In today’s hypercompetitive and fast-paced world of business, enterprises are constantly on the lookout for ways to evolve, to become better at what they do. One of the more effective ways that allows them to be able to do just that is to leverage the staggering amount of electronic data that they produce every day.
With the help of smart software solutions, enterprises and institutions can perform data analysis and data integration, allowing them to streamline their operations, discover pain points in their processes, zero in on consumer preferences, study market trends, and create better products and services. Here are some of the industries that have found a path to optimization through real-time data analysis.
Many retailers today use real-time data analytics to optimize how they run their business, especially when it comes to ensuring that their retail outlets or e-commerce stores never run out of vital goods to sell. By applying predictive analytics to the streams of data that come from all aspects of a retail business— from consumer transactions to warehouse activities—retail businesses can adjust their supply chain and product distribution to take into consideration any business-disruptive elements. These things can range from natural disasters, product shortages, inclement weather conditions, and even political events.
Real-time data replication via a database replication software can also help in this regard, especially where logistics and delivery are concerned. By keeping their data constantly updated and integrated throughout all their assets—be it their offices, outlets,ships, trucks, and so on—businesses can better keep to their target schedules, as well as proactively prepare against disruptive events.
Besides this, data analytics can also help retailers tailor online and in-store shopping experiences for their customers. By analyzing the product listings that an online shopper clicks on most frequently, for example, they can customize a webpage to display similar products that appeal directly to that shopper’s preferences, and thus maximize the chances of a buy-in. This is called targeted marketing. The same concept of analyzing customer preferences is also used when it comes to choosing which items need to go on sale or get saddled with deep discounts.
Another industry that has begun to reinvent the way it does business through big data analytics is the healthcare industry. By analyzing patient medical records, physician notes, treatment histories, hospitals and healthcare companies can now more easily tailor the way they provide healthcare to specific patients. A patient-centric, value-based paradigm of healthcare often translates to better health outcomes, reducing the burden of healthcare for patients, health insurance providers, and the state.
First, costly examinations and unneeded medical procedures will be lessened,and secondly health providers are able to figure out the most effective and affordable treatment routes for their patients, allowing them to not only improve the quality of their service but to cut down on resource wastage as well. Moreover, data analytics can also help heath providers and health payers predict and pinpoint instances of healthcare fraud, reducing the financial burden that illegal activities imposes on them.
Data analysis has also helped law enforcement agencies to better perform their crime-prevention and criminal-apprehending duties. Through automatedanalysis of all intelligence and incident reports that they gather on a daily basis, law enforcement agencies can quickly identify crime hot spots within their areas of jurisdiction.
Armed with this information, they can then formulate a better plan of action to address the incidence of crime in that area—whether to increase visible police presence or to coordinate with neighboring agencies and concerned citizens for raids, stake-outs, and proactive arrests.
Large banking and financial institutions have long used data analysis to optimize their business practices. One of the ways they do this is by analyzing their customers’ transaction histories. In doing so, not only can they further tailor their services to meet customer needs, they can also quickly identify specific friction points in their business processes.
Banks are also using data analysis in order to predict and prevent incidents of fraud, money laundering, and other financial crimes. Big data analysis can easily provide bank investigators evidence of suspicious behaviors or correspondences, which could then lead to proactive arrests.
These are only some of the huge industries today that have benefitted from leveraging the huge amounts of data that they gather and accumulate in their day-to-day operations. However, it’s not just big industries or enterprises that can do this—smaller businesses and institutions can just as easily reap the benefits of data in the optimization of their business, so long as they adopt and integrate the proper analytical and data replication solutions to their processes.