumer ratings on social media or even political trends. Instead of reacting to market changes, BI predicts and validates trends, and continues to provide evidence to support decision making at every stage of the business journey.

Business intelligence and the importance of data management

For business intelligence to deliver more valuable insights, accurate and quality data is essential.

The issue is that often companies start collecting data with no clear vision of what they need in the future. Each department collects only the data required for their business activities using their own tools.

Additionally, businesses may jump straight into analytics without realising the significance of a clean data structure and consistent data collection approach.

Both these approaches result in a duplicated and incomplete data set that reduces the effect and impact of conducted analysis.

Therefore, establishing a consistent approach for data collection across the company is the very first step that any business should take.

Many businesses are storing data through software vendors of the applications they’ve purchased to suit their business needs at that time. This means the data is stored in the vendor’s database, which is not directly available for most companies to manage.

Businesses must do a robust review of the software vendor’s data policy and security measures to safeguard the data. In particular, they must ensure their software vendor comes with an endorsement from data security professional bodies such as ISO.

ELMO has recently established a partnership with the University of Technology Sydney (UTS) to develop AI-driven predictive analytics solutions. By drawing upon the combined strengths of both entities, ELMO will be able to provide HR and payroll professionals with a deeper understanding of their workforce, so that they can make more data-informed business decisions, at a faster pace.

Are you passionate about business intelligence? Great news – we’re looking for AI and BI specialists to join us in helping deliver these solutions. Visit our careers site to find out more or get in touch with ELMO’s talent acquisition team via email on [email protected].

Learn more about how ELMO can help your organisation.