Big data analytics plays an important role in supply chain management. 97% of supply chain executives have reported how big data analytics helped them to grow their business and only 17% of any particular industry have implemented this process. This process generates higher visibility and deeper insight to the customer behaviour and demand supply scenario. It also helps to discover and manage supplier relationships more effectively. Big data help to understand customer needs and make a 360 degree analysis regarding marketing channel, segmentation and acceptability. Predictability helps to create more efficient supply chain progress (increased ~10%). It identifies supply chain risk by considering the previous demand, supply scenario almost accurately. Supply Chain Traceability and recalls are data-intensive and highly correlated to supply chain risk. The ability to quickly meet customer fulfilment is an important driver. It helps in competitive advantage across all industries which can be achieved by big data analysis.

To read, follow: http://www.computerworld.com/article/3035144/data-center/overcoming-5-major-supply-chain-challenges-with-big-data-analytics.html

Nowadays, medical sensors and data analytics are used to boost medical devices. Devices can forecast unfavorable outcomes before they occur. After analyzing large data sets, researchers can identify small changes in patient behaviors. Combining with data analytics, implantable medical sensors will allow monitoring patient health. Utilizing predictive analytics, smart sensors identify unfavorable changes in data which helps to detect medical crises very fast. Data analytics is used to influence smart devices that provide guidance to patients. These devices receive inputs from their sensor data. Predictive analytics help to make unique medicines. Smart devices use data to predict how an individual patient will respond to specific courses of action. Data analytics also help manufacturers to go beyond the general results of clinical trials to better interpret the value their devices for specific groups of patients. Read more about this article written by Battelle : http://www.healthcareitnews.com/news/big-data-difference-predictive-analytics

Data analytics are the most essential part of any organization these days and requires efficient personnel having a greater skill set in data science. But, there is not enough parity between demand and supply. According to a recent study, it was found that there is demand for computer programmers with a background in data analytics, but out of the 332,000 computer programmers in America, only 4% had the necessary skill sets. So to bridge the gap, the online training method can be a helpful process and is flexible and this in turn enhances productivity. This is a continuous process of development and helps to figure out new talent within the organization. But all these processes can only be possible if colleges and universities encourage their student to learn data science and master in those skillet.

To read, follow:  :  http://www.cio.com/article/3033887/careers-staffing/can-online-training-bridge-the-big-data-skills-gap.html

Optimization of CRM is highly correlated to the social media presence of a company. Customers frequently generate queries via social media. So there are some steps that can be followed to create a position in the customer's mind by establishing good connections between social media and CRM.

1. Right platform should be chosen.

2. Must have a dedicated human resource to handle the social media activity and patch them up with marketing team who handles CRM.

3. Instead of putting one liner FAQs, try to personally resolve critical issues in time.

4. If you have a different presence in multiple social media, then deploy time understanding the importance

5. Start listening your customers’ point of view about you and react proactively.

6. When you are segmenting your customer, you should be prepared for queries. Centralize them and solve them in real time

7. Reward your customer by discount offers, free e-books and promo offers.

To read, follow: https://www.cmscritic.com/10-steps-to-social-crm-success/

The use of analytics can bring major change in the hospitality sector. It is important for hoteliers to understand the preference of the guests, purchase behavior and profitability in order to increase the brand loyalty. By using analytics, it is easier to do segmentation according to booking trends, behavior and other constituents. To know more about the use of analytics in the hospitality sector, read the following article by Bernard Marr (Contributor at Forbes)-:

http://www.forbes.com/sites/bernardmarr/2016/01/26/how-big-data-and-analytics-changing-hotels-and-the-hospitality-industry/2/#7135d10f19b6

Data scientists have categorized this new era of data with "four Vs". They are volume of the data, variety of the data sets, velocity of analysis of data and veracity of data quality. Nowadays, companies are turning to external Big Data for answers. Organizations want to distinguish which external factors will influence the sales and demand of a particular product in the future. The answers they get from the above questions, is setting the trend for three distinctive predictive analytics process. They are - Predictive hypothesis testing, Closing the gap between data and delivery, shrinking the barrier between internal and external data.  With the speed of technology diversity of data continues to grow. Read more about this article written by RICH WAGNER(Author) at:

http://www.information-management.com/news/big-data-analytics/a-new-era-of-predictive-analytics-2016-trends-to-watch-10028253-1.html

A cyber - attack may happen anytime in today's world. Big data and predictive analytics help in cyber defense and convert data into actionable intelligence. Predictive indicators can identify new risks and assist in security. They can go undetected. Predictive analytics can detect these unusual data, including hidden data. By finding these unusual patterns, predictive analytics help to reduce a company's overall risk. With predictive analytics, risks are evaluated and ranked in importance. Managing the predictive analytics process requires an organization to handle the false positives and false negatives that are generated during the threat surveillance process and it cannot be too restrictive as it will block logical traffic, which can lead to a reduction in profit or customer service. It depends on how a person is using it to get the best results. Read more at:

http://www.information-management.com/news/big-data-analytics/using-predictive-analytics-to-identify-cyber-security-risks-10028270-1.html

Investment in shares requires analysis of huge historical data. Analysis is the primary phase and it forecasts the future investment process. Broking house plays a clinical role in this context and charges a percentage of hike in shares. But these days such information is frequently available in different websites and are updated on a regular basis. The usage of technology for predictive analysis is hugely correlated with big data. These are limited to institutional buyers. The automation in predictive analysis requires a huge precision which is cost effective, but its implementation could be a game changer.

To read, follow: http://www.thehindubusinessline.com/markets/stock-markets/big-data-robo-analytics-to-drive-next-phase-of-growth/article8249330.ece

Any decision pertaining to designing products, environments and brand experience is closely connected to the use of colour because it depends on the buying behaviour of customers, brand perception, strategic differentiation, and user experience. But availability of information related to colour perception is limited. Organizations are using big data to analyse colour preference and perception which contains over a 100 years of data. They divided their study into four categories regarding colour data, analytic and insight:

1. Colour competitive intelligence is relevant for aggressive in brand competition.

2. Colour legal intelligence helps to identify the colour norms available to different countries.

3. Colour Research Intelligence collates colour studies that have been conducted over the past century, world-wide, about the industry and product segments.

4. Colour listening intelligence signifies how much buzz about a particular colour is popular in the market.

These all studies benefit other companies by creating their own colour mix to attract new customers, branding and dictate consumer preference trends.

To read, follow: http://www.forbes.com/sites/michellegreenwald/2016/02/17/a-new-comprehensive-4-in-1-big-data-resource-to-aid-color-innovation/#6e729df04012

The super bowl is the place where the big corporate battle within themselves to win a commercial spot. They use real time data. The use of real time data is helping marketers to solve some of the continuing mysteries of media value and also helping brands to understand the connections between paid and earned engagement. Want to experience more, then read this article by Rob Salkowitz (contributor in Forbes)-: http://www.forbes.com/sites/robsalkowitz/2016/02/07/whos-winning-the-super-bowl-ad-battle-live-blogging-the-big-game-with-real-time-data/#208c134c44c6

Design thinking is at the top of mind for business teams of big giants as well as startups. The traditional "If you build it, they will come," mentality has been taken from techniques like customer journey mapping and empathy-driven prototyping. Many companies are unsure how to implement it to improve their business - especially in areas like data analytics and decision sciences. The first step is to ask:  for whom are we designing and what is the problem they are experiencing? The second: to what end are we modeling the design - to boost consumption and engagement, improve performance, or to achieve scale? These same needs to be asked at the outset of any analytics effort. Here are five simple steps that are key to infusing analytics with a designer mindset.

1) Create a design framework that allows you to fail fast.

2) Empathize with your customer to impart emotion into your product.

3) Focus on problem-solving that allows for rapid experimentation.

4) Employ methods to inspire creative brainstorming across teams.

5) To design the killer solution, let nature be your guide.  

To read more visit at:  http://www.datanami.com/2016/02/16/what-design-thinking-means-for-data-analytics/

Doctor or healthcare professionals treat us according to recent scientific arrangement. EBM (Evidence Based Medicine) is the orthodox standard for the provision of healthcare. But, in the era of big data, it is about to change. Clinical trials work compares the new treatment to other treatments by separating random patients into different groups. There is a risk of methodological flaws and the small populations used. By mining the practice-based clinical data, i.e. actual patient records for information on who has what condition and what treatments are turning for better treatment of the individual. Almost 80% of medical information about patients forms of unstructured data. For better care of individuals and to understand about the health of the population, we need to be able to mine unstructured data. So before analyzing any data, the first thing is to extract the data from these diverse sources. Then turn that information into something that computers can break down. The data can then be dissected at an individual level to create a patient data model. Data theft can be scaled down by encrypting patient data. Read more about it in the article written by Bernard Marr (contributor) :  http://www.forbes.com/sites/bernardmarr/2016/02/16/how-big-data-is-transforming-medicine/#28d063381cd4

Companies which have process manufacturing as an activity to do on their list, face potential challenges with ERP. Process manufacturers need highly customized ERP packages as every process has its own special features. If the ERP package that you choose doesn't have all the functionalities to handle your needs and wants, then it can result in an expensive customization which will result in a significant hike in your costs. Traceability is a very important aspect as well. Manufacturing ERP systems need to be robust for effective tracking. Documentation is another important factor which should be kept in mind. In addition to this, process manufacturing ERP must have features for quality assurance and quality management. Read the complete article at - http://it.toolbox.com/blogs/inside-erp/process-manufacturing-erp-71400

For every start-up, customer engagement and promoting their brand is a big challenge. So if your business is in the start-up stage, integration of social media in your CRM will give you enormous opportunities to grow your business.

Social media in CRM aka Social CRM on cloud gives an extra edge to your business as engaging with your target audience will be limitless and creating brand communities which helps in monitoring and analysing customer’s demands will be very easy.

Here are the 5 benefits of having social CRM in your start-up -:

1.      Discover opportunities to engage with customers

2.      Monitor your notifications

3.      Real time updates in your customer contact records

4.      Integrate your marketing software and your contact records

5.      Share customer messages

To read visit on -: http://www.intellika.in/blogs/post/5-benefits-of-social-crm-for-startups

Today world is changing at a rapid speed. Technology is playing an important role. Agriculture technology is also advancing and promises to unleash its productivity. The combination of advanced mathematics, automation, advancements in sensor systems and next-generation plant breeding are setting the stage for the next Green Revolution, which is needed to ensure a better future. Next-generation farms are putting science and technology to work towards delivering a step change in yields and growing more from less. Here are the four most exciting developments in 2016.

1) The Mathematics revolution.

2) The Sensing Revolution.

3) Putting it together with automation.

4) Next generation plant breeding of corn.

Read more at: http://www.forbes.com/sites/gmoanswers/2016/01/26/four-technologies-that-will-usher-next-generation-farming/#3cfe147b69f5

Cloud marketing is influencing many industries including marketing. The banner ad and pop up you see online is stored in the cloud. But, marketing cloud also needs to upgrade itself in a few areas. They are – Security, Customer Satisfaction, New Technology, and many more. Read more at - http://it.toolbox.com/blogs/tech-advances-business/5-aspects-of-the-marketing-cloud-that-need-foolproofing-71413

The goal of marketing technology is to deliver "the right message to the right customer or audience at the right time," says Jake Sorofman, research vice president at Gartner. Marketing technology has evolved into a combination of complex software and data. Tools which are used today with marketing technology also create new complexities and difficulties. It can't solve the ad- waste dilemma. This means that the marketing team wastes billions of dollars on digital ads that no one sees. Marketing tech can't tell about the impact an advertisement had about the brand to the viewer. Read the complete article here: http://www.cio.com/article/3024934/marketing/how-and-why-marketing-tech-fails-to-deliver-on-its-promise.html

CRM software market is growing at an incredible rate. It is estimated that by 2017, the market will grow more than a $36 billion. So, this CRM market will see many providers who will want to improve the software's capabilities on a regular basis, and in turn, the organizations will keep pace with the industry trends. Read more at: http://it.toolbox.com/blogs/insidecrm/why-worry-about-crm-trends-71397

Some volunteers of a nonprofit volunteer outfit are going door to door in Odisha. They are collecting data about schools, health facilities, Panchayat, roads, etc. These data points are being analyzed by a not-for-profit development organization which will use this data and will draft a development plan for Member of Parliament. The idea is to filter the data into meaningful information which will help in reducing the gap between real needs and actions. Some big consultancies are also working together with politicians for the same purpose. Data analytics tools are used to determine demographic profiles and socioeconomic aims. Read the full article here: http://articles.economictimes.indiatimes.com/2016-02-02/news/70283182_1_data-analytics-tools-prime-minister-narendra-modi

With the expansion of Analytics, each sector is trying to utilize it to the fullest. By implementing analytics, the managers are able to identify the behaviors that lead to positive outcomes and also identify the problematic areas. Therefore, organizations must develop the best practices that can streamline the work. By applying this to the calls, customers can analyze the customer - agent interactions. So they can identify the most important factors and can even reduce the volume in maximum traffic hours. The advance speech analytics software not only means, evaluates and presents audio and textual data, but also collects information regarding reasons for calls, emotional nuances in a customer's voice and how well agents are addressing a customer's needs and expectations. This even helps them keep a check on their marketing strategies so that it can be altered for the better. These generate very meaningful insights for why a customer needs to contact the support centers and thus exposing the root cause. So this helps in decreasing the average call time and monitoring the resources spent. Read more at : http://customerthink.com/top-5-benefits-of-call-center-speech-analytics-why-your-call-centers-success-depends-on-speech-analytics-solutions/