Predictive analytics increases the overall competitiveness of individual companies and even entire sectors. Since predictive analytics is using current data sources to make scientific assessments, it can be applied to almost all industries; but, there are a few for which it is particularly beneficial.

  1. Retail

It is essential for retail outlets to stock adequate inventory to retain customer interest and loyalty. Using Big Data analytics in outlets and supply chain planning offers strategic insights on timings, stock volumes, and customer preferences, based on current sales. These insights empower the strategists to ensure the shop floor never ceases to interest the customer.

  1. Health Care

The study ‘Using Future Information to Reduce Waiting Times in the Emergency Department via Diversion,’ by Kuang Xu from Stanford Graduate School of Business and Carri W. Chan from Columbia Business School that was published in Manufacturing & Service Operations Management journal, mentions that predictive analytics can reduce emergency room wait times by 15%. Predictions about future visits can help shift managers make more refined decisions by putting adequate employees on a schedule to deal with the anticipated rush.

  1. Cybersecurity

Enterprises of all sizes have to stay abreast of cybersecurity threats and even work hard to reduce them. Hackers are always a step ahead, so reactive approaches to security may not help anymore.  Predictive analytics has provided the tools to identify vulnerabilities and be prepared for the risk by using robust, preventive measures to detect and analyze threats before they can infiltrate the systems.

As big data platforms are being incorporated into enterprises’ cybersecurity strategies, team members spend more time on strengthening networks, so are able to respond promptly to outages, before substantial damage. There have also been instances where security teams have applied data-based tools to identify risk and vulnerabilities.

  1. Manufacturing

High end, sophisticated analytics are today incorporating parameters that would earlier not be a part of a risk study-  operating environments, stress factors, and quality levels- to name a few.

In the manufacturing industry, for instance, security experts depend on predictive analytics to plan maintenance and repairs in order to not face a breakdown or downtime in production.

Predictive analytics also provide data about future sales and output a need that gives the plant managers the required insights to scale up operations to keep clients satisfied.

  1. Public Transport

As per data from the American Public Transportation Association, Americans take over 10 billion public transit trips. Transportation officials use predictive analytics to compile anonymous commuter data and analyze where the riders are most likely to disembark. Today, the authorities have updated information about the commuters that lets them plan and make the necessary adjustments.

Predictive analytics clearly allows enterprises to strategize on better planning, cost optimization, and increased efficiency.

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