A recent survey states that the marketing companies will allocate their budgets to analytics. Though the top marketers report that analytics’ effect on company’s performance will remain moderate. There are two forces which couldn’t make this happen- the data used and the data analyst. This article discusses about why the organisations couldn’t realise the full potential of marketing analytics with their increased spending. Some of the main areas where the problems may arise are:
• The data challenge
• The data analyst challenge
• Algorithms and data resolving business plans
• Company’s goals
• Expanding skill boundaries

To know more visit:

https://hbr.org/2018/05/why-marketing-analytics-hasnt-lived-up-to-its-promise    

Google’s new machine learning tools has helped in mailing services. This will help people save time and energy. It will also check for typos and grammatical errors. The smart compose feature doesn’t write the full texts but suggests new texts after analysing the existing messages. Gmail’s text suggestions appear in lighter grey and if we wish to use them then we can press the tab button on the keypad. The smart compose tool can speed up the message creation and reduce errors simultaneously. When we use Google’s products, we are sharing our information with Google.

To know more visit:

https://www.nytimes.com/2018/06/01/technology/personaltech/gmail-smart-compose.html?rref=collection%2Ftimestopic%2FArtificial%20Intelligence 

India devotes only 0.6% of the GDP to research and development and it is  estimated that AI will increase global GDP by 14% by 2030. Of this trillions accrue to china and North America and only 957$ billion to India. The sector is dominated by American firms and around 70% of the AI research is carried out by non-Indian firms. The central government has increased the investment for digitalizing India. Also the ministry of commerce and industry has made a special taskforce on AI that encourages new policy development in these areas. AI is being used in the following areas:
• Finance
• Healthcare
• Manufacturing
• Crime detection
• Precision agriculture

To know more visit:

https://www.brookings.edu/blog/techtank/2018/05/17/artificial-intelligence-and-data-analytics-in-india/  

IT sector is now supported by artificial intelligence and has transformed itself from cost-center to innovator. AI and machine learning is the solution to the challenges faced by the firms. The time saved can be used for more complex problem solving and also to improve customer satisfaction. IT teams should have proper bandwidth to develop best AI solutions. But there is no longer need for that. Many products and services in the market can help improve the work of IT teams by:
• Log analysis
• Employee support
• Cybersecurity checks
Moreover, AI powered marketing solutions help to maximise the ROI of the companies. AI analytics helps the employees to summarise the reports which could have otherwise be done by a data scientist.

To know more visit:

https://www.cio.com/article/3269212/artificial-intelligence/how-artificial-intelligence-will-transform-the-role-of-it-in-2018.html

Multi-task metric learning was introduced by Caruana in 1997. The performance is improved by considering multiple learning tasks and sharing information with other tasks. The metric is used as a measure of similarity or dissimilarity and there are various distance metrics such as Euclidean distance, cosine similarity, Hamming distance, etc. there are various evolving challenges in obtaining training data set which has become a costly process. To overcome these problems multi-task has to be introduced. This article includes the basic concepts, strategies and applications of metric learning.

To learn and know more please refer this link:

https://link.springer.com/article/10.1186/s41044-018-0029-9 

Technology has helped Nike and Adidas to build such shoes for runners that brings back the energy you lost with every stride. Nike introduced a shoe named vaporfly elite to help the marathoner Eluid Kipchoge. The shoes has a midsole and a curved carbon-fiber plate. Both of these features help the runner to move forward and increase the shoes energy return. So whenever the runner takes a stride, the runner’s energy gets transferred into the shoe. Energy gets absorbed into shoes cushion pushing it down. When the runners lifts up its foot, the energy gets transferred back to the runner. The more the energy returned the bouncier the shoe becomes.

To know more about the zoomX midsole foam visit:

https://www.popsci.com/nike-pegasus-turbo-review-faster-training-runs  

The companies are of the concern for big data and its use. The big companies fear that the emerging start-ups in the fintech space will disrupt them. The surveys of 2018 on AI show that both AI and big data will be disrupted by start-ups. Exploring data and making as much use of it is in the hands of the companies. Machine learning is one of the best tools to make use of the data very effectively and quickly. Generally, companies are investing in traditional analytics, big data and AI. The companies are not making fast efforts to move towards a data-driven culture.

For knowing more about the issues visit:

https://hbr.org/2018/02/big-companies-are-embracing-analytics-but-most-still-dont-have-a-data-driven-culture 

People analytics is the sharing of data across the employees of the companies to make the companies grow faster. The managers of the company then become serious with their work. According to a survey by Deloitte, 32% companies are ready to adopt people analytics. However the start-ups doesn’t find these necessary as they are expensive tools. Some of the situations which a company can avoid using people analytics:
• Poor candidate experience
• Mismatched employees
• Incorrect assumptions of employees
• Missing trends
• Costs of employees
Therefore stopping an unemployment claim is also a part of savings for the company.

For more information visit:

https://www.entrepreneur.com/article/289042 

Predictive analysis is the need of the hour for all the businesses. Ample data is available and can be used by the companies for making analysis right for customer satisfaction trends. Data collection is becoming cost effective and can be used by any medium scale enterprise also. The analysts use them to draw meaningful results to help their companies grow. The techniques in predictive analysis include: clustering, decision trees and linear regression. The applications where predictive analysis can be used are:
• Content marketing
• E-commerce
• Social media marketing
Thus, predictive analysis is a useful tool that can help the business to provide better products and services. 

For more information visit:

https://www.entrepreneur.com/article/305460 

Big data and analytics have been the biggest contributor in the recent years. By the end of 2020, the big data volume is going to reach 44 trillion gigabytes. Data analytics provides many innovative solutions for insurance, FMCG, retail and financial services. AI and machine learning helps in predictive analysis and helps in making accurate predictions for the growth of the business. Big data science and analytics have advantages of speed and compiling big volumes.

For more information visit:

https://www.entrepreneur.com/article/316057 

Technology has helped develop such apps which provides services at the door right from cabs to groceries. Provision of other services like plumber, electrician and other maintenance services still are unavailable on apps. Providing these services is not a good option because if we see the calculation then the overall costs is more than the money paid by the customer. To break-even the customer should use their services at least 10 times to average the price to 44 Rupees. There are other factors too like loyalty of customers and discounts which is definitely not sustainable for the company. This market is unorganised sector in India and has a lot opportunities. Customers complained about quality of services and prices and hence this needs to be rectified.

For more information visit:

https://www.entrepreneur.com/article/308191 

Six Sigma and Lean is being used in every industry right from software development to multinational companies. As far as the history of Six Sigma is concerned it was developed in the year 1900. Officially this product was launched in 1980s to reduce variability. Lean deals with data, philosophy and also removes the waste that creates a good environment. The secrets that link consumers’ satisfaction to company’s strategy are:
• Customer’s value
• Achieving goals of the company
• Increasing productivity through motivation of the company

    
For more information visit:

https://blog.edx.org/six-sigma-lean-3-secrets-success?track=blog 

The economic productivity of the country should rise up if there are improvements in technology and artificial intelligence but this is not the case. When the industry employs AI then this lead to more leisure on people’s part and making them useless. According to a survey it has been found that there is a rise in inequality in wages and hence AI needs to be implemented. There should be greater productivity gains but it is dipping. The reason could be slow commercialization. Though it displaces labour but it creates jobs in other sectors. Automation does not replace jobs but it does a part of the jobs.

For more information visit:

https://analyticsindiamag.com/why-has-the-economic-productivity-not-picked-up-despite-the-advancements-in-ai/ 

Six sigma technology helps in improving processes and making them efficient. Multitasking is a good sign for consistency but what if more than two processes have to be used? Then it becomes a problem as there are multiple variations. The variations are considered as an error or defect. So this will reduce the consistency of the business and it will lose its customers. Thus, Six Sigma helps in reducing these defects or variations. So there are a number of ways to reduce variations in the processes of your business which are as follows:
• By using tally sheet
• Pareto chart
• Flow chart
For more information visit:

https://www.6sigma.us/customer-service/consistency-breeds-perfection-in-business  

Amazon’s Alexa and Apple’s Siri have influenced people in a variety of ways. They are a form of artificial intelligence and performs various activities like playing the music list, prepare shopping list, calling, sending voice messages and what not. Other examples of AI are AlphaGo, self-driving cars and a spam filtering machine which detect junk messages. Software’s and computers which are supported by AI can help perform serious tasks like help doctors treat cancer or help scientists perform mathematical analysis.

For more information visit:

https://www.sciencenewsforstudents.org/article/ai-can-guide-us-or-just-entertain 

Technology has its own pros and cons which people should understand and therefore should stay away from their screens. Google and Apple has led people to become an addict to their cellphones. But both the companies now support the digital well being initiative. The android P software will show users the amount of time spent and also allow people to set limits on various apps. YouTube will have “custom breathers” that will remind people since how long they have been watching. Also the large amount of never ending content on the social media apps keep our brains addicted to them. People become addicted to the refresh button and continue to watch and read news feed. It is high time that people should set screen timeouts for their digital well-being.

For more information visit:

https://www.popsci.com/smartphone-gadget-addiction.  

Artificial intelligence (AI) is reaping benefits for early adopters but for laggards it is posing a problem. Due to developments in AI there have been a lot investment by tech giants such as Amazon, Google etc. but outside the tech sector, investments in AI is very less as adoption of AI is still at an experimental stage. Those who have adopted AI have found not only a surge in profits but also reduction in operations cost. The gap between the adopters and non-adopters of AI is increasing and it would be difficult for the laggards to reduce the gap. The government can setup retraining programmes where the employees can be taught how to work with machines and not compete against them.

For more information visit:

https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-artificial-intelligence-can-deliver-real-value-to-companies?cid=other-eml-ttn-mgi-mck-oth-1801. 

The old practice was to study the analytics from a historical perspective but in today’s marketing scenario, we need analytics that present a forward-looking view. There is more potential in data and analytics. Thus, that’s what the McKinsey Global Institute’s partners Michael Chui and Nicolaus Henke share their views with McKinsey Publishing’s Simon London. The age of analytics: Competing in a data driven world is a new McKinsey Global Institute research report in which Nico and Michael are among the co-authors of it. In the McKinsey Podcast, according to them data and analytics is important for customer engagement and satisfaction because a lot of data is available, connections are many and there are many understandable machine techniques and languages through which it’s easy and comfortable to analyze data and to take decisions differently. The data analyzed must be organizable in the ways needed. The data must be such that it develops helpful use cases.

For more information visit:

https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-to-win-in-the-age-of-analytics?cid=other-eml-ttn-mip-mck-oth-1801.   

The world is really moving at a fast pace and is revolving around artificial intelligence. Do you think is it possible to have a three dimensional figure just by looking at a two dimensional figure? Yes, it is possible. The researchers can make a three-dimensional figure just by having few two-dimensional figures. But this system which they have made is not available for commercial applications. This system can be used for self-driving cars and household robots. This system has a very good grasping power as it is able to learn in a very smart way from little observations.

For more information visit :

https://spectrum.ieee.org/cars-that-think/robotics/artificial-intelligence/alphabet-deep-mind-makes-a-key-advance-in-computer-vision 

The plaza del sol in Barcelona has become a place of hangover for the young generation. People spend their leisure time and also party with friends. This has become a problem for the residents staying in that area. To curb this, one of the laboratories has developed a sensor that can detect the noise levels, temperature and air pollution. The lab developed this sensor which was low-cost and easy-to-use. Families installed these sensors in their balconies and detected night time noise levels to be exceeding 100 decibels. Mr. Tomas Diez who runs the lab said that he desires to make a project named Fab city which will be a collection of 18 cities from Europe, America, India and China. This project aims to create cities which will be sustainable and self-sufficient to meet their needs.

For more information visit:

https://www.bbc.com/news/technology-41015486