Scientific Decision Making

The scientific approach to decision-making involves the use of data and logic as opposed to hunch and intuition.

What is Scientific Decision Making?

All business decisions involve some uncertainty. However businesses and managers increasingly want to reduce that uncertainty and risk by applying logic to decision-making, supported by relevant data.

Scientific decision-making involves the use of:

• Data mining and big data to source relevant data to inform decisions
• Application of software logic and predictive models to analyse scenarios
• Forecasts to consider the possible implications of business decisions

Quite a few of the models you explore as a business student can be linked to scientific decision-making (although they also involve some qualitative judgement), including:

• Decision trees
• Investment appraisal
• Sales forecasting
• Sensitivity analysis
• Network analysis

Reasons Why Scientific Decision Making is Becoming More Popular

• More widespread availability of data
• Greater sophistication of data analytics & skills / experience of data analysts
• Management expectation that data will be used wherever possible, particularly where a decision is significant to the business