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Positive Impact of Big Data on Business Decision-Making in 2022

 

 

Studies suggest that we generate approximately 2.5 quintillion bytes of data daily. Today’s businesses have access to a variety of data collected through client touch points such as websites, business apps, social network pages, mobile devices, blogs, papers, archives, and more. However, simply collecting data is insufficient to have a beneficial impact on your company. The compiled data must be analyzed and transformed into information with added value.

 

In today’s article, we will discuss the impact of big data on decision-making and even cover 2 case studies related to it. Without any further ado, let’s get started.

 

Impact of Big Data on Business Decision-Making

The following are the points that show the impact of big data on business decision-making.

 

Real-time Data to Enhance Customer Involvement and Engagement

Today, firms must provide analytics on customer service as one of the most crucial aspects. Businesses have been utilizing real-time data to provide individualized services and solutions to their clients. Kroger leverages Big Data to serve its consumers with individualized loyalty programs. The company uses the data acquired from about 770 million people to provide actionable insights that assist the brand in boosting customer loyalty and profitability. Kroger asserts that loyalty cards account for 95 percent of company sales and has recorded redemption rates of 60 percent and incremental income of over $12 billion. This has enabled the business to remain profitable despite the worldwide slump.

 

Improve Operational Performance

Currently, firms are utilizing data to automate operations, optimize selling methods, and improve their overall efficacy. For instance, Tesla’s automobiles are equipped with sensors that collect data and transfer it to the central servers for processing. This aids the corporation in enhancing the performance of its automobiles. Additionally, the firm notifies individual car owners of any repairs or maintenance that are deemed urgent. Tesla’s autopilot software is another example of Big Data that is valuable. Today, Tesla records more kilometers per day than the total miles logged by Google’s driverless car program since 2009. By storing all of this information in the cloud, it has also produced roadmaps for autonomous vehicles. These maps are believed to be one hundred times more accurate than normal navigation systems. The upgraded autopilot software assists in matching a vehicle’s speed to traffic, guiding lane changes, and performing autonomous parking without human assistance.

 

Capacity Enhancement Without Additional Investment

Can you conceive of growth in the customer base without the deployment of more resources? By analyzing real-time data, the telecommunications corporation Sprint uses Big Data analytics to reduce network failures, maximize resources, and enhance the customer experience. The brand’s delivery rate has increased by 90 percent as a result.

 

Big Data Case Studies

The following are the case studies of 2 giant companies and how big data impacted their decision-making.

 

Walmart

Walmart is the world’s largest retailer and largest firm by sales, with over 2 million workers and 200,000 stores in 28 countries. It began utilizing big data analytics even before the term “Big Data” was coined.

 

Walmart employs Data Mining to identify patterns that can be utilized to make product recommendations to the consumer based on the products that were purchased together.

 

Walmart’s customer conversion rate has increased as a result of its application of effective Data Mining. It has accelerated big data analysis to create best-in-class e-commerce solutions with the goal of delivering an exceptional customer experience.

 

Big data storage at Walmart is primarily intended to enhance the in-store shopping experience of customers.  Walmart develops big data solutions to revamp worldwide websites and create novel applications to personalize the customer’s shopping experience all while improving logistics efficiency.

 

Hadoop and NoSQL are used to give internal users access to hard data gathered from numerous sources and centralized for efficient use.

 

Uber

When it comes to transporting people and doing deliveries, Uber is the first choice for people all over the world. It uses the user’s personal information to closely monitor which parts of the service are more frequently utilized, to analyze usage trends, and to identify where its services should be more targeted.

 

Uber emphasizes the demand and the supply for its services, resulting in fluctuating costs for its services. Consequently, surge pricing is one of Uber’s principal data applications. For example, if you’re moving late to your appointment and you reserve a taxi in a crowded area, you should be prepared to pay double the normal rate.

 

On New Year’s Eve, for instance, the cost to drive one mile can range from $200 to $1,000. Short-term use of surge pricing influences the rate of demand, however, long-term use may be the determining factor in retaining or losing clients. To assess where demand is greatest, machine learning methods are considered.

 

Final Words

With this, we come to an end for today’s article. We discussed a few important impacts of big data on business decision-making, taking examples of Kroger, Tesla, and Sprint, and then we even discussed 2 case studies taking Walmart and Uber as examples. The impact of big data is massive at every stage of a business.

 

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