When we are behind the wheel; we not only keep our eyes on the road ahead of us; we also keep an eye on what is occurring in the rear-view mirror. In the same vein, every business will find this to be true. All aspects of the company's history, present, and future must be carefully examined if a healthy expansion is to occur. Business intelligence, which delves into the history and present of an organisation, and advanced analytics, which projects into the future, are the approaches that help in business analysis and growth.
Business intelligence and advanced analytics are both data-driven techniques that benefit companies of all sizes, from one-person enterprises to multinational conglomerates. The best way to understand the difference between the two, is to think about the different questions they answer. Refer the infographic below:
The above graph illustrates how BI may be used to answer the questions we've posed and the data we've requested. Advanced analytics, on the other hand, will provide us with solutions to the queries we're likely to have and the data we'll want, in the future. Let’s elaborate this further:
With the help of business intelligence, a business can:

Know what happened and why it happened.

Have access to reliable information for strategic decisions.

Implement near term measures to improve overall business.

Reduce costs.

Answer questions such as what can happen in future?

Get actionable insights for future problems.

Improve business functions and provide better return on Investment (ROI)

Apply predictive analytics to generate highly accurate predictions about future business trends.

Generate simulations on what if analysis and explore possibilities to increase stakeholder value
In practise, the distinction is not always clear, but the past-versus-future distinction serves as a rule of thumb for understanding how to apply these two strategies to your own operations
Let’s look at Starbucks to understand in detail how advanced analytics complements Business Intelligence. Through its mobile app, Starbucks launched their loyalty reward program that helped them to have data of more than a million customers. With this information and using BI tools, Starbucks was able to predict purchases in near future and inform customers about the individual offers via their app or email. This helped them to pull existing customers into the stores more frequently and thus increase their sales volumes and revenues.
They went one step further and applied advanced analytics to give more personalised customer experience. They did so by using the digital flywheel program, a cloud-based artificial intelligence engine that had the ability to recommend food and drink items in a precise manner. Advanced analytics helped them to identify the customer through their phone and give their preferred order, even when a customer visited a new Starbucks location. Using advanced analytics, they were able to suggest a new product to a customer based on their unique preferences and give them discounts and rewards on certain items. They went one step further and provided customers more personalised experience by corelating weather conditions with customer order patterns. For instance, a customer from Australia who enjoys lemon-based drinks would be presented with one on a hot day during his travel to London. Refer for a comprehensive analysis of starbucks.
So, in this way they were able to increase the wallet share from an individual person.
The field of Business Intelligence and Advanced Analytics is helping companies to collect and analyse historical data, ask questions, identify meaningful patterns, and understand what is likely to happen in the future. Both Business Intelligence and Advanced Analytics help in improving business decision making. When Advanced Analytics is used appropriately with Business Intelligence it aids in reaching the efficiency pinnacle and thus benefitting all the stakeholders.
While many companies are already using and have operationalized business intelligence applications within their business processes today, they have just scratched the surface of what they can accomplish with external and internal data. The predictive analytics industry is expected to expand from $12.492 billion in 2022 to $38.038 billion in 2028, according to a research report by The Insight Partners. Adopting Advance Analytics is inevitable although it would need more investment in terms of time and money by the organizations.