Big Data Made Simple - One source. Many perspectives.

Employee well-being is a major concern for organizations, especially when those entities are concerned about productivity.

Data from the Bureau of Labor Statistics published a report revealing that in 2016, there were 2.9 million reported workplace-related injuries and illnesses.

Nearly one-third of them required workers to take days off work. Those are significant numbers considering that many workers do not formally make reports to their bosses when they get sick.

In the United Kingdom, data shows there were 25.7 million days of work lost in 2016 and 2017 due to illnesses. Also, 12.5 million of those cases were related to depression, anxiety or stress.

It’s not surprising that many employers are investigating ways to take proactive measures to prevent employees from getting sick.

One of their main efforts involves using big data and poring over statistics that could indicate instances of ill health are on the rise or going down. However, both potential positive and negative aspects of that approach exist. Here are some thoughts.

People Can Get Healthier Together

Many of the advantages of collecting employee data involve people teaming up to track their metrics over time and work toward a common goal, such as weight loss. In those cases, participants can encourage each other and see the changes in their colleagues.

Employers Experience Cost Savings

When employees can’t work due to illness, they frequently cause their colleagues to bear the burdens of their absence and may disrupt operations in the process, creating new expenses. Also, if key individuals working on critical projects get sick, organizations could face costly consequences due to missed deadlines.

When employees are healthier, workplace representatives may choose less expensive, more appropriate health insurance premium packages, too.

Employees Could Feel Discriminated Against

Some companies reportedly track employee health data to see how many employees are likely to become pregnant.

Women frequently already experience a great deal of anxiety about telling their employers they’ll need to take maternity leave or otherwise adjust their work schedules due to pregnancy, and this new development could make that worse.

One app called Castlight gathers data about employees and uses it to urge them to make better decisions about their health. Not surprisingly, some individuals assert that practice is too invasive.

The company says it cannot give organizations data about individual employees, but that does not always make people feel better.

That’s because current laws give more freedom to sort through health data that does not identify a person compared to the material that does.

Even if a worker’s data is represented in a larger segment, he or she might wonder if data pulled from a software suite is causing a boss to have unfavorable views of the individual’s dietary choices, decision to smoke cigarettes or the fact that he or she drinks lots of soda at work.

Fearful Feelings May Increase

Also, individuals are already wary about how the apps they use collect and evaluate data about them. That’s because many of the apps do it silently in the background.

Sometimes, the data collection practices are part of the terms of use for an application, so if users do not consent, they cannot access the app.

If people do not understand how their workplaces use collected information and feel they cannot go to a designated individual or department to ask questions, they may become so uneasy that their work outputs decrease.

If the pressure feels too great, they may look for other employment prospects.

Being Transparent Is Often Preferable

When an organization decides to start using big data for employee tracking purposes, that conclusion could mean many things.

Some specifics must be determined. For example, what statistics are gathered, and why? Also, are employees aware of the data tracking methods, and can they opt out of them without fear of being seen as non-compliant?

It’s crucial for workplaces to keep ethics in mind at all times when collecting and using data. They must determine the best ways to protect employee privacy while meeting organizational objectives.

Coming up with an information governance plan and asking for employees’ input is a great start. Furthermore, workers should get the opportunity to formally say they do not consent to their details being collected and not have to give reasons why that’s the case.

Making employees aware of what to do if they have questions about data use at work is another excellent step to take.

Also, employers should strive to show they’re genuinely open to receiving feedback. Being able to provide it should make employees feel they still have some control over data about themselves and how it is used.

Health data collection is a practice likely to continue gaining popularity in modern workplaces.

However, keeping employees on board with the idea and not making them consider working elsewhere involves honesty and openness about the techniques used and what purposes they serve.

The post The pros and cons of using big data for employee wellness appeared first on Big Data Made Simple - One source. Many perspectives..

Source: http://bigdata-madesimple.com/the-pros-and-cons-of-using-big-data-for-employee-wellness/

Chatbots are conversational tools, capable of engaging multiple users to give structured responses to the most basic queries. Due to their instantaneity and ease of use, they have demonstrated significant potential on E-Commerce websites. As users face issues getting to their desired product page on the website and making a purchase decision thereafter, chatbots can prove to be useful for enticing these users that are about to leave the website without purchasing.

In addition to increasing overall efficiency of customer service, chatbots can also be successfully targeted on relevant product pages to display offers and promotions in order to persuade users that are on the page. If used effectively, they could be great learning tools to know more about your customer’s shopping habits with the intention to offer more relevant products in the future. As research shows that more than 80% of businesses will have some sort of automation through chatbots by 2020; the future for chatbots in e-commerce does look very promising indeed.

This infographic by Market Inspector shows how chatbots optimize a customer’s online purchase experience using the most recent user surveys.

The post Unlocking the potential of chatbots in eCommerce (Infographic) appeared first on Big Data Made Simple - One source. Many perspectives..

Source: http://bigdata-madesimple.com/unlocking-the-potential-of-chatbots-in-ecommerce-infographic/

Artificial Intelligence or AI is expected to be in major demand by retail consumers due to its ability to make interactions in retail as flawless and seamless as possible. Many of us do realize the potential of AI and all that it is capable of, along with the support of Machine Learning or ML, but don’t realize that the implementation of AI in certain segments has already begun.

AI in Retail

The future for AI and the complicated computer processes involved behind it is really bright in the field of retail. AI currently has numerous data sets working along with computer visualization methods to ensure that the users get the most seamless experience when it comes to AI in the workplace. There are some interesting facts that pertain to the use of AI in retail. Here we have some of them to build the insight into what you can expect during the feature;

• It is expected that customers will manage 85% of their relationship with the enterprise without interacting with a human.
• According to a report by Business Insider it is said that customers who interact in online opinions and reviews with retailers are 97 percent more likely to convert along with the retailer during this phase of change.

With such promising figures on the card, one cannot help but notice the wave of change that has already started in the field of retail. With work already in progress, major retailers such as Amazon and Walmart have made advances that are expected to dictate this transition to AI in retail. We will be looking at these advancements, and will see how they can work out in the future.

Walmart’s Shelf Scanning Robots

You might have heard of shelf-scanning robots being tested by retailers, but we’re just about to witness one of the most interesting advances in the deployment of these robots. Walmart, which is one of the biggest physical retail chains across the world, is planning to extend the tests for its shelf-scanning robots across 50 additional stores, including some from its native land of Arkansas.

The machines, which have been deemed to be the future of shelf scanning, will roam around the aisles to check all factors including pricing, misplaced items, and stock levels, to assess the level of stocks within the store. This would not only save human staff all the hassle of checking these trivial details by themselves, but would also mean that they can focus on other more important details. The machines will require technicians to be present on site to handle the situation in case of a technological impairment, but the robots are currently fully autonomous to handle their tasks themselves. These robots will be using the concepts of 3D imaging to roam around aisles, dodge obstacles, and to make notes about the blockages in their pathway.

Amazon Go

Amazon Go is the latest wave of technology in retail that is expected to lead the way to the future of AI in retail. The basic concept behind Amazon Go is that it is a new kind of store that flourishes on the concept of no checkout requirements. Consumers who walk into a store can take whatever they want without having to go through the hassle of lines and waiting for checkout.

The checkout free shopping experience in Amazon Go is only made possible through the use of the same technology that is currently in place behind computer vision, sensor fusion, and self-driving cars. The technology automatically detects all that is being taken and keeps track of them in a virtual cart. Shortly after the consumer leaves, they will be sent a receipt and charged through their Amazon account.

The post AI’s impact on retail: examples of Walmart and Amazon appeared first on Big Data Made Simple - One source. Many perspectives..

Source: http://bigdata-madesimple.com/ais-impact-on-retail-examples-of-walmart-and-amazon/