How Data-driven Trend Intelligence Makes a Business Future-ready

Data-driven decision is the new master-key for unlocking profitable business avenues. But what are the right steps to capitalize on big data potentials? Let’s find out!

Big data has become the bread and butter for most businesses by now. The obvious answer to gain a competitive edge is data-driven intelligence. So how do new trends influence business activities in organizations and what are its long-term impacts? Let’s explore!

What is Data-driven Trend Intelligence?

Data-driven trend intelligence is a technique where business owners gain cognizance about ever-evolving market trends like falling raw materials prices, increase in dollar rates and new geo-politics activities with the help of software & technology platforms. This type of trend intelligence has been helping business owners to map long-term implications of the COVID-19 pandemic and its effects to overcome supply chain disruptions, logistics availability and product delivery.

How Trend Intelligence Makes a Business Future-ready?

Trend intelligence helps business organizations to accurately predict, monitor and act on possible future trends that tend to influence consumer behaviors. For instance, the ongoing veganism trend in the food industry is compelling manufacturers to innovate in ready-to-eat products using plant-based foods.

How AI and Big Data Makes Trend Intelligence More Lucrative for Profits

Since artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions, AI holds potentials for trend tracking to help market players gain a competitive advantage. Since data is the new oil and has surpassed the valuation of oil revenue in the world, big data helps to provide a wealth of insights that help to simplify business processes as per future trends.

Opportunities and Challenges of Data-driven Trend Intelligence

Though data science plays a monumental role in allotting financial budgets for long-term business activities, its challenges include inaccurate information since real-time changes in trends affect machine learning (ML) algorithms. To overcome these challenges, business organizations are now analyzing broad sets of data with many inputs to find key insights in real-time. Continuous troubleshooting in ML algorithms is another strategy to gauge accurate market trends. Data science experts are pulling up dashboards to acquire key information from broad data sets.

Thus, data-driven trend intelligence is paving the roadmap for intelligence as a service model that enables C-level executives and managers to excel in organizational leadership & generate high return on investments (ROIs).

Artificial Intelligence to play a role in Preventive Healthcare

For patients of diabetes and heart disease, an important part of the treatment is staying healthy outside the hospital. And, not to return to the doctor’s clinic with further complications. Nonetheless, there involves probability factor to reach out to the most vulnerable patients at the time of need than clinical assessments.

Artificial intelligence displays the potential to play a role here. The role to help clinicians handle such problems. It does so by examining large datasets to spot patients that would benefit most from preventive measures.

Nonetheless, in order to leverage artificial intelligence, this requires healthcare organizations to employ their own data scientists. Alternately, healthcare organizations can settle for one-size fits all AI solutions that are not optimized for all patients.

New Analytics Solution suitable for Raw Patient Data

To address this, the startup is playing a role. It is helping healthcare organizations leverage the power of AI with flexible analytics solution. Employing this solution, it enables healthcare organizations quickly feed their data into machine learning models and obtain actionable results.

Importantly, the platform is being used to help determine the patients that have higher probability to miss appointments, benefit from routine check-ups, acquire infections like sepsis, and more.

Furthermore, the platform finds use for health insurers as well. Health insurance companies are using ClosedLoop for population-level predictions. Such predictions are around things such as patient readmissions and the start or progression of chronic diseases.

“ClosedLoop developed a healthcare data science platform to be suitable for any kind of data that organizations have, build models specific to patients and deploy the platform,” stated the CTO of ClosedLoop.

The platform developed by ClosedLoop is of immense value. It provides the ability to use somebody’s raw data in the way it is in their system and to convert it into a model that can be readily used.

Artificial Intelligence holds Promise to Mitigate Healthcare Revenue Cycle Waste

Following patient care, artificial intelligence is now seeking opportunities for improvements of administrative processes in the healthcare sector. With maturation of the technology and its increasing viability, revenue cycle management is one area wherein artificial intelligence is evident.

Meanwhile, several current revenue cycle processes result in lot of friction and waste. According to an industry data cited at a HIMSS20 digital presentation, inefficient revenue cycle practices in the healthcare system can result in administrative waste amounting to as much as US$200 billion. The waste generated in the system between providers and payers is due to lot of inefficiency, lack of transparency, inaccurate documentation and coding, and lack of awareness regarding certain steps on both sides.

According to statistics provided by technology enterprise Optum360, hiring data illustrates administrative spending has increased. While hiring for physicians has increased since 1970, but administrative hires have increased by 3,000% since then.

AI to translate into Positive ROI for Administrative Applications, says industry statistics

Owing to this, the sentiment of healthcare professionals towards the technology to mitigate waste is positive. According to data provided by Optum, 97% of healthcare personnel trust AI to handle clinical or administrative applications, whereas 85% are currently developing or implementing some kind of AI strategy. About 55% healthcare personnel, which is more than half, expect to achieve positive ROI in less than three years.

Organizations on an average are investing US$39.7 million on implementation of AI over the next five years. At present, almost one-third of health plans, employers, and providers are automating processes such as customer service or administrative tasks, and almost 56% of health plans are using technology to combat waste, fraud, and abuse. Furthermore, the technology finds use y thirty-nine of providers to personalize care recommendations.