Business Analytics is used to develop new business insights and to understand business performance. There are four key approaches, each with their own unique business benefits. So, how do you know which is right for your organisation? Read on to find out.
The 4 different types of Business Analytics
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
What they mean in plain English
- What happened?
- Why did it happen?
- What will happen?
- How can we make it happen?
Descriptive Analytics (what happened)
This approach is generally used for Financial Reporting and compares historical data sets in revenue and expenses, such as:
- Yearly results
- Month to month movements
This information helps management compare KPIs between different areas of the company and delivers a clear view of strengths and weaknesses in different departments.
Fig 1 Aradhana Pandey – Mastech Digital
Diagnostic Analytics (why did it happen)
This is where we take a deeper look at the data to try and understand the cause of events and behaviours. It usually takes the form of:
- Data discovery
- Data mining
- Correlation techniques
This allows the organisation to understand data quickly and answer critical questions through the use of visualisations.
Predictive Analytics (what will happen)
Here we take current and historical data then use statistics and modelling techniques to look for patterns and determine if these patterns are likely to occur again.
Pattern matching allows an organisation to plan their resourcing to take advantage of possible future events.
There are different types of Predictive Analytics such as:
- Data mining which includes the analysis of large quantities of data
- Test analysis is similar to data mining but looks at large blocks of text
Fig 2 Methods for Predictive Analytics https://www.sciencedirect.com/science/article/pii/S0268401218309873#fig0010
Predictive Analytics is widely used in:
- Insurance / Risk Management industries for determining future claims based on the existing pool of policyholders.
- Marketing Companies look at how consumers have reacted to past campaigns and economic conditions when planning future campaigns.
- Stock Market traders will look at moving averages and break points based on historical data.
Prescriptive Analytics (how can we make it happen)
Here we use Predictive Analytics (the review of current and historical data patterns to determine future patterns) but take a step further by analysing the data to recommend future action, rather than just repeating favourable patterns.
Fig 3 Methods for Prescriptive Analytics https://www.sciencedirect.com/science/article/pii/S0268401218309873#fig0010
Prescriptive Analytics utilises artificial intelligence techniques, including machine learning, where computer programs understand and analyse data without additional human input.
Prescriptive Analytics can be used to:
- Limit risk
- Increase efficiencies
- Attain business goals
- Prevent fraud
However, it’s limited by the organisation asking the correct questions and knowing how to react to the answers. If the inputs going in are invalid, then the outputs will be inaccurate.
Used correctly, Prescriptive Analytics’ strength lies in helping the organisation make decisions based on facts and probable projections, rather than on individual intuition or instinct.
Prescriptive Analytics is widely used in the government and financial and health care sectors, due to the high exposure of human error. Example uses could be city wide fire evacuation plans, analysing hospital patients’ chances of re-admittance or airline pricing due to natural disasters.
Fig 4 Category of methods https://www.sciencedirect.com/science/article/pii/S0268401218309873#fig0010
Based on its use of sophisticated technology and ability to tailor solutions to meet future needs, Prescriptive Analytics is growing in popularity.
So while Descriptive, Diagnostic and Predictive Analytics are currently the most common types of Business Analytics, Prescriptive Analytics is where the future is heading.
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