With more than three million Americans being affected with Hepatitis C Virus (HCV) and the virus posing serious challenges to reducing the costs of disease management and control, recent research from University of Michigan is promising some hope. By making the use basic EHR data, predictive analytics algorithms can now flag the affected patients who are at high risk of developing complications from the virus. Although one-third of the HCV patients are at risk, all the patients are treated which lead to huge unnecessary healthcare spending. This is where the predictive analytics model is expected to be of great use. Further integration of the model with EHR will enable the providers to deliver more targeted treatment and a chronic disease management plan can chalked out. Read more :- http://healthitanalytics.com/news/predictive-analytics-identify-high-risk-hepatitis-c-patients

Healthcare Analytics Market has been predicted to have tremendous potential over time with low cost and improved population health. Survey report gives an increase in analytics adoption rate though many still don't use predictive modelling techniques. Data integration is required to derive analytical value which comes as a big challenge. Data Breeches and Data Security is a lesser factor than the former one since enterprises take their own data. But this factor works when external data is taken into account. People with a unique combination of statistics training, technology skills, and data knowledge are also required in large number. Also, infrastructure improvement for analytics must be done according as many healthcare decision makers. Thus analytics is getting much priority in healthcare in recent times. Read more about this article at:  http://www.cio.com/article/2904270/healthcare/healthcare-analytics-4-things-impacting-the-adoption-rate.html

Big data is now helping recruiters to develop a system of fair recruitment procedure which minimizes any kind of discrimination. Acquiring and retaining talent is an important factor when it comes to human capital management. Often it is seen that the talent of many applicants or employees go unnoticed due to certain forms of discrimination or bias.  Data driven procedures and predictive analytics are making remarkable impact in reducing such discrimination in organizations. Various attributes within the organization such as revenue contribution, pay gap, additional benefits received, risk of resigning etc.  are being monitored continuously and algorithms being are designed to pin point events when a hardworking employee is not appreciated. To know more read: http://www.huffingtonpost.com/anne-loehr/big-data-for-hr-can-predi_b_6905754.html?ir=India&adsSiteOverride=in

Predictive analytics make use of statistical or machine-learning techniques to analyze current and past facts to predict the future. Companies, by using predictive analytics, can make better and decisions at low-cost. Predictive analytics can help companies to get an idea of every possible event, thus allowing for risk management and calculating potential ROI. Using predictive analytics, companies can remove politics from the decision-making process. There is a growing awareness among companies about predictive analytics and companies that adopted this method have reported success and increased ROIs. Optimizing predictive analytics to produce better choices leads to decision modelling. Through decision modelling companies can gain insight into how predictive analytics can add value and how ROI can be measured. Read more at:https://channels.theinnovationenterprise.com/articles/making-faster-decisions-with-predictive-analytics  

With plenty of big data on its hands, the healthcare industry will be able to improve quality and patient outcomes only if it is able to extract meaningful, actionable insights from this bounty of raw information. To reap the benefits of healthcare big data analytics, organizations should bring about cultural and leadership changes to promote analytical approach to the practice of medicine. Research puts it that to achieve improvement, multiple types of data are required which can identify opportunities, measure progress, and help users understand what works. Using predictive analytics to identify high-risk patients, reducing infections and adverse cases through implementing evidence based protocols and realizing the importance of patient-centred care are some of the measures that have been reported to have made an impact. Read more at: http://healthitanalytics.com/news/healthcare-big-data-analytics-plays-critical-role-in-quality

The Internet of Things has the ability to benefit the healthcare sector vastly in the future. With EHR clinical analytics and sophisticated machine learning combining with big data from wearable, home monitors, medical devices, the Internet of Things has a huge potential for creating a productive environment of predictive analytics and prescriptive insights. Yet the concept is met not without challenges. In order to successfully reap the benefits, Jennifer Bresnick suggests development of certain core competencies, like "Developing the Mindset", "Building the health IT infrastructure" and others. Read More at: http://healthitanalytics.com/news/five-core-competencies-for-the-healthcare-internet-of-things

Predictive marketing has taken hold of enterprises today. Marketers are now making use of predictive analytics and this has given birth to predictive marketing. Predictive marketing is the application of algorithms and machine learning tools to Big Data in order to help marketers direct their efforts in the most profitable direction. Using predictive analytics tools, marketers can gauge future sales and thus formulate appropriate marketing strategies to help boost sales. Predictive analytics can be used for segmenting customers, deciphering the pattern in their behavior and thus offering them the appropriate deals. Marketing and sales are the areas where predictive analytics is most used. Read more at: http://www.cio.com/article/2934274/why-marketers-are-betting-big-on-predictive-analytics.html

Predictive Analytics is making its entry into the toolbox of small companies. Predictive Analysis is a three-part formula- analysis of past performance of situation under consideration, understanding the present and applying the past to present to predict the future. For small businesses, it can be applied for customer retention, target marketing, demand forecasting, and overall marketing. However, it is crucial to ascertain the purpose for using Predictive Analysis, as the technology may not necessarily be right for every company or for every situation in the small business sector. Read more at: http://www.smallbusinesscomputing.com/News/Marketing/can-predictive-analytics-help-your-small-business.html

The role of risk management has become more pronounced than before and companies are resorting to predictive analytics along with business insights to visualize and manage risk. Predictive analytics has gained immense popularity in the area of risk management due to its ability to identify and predict vulnerabilities, fraud, security breaches and the quality of control systems and governance, as pointed out by Rita Sallam, a research Vice President and analyst. Several firms are utilizing the advanced techniques for data extraction to manage risks. Post data gathering and visualization, firms are able to identify risks and mitigate them. Firms engaging in risk modelling produce impressive returns. Read more at: http://channels.theinnovationenterprise.com/articles/risk-visualisation-and-predictive-analytics-in-risk-management

Nowadays, daily sales are not enough to ensure longevity of a business. Markets are beginning to realize the necessity of predicting future sales. They are tapping into the business trends and applying machine learning algorithms on big data to allow businesses to maximize their efforts in the most profitable areas. By knowing ahead of time, what a customer will buy, profits can be maximized and businesses can be tailored accordingly. Predictive Analytics allows us to segment customers, find patterns in their behavior and take preemptive measures to reduce churn. Analytics can be used to identify correlations and also to find causation. It can allow us to predict an individual's purchase behavior once we understand the causation underlying a pattern. Read more at: http://www.computerworld.com/article/2934086/business-intelligence/marketers-are-betting-big-on-predictive-analytics.html

Don't ignore your supply chain risks if you love your profits, that's the advice Keith Peterson, president and CEO of Halo, is giving in his article. He talks about:

• Various supply chain risks
• The department they affect
• Its financial impacts
• Finally! Solution. 

Solution to all the problems these days is in analytics. Right software and analytics programme will increase your profit generating abilities to multiple folds. Intrigued? Follow the link at:http://smartdatacollective.com/keith-peterson/322401/solving-supply-chain-risks-infographic

Content marketers are delving more into analytics to give interesting insights about their past content. With some careful analysis of this content they are able to come up with new content to meet the needs of their customers. This exercise of tracking the past performance data is important for the content marketers in many ways. Even without analytics, most rigorous analysis and tracking of the data can give information about what to do next. The usage of analytics is giving better pay offs and is the new trend among Content marketers. With the new technologies emerging the usage of analytics tools is expected to make valuable recommendations to help identify the right strategies. 

Read more at: http://www.acrolinx.com/blog/predictive-analytics-content-marketers/

The factors currently stressed by predictive analytics, in talent management are:
1. Recognition of potential employees with a flight risk.
2. Recognition of selection factors which can predict the performance of the newly hired employees.
3. Prediction of the productivity initiation time of employee studies.
With the evolution of predictive analytics, new factors that can be expected to be focused on, in the near future include:
1. Projection of the revenue pay-off of a company’s talent programs.
2. Projection of the company’s corporate revenue and labor cost ratio.
3. Projection and comparison of performance indices of a company’s managers, teams and employees.
4. Projection of employee replacement costs.
5. Prediction of upcoming productivity issues and opportunities in the firm.
6. Prediction of the feasibility of new technology solutions.
7. Prediction of diversity bottlenecks.
To know more, visit:

http://www.ere.net/2015/03/09/the-future-of-predictive-analytics-the-next-generation-of-talent-metrics-to-consider-part-1-of-2/

Big Data and Predictive Analytics are booming and Indian recruitment agencies are jumping on board to hire more and more Data Analysts. According to a TeamLease report, the key trends that will dominate the recruitment industry over the next six months include Information Technology (IT), engineering. It is also predicted that startups will be key hirers and adoption of Recruitment Process Outsourcing (RPO) will increase. The nation is quickly realizing the importance of Big Data and Predictive Analytics and both large companies and start-ups are beginning to employ Data Analytics into their workings. The fields where Data Analytics will primarily be required include market risk analytics, facility management and mobile applications employing data sciences. Read more at: http://timesofindia.indiatimes.com/business/india-business/Big-data-and-predictive-analytics-likely-to-dominate-recruitment-TeamLease-report-says/articleshow/47588357.cms

Advanced analytics is considered as a game changer in all industries today. The benefits received from its application are tremendous. These benefits can also give the user firms – a competitive advantage- which further gives them a lead in their industry. Gavin Seewooruttun, in his article at abc.net, has listed five top applications of advanced analytics, that will prove to be a winning element for its users. They are:

• Gaining the whole customer view
• Customer micro targeting: upselling and cross selling
• Customer micro targeting: acquisition and churn management
• Customer micro targeting: value addition
• Proactive maintenance

To understand them in detail, please visit the following link:

http://www.abc.net.au/technology/articles/2015/06/04/4248646.htm

To more than a billion cricket frenzy people in the country and outside, how can cricket be made more interesting? Is there a way organizers of the game can make fans grip to it with increasing fervor? Apparently these are the key points ICC tried to focus on in this world cup. Predictive analytics is what ICC banked on to increase fan engagement. ICC Cricket World Cup 2015 was considered as the most digitally advanced in history. ICC, with support from SAP, came up with the much insightful Match Center through which statistics, comparison techniques which earlier used to be available, albeit not very advanced, to coaches of teams, and commentators were available to any owner of a smart phone with the touch of its app. ICC has increased its use of analytics lately, and will sure rely on it more than less in coming years.

To read more, follow:  http://www.financialexpress.com/article/industry/tech/when-cricket-married-predictive-analytics/58534/ 

Software as a service (SaaS) is a software licensing and delivery system in which software is licensed on a subscription basis and is centrally hosted. The advantages of the SaaS model are that it is easier to manage and that all the users have the same version of the software because updates and patching is done automatically. It grants global accessibility, making remote working models easier, which reduces costs and improves performance. The SaaS industry is now maturing beyond simple, historical financial measures towards a sophisticated operational measure in the form of a new Customer Success Metrics and Predictive Analytics.
Some of the giants in the industry are Salesforce, LinkedIn and Workday and while their services vary, the most significant one remains their cloud computing applications and platforms. Read more at: http://zeendo.com/info/top-10-software-as-a-service-saas-companies/

In business, the 'black swan' is a form of disruption, which is usually least expected by a firm. Again, 'ugly duckling' refers to the day to day disruptions, which are always expected, and the firm remains prepared for it, hence, the coining of the term.  Companies don't pay attention to these disruptions with the expectation that they will remain small and never grow up to be as big and disruptive as the 'black swan'. Majority of the companies have risk management departments who focus on regulations and the traditional risks, completely ignoring the extreme ('black swan') cases. The 'black swan' has the capability of even surpassing the traditional data analytics procedures. Hence, comes into the picture, big data and advanced analytics, which gathers newer insights even about the most uncommon and worst case scenarios that may happen in the near future. Armed with information, much beforehand, the companies can make themselves immune, even to the worst of the situations. Predictive analytics thus plays a major role in recognizing 'black swan' events, often from the data of past 'black swan' episodes. Read more at:

http://www.teradatamagazine.com/v15n02/Features/Ugly-Duckling-or-Black-Swan/

“Predictive analytics have the potential power to produce remarkable services and longer lives”

-James Heskett

All of us must have heard of uses of predictive analytics in marketing i.e. it helps to understand the needs of the customer. But, have you ever wondered that the scope of predictive analytics can be much more than that.

“Predictive analysis applied to humans is now one of the hottest concepts to come along.” It can now be used in the following situations:

• Development of concepts such as 30-minute package delivery
• Big Data analysis of target customer's and others' purchases, combined with related information to identify their needs even before they arise
• Personalized logistics

These situations seem to be amazing but turning them into reality is what that needs to be done. To know more, please read the following article by James Heskett at HBS Working Knowledge:

http://hbswk.hbs.edu/item/7527.html

Lots of experiments are going on in using predictive analytics in health care. But, only few succeed. The need is to learn from what has been done and work further.

Jennifer Bresnick, in her article on HealthITAnalytics.com, has summarized some of the ways healthcare organizations have already found success by turning big data into a strategic asset that can help providers react quickly and effectively to the ongoing challenges of quality care delivery. They are:

• Hospital quality and patient safety in the ICU
• Precision medicine, personalized care, and genomics
• Population health management, risk stratification and prevention
• Reducing preventable hospital readmissions

To know more, please visit the following link:

http://healthitanalytics.com/news/four-use-cases-for-healthcare-predictive-analytics-big-data