How Businesses Are Evolving to Accommodate Big Data

For the past decade, big data has been considered as a cutting-edge technology that’s practically required to remain competitive. With the right data and the right analytical tools, you can make far better business decisions. But how has the need for big data changed the way businesses operate? How are businesses evolving to “lean in” to big data?


In the healthcare industry, businesses and organizations are relying on big data to understand their patients better—and improve their financial management at the same time. With the help of healthcare analytics consulting, institutions throughout the United States and around the world have incorporated new devices and monitoring systems to collect data on patients. From there, they’ve been able to develop algorithms capable of predicting infections, charting recovery patterns, and detecting warning signs of serious illnesses.


In the retail sector, retailers are shifting their approach to provide customers with a much richer, more personalized experience. This is especially true of the online shopping and eCommerce world, where retailers can collect millions of data points on customers, such as how long they spend on various product pages, how often they purchase certain items, and what leads them to complete a purchase rather than abandoning a cart. Over time, brands can learn to make better personalized recommendations for what to buy next.

The physical retail space is also evolving, integrating new tools to track metrics that were previously hard (or impossible) to track, like in-store customer behavior.


Manufacturing has long been a staple of the American economy, but the way manufacturing businesses operate is changing to adapt to new data analytics technology. For starters, supervisors are starting to track more metrics related to both machine and human performance, detecting potential productivity issues proactively. Smaller devices are also being used to increase the safety of human workers—including sensors that can detect when someone is overworked, or when they’re conducting a procedure unsafely in some way.


In the finance world, big data is necessary for making better long-term financial decisions. But it’s also being used to offer more dynamic, insightful products to customers—and provide them with better overall service. For example, credit card companies are using big data to better understand the hallmarks of a fraudulent purchase, so they can take proactive action if they detect an instance of potential fraud. Other banks are offering unique apps or banking products to better serve their target demographics’ needs.

Transportation and Logistics

The existence of big data is also leading to transformation in the transportation and logistics industry, as well as supply chain management. Warehouses are now using RFID chips, digital cameras, and other technologies to track individual shipments, as well as stock levels. With the help of machine learning algorithms and automation, human manual effort is sharply reduced, and businesses can learn more about the ebb and flow of supply and demand. Long-term, better data can also optimize routing and improve the maintenance of vehicles and other equipment.

General Trends

There are big data-related effects transforming almost every sector in different ways, but what are some of the big picture trends that are affecting all industries?

  • Gathering data in more places (and in new ways). It almost goes without saying that businesses are working harder to collect data in more places and in new ways. Organization leaders are implementing new devices and monitoring systems so they can gather information about every aspect of the business.
  • Hiring or training an analytics team. Big data doesn’t mean much unless you have an experienced team who can process it. That’s why businesses are increasingly turning to analytics consulting firms, who can guide them in better processing the information they gather. Other businesses are working to hire and/or train in-house analytics teams who can process data efficiently and form accurate conclusions faster.
  • Higher efficiency/productivity. Most businesses are using big data to improve efficiency and/or productivity in at least some ways. In manufacturing, this means churning out more products, but in healthcare, this means accelerating recovery.
  • Greater personalization. Everyone needs something a little bit different. With big data, companies are able to serve those individual needs.
  • Improving adaptability. Perhaps most importantly, big data and resulting analytics are forcing businesses to become more adaptable. Business leaders know that new data could quickly alter their understanding and force them to make a change, so they have to be ready.

Big data is likely to continue pushing the world to evolve. In the coming years, we’re going to get access to even more sophisticated tools for collecting, storing, and managing data—and better algorithms for processing and interpreting those data. If we’re going to make the most efficient use of these new insights, we’ll need to transform our businesses to accommodate them.

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