SigmaWay Blog

Big data for a long time has been handled wrongly, as there is problem lies in assigning meaning to data. There is acute skill shortage and the human factor also complicates big data. Here are a few ways how we can get better benefits from big data.
1. The business has to say what it wants to achieve from collating and analyzing data.
2. Asking relevant questions, so the data can provide answers.
3. Start small and then get bigger, trim irrelevant data.
4. Managing costs better
5. Understanding what data matters to the business the most.
To know more, follow: http://www.information-age.com/technology/information-management/123459617/big-data-phenomenon-broken-5-tips-doing-analytics-right-way

People analytics is a data-driven approach to managing people at work. Those working in people analytics strive to bring data and sophisticated analysis to bear on people-related issues, such as recruiting, performance evaluation, leadership, hiring and promotion, job and team design, and compensation.

The 5-step path to people analytics:

1.Bridge the gap-To ensure you have everything you need- people, processes and technology

2. Knowing the stakeholders- involves understanding their challenges, goads and opportunities

3. Setting goals and objectives- This involves agreeing upon mutual goals and objectives

The increasing number of startups have surpassed the big players with data driven business models. Data science has become obsolete! The next big thing is predictive analytics.

But there are fears associated with adopting this new technology like the fear of complexity, replacement and failure. 

How effective predictive analytics will be depends on how the organization perceives it. When everyone in the business starts thinking about how predictive analytics can improve their organization, it results in big wins for the company. 

To move forward with predictive, the business needs to leave data science behind. Predictive analytics is a completely different approach. Applied to business, predictive models are used to analyze current data and historical facts in order to better understand customers, products and partners and to identify potential risks and opportunities for a company. It uses a number of techniques, including data mining, statistical modeling and machine learning to help analysts make future business forecasts.

To know more- https://icrunchdatanews.com/3-keys-smooth-migration-data-science-predictive-analytics/

Project management now a days requires a more flexible approach than traditional methods. This involves taking step by step actions which are ranked based on priorities.

4 Good Reasons To Do Agile Project Development-

1. Quality -A key principle of agile development is that testing is integrated throughout the lifecycle, enabling regular inspection of the working product as it develops. This allows the product owner to make adjustments if necessary and gives the product team early sight of any quality issues. 

2. Flexibility- In agile development, change is accepted. In fact, it’s expected. Instead the timescale is fixed and requirements emerge and evolve as the product is developed. 

3. Revenue -The iterative nature of agile development means features are delivered incrementally, enabling some benefits to be realized early as the product continues to develop.

A U.S. regional bank while reducing its staff and technology cost wanted to see how it could maintain its collection rate. A consultancy based in Chicago and Bangalore analyzed the actions of a U.S. regional bank such as calls, mailers and IVRs and concluded that the bank was overspending.  The bank was thus able to reduce costs by a million $. Analytical companies are now investing in platforms and products to fill the void in analytic stack. To know more: 

http://www.forbes.com/sites/tomgroenfeldt/2015/07/08/bank-reduces-debt-collection-costs-through-big-data-analytics/

Big Data is the game-changing opportunity for marketing and sales. Airlines are spending on advertising. With the help of big data and analytics airlines can see how to allocate ad dollars. Marketing mix is one example of analytics which helps us understand which media vehicle works best. Following are the three key aspects of marketing mix-

1. Examining the noise- Airlines should take into account the impact of noise.

2. Normalizing the data- This means to adjust the data for external factors (those outside marketing campaign).

3. Performing a regression analysis- To calculate the return on each investment made for marketing and to know the mean impact of each campaign analysis of data is necessary.

To know more- http://revenueanalytics.com/blog/airlines-can-maximize-return-on-marketing-spend-with-predictive-analytics/

Big data is an emerging phenomenon. Nowadays, many organizations have adopted information technology (IT) and information systems (IS) in business to handle huge amounts of data and gain better insights into their business. Many scholars believe that Business Intelligence (BI), solutions with analytics capabilities, offer benefits to companies to achieve competitive advantage towards their competitors. But this journey of increasing adoption of analytics requires much more thinking with an organization.

1. Promotion of decision making based on business outcomes: 

Investment should focus on implementation of analytics rather than infrastructure. Great companies link analytics to results to ensure gains.

2. Data –led decision making: 

Adoption of analytics should be encouraged and intuitive decision making should be discouraged.

Hospitality industry has not been concerned about technology and big data which resulted in widening of the gap between customers and industry. Big Data can result in improved customer satisfaction and personalized marketing campaigns. In addition, Big Data results in a boost in employee productivity and more efficient operations. The advantages of Big Data for the hotel industry are enormous.

1. Improving Customer experience through Personalization  

To improve customer experience, businesses must work towards gauging preferences .There is likely to be an enormous amount of information about every person on the Internet, so the key is to mine this information, and get the most relevant details out of it

2. Marketing Strategies

Big data can help companies devise the best marketing strategies for each target segment, based on their activities and preferences. When businesses understand their customers well, they can devise the right strategies to reach out to them. For example, if a company knows that a particular target group is spending an average of thirty hours a week on social media, they can devise their marketing strategies through social media channels. Such a strategy will give the greatest visibility for the company within their target group. 

Actionable data to support or automate decision making is used by predictive and prescriptive analytics. Prediction of a quantity i.e. regression is required by many use cases. The actions based on the predictions is more important than the actual quantity predicted. Predictions of future events in the context of predictive and prescriptive analytics needs a full probability density distribution. The predictions might give some estimated value of expected fluctuations, but details will still be hidden in the full probability density distribution. In this case, advanced predictive models can be used to derive best point estimator for a given scenario.
Read more at: http://www.blue-yonder.com/blog-e/2015/07/20/predictions-as-a-probability-density-distribution/

Big data is growing now days because companies are demanding more output from big data. Data and data management solutions have helped companies to modify the customer interaction and tackle the risk of uncertainty in timely communications. After having good views of customers, agents can help transforming marketing qualified leads into sales qualified leads with smarter interactions. There has been a change in the role of Chief Data Officer (CDO) who was earlier working as data scientist to help transforming big data into new repositories. Today there is compensation for CDO for the value they extract from all sources of data. The large volume and variety of data from other sources and social media has made the marketers very busy. CDO’s are held responsible to judge the relevance of consumer data and assign a particular value.  Read more at: http://www.smartdatacollective.com/gayle-nixon/332221/data-within-and-data-without

As soon as Big Data started transpiring into the future, it is believed that it would transform the way companies sell, market, communicate, educate etc. There has been an enormous progress of Big Data which helps in data integration and analytics. Nowadays much of the work is concerned on future and therefore it focuses on identifying the consequences of it. The prospect of Big Data has enlarged in recent days and there are key "first-order", second and third order, sample "second-order", sample "third-order implications of Big Data. With the conversion of Big Data into Implications Wheel, it furnishes everyone with new perception and control.

Read more at: https://channels.theinnovationenterprise.com/articles/7899-the-implications-of-big-data

A recent survey on how organization's active data is growing on a year on year basis, looked at two distinct groups:
• Companies experiencing data growth exceeding 50% annually.
• Companies experiencing data growth of 10% or less annually.
So what did the survey reveal?
For starters, companies experiencing rapid data growth were more likely to uncover business opportunities and drive growth. These companies were better able to leverage a wide variety of data types that are both structured and unstructured. And, in comparison to companies with lower rates of data growth, rapid data growth companies:
• 64% more likely to have an executive champion for their Big Data initiatives.
• 68% more likely to have the ability to discover and classify all relevant business data as it arrives.
• 4.3 times more likely to have defined a chief data manager role.
All evidences points to the conclusion that there cannot be a case for excess data. When it comes to data – the more the better.

For more information visit:
http://www.attunity.com/blog/data-growing-out-control-that%E2%80%99s-good-news-your-business

All that glitters is not gold – and the same is true for data as well. To be frank, there is a lot of ordinary in our data management world.
And the most worrying part is that most companies do not actually realize this threat, which is not particularly surprising to be honest, with most companies sticking to well defined data rules which have been in places for quite some time now. This is because data is living under outdated data policies and rules. Data processes and systems are persisting single-purpose data. These outdated processes have given rise to zombie data, which when used can prove to be detrimental rather than beneficial to your corporation.
The only solution is to reassess the founding blocks of data analytics to crush zombie data and ensure progress in the field of data analytics.

For more information visit:
http://blogs.forrester.com/michele_goetz/15-07-14-is_zombie_data_taking_over

Predictive analytics can be seen as business investment rather than an IT investment. But researchers found that there has been shift of funding from general business budget to IT business budget. According to research 15 percent of the organizations prefer to purchase predictive analytics. But truly speaking you will find that there is increasing demand for predictive analytics. This can let businesses to respond faster to market activities and threats. Business investment in predictive analytics has occupied more space in front office but according to research IT and operations are closely related to these operations. To use such analytics technique, the requirement is just a permission from high level management of organization.  Read more at: http://www.smartdatacollective.com/tony-cosentino/332022/predictive-analytics-investing-and-selecting-software-properly

There is an upward trend in the use of big data in the present scenario of the business world. The structured and the unstructured data comprise of the big data. The big data gets analyzed from the market view point and looks for the right time to fetch the right customers. The big data not only helps in sustainable productivity but a development for the employees on an individual levels as well .The use of big data have benefited many sectors in the business and will help more with the combined effect of the modern technology.

Read more at: 

http://www.business2community.com/big-data/big-data-a-big-impact-on-productivity-01274278

Big Data is perceived to be a high tech thing that allows us to gain insights and solve problems like never before. Big Data is processed using brand new computers possessing huge processing power. To utilize data to its full potential, constantly updating systems is necessary. Contrary to our belief that data is a new age concept, data has been in use since a long time as is evident from Willard Brinton’s book Graphic Methods for Presenting Facts published in 1914. Most of the techniques discussed in the book are relevant even today. The only difference between then and now is that the size and availability of data has increased manifold thanks to our growing digital footprint. Big Data is becoming bigger with time but the relevance and use of data remains unchanged. Read more at:https://channels.theinnovationenterprise.com/articles/big-data-its-not-new

The key to achieving better efficiency in CRM is through analytics. CRM will help sales teams to identify leads and retain customers. Marketing teams can use CRM to plan strategies for future. One should keep the following things in mind to successfully leverage CRM data:

(i) Data should be clean and devoid of bad data. Clean, filtered and structured data is essential for gaining meaningful insights.

(ii) Fixing systematic failures and finding ways to improve processes is important. Methods to capture data should not be broken. (iii) Adopting use of data quality tools so that one can use self-service tools and prepare data thus leading to improved productivity with progress of implementation.  

Read more at:http://www.business2community.com/big-data/taking-control-crm-data-01253472

In our daily life we came across new technologies and making our life simpler. Today people are enjoying benefits of internet in form of online shopping, easily sending emails and transactions with friends online. Data is collected on the bases of these activities and improvements are made according to people’s preferences and tastes. Data mining is the key to collect big data and most of the businesses are dealing with these data to provide good services to consumers. Both of the large and small organizations are using big data. Earlier big data was providing benefits to retail and sales industry but now it also giving advantages to learning and development industries. Big data is also beneficial for employee training and can improve performance of current employees. Transformation of training process from traditional to modern techniques there has been a significant improvement in employees’ performance. Employers can easily motivate and inspire their employees. After getting good output from employees, employer gives more importance and satisfaction to employees. So, big data help employers to better understand their employees. Big data help companies to understand people’s requirements and providing facilities according to their preference. It also came in a form of learning and development tool for businesses to improve the performance of employees. Read more at: http://www.smartdatacollective.com/briggpatten/331869/how-big-data-shaping-future-learning-and-development-industry

Data provides valuable information to a firm to optimize its performance. Decision makers and strategists analyze data and take optimal decisions. Data analysis shows the firm its ongoing productivity and making predictions will lead to future growth. Employees also get benefit in terms of more productivity when they use data-driven tools providing more enhanced methods which they can use. Customer relations have been improved, as employees are more productive and can give more enhanced solutions to their customers. Analyzing the data collected from social media can determine how successful the conversations have been. This is possible just because of changing consumer behavior and innovations that lead to such change. Ideal business is one that reacts to social change. Analytical tools enhances culture among employees. More data is needed to improve customer service than before. Today there is a lot of pressure on employees as work is increasing with large data size. Here the data-driven technique  plays its role helping them to handle such pressure leading them to be more interactive and informative. Improvement in employee's performance will result in enhancement of sales process, training and innovation. This change will bring some excitement for employees, working with modern tools far better than those boring traditional tools. Building up the transparent system will bring good feedback from upper management for employees leading them to provide more optimal output. Read more at: http://www.smartdatacollective.com/daanpepijn/329438/data-changing-way-enterprises-optimize-employee-productivity

Data provides valuable information to a firm to optimize its performance. Decision makers and strategists analyze data and take optimal decisions. Data analysis shows the firm its ongoing productivity and making predictions will lead to future growth. Employees also get benefit in terms of more productivity when they use data-driven tools providing more enhanced methods which they can use. Customer relations have been improved, as employees are more productive and can give more enhanced solutions to their customers. Analyzing the data collected from social media can determine how successful the conversations have been. This is possible just because of changing consumer behavior and innovations that lead to such change. Ideal business is one that reacts to social change. Analytical tools enhances culture among employees. More data is needed to improve customer service than before. Today there is a lot of pressure on employees as work is increasing with large data size. Here the data-driven technique  plays its role helping them to handle such pressure leading them to be more interactive and informative. Improvement in employee's performance will result in enhancement of sales process, training and innovation. This change will bring some excitement for employees, working with modern tools far better than those boring traditional tools. Building up the transparent system will bring good feedback from upper management for employees leading them to provide more optimal output. Read more at:http://www.smartdatacollective.com/daanpepijn/329438/data-changing-way-enterprises-optimize-employee-productivity