The intelligence of big data analytics has reached the day to day of companies. Big Data is already part of our history.
Although many companies still do not feel ready to allow Big Data to transform their business models, hiding behind the excuse that data analysis and Machine Learning algorithms are not yet delivering measurable results, many organizations from different sectors of the market have already learned how to increase their revenues and decrease their expenses with the tools of this new intelligence.
Today, Big Data is already considered one of the fundamental pillars of the digital transformation of companies, helping to retain and win new customers, as well as plan and optimize their processes. Big data and data analysis can help – and do a lot – companies to understand and monitor the habits and preferences of their consumers, identifying opportunities for innovation and marketing and capturing market fluctuations that can be harmful to their business, preparing themselves, thus, to reverse potential crises.
Predictive analysis, as they are called, speaks less about the market in which companies operate today and more about what it will look like tomorrow, showing how organizations can benefit from these changes. We cannot ignore the fact that this capacity for adaptation is fundamental for the perception, before the competition, of possible changes and trends, becoming the biggest differential in the volatile world in which we live today. See how 4 companies are transforming their results with the use of Big Data!
1. Walgreens brings Big Data Analytics to health offices and clinics
Walgreens is today the largest pharmacy chain in the United States, providing health and wellness products and services to nearly 6 million Americans a day. A few years ago, the company decided to combine advanced big data analytics with results-focused interventions, analyzing 8.3 billion medical event data to bring analytical insights to its health programs. The objective was to implement a patient assessment tool that could be used to improve care programs.
Risk assessment scales are essential tools for medical teams, both home visits and medical clinics can prioritize consultations, treatments and medications based on each patient’s family and life history. The result? The teams can better assess their patients and being able to give recommendations. Healthier patients medicated and treated early, less sick in hospitals, less spending on medications and consultations.
2. McDonald’s: how to find your customers’ favourite snack?
McDonald’s, the largest fast-food restaurant chain in the world, plunged into the world of Big Data once and for all. Although data analysis and artificial intelligence were already being widely used by the chain to optimize its processes. But the turning point was when technology came in to bring concrete results to the company. Every fast-food chain has as main objective to offer products at the lowest price and increase its profitability. For this to be possible, McDonald’s would need to understand the preferences of its consumers and translate that data into new trends.
This data generates very important information about the business, such as when and where customers consume their snacks, how often they use the drive-thru and what they consume. As a result, started testing important changes to their menu. In Canada, restaurants already have digital menus that can change according to the climate, increasing sales by about 3.5%. Another change was to offer breakfast, previously available only until 11 am, throughout the day, creating the All-Day Breakfast. This change alone impacted 3.7% of sales in the USA.
3. United Parcel Service: technology in search of faster and faster deliveries
The American United Parcel Service, also known as UPS, is one of the giants in the logistics market. They are transforming their businesses through Big Data to improve even more the company’s agile logistics network. The goal is to optimize the routes used by the company by sending messages to its drivers through navigation device. In addition, the system should automatically optimize delivery routes. The company is also gathering information to understand what type of distribution solutions can work best in each different region. With 55,000 drivers, the changes will impact the reduction of 100 million miles travelled during its deliveries, in addition to 100,000 metric tons of carbon emissions. Efficiency results not only in the business but also in the company’s sustainability projects.
4. Merck: vaccine optimization with Big Data analysis
Let’s see the use of Big Data intelligence by the giant Merck. The manufacturer specializes in the production of vaccines, essential products to ensure the health of people across the globe. However, vaccines are extremely sensitive products to be produced, requiring precise conditions throughout the process. Otherwise, the materials must be discarded, directly impacting the yield of their formulas. Imagine that, during the production process, the discarded material can be worth millions of dollars in lost revenue!
With Big Data, they map each batch of vaccines and observe the data patterns, verifying the yield of each production. Each piece of data was collected and analyzed. As a result, after three months, 15 billion calculations and more than 5.5 million batch-to-batch comparisons, Merck made a major discovery: certain characteristics in the vaccine production phase were closely linked to the final yield. Insight is very important for the mass production of vaccines, which changed the performance of Merck’s formulas.
Why more and more businesses are focusing on Data Analytics?
To answer this question, Cupid Chan former CTO of Index Analytics and currently the Managing Partner of 4C Decision said, “Data analysis can help companies better understand their customers, evaluate their ad campaigns, personalize content, create content strategies and develop products. Ultimately, businesses can use data analytics to boost business performance and improve their bottom line”.