SigmaWay Blog

Data is an important tool which manages a lot of important activities in the business. And this is further enhanced by artificial intelligence and machine learning and by ease of collecting and storing data. Managers rely too much on data for the guidance which abdicates their knowledge and experience. In a big data project the manager connects the internal and external team to collect and process the data in order to solve the problem. Data must be in usable form and the algorithms must identify statistically significant patterns. The results are then presented to the manager through different visualizations. The main problem is the managers are not good with data science and the scientists are not good with the businesses.  Read more at: https://hbr.org/2017/06/the-best-approach-to-decision-making-combines-data-and-managers-expertise

Data driven analytics is must for all business functions because of increasing complexity and market volatility. According to the survey of more than 300 executives in North America, U.K. and Ireland conducted by Dun & Bradstreet and Forbes Insights, 1.) Senior executives finally understand the value of analytics and are making investments in technology, people and processes. 2.)Data analytics skills gaps persist across the enterprise, as 27% of analytics professionals surveyed cite this skills gap as a major impediment in their data initiatives.  3.)Analytical methods and tools trail both the appetite and ambition of most business leaders. Analytics now drives today’s enterprise, from formation of business strategy to powering operational excellence. It has clearly moved from being an optional operational element to serving as the core of corporate activities. Read more at: https://www.entrepreneur.com/article/295522

Measuring the effect of quality on revenue and profits is one of the biggest challenges faced by digital publishers. It can be measured by measuring engagement of customers, i.e., their frequency of visits, how recent their last visit was, etc., which confirms the quality of the product. The next is that the publisher’s dilemma is balancing advertising revenue with audience revenue. Advertising revenue depends on quantity of audience impressions while audience revenue depends on quality of content. Also, more audience revenue requires higher quality user experience. As digital advertising revenue, particularly display ads, the need for greater audience revenue is very important. To measure success, the important data to capture are revenue by individual user. Using these data, the publisher can identify the combination of product attributes and price point, thus maximizing expected advertising revenue and audience revenue. Read more at: https://www.webanalyticsworld.net/2017/02/digital-publishers-analytics-dilemma.html#more-23565

To become a digital expert, customer experience should be put above everything and methodologies should be found to adjust to the continuously changing demands. The following are some ways to do so. The first is to become a top-notch expert with industrialized IT services, where quality should be improved and it should be ensured that the product line is aligned with business needs. The next is to modernize, during which architecture must be planned and implemented. The last stage is Optimize in which improvements are made. The second is switching to agile operations to achieve maximum efficiency. Third, is to create an engaging experience for the consumers by designing a unique omni-channel approach, analyzing real-time data, thus improving purchase journey. Lastly, opportunities for digital services must be availed. The end result is the delivery of a truly digital experience. Read more at: http://www.datasciencecentral.com/profiles/blogs/enterprise-journey-to-becoming-digital

Nowadays, finding a desired job is not easy, but with personal branding, one can find it easily. Personal branding is a term coined by Tom Peters, in his breakthrough article “ A Brand Called You”. Every person is unique in its own skills. There are a lot of reasons why understanding and building your own personal brand will help you achieve success in the future. Some of which are: 1.) Question yourself: Ask yourself  Who are you ? What are you? Once you start identifying the blocks that build your personality, you can find yourself standing out from the crowd. 2.)  Social media: In the  present era you need  not go out to search for a job. What you can do is maintain your social media. A lot of  business partners who are currently running their successful businesses had their first encounter with social media. Does anything get better than this? Read more at: https://www.entrepreneur.com/article/295522

Demand for credit is increasing in the cashless economy where there is rise of digital money. Various startups are emerging that allows the user to buy now and pay later. They are targeting those consumer segments of India that does not have access to a Credit Card. Banks take loads of paperwork and much more time while giving loan, whereas these startups determine credit worthiness through social media. Slicepay is targeting college students aged 18-26 who usually don’t have credit cards and this segment of people need small ticket loans which other banks don’t provide. Also, for the loans given, they believe that it won’t lead to debt crisis because i) Credit taken are in small amount. ii) Analysis is secured. Read more at: https://www.entrepreneur.com/article/295918

HR analytics is a key element in any company’s progress. The slow growth of HR analytics has been a great concern for companies. HR leaders can present analysis in a more impactful manner by using the LAMP framework. 

• Logic- with trends, the logic for the occurrence should also be explained.

• Analytics- provide important insights from data using tools and techniques.

• Measures- verified and accurate numbers should be used in analytics.

• Process- motivate decision makers to act on data insights using right communication channels.

LAMP elements can play a strategic role in the organization and should be utilized to its full potential.

Read more at https://hbr.org/2017/06/hr-must-make-people-analytics-more-user-friendly

One should search himself online and keep track of photos. There has been continuous warnings from the guidance counsellors. Research says that at the time of admissions the profiles of the students are checked by the institutes, which might lead to the revoke of admission. One also shouldn’t post false information about the wrongdoings. Posting forbidden information online is considered illegal as it may violate institutions rule. It should also be made sure that the information entered by the individual is appropriate about name, email address, etc. these information must not be made to look unprofessional in any manner. Also others should be treated nicely on the social media including comments and trolls. Read more at: https://mobile.nytimes.com/aponline/2017/06/19/us/ap-us-college-admissions-social-media-tips.html?rref=collection%2Ftimestopic%2FSocial%20Media&action=click&contentCollection=timestopics&region=stream&module=stream_unit&version=latest&contentPlacement=7&pgtype=collection&referer=https://www.nytimes.com/topic/subject/social-media

In describing the key traits that a successful business man possesses, one cannot say who is the best. Just to get the idea while using IBM's supercomputer Watson, online career management website "paysa" analyzed the speeches, essays, books and interview transcripts of today's most powerful leaders. So to do this, it surveyed 8 industries. And in majority of these , Watson discovered "intellect" was the top personality trait for leaders. It also identified other traits, i.e. imagination, cautiousness, assertiveness, adventurous and more. Elon musk scored the highest score for the "most cautious leader". Above all, Bezos, Cook and Meg Whitman each tied for "most altruistic leader" at 98 percent. Whitman also topped the list for the most "achievement-seeking leader." Mark Zuckerberg seemed to exhibit the least amount of top common success traits identified by Watson. Although that doesn't mean much -- the Facebook co-founder and CEO just has his own set of unique traits that make him stand out. Read more at: https://www.entrepreneur.com/article/295452 and  

https://www.paysa.com/blog/2017/05/24/watson-personality-analysis-by-industry/

Data can be put to use in many ways and it should be explored. Data should be used to its full potential, this is not about technology but management. A team of data scientists employ a series of various analysis to look into the entire series from data insight to profit. There are 7 methods to put data into work. 1) Use data to make better decisions along the chart. 2) Use innovations in products, services and processes. 3) Making existing products more valuable. 4) Improve quality, eliminate costs and build trust. 5) Sell or license richer data. 6) Asymmetries should be exploited. 7) Connect providers and those who need the data. These help to provide greater value to others. Read more at: https://hbr.org/2017/06/does-your-company-know-what-to-do-with-all-its-data

The present business environment is volatile and full of uncertainties. Therefore, a need arises to improve efficiency and profitability. Though many organizations rely on traditional techniques, predictive analytics is the new trend of managing risks and monitoring frauds which eliminates all the guesswork. Predictive analytics help us in reaching the source of fraudulent transactions and in dealing with future plausible attacks. Lack of corporate transparency and missing public trust should be dealt with by using advanced tools for managing huge data and ensuring accountability. Predictive analytics helps in building the customer profile to know his credibility which is useful for banks. Read more at : https://blogs.metricstream.com/ready-predictive-analytics-revolution/

Big data has now become old, organizations are very well familiar with it. But some of them are still struggling with data. Data lakes provides easy access of data and data mining. Due to management defaults data may turn into data swamps making analysis difficult. Data Lake has a lot of benefits, but the data growing in size becomes difficult to handle. To avoid this problem following steps are taken at the time of creation. 1) Too much data must not be collected at the beginning. 2) Data insighting cannot be done manually, so machine-learning capabilities should be enabled. 3) Businesses should keep an eye on changing data statistics and the employed models. To make it successful one needs to integrate it with business strategy and outcome. Read more at: https://www.readitquik.com/articles/elastic-computing/smart-ways-to-manage-your-big-data/

SecondMuse, place of work that collaborates with organizations to assist solve complicated issues, looked to the most recent drone and 360 video technologies to assist showcase cultivation — the farming of aquatic life-forms — in United Republic of Tanzania.

Led by the Australian Department of Foreign Affairs and Trade’s InnovationXchange, in partnership with SecondMuse, the goal was to award comes that each facilitate scale back environmental impact and increase property.

Ben Kreimer, a drone and computer game individual, and Brett Garling, producer and founding father of Cut Canvas inventive, shot 360 video underwater, on land, and within the air to document 3 of those initiatives.

More than seventieth of Tanzanian alga farmers square measure ladies, and rising ocean temperatures square measure reducing the economic viability of alga farming, per the Blue Economy Challenge web site.Read more at : http://blogs.discovermagazine.com/d-brief/2017/06/08/drones-showcase-aquaculture-in-tanzania/#.WUK_3BN968V

The difference between steam video and live casting s that live casting is uninterrupted steaming directly into the web. Livecasting offers a much better job at communicating. It allows the views to feel the experience as if they were alongside the participants. Also it lets the audience draw their own conclusions. Video take livecasting altogether to a different level. Livecasting creates an opportunity which adds that missing human element, traditional advertising is thus pushed away. Live video allows brands to communicate emotions in a way that is less likely to be misconstrued. The relationship between AI and livecasting is evolving and is focused around user-generating content. Livecasting creates a platform for brands to connect, build, trust and convey emotion. Read more at: https://blogs.adobe.com/digitalmarketing/social-media/hey-brands-busy-lifecasting-arent/

Artificial intelligence and improved technology without structured analytics can prove to be costly and can leave the company paralyzed. However, companies with strong analytics can make excellent use of it. Before Adopting artificial intelligence, the following points should be considered. 

1. The basic processes should be automated.

2. Structured analytics and centralized data processes.

3. Integration of structured analytics with artificial intelligence.

Artificial intelligence, if exploited to its full potential, can reinvent business. Read more at https://hbr.org/2017/06/if-your-company-isnt-good-at-analytics-its-not-ready-for-ai

Machine learning can be used in our daily lives such as filtering the spams in our mailbox or for banks judging the credibility of customers before issuing credit cards to them. We can even deposit checks through our phone. Machine learning models train itself, gather inputs and generate output. Machine learning tools are used as a part of business intelligence. Through Natural Language Processing (NLP) machine learning can comprehend speech or written words and generate graphs and figures. It can correct any anomalies in business and find out when the demand for your product is high. The more inputs one feeds in faster it learns. Read more at: https://www.sisense.com/blog/beyond-hype-machine-learning-unlocking-power-bi/

Traditional methods of procurement of inputs like person hours, capacity and other components are ineffective and costly for the clients. According to output-based pricing model output is pre-determined by the vendor and he’s accountable for achieving that level. There has been reduction in checkout time as analytics solutions for optimization are available to the vendors. Vendors face the overall risk of an outcome and at the same time have a share in profitability. In India, due to unawareness of analytics, companies have not yet adopted the model. Companies in India are unwilling to buy analytics services. A more output based approach can cost-friendly. Read more at:http://analyticsindiamag.com/outcome-driven-pricing-model-analytics-really-work/

Google Attribution 360 is the updated version of Google Attribution, an extremely useful app for Marketers. It helps you understand whether your marketing is working, turn audience insights into action, and deliver more relevant customer experiences. Salient features: Fast setup, Flexible data, Measures TV, Easy to take action, works across channels and across devices. Attribution 360 is also designed to be highly customizable and can measure ads from DoubleClick Campaign Manager. Read more at https://analytics.googleblog.com/2017/05/solving-enterprise-attribution-challenge.html?m=1

Machine Learning models are useful in solving a number of business problems, but there is always a trade-off between accuracy and interpretability of models. Businesses tend to use easily interpretable algorithms which come with lower accuracy. In this article, the author attempts to resolve this issue and shows how powerful black-box algorithms can be used for predictions. He has taken the help of one such algorithm called LIME (Locally Interpretable Model-Agnostic Explanations) that can effectively explain the predictions of any regressor by approximating it locally with an interpretable model. Read more at: https://www.analyticsvidhya.com/blog/2017/06/building-trust-in-machine-learning-models/

Adobe Analytics Cloud is a premier customer-intelligence engine which helps brands to not only analyze vast amounts of dispersed data, but also translate that data into customer profiles. It is built on the Adobe Cloud Platform which uses Adobe I/O and Adobe XDM, and an artificial-intelligence framework called Adobe Sensei. Virtual Analyst, the latest algorithm that was introduced in the market, delivers valuable personalized insights into incongruities which impact your business. Also to integrate Adobe Analytics with additional data sources new content packs for Microsoft Power BI have been introduced, including:Traffic Analysis to quickly discover and analyze digital-traffic trends; and Mobile App Analysis to take an in-depth look at mobile app user engagement and performance. Read more at : https://blogs.adobe.com/digitalmarketing/analytics/next-chapter-virtual-analyst-powered-adobe-sensei/