So, in this post, I will cover the story of the Coca-Cola company and how they have leveraged technology to stand at the top.
Thirty Years ago, Coca-Cola Announced that it would discontinue its beloved Coca-Cola in favor of a new product that millions derisively called “New Coke.” and they stated that this new Coke will Have a smoother, sweeter taste similar to diet coke but sweetened with corn syrup.
Based on Market researchers and Individual Opinions The New coke is going to be a big hit but How ever only 13 % people only liked New Coke after the production, This experiment was not accepted by the Consumers.
Coke drinkers launched grassroots campaigns across the country to force Coca-Cola to bring back the original coke, which compelled the company to work on it.
Now lets see where the company go wrong
Well the fact is Company Poured its Money, Time and skills into consumer research on its new Launch and could not measure the emotional attachment to original Coca-Cola felt by so many people and finally Company failed to take the right business decisions.
Then what is the right Business decisions?
The Right Business decision helps to Achieve :
- Achieve High revenue
- Reduce Expenses
- Meet Customer Expectations
These Business Decisions Involves a series of methods & techniques to measure performance and improve them. This is Called Business Analytics.
Business Analytics is a Scientific Process That transforms data into insights that are used for fact-based or data-driven decision making. It uses Tools to create reports,graphs,optimization,data mining and simulation.
Types of Business Analytics: 
- Descriptive Analytics
Descriptive analytics looks at data statistically to tell you what happened in the past. Descriptive analytics helps a business understand how it is performing by providing context to help stakeholders interpret information. This can be in the form of Data Visualization like graphs, charts ,reports and dashboards.
How can descriptive analytics help in the real world? In a healthcare setting, for instance, say that an unusually high number of people are admitted to the emergency room in a short period of time. Descriptive analytics tells you that this is happening and provides real-time data with all the corresponding statistics (date of occurrence, volume, patient details, etc.).
2. Predictive analytics
This Takes historical data and feeds it into a Machine learning model that considers key trends and patterns. The model is then applied to current data to predict what will happen next.
Back to our hospital example, predictive analytics may forecast a surge in patients admitted in the next several weeks. Based on patterns in the data, the illness is spreading at a rapid rate.
3.Prescriptive analytics
This takes predictive data to the next level. Now that you have an idea of what will likely happen in the future, what should you do? It suggests various courses of action and outlines what the potential implications would be for each.
Back to our hospital example: now that you know the illness is spreading, the prescriptive analytics tool may suggest that you increase the number of staff on hand to adequately treat the influx of patients.
