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Virtual Retail intensifies customer experience

As with most other industries, the ever-moving evolution of technology has had a direct, and impressive impact on retail. The way that consumers shop, purchase, and receive the product points to the fact that it is a radically different world today than it was a short generation ago.

Virtual Shopping. According to Business Insider, “eBay launched what it has dubbed the first-ever virtual reality department store in partnership with Australian department store Myer.” eBay Australia is utilizing “shopticals” that allow customers to navigate the store, and to purchase items using just their line-of-sight. It’s the first of its kind, but definitely not the last.

Virtual Try-Ons. Retail companies have implemented tech services that allow consumers to see themselves in apparel, without even trying it on. One simple photo upload, and instead of visiting a store or even ordering samples, the customer can see themselves in as many different glasses oroutfits as they wish, all from the comfort of their couch. This extends far beyond just apparel though. For example, today’s consumer need not fret over the wrong color choice for their home when they can see it first.

Virtual Experience. Now, in 37 states AT&T customers can benefit from AT&T’s partnership with Samsung Electronics. At 133 stores, “Samsung Gear VR by Oculus lets users virtually experience a Carnival Cruise.” That’s right, you can go shopping for new headphones, and experience a cruise while you’re at it.

The aforementioned are only a few examples that point to the wide-ranging implications of a retail industry that is being drastically altered by both the technology that is the child of modern science, as well as the expectations of the tech-savvy consumer.

However companies have to invest in Cybersecurity Tools in order to improve security and privacy for customers. For instance, the scope of corporate data is widening, and cyber criminals are finding more reasons and ways to undermine that data for profit. Cybercrime is a quickly-growing area of crime due to the anonymity and convenience it provides. So it’s understandable to find the Internet unpredictable and rife with risk.

A case study from the Internet Society offers us acumen in this regard. In 2016, they interviewed over 3000 technology partners from both the public and private sectors on the current drivers of change in their sectors. Their goal is generate recommendations on increasing trust in the Internet, despite news of data breaches and surveillance. Clearly one of the sectors they focus most closely on is cybersecurity.

One outlook is that companies are increasingly depending on multiple companies to handle their security services. Any divide in security is a potential backdoor for cybercrime. That only leaves openings for unexpected costs and lost customers. You want them to trust that you have protected them from data breaches by first protecting yourself.

You also want to protect your employees. The US Office of Personnel Management had records on 21.5 million past, present, and potential employees, stolen from under them. This could happen to an organization due to an employee giving out the info or a program installed that wasn’t detectable until it was already active. Being backed up by an all-encompassing security company can greatly mitigate this risk.

healthcare

IOT improves healthcare

Healthcare stakeholders are searching for ways to apply Big Data to drug development. Until recently, clinical trials were the primary method of collecting data and measuring whether a drug worked well and was safe. But the recent digitization of health records and healthcare claims has sparked new ideas about which data is relevant when evaluating drugs, including real-world evidence.

Real-world evidence is data from patients’ experience with a drug, outside of research settings. Pharmaceutical companies, regulatory authorities, and insurance companies are determining how this data will affect recommendations for prescribing drugs.

If you stay current with technology news, you have certainly heard of the Internet of Things. If not, in a nutshell, the term essentially refers to any item or the capability of any item to be equipped with a sensor (e.g. in healthcare). This sensor would be able to collect data, and send it to another sensor or databank, and also be capable of taking action based on data recorded.

As far as healthcare is concerned, the IoT is not being utilized anywhere near its potential. There are devices and monitors in use now, but they are primarily personal use items such as fitness trackers and such.

There are an infinite number of uses for IoT in healthcare. There is the potential to improve patient care, facilitate research, streamline physician workloads, and from the administrative end of healthcare, save large amounts of time and money.

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Happy New Year 2019

We wish our customers, partners, friends all the best for 2019.

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Home is where the customer is

“Home” is where the customer is. The physical home is an extended home-zone, nowadays. If you want to be successful with your services, you have to reach the customer at his home where he uses his devices and sensors. More and more services are anchored at the customer-home – more services for easier coping with everyday life. The customer autonomy continues.
The battle for the living room of the consumer has not ended, as traditional lines of business still have to find their way to the living room of the customer. Technology is the enabler to reach the customer. The right sensors, the right App, the right Infrastructure is needed to generate a value added for the customer. And finally, (Data-)Security and Data Intelligence have to create real benefits for the customer.

Latest developments and examples are:

  • 3-D printing: manufacturing at home
  • Drones: logistics to your door
  • Smart meters: energy autonomy for your home
  • IoT: Sensors and Data-Intelligence decide for a lot of repetitive tasks what to do
  • Streaming vs TV: you decide what to watch
  • Smart loudspeaker

All those customer centric services increase customer autonomy. Technology is hereby an enabler. The more your business model supports customer centric autonomy, the higher the revenue potential.

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predictive analytics

Better Planning with Predictive Analytics

In industries with longstandig customer relationships, you want to know how customer-churns are impacting the customer value. The better you can analyse the future churns within or outside your company, the better you can react to these changes. Typical industries for this analysis are: Telecommunications, Banking, etc. The ability to access and analyze data from many cultures and geographic regions is one way the current machine learning platforms can produce models that deal with global human behavior. In the past, when we were dependent on subject matter experts, predictions were often limited by geography and culture.
Predictive analytics will help you to make more meaningful analysis with Big Data and allows you to make forward-looking business decisions. Before starting a predictive analysis, you need to know the components of your value drivers in details. E.g. the churn rate is one important value driver and the financial contribution margin analysis includes the following categories:

Net Revenues
-Direct Costs
Contribution Margin 1
-Acquisition and Retention costs
Contribution Margin 2
-Network Costs
Contribution Margin 3

Customer segmentation and churn modeling are important underlying tasks in order to make relevant predictions in the telcommunication sector. See example:
• Churn within your company (within price plans): In order to predict the churn-likeliness of customers you need to take into consideration the Social Data and Usage Data of your customers. The usage data includes trends of the following pricing components: Voice-Call-Patterns, Data-Usage, Roaming, Wholesale, etc. New market-developments like new handset models need also to be incorporated in your analysis. Social Data includes social network data (comments, recommendations) of your customers. Both (social and usage data) need to be merged and analysed (time line, clusters, regression, etc.).
• Churn outside your company: To get a better accuracy of churns outside your company you need to include the pricing developments of your competitors in your analysis.

Trying to measure the success of a group of company based on a limited number of KPI will not lead to a fair, motivational decision. It will lead to an oversimplified judgement of a situation and to shortsighted conculsions.
What can be done in order to improve a decision making process of a group:
• Use as many data sources as you have (big data, data lake)
• Use external data and research data – to bring the external view in the decision making process
• Find patterns relevant for your group or company – the patterns are different for all companies (you can’t guide companies with the same five KPI).
• Look at trends and personal feedback – build a story around the data
• Use IT extensively to measure and analyse data.
• Do not measure the KPI in a traditional financial form – the new KPI is explained in multidimensional ways.
• Automated processes are welcome, but be aware, that for an holistic picture you need good human analysts.
With today’s tools you can evaluate complexity much better than years ago. It’s possible to make better decisions in a more sophisticated world. Predictive Analysis helps you bringing your Business Intelligence to the next (analysis-)level and predicts how your customers are going to react in your price plans in the near future.

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lawyers

Insurers and Lawyers are stepping into AI

The insurance business revolves around measuring and pricing risks. In short, it’s a business about caution. Perhaps that’s the reason why insurance companies have lagged other industries, such as banking, in adopting new technologies that offer more powerful analytics capabilities. But the insurance industry’s reluctance to adopt new technologies is breaking down. So-called insurtech is one of the industries drawing investor interest as startup companies test and market new software solutions, Coin Journal reported, citing a report from CB Insights and KPMG. Insurance companies are interested in using Internet-of-Things technologies to identify and mitigate risk, while also incorporating other technologies that identify fraud, improve efficiency, and cut costs.

Financial services quickly embraced new technology because its use in improving profits was readily apparent to bankers and investors. Gathering information in real-time and timing transactions based on the steady flow of information helps financial industry players make money. In the insurance field, the name of the game is saving money. New technology can help insurance companies more accurately price policies to risk and while also cutting down on fraudulent claims that are costly to the industry. Daily Fintech notes that one of the more transformative developments in insurtech is the emergence of telematics. The capability to gather and transmit near-real time information produces even more data points from which an insurer can more precisely make their risk assessments. These bountiful data sources produce a tremendous amount of data from the home for home insurance, and from the car for property and casualty insurance, Daily Fintech explains.

The collection and analysis of data is not limited to the home and the car. Wearable technology first found its place in people’s lives in fitness applications. But these technologies have matured to a point where they can be used for healthcare applications. The ability to monitor people and collect data of a person over a longer period of time yields measurable data that insurance companies can use to assessing health risks for life and health insurance, Daily Fintech says. Continue reading

supply chain

Managing the global and local supply chain

The term glocal, used to describe global and local actions together, is used in several ways by business today. Many people supporting the local movement, such as local food advocates and those proposing ways to use local business for community building, suggest that some business activities should always consider transportation to the end market, including supplies in the supply chain. In an effort to reduce carbon footprint associated with shipping costs, the closer to home a built, manufactured, or grown product can be sold and used, the better. Global communication allows language, culture, news, and other exchanges of human knowledge and expression to be freely shared across cultures.

Maintaining a local business across the supply chain is quite difficult to do, even for artisans and those in the cottage industries, but for many the needed changes that will come with the local movement are worth the extra effort and expense to source goods locally. But for business, the use of glocal also suggests the cultural influences in attempting a new product launch into a global market.

A new startup develops a prototype and finds manufacturing partners that meet needs for productivity, supply, cost, and collaboration. When the product is ready for launch into other markets, local cultures will dictate how a product should be advertised, marketed, presented, and sold, as well as legal and regulatory issues. A piece of wearable tech designed to help women get pregnant by using biomarkers will be marketed differently in Kenya, Japan, and Iceland, for example.

Having specialists on board who are attending to anticipated glocal needs for a product launch early in the planning stages is important, but at the time of product launch, local partners will probably need to become involved. Continue reading

healthcare

Behavioral variables and nanobots in healthcare

Big data and machine learning platforms are in a unique position to analyze one of the most challenging aspects of medical research: behavioral variables that are not reported accurately by common assessment methods. While EMRs (electronic medical records) prompt healthcare providers to collect a great deal of subjective information that impacts healthcare, such as compliance with medication regimes or alcohol intake, the validity of the information collected is questionable.

The subjective nature of the reasons people conceal or alter information given to a health care provider are as complicated at the whole of the human population. People feel social pressures to conform and please a questioner. They don’t want to admit to money problems that impact health care. They do not accurately see their own behavior. Cultural norms regarding personal information vary widely, as does disclosure by age and gender and social class. But new methods of gathering and quantifying data across populations has the potential to give greater insights into human behavior that can change the results of medical research.

Relying solely on patient reports of behavior is a method of gathering data that is extremely limited and may significantly impact the results of healthcare research. But gathering self reports, along with subjective research reports, pharmacy records, laboratory test results, social media, buying behavior, financial records, employment records, and other sources of data, and then analyzing across populations, can give a more accurate picture of what people are actually doing. By having a more accurate picture of human behavioral variables, healthcare research can more accurately assess the impact of human behavior on health care outcomes, and propose treatment modalities that are fine-tuned to the people we actually are. Continue reading

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New technologies for improving healthcare

Various thought leaders have opined that we are in the Fourth Industrial Revolution, as seen by the fact that new technologies are disrupting all industries, disciplines, and economies. By 2020, the digital universe will be 44 trillion gigabytes. This amount is doubling every two years.  Big Data will become so large that artificial intelligence (AI) will make sense of it for us. Already Google has launched the Google Deepmind Health project to scrutinize the data of patients’ medical records and provide better and faster service.

Mitchell Weiss, a robotics safety expert, identified the top three trends impacting occupational health and safety in 2017. They involve complexity of automation, collaborative automation, and complexity of user interface. Along with this there is an increase use of Big Data, artificial intelligence, and IIoT (Industrial Internet of Things) to do medical work.

Internet of Things (IoT) — the ability to connect any device to the Internet through an on and off switch — is a major component of telemedicine, which allows healthcare professionals to communicate with people long distance and provide consultation, diagnosis and treatment of various medical conditions. IOT Telemedicine, which has been gaining in popularity, is now expanding globally.

A Brief Primer on the Internet of Things

Internet of Things is a concept that can apply to things like washing machines, coffee makers, headphones, even parts of machines. The research and advisory firm Gartner estimates  that by 2020, more than 26 billion devices will be connected to IoT. Some analysts say the figure could go as high as 100 billion. In only a short time, our society will be a network of connected “things.” And these “things” include the robots and other devices that are connected to the Internet and can therefore consult with physicians and patients thousands of miles away.

Internet of Things in Healthcare Continue reading

predictive analysis

Predictive Analysis and human behaviour

Predictive Analytics is the branch of machine learning that is putting all the data to work. It takes large data sets and uses mathematical algorithms to form predictive models. Then statistical methods such as regression analysis are used to find the variables that influence the models. Finally, machine learning platforms use those predictive models to find patterns in the past that can allow predictions of patterns in the future.

Human behavior can be seen as a series of patterns that repeat, both individually and as a group, over time. This statistical fact doesn’t negate the possibility of free will; it allows us the use of our free will to repeat patterns of behavior that are most comfortable to us, considering the social, cultural, and family pressures that also influence us.

The analysis of patterns of behavior in humans as a group has been the work of historians, who can look back at great sweeps of time and see patterns that repeat. With the amount of data being collected now through online interactions and geotracking tools such as GPS, machine learning platforms are engaged in how to mine that huge amount of data for the very specific data needed to answer questions.

Predicting the future has been an art in which intuition based on expert knowledge and experience was used to make a predictive analysis. Those who are considered masters in their work combine experience with knowledge, and can see patterns from the past and predict patterns into the future. But we are constrained by the depth and breadth of experience and knowledge we can acquire; we are further constrained by unconscious bias and other human attributes. Continue reading