All posts in “predictive analytics solutions”

How can predictive analytics technology help prevent prescription drug overdose?

Combating Prescription Drug Overdose with Predictive Analytics

Over the last two decades, the U.S. has been plagued with high rates of prescription drug overdose. About 142 American citizens die every day from drug overdoses, many of which are caused by prescription medications obtained legally. Additionally, the number of opioids prescribed as of 2015 is three times as high as the number of prescriptions given out in 1999. Due to these staggering statistics, doctors and data scientists are working towards using predictive analytics to reduce the number of prescription drug overdoses.

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PA Supply Chain Inventory Management

Predictive Analytics: Reducing the Cost of Supply Chain and Inventory Management

With supply chains becoming larger and more complex, it is becoming more difficult to improve service through a reduced order-cycle time while enhancing inventory availability and reducing operating costs at the same time. Big data is revolutionizing the optimization of supply chain and inventory management by improving visibility. It is telling a compelling story that is making leaders listen. Companies that have adopted predictive analysis see up to a 50% reduction in non-performing inventory and a 25% reduction in inventory holding costs, thus freeing up working capital.

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Healthcare organizations are using predictive analytics technology for innovative solutions.

Predictive Analytics for Healthcare: How PA Technology is Used in the Health Sector

We live in an increasingly digitized world where developers are using data to help companies gain valuable insights regarding their business. This information can be leveraged to determine flaws in an organization’s structure and operations, churning out smart solutions that reduce costs and increase revenue. This is especially true in the healthcare industry, where predictive analytics (PA) plays a key role in bolstering a patient’s treatment plan and reducing out-of-pocket costs.

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How can predictive analytics help your ecommerce business?

3 Ways Predictive Analytics for eCommerce Can Help You Destroy the Competition

Predictive analytics (PA) have lots of different applications, from weather forecasting to contextual advertising, business projections and more. But there’s one area where this technology really shines, and that is the realm of ecommerce. By using predictive analytics for ecommerce, you’ll have the ability to anticipate a shopper’s wants and needs, increasing sales by a significant margin in many cases. So what are the best strategies for using predictive analytics for ecommerce? And how do you implement this technology with your existing virtual storefront?

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Predictive analytics and modeling can greatly improve your business.

Predictive Analytics and Modeling: High-Tech Fortune Telling for Your Business

In nearly all areas of life, we consider the facts and probabilities before making a decision. This is true whether you’re making important investment choices or simply wondering whether to park on-street in a metered space or inside a parking garage. So it seems rather illogicaland even downright recklessto make critical business decisions without a probable and factual basis. Yet company leaders make such determinations every day, with some choices carrying a multi-million dollar impact.

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Predictive analytics can help your app make more money.

Three Ways Predictive Analytics Can Increase App Revenue

Over the past decade, predictive analytics technology has been introduced into the mainstream. This application of predictive analytics has some useful features, including eBook recommendations based on your reading history and cutting-edge matchmaking systems that leverage societal trends and specific user information to identify potential soulmates. And while the end user may not realize a particular mobile app feature is powered by a predictive analytics engine, this technology’s impact can go a long way toward helping companies achieve their goals and guiding customers to products and solutions that actually interest them.

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predictive analytics best practices for mobile apps

Know Your Users: Predictive Analytics Best Practices

You’ve developed the perfect app concept. The market research has revealed promising data, and you’ve come up with some killer branding. You feel pretty confident going into the development processexcept when it comes to the predictive analytics engine. That’s a region of uncharted territory, as you’ve never integrated this technology into a mobile app interface before. So, how do you ensure you’re on a path toward success?

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A predictive analytics engine is the heart of your PA mobile app.

What is a Predictive Analytics Engine?

Predictive analytics (PA) are becoming more and more mainstream. According to an October 2017 projection from Stratistics MRC, the worldwide predictive analytics marketplace is expected to grow from $3.89 billion in 2016 to $14.95 billion in 2023. PA technology is already a noticeable part of everyday life, from product recommendations on Amazon to the search queries autofilled on Google and the advertisements you see while surfing the web.

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