SigmaWay Blog

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

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/

According to Vincent Weafer (Senior Vice President of Intel Security), analytical capabilities will help you to be ahead of your competitors. Predictive Analytics help you to analyze the future trends more accurately and help you to realize your threats and opportunities which affects budget, purchase and staffing decisions. For prediction, a large amount of data is required from a range of activities which organizations perform, historical events and third party intelligence and to make predictive analytics more effective, you need to build foundational abilities like real-time hunting, prioritization and scoping of security incidents in their environment. You need to analyze your stakeholders for blocking decisions. Read more at: http://www.darkreading.com/partner-perspectives/intel/predictive-analytics-the-future-is-now/a/d-id/1319956

 According to Dave Blanchard (Industryweek), customer’s demands for lower delivered costs are seen to be a big challenge. But, by using predictive analysis, we can identify patterns and predict future events. An organization using predictive analysis can make better decisions. George Prest (CEO of MHI) says that companies that continue to use traditional supply chain models will struggle in the future.  According to the MHI/Deloitte study, it was found that less than 25% of companies have adopted predictive analytics though that number is expected to climb to 70% over the next three to five years.

 Read more at: http://www.industryweek.com/supply-chain/predictive-analytics-let-manufacturers-see-more-clearly-their-supply-chains

According to Jayakanthan Chidambaram (Associate Technical Architect, Aspire Systems), sustaining in the market with a persistent growth is considered to be one of the greatest challenges in any industry. Companies are focusing their investments on business intelligence technologies in order to predict behavior and consequences from patterns found in large volumes of data. Predictive analytics transforms data into important and useful information. Data analysis can be broadly categorized into 4 types - Descriptive, Simple Statistical Summations, Prescriptive and Predictive. Personalization based on location, behavior and preferences are driving how organizations should cater to customer needs and grow their business. When organizations adopted Business Intelligence, they took the first step towards understanding what is currently happening in their business. Now is the time to take that maturity to the next level where the need is not only to know what is happening but also be able to predict what is about to happen. Read more at: http://www.informationweek.in/informationweek/perspective/298003/predictive-analytics-future-business-intelligence?utm_source=referrence_article

Big data generated by drones is useful in every sector including monitoring data of animal cruelty on farms and surveillance data from military drones. The drones' usage needs a revolution in big data cloud services. However, flying a drone and taking pictures is the first step in data collection process. Since software to reason directly from video feeds is still in a research phase, drone data handling needs to be improved. The use of a cloud-based in-memory computing platform can enhance analytics, processes, and predictive capabilities. Amazon recently proposed to increase sales and revenue by providing the delivery of food using drones. By gathering data on a large scale, service providers will be able to process unique levels of details and turn it into usable information. To know more, go through Abhishek Sharma (author of InfoQ)'s article: http://www.infoq.com/news/2014/09/drone-data-big-data-analytics

There is no privacy in the era of big data. Personal data is collected and traded and there are few ways to control it. "We're being monetized in essence. We are being mobilized as products with inducement of the services of we use such as Facebook and Twitter" says Rob Livingstone, a fellow of the University of Technology and the Head of a Business Advisory Firm. However, major problem that regulators are facing is - how they can regulate the collection, storage and trading of personal data on the internet, when all of these activities, and corporations, operate across multiple continents and jurisdictions. Read more at: http://analytics.theiegroup.com/article/53a4371c3723a8398400014e/Little-Privacy-In-The-Age-Of-Big-Data

20-30% of the business decisions really need the use of advanced techniques like predictive analytics.   70-80% of marketing decisions can be judiciously carried with simple analytics techniques. A CMO broadly expects 3 key outcomes for his business:

• Bring more “future” customers in the most cost-effective manner.

• Convert those who come to the door into customers.

• Maintain the current customers “buying.”

Predictive Analytics need advanced skills and constant maintenance. A product manager or an operations manager equipped with the right “Data to Decisions” framework and easy access to data can optimize 80% of their daily workflow on their own, without having to depend on little and costly analytics resources. For 20% of decisions, where the potential ROI justifies the use of advanced techniques, they can work with their analytics counterpart. In summary, a smart CMO knows that a marketing team equipped with a “Data to Decisions” framework and easy access to data without the company of a data science team would emerge much better than a marketing team lacking data skills supported by a large data science team.  Read more at: 

http://www.forbes.com/sites/piyankajain/2013/05/26/the-8020-rule-of-analytics-every-cmo-should-know/

Social media is an ever changing scenario where social media marketers are increasingly using predictive analysis to ensure longevity. Various brands are using predictive analysis technologies to trawl through social media chatter to identify upcoming trends. It will also ensure that your brand be one of the first few to take advantage of the trend and gain maximum exposure. Your social media campaigns will also be much more refined compared to those of brands that don’t use predictive analysis. With predictive analysis, your brand will be able to pick out the right news, items, etc. that could become the next big thing on social media landscape, giving you ample time to prepare. Now smart brands are realizing that predictive analysis can be used in social media marketing to understand what consumers are looking for. Predictive analysis tools ensure that brands understand consumer behavior on social media.

Read more about this article at:

http://www.simafore.com/blog/bid/205332/How-Predictive-Analytics-Can-Boost-Your-Social-Media-Campaigns