Decision Intelligence: Leveraging Behavioural Science for Better Business Decisions
In the business world, decision-making is a critical component of success. Whether it’s a small decision, like choosing a vendor, or a big decision, like entering a new market, the outcome can have a significant impact on a company’s bottom line. As such, decision-making processes have been studied and improved upon for decades. One field that has recently come to the forefront in this area is behavioural science, specifically the study of behavioural economics. In this article, we’ll explore how behavioural science is related to decision intelligence and business decision-making and provide real-world examples of why this is a smart choice for businesses.
What is Decision Intelligence?
Before diving into the relationship between behavioural science and decision-making, it’s essential to understand what decision intelligence is. Decision intelligence is the practice of using data, analytics, and decision models to improve decision-making. It is a holistic approach that brings together multiple disciplines, including data science, behavioural science, and artificial intelligence, to create a framework for making better decisions.
One of the primary benefits of decision intelligence is that it helps organizations make data-driven decisions. By analysing data and building decision models, decision-makers can see the potential outcomes of their choices before making a final decision. This approach helps companies avoid making decisions based on gut feelings or personal biases, leading to better outcomes in the long run. — Check the first article of this series for a deeper explanation
What is Behavioural Economics?
Behavioural economics is a branch of economics that combines psychology and economics to understand how people make decisions. Traditional economics assumes that individuals are rational decision-makers who always act in their best interest. Behavioural economics challenges this assumption by examining the cognitive biases that affect decision-making.
The field of behavioural economics has identified several cognitive biases that can influence decision-making, including the following:
Anchoring bias: The tendency to rely too heavily on the first piece of information presented when making a decision.
Confirmation bias: The tendency to seek out information that confirms one’s existing beliefs or hypotheses.
Availability bias: The tendency to overestimate the likelihood of events that are easy to remember.
Status quo bias: The tendency to prefer the current state of affairs over a change, even if the change may be beneficial.
By understanding these biases, decision-makers can make more informed decisions that take into account the irrationalities of human behaviour.
The Relationship Between Behavioural Science and Decision Intelligence
Behavioural science and decision intelligence are closely related because behavioural science provides decision-makers with insights into human behaviour. By understanding the cognitive biases that influence decision-making, decision-makers can build more accurate decision models and make better decisions.
For example, suppose a company is considering launching a new product line. Traditionally, decision-makers might rely on market research and gut feelings to make this decision. However, by incorporating behavioural science into the decision-making process, decision-makers can better understand how consumers might react to the new product line.
One way to incorporate behavioural science into this decision-making process is to conduct experiments with potential customers. By testing different product concepts and measuring customers’ responses, decision-makers can gain insights into how customers might behave in the real world. These insights can then be used to build more accurate decision models and make better decisions.
Real-World cases of Behavioural Science in Business Decision-Making
Several real-world examples demonstrate the benefits of incorporating behavioural science into business decision-making. Let’s explore a few of these examples:
The Power of Defaults
In 2012, the UK government made a small change to the way pension plans were structured. Instead of requiring individuals to opt in to a pension plan, the government made it a default option. Individuals had to actively opt out if they did not want to participate in the plan.
This small change had a significant impact on pension plan participation rates. Before the change, only 42% of individuals were enrolled in a pension plan. After the change, enrolment rates increased to 83%. The power of defaults demonstrated that individuals often choose the default option, even if it’s not the best option for them.
This example shows how behavioural science can be used to nudge individuals towards better decisions. By making the default option the desired option, decision-makers can influence behaviour positively.
The Pricing Effect
Pricing is a critical component of business decision-making. Behavioural science has shown that the way prices are presented can have a significant impact on purchasing behaviour. For example, the “charm pricing” effect suggests that prices ending in “9” are more attractive to consumers than prices ending in “0”. This effect is so powerful that retailers often use it to increase sales.
Another pricing effect is the “decoy effect”. The decoy effect occurs when a third option is added to a set of two options, making one of the original options more attractive. For example, suppose a company is selling a basic and premium product. By adding a decoy option that is priced slightly higher than the premium product but has fewer features, the premium product may appear more attractive to consumers.
These pricing effects demonstrate how behavioural science can be used to influence consumer behaviour and improve business decision-making.
In case this is still too broad for you, let’s look into industry-specific cases in which behavioural sciences were used to improve decisions:
Financial Services Industry: Financial advisors use behavioural economics principles to help clients make better investment decisions. For example, advisors may use loss aversion to explain to clients the risks of investing too conservatively and missing out on potential gains.
Healthcare Industry: In the healthcare industry, behavioural economics has been used to improve patient outcomes. For example, a study found that reminding patients to take their medication using a simple text message increased medication adherence by 10%.
Marketing Industry: Behavioural economics principles have been used in marketing to influence consumer behaviour. For example, scarcity bias has been used to create a sense of urgency and increase sales. Limited-time offers and low stock alerts are examples of how scarcity bias is used to influence consumer actions.
What can we learn here?
Incorporating behavioural science into decision-making processes can lead to better business outcomes. Behavioural science and decision intelligence are related because behavioural science provides insights into human behaviour that decision-makers can use to build more accurate decision models. By understanding cognitive biases that influence decision-making, decision-makers can make more informed decisions that take into account the irrationalities of human behaviour.
Ultimately, understanding behavioural science can help decision-makers make more informed, data-driven decisions, leading to better outcomes in the long run.
Thanks for reading! Follow me to continue with the series — Vinícius A. R. Z.
I’m a Senior Data Analyst and when people ask me what do I work with, I always say “I work with decision intelligence” because I try not to limit myself to data! It’s like they say, you have to be smart as a fox… 🦊