Business Analytics 101: This article captures the importance of analytics and data-driven decision-making. During the earlier times many companies made decisions based on opinions rather than data analysis. Opinion-based decision making can be very risky and often lead to incorrect decisions. One of the primary objectives of business analytics is to improve the quality of decision making using data analysis.
Through great strides in technology and an increase in available data, harnessing the power of analytics in business is easier than ever. And as more companies look to data for solutions, business analytics professionals fill the growing need for data expertise.
Data is what you need to do analytics, Information is what you need to do business – John Owen
Why Analytics?
Given the scale of operations of the modern companies, it is almost impossible to manage them effectively through analytics. Many companies use analytics as a competitive strategy and many more are likely to follow. Analytics can be used for various purposes and are not only limited to the imaginations of the human mind.
- Forecasting demands of products,
- Identifying fraudulent transactions in a financial transaction,
- Predicting delivery time or what the customer is likely to buy in the future based on the recommendation systems.
The best use of analytics for decision making still depends on the humans to take the right decision in adopting the correct model based on which the analytics is performed, and the decision is taken. A typical example of human decision making is given below for you to ponder upon.
Monty Hall problem
A great example for human’s inability to take decisions is the famous Monty Hall problem in which the contestants of a game show are shown three doors.
Behind one of the doors is an expensive item (such as a car or jewellery); while the other two doors contain inexpensive items (such as goats). The contestant is asked to choose one of the doors.
Assume that the contestant chooses door 1: The game host would then open one of the remaining two doors. Assume that the game host opens door 2, which has a goat behind it. Now the contestant is given a chance to change his initial choice (from door 1 to door 3).
The problem is whether or not the contestant should change his/her initial choice. Note that the contestant is given and option to switch door irrespective of the item behind his/her original choice of door. The problem is based on a famous television show “Let’s make a deal” hosted by Monty Hall in the 60s & 70s.
In this problem, the contestant – decision maker -has two choices; Either change initial choice or stick to initial choice. Think about what you would do? If after you made the choice and the door that opened had a goat, would your choice change? If you did not change your initial choice, you might want to rethink as the probability of winning is higher when the initial choice is changed from 1/3rd to 2/3rd.
| Item behind door 1 | Item behind Door 2 | Item behind Door 3 | Result if stayed with Door #1 | Result if the door is changed |
| Car | Goat | Goat | Car | Goat |
| Goat | Car | Goat | Goat | Car |
| Goat | Goat | Car | Goat | Car |
| Probability of winning | 1/3 | 2/3 | ||
Conclusion: Data analytics is just as useful as you are. If you are not good at decision making, then use of data analytics tool isn’t going to serve the purpose for you. Data-driven decision-making through analytics is not just an option anymore, it is an essential capability that every organization must possess these days.
Read about how data analytics works in Internal Audit here.
Very insightful
Interesting to know about “the Monty Hall Problem” & the best conclusion as well. Looking forward more such posts on DA. Great Learning.