Big Data Analytics: Necessary but Not Sufficient

Posted by John Mack on Thu, Jun 30, 2016

Part 2 of 4: Grow Revenue from Your Existing Customers: How Big Data Analytics Can Help

This post is the second in a four-part series. The first installment, “Go Beyond the Symptoms: How to Overcome Revenue Growth Challenges,” discussed the key signs of slowing growth and the first steps organizations can take to turn it around. Here, we’ll discuss three new ways in which companies can use Big Data analytics to improve a business’ ability to consistently improve revenue growth from their existing customers.

Big Data analytics in 2016 occupies roughly the same spot in the corporate consciousness as did the concept of cloud computing in 2008. By now, every world-class company that generates vast quantities of data has recognized that this data has exceptionally high value as an asset. These companies have made technology investments accordingly, procuring software solutions to organize, analyze, and manage the data, storage solutions (cloud or on-premise) to facilitate access to and distribution of the data, and often also professional services to enable and operate this infrastructure.

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Topics: Big Data, Signal Hub Technologies, Analytics

5 Obstacles to Achieving Scalable Data Science, and How to Overcome Them

Posted by Anatoli Olkhovets on Wed, Jun 22, 2016

The struggle is real — and it’s becoming increasingly apparent to companies that have dipped their toes into popular data science tools. As enterprises test the limits of their new tools, old technology, and data scientists’ time, their infrastructure is starting to show its cracks. Read on to see how these issues are revealing themselves — and more importantly — gather some ideas on what to do about it.

Over the past year, I have been averaging 2–3 customer meetings per week, resulting in over 100 customer and partner conversations around Big Data, analytics, and data science for the enterprise. From these conversations, I have found one key recurring theme: scale. Large enterprises no longer want to build one model quickly or implement just one use case in production. They all struggle with a large backlog of ideas. They need a way to rapidly turn these many ideas into real use cases that deliver tangible business value.

However, many companies simply can’t find a pathway to make this happen. Across my numerous conversations, I noticed very similar patterns and identified 5 common obstacles that can prevent companies from achieving scale for data science.

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Topics: Big Data, Data Science, Signal Hub Technologies, Machine Learning, Hadoop, Analytics, Spark

Grow Revenue by Using Big Data More Intelligently

Posted by John Mack on Fri, Jun 17, 2016

Part 1 of 4: Go Beyond the Symptoms: How to Overcome Revenue Growth Challenges

This post is the first in a four-part series. Here, we discuss the key signs of slowing revenue growth and the first steps organizations can take to turn it around.

It isn't hard to Identify the symptoms of declining revenue growth. Often, more than one of the classic signs will be evident at any given time. A declining growth rate or a shortfall in revenue vs. the target level are perhaps the most obvious indicators. Operating expenses growing faster than revenue can be yet another strong harbinger of revenue growth challenges, as well as a potential indicator of a cost structure that is no longer aligned with the business’ sales capabilities. While they require more research and calculation to derive, declining market share or shrinking revenue growth rates vs. competitors are other telltale signs.

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Topics: Big Data, Signal Hub Technologies, Marketing

Customer Aspirational Value – A First Principle for Business

Posted by Georges Smine on Fri, Jun 10, 2016

Conventional wisdom leads you to think that when a company knows its customers, it ends up providing better service, increasing loyalty, and generating more sales. Right?

Yes, but the truth lies between what is desired and what is achieved.

Opera Solutions has been helping Fortune 500 companies apply Big Data analytics to address challenges in operations, sales, and marketing, among other business functions. In today’s business climate, one of the most relevant challenges is how businesses can most effectively grow revenues from their existing customers. We have chosen this to be the topic of our next webinar.

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Topics: Signal Hub Technologies, Marketing

5 Key Big Data Trends to Watch

Posted by John Mack on Tue, Feb 23, 2016

As a company that works intensively with Fortune 500 companies, our finger is firmly on the pulse of the latest needs, wants, and aspirations of the world’s biggest Big Data drivers. Here are five key trends we’re seeing for 2016 and beyond.

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Topics: Big Data, Machine Learning

5 Things to Consider When Buying a Big Data Solution

Posted by Abhishek Rathi on Thu, Dec 17, 2015

Any time you sign onto a long-term agreement for your company, you're making a major commitment. These five critical considerations should make the decision-making process a little easier.

Buying Big Data software and services is a Big Deal — regardless of the size of your organization. The category is ambiguous: There are too many providers offering too many flavors of Big Data software and services, and implementing the wrong or inadequate tools and technologies can derail your efforts. In addition, technology and business needs are evolving quickly, so companies need a solution that is agile and doesn’t become obsolete in five years. In the same vein, once a certain path is chosen and a significant investment is made, companies may be stuck with that decision for years to come. And finally, while your organization likely knows it needs a Big Data solution, those who make the purchasing decisions may not have a full understanding of all the disciplines involved in deploying one to fully exploit its benefit and transform your business.

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CMS Chooses Opera Solutions for Analytics — Again

Posted by Sarah Anderson on Tue, Nov 17, 2015

Once again, we are pleased to announce that CMS, the Centers for Medicare and Medicaid Services, has chosen Opera Solutions for a three-year, $28 million contract that will enable Opera Solutions to provide the operational analytics that drive the Health Insurance Marketplaces of the Affordable Care Act. In this role, Opera Solutions will continue to build on the strong foundation it has built in the first three years of this relationship, adding more advanced analytics and ensuring data integrity across the widespread, diverse data environment within CMS.

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Topics: Healthcare, Press Releases

The Key to Making Big Data Valuable: Make It Personal

Posted by Laks Srinivasan on Mon, Oct 26, 2015

Most companies realize they are sitting on a treasure trove of customer data that has the potential to deliver tremendous business benefits; however, most also have no idea how to realize those benefits. How can companies use their data to bring in more customers, increase the amount they spend, and make them more loyal? How can companies use data to turn unhappy customers into loyal champions of the brand? And perhaps most important, how can companies use that data to drive a significant increase in revenue?  

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Topics: Big Data, Data Science, Marketing

Analytics in Healthcare: How to Survive the ICD-10 Transition

Posted by Sarah Anderson on Thu, Oct 01, 2015

Is now the right time to add machine-learning analytics into your charge-capture management system?

ICD-10 is here and chances are, as a provider, you’re as ready for it as you can be, knowing there could be some hiccups and impact on revenues. Most predict that the impact will be confined to inpatient revenues, driven by significant adjustment issues in grouper methodologies. But what if the impact extends well beyond that, to outpatient revenues?

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Topics: Healthcare, Machine Learning

How Natural Language Processing Can Improve Spend Analytics

Posted by Sushil Sharma on Wed, Aug 19, 2015

Have you ever wondered how Google or Hotmail finds and blocks a single spam email out of billions of emails? Or how companies analyze tweets for customer sentiment? Or how questionable content is identified on a Website? Natural language processing (NLP) does this in real time — and it can be used for a lot more than spam filtering.

When it comes to analyzing a company's spend, the old adage "what gets measured gets managed" is definitely true. However, measuring an enterprise's spend when you have free-text fields, or fields where employees can type in any response they want, can be an insurmountable task. Rarely do two people use the same words and phrases to describe the same thing. Even spelling varies. These variations make measuring how much is being spent on a given category or with a given vendor a very common challenge.

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Topics: Big Data, Supply Chain & Operations