The digital revolution has created significant opportunities and threats for every industry. Companies that cannot or do not make significant changes faster to their business model in response to a disruption are unlikely to  survive

adopt the ones which makes more sense to your business.

Finally you know when you are digital transformed?

With its growing prevalence, the Internet of Things is ushering in a new form of ecommerce – the Commerce of Things, where everyday objects are internet connected and capable of initiating a series of purchases on their own. This new way of buying and selling online is radically changing traditional ecommerce rules and creating a new set of challenges for companies. In this new world of commerce, the product sale is no longer just a transaction; it’s the beginning of an ongoing relationship between brands and customers. Successful online brands are focused on nurturing this relationship – and taking deliberate steps to turn transactional customers into loyal members. 

There is a subtle but critical difference between a repeat customer and a member. Understanding this difference is the key to succeeding in an environment that is swiftly becoming a hyper-connected network of consumers who value the access and amenities that come with membership.

How do you build these relationships?

1.)   Create lasting relationships to make members out of customers. Members share the experience and the story of the brand, rather than just execute a basic business transaction or product purchase. For years, Disney, where everything is a show and employees are cast members, has stood by the adage “Be Our Guest,” calling to their customers in a more intimate, personable way. Cable companies refer to their customers as “subscribers;” LinkedIn has always called users “members.”

To move customers from “transaction to membership” on a relationship continuum, companies must provide extra, incremental value that replaces pure monetary benefits with more intangible rewards of being, in Disney’s case, a guest.

2.)   Use data and metrics to strengthen relationships. Once a company starts to grow its base of members, a whole new set of metrics becomes the benchmark for evaluating the customer relationship.

Asking one simple question, “What is a subscriber’s actual usage?” can yield revelations regarding whether someone is a transactional customer or an invested member. For example, January is the peak season for signing new members at fitness centers around the country. Are those who sign up then really members? If they are not actually getting personal value out of their membership, then the relationship remains transactional and fleeting at best.

Good data is powerful. If the data shows customers are not acting like members, then a company can follow up to discern the true nature of the relationship and figure out how it can become more valuable to the customer. This creates a win for both the customer and the company. 

Delta Airlines’ SkyMiles program, for example, makes great use of data to cut through barriers that could otherwise prevent strong relationships from developing. When members call in, the automated phone system quickly recognizes callers based on their phone numbers, addresses them by name and asks about recent or upcoming trips.

Personalizing interactions, continually making improvements and utilizing customer insights are key in this new, Commerce of Things world. Taking these steps can help transform transactional customers into loyal members – and take an online business to the next level.

By now, most manufacturers have heard of the promise of the Industrial Internet of Things (IIoT).

In this bold new future of manufacturing, newly installed sensors will collect previously unavailable data on equipment, parts, inventory and even personnel that will then be shared with existing systems in an interconnected “smart” system where machines learn from other machines and executives can analyze reports based on the accumulated data.

By doing so, manufacturers can stamp out inefficiencies, eliminate bottlenecks and ultimately streamline operations to become more competitive and profitable.

However, despite the tremendous potential, there is a palpable hesitation by some in the industry to jump into the deep end of the IIoT pool.

When asked, this hesitation stems from one primary concern: If we invest in IIoT, what specific ROI can we expect and when? How will it streamline my process such that it translates into greater efficiencies and actual revenue in the short and long term?

Although it may come as a surprise, the potential return can actually be identified and quantified prior to any implementation. Furthermore, implementations can be scalable for those that want to start with “baby steps.”

In many cases, this is being facilitated by a new breed of managed service providers dedicated to IIoT that have the expertise to conduct in-plant evaluations that pinpoint a specific, achievable ROI.

These managed service providers can then implement and manage all aspects from end-to-end so manufacturers can focus on core competencies and not becoming IIoT experts. Like their IT counterparts, this can often be done on a monthly fee schedule that minimizes, or eliminates, up-front capital investment costs.

DEFINING IIOT

Despite all the fanfare for the Internet of Things, the truth is many manufacturers still have a less-than-complete understanding of what it is and how it applies to industry.

While it might appear complicated from the outside looking in, IIoT is merely a logical extension of the increasing automation and connectivity that has been a part of the plant environment for decades.

In fact, in some ways many of the component parts and pieces required already exist in a plant or are collected by more manual methods.

However, a core principle of the Industrial “Internet of Things” is to vastly supplement and improve upon the data collected through the integration of sensors in items such as products, equipment, and containers that are integral parts of the process.

In many cases, these sensors provide a tremendous wealth of critical information required to increase efficiency and streamline operations.

Armed with this new information, IIoT then seeks to facilitate machine-to-machine intelligence and interaction so that the system can learn to become more efficient based on the available data points and traffic patterns. In this way, the proverbial “left hand” now knows what the “right hand” is doing.

In addition, the mass of data collected can then be turned into reports that can be analyzed by top executives and operations personnel to provide further insights on ways to increase operational savings and revenue opportunities.

In manufacturing, the net result can impact quality control, predictive maintenance, supply chain traceability and efficiency, sustainable and green practices and even customer service.

BRINGING IT ALL TOGETHER

The difficulty, however, comes from bridging the gap between “here” and “there.”

Organizations need to do more than just collect data; it must be turned into actionable insights that increase productivity, generate savings, or uncover new income streams.

For Pacesetter, a national processor and distributor of flat rolled steel that operates processing facilities in Atlanta, Chicago and Houston, IIoT holds great promise.

“At Pacesetter, there are so many ways we can use sensors to streamline our operation, says CEO Aviva Leebow Wolmer. “I believe we need to be constantly investigating new technologies and figuring out how to integrate them into our business.”

Pacesetter has always been a trendsetter in the industry. Despite offering a commodity product, the company often takes an active role in helping its customers identify ways to streamline operations as well.

The company is currently working with Industrial Intelligence, a managed service provider that offers full, turnkey end-to-end installed IIoT solutions, to install sensors in each of its facilities to increase efficiency by using dashboards that allow management to view information in real time.

“Having access to real-time data from the sensors and being able to log in and see it to figure out the answer to a problem or question so you can make a better decision – that type of access is incredible,” says Leebow Wolmer.

She also appreciates the perspective that an outsider can bring to the table.

“Industrial Intelligence is in so many different manufacturing plants in a given year and they see different things,” explains Leebow Wolmer. “They see what works, what doesn’t, and can provide a better overall solution not just from the IIoT perspective but even best practices.”

For Pacesetter, the move to IIoT has already yielded significant returns.

In a recently completed project, Industrial Intelligence installed sensors designed to track production schedules throughout the plant. The information revealed two bottlenecks: one in which coils were not immediately ready for processing – slowing production – and another where the skids on which they are placed for shipping were often not ready.

By making the status of both coil and skids available for real time monitoring and alerting key personnel when production slowed, Pacesetter was able to push the production schedule through the existing ERP system.

This increased productivity at the Atlanta plant by 30%. Similar implementations in the other two facilities yielded similar increases in productivity.

TAKING THE FIRST STEP

According to Darren Tessitore, COO of Industrial Intelligence, the process of examining the possible ROI begins with a factory walk-through with trained expertise in manufacturing process improvement and IoT engineers that understand the back-end technologies.

A detailed analysis is then prepared, outlining the scope of the recommended IIoT implementation, exact areas and opportunities for improvement and the location of new sensors.

“The analysis gives us the ability to build the ROI,” says Tessitore. “We’re going to know exactly how much money this will make by making the changes. This takes much of the risk out of it so executives are not guessing how it might help.”

Once completed, a company like Industrial Intelligence can then provide a turnkey, end-to-end-solution.

According to Tessitore, this covers the entire gamut: all hardware and software, station monitors, etc.; the building of real-time alerts, reports & analytics; training management on how to use data points to increase profits; and even continuously monitoring and improving the system as needed.

“Unless you’re a huge company, you really don’t have somebody who can come in and guide you and create a cost effective solution to help you compete with the larger players in the space,” says Pacesetter’s Leebow Wolmer. “I think that’s what Industrial Intelligence offers that can’t be created on your own.”

“It’s not a one-size-fits-all approach,” she adds. “They have some things that can give you a little bit of IIoT or they can take an entire factory to a whole new level. By doing this they can be cost effective for a variety of sizes of organizations.”

For quite some time, the term “machine learning” and “deep learning” seeped its way to the business language, especially when it is related to Artificial Intelligence (AI), analytics and Big Data. Frankly, the approach directed to AI which provides a great promise with regard to creating self-teaching and autonomous systems that can revolutionize various industries. 

What is Machine Learning (ML)?

One of the subfield of AL is machine learning. Here the basic principle is that machine, collect data and they learn it for themselves. No doubt, this is the most awesome tool of the business’s Artificial Intelligence kit. One of the interesting advantages of the ML is that you can easily apply the training and knowledge received from analyzing huge data set to perform various functions and excelling at them like speech recognition, facial recognition, translation, object recognition, and various other tasks.    

Compared to the hand-coding a given software tool filled with specific instructions which can be used for completing the task, the ML provides a suitable system to understand the pattern by itself and make the required predictions.

What is Deep Learning?

Frankly, a subset of the ML is called as deep learning. Here one utilizes ML techniques for solving various real-life issues, and this is possible by accessing the neural networks which easily help in stimulating the decision-making of human beings. In addition, deep learning is kind of expensive and one will need extensive data sets to train. This is because there are various number of parameters that one might need to have an understanding, possible by learning about the algorithm. Thus, this can be present at the initial stages and create various kinds of false-positives.

To have a fair understanding, let’s check how deep learning algorithm can be used for understanding how a cat looks. So, a huge amount of data set of pictures is used for underlying the basic details which separates the cat from other like panther, cheetah, fox etc.

How Machine Learning And Deep Learning Affects Job

There is a kind of hysteria of doom-and gloom surrounding the machine learning AI. The majority of it is all about how people will be out of work, as there are quite successful stories where machines were able to carry out specific job-related works and bought about extensive results in it.  

Indeed it has become a huge paranoia, but it turns out that machine learning only performs tasks, and not the job. Of course, many tasks constitute a job but ML programs are not much flexible.

However, it doesn’t mean that both machine learning and deep learning will not affect your job, as they have already done and will simply continue to do so. Most importantly, whether it will be a benefit or threat will depend on how you are going to react when you identify it.

No doubt, there are quite a lot of reasons on how white-collar jobs can be a great invitation for deep learning and other related technologies. There are various experts who feel that the professional impact which AI and deep learning along with other automated technologies can drastically affect the work force count.

Conclusion

In short, there have been certain reactions or changes with regard to how machine learning and deep learning brings. It has drastically reduced the role of various professionals who are considered as knowledge gatekeepers. Plus, there has been a positive trend towards proactive and reactive services. 

Antarctica inhabits a unique place in the human exploration mythos. The vast expanse of uninhabitable land twice the size of Australia has birthed legendary stories of human perseverance and cautionary tales about the indomitable force of nature. However, since those early years, Antarctica has become a rich research center for all different kinds of data collection – from climate change, to biology, to seismic and more. And although today there are many organizations with field stations running this data collection, the nature of its, well, nature still presents daily challenges that technology has had a hand in helping address.

Can You Send Data Through Snow?

British Antarctic Survey (BAS) – of recent Boaty McBoatface fame – has been entrenched in this brutal region for over 60 years, the BAS endeavors to gather data on the polar environment and search for indicators of global change. Its studies of sediments, ice cores, meteorites, the polar atmosphere and ever-changing ice shelves are vitally important and help predict the global climate of the future. Indeed, the BAS is one of the most essential research institutions in the world.

In addition to two research ships, five aircraft and five research stations, the BAS relies on state of the art data gathering equipment to complete its mission. From GPS equipment to motion and atmospheric sensors, the BAS deploys only the most precise and reliable equipment available to generate data. Reliable equipment is vital because of the exceedingly high cost of shipping and repair in such a remote place.

To collect this data, BAS required a network that could reliably transmit it in what could be considered one of the harshest environments on the planet. This means deploying GPS equipment, motion and atmospheric sensors, radios and more that could stand up to the daily tests.

In order to collect and transport the data in this harsh environment, BAS needed a ruggedized solution that could handle both the freezing temperatures (-58 degrees F in the winer), strong winds and snow accumulation. Additionally, the solution needed to be low power due to the region’s lack of power infrastructure.

 The Application

Halley VI Research Station is a highly advanced platform for global earth, atmospheric and space weather observation. Built on a floating ice shelf in the Weddell Sea, Halley VI is the world’s first re-locatable research facility. It provides scientists with state-of-the-art laboratories and living accommodation, enabling them to study pressing global problems from climate change and sea-level rise to space weather and the ozone hole (Source: BAS website).

The BAS monitors the movement of Brunt Ice Shelf around Halley VI using highly accurate remote field site GPS installations. It employs FreeWave radios at these locations to transmit data from the field sites back to a collection point on the base.

Once there, the data undergoes postprocessing and is sent back to Cambridge, England for analysis. Below are Google Maps representation of the location of the Halley VI Research Station and a satellite image (from 2011) shows the first 9 of the remote GPS systems in relation to Halley VI.

The Problem

Data transport and collection at Halley VI requires highly ruggedized, yet precise and reliable wireless communication systems to be successful. Antarctica is the highest, driest, windiest and coldest region on earth and environmental condition are extremely harsh year round. Temperatures can drop below -50°C (-58 °F) during the winter months.

Winds are predominantly from the east. Strong winds usually pick up the dusty surface snow, reducing visibility to a few meters. Approximately 1.2 meters of snow accumulates each year on the Brunt Ice Shelf and buildings on the surface become covered and eventually crushed by snow.

This part of the ice shelf is also moving westward by approximately 700 meters per year. There is 24-hour darkness for 105 days per year when Halley VI is completely isolated from the outside world by the surrounding sea ice (Source: BAS Website).

Additionally, the components of the wireless ecosystem need to be low power due to the region’s obvious lack of power infrastructure. These field site systems have been designed from ‘off the shelf’ available parts that have been integrated and ‘winterized’ by BAS for Antarctic deployment.

The Solution

The BAS turned to wireless data radios from FreeWave that ensure uptime and that can transport data over ice – typically a hindrance to RF communications. Currently, the network consists of 19 FreeWave 900 MHz radios, each connected to a remote GPS station containing sensors that track the movement of the Brunt Ice Shelf near the Halley VI Research Station.

The highly advanced GPS sensors accurately determine the Shelf’s position and dynamics, before reporting this back to a base station at Halley VI. Throughput consists of a 200 kilobit file over 12 minutes, and the longest range between a field site and the research station is approximately 30 kilometers.

Deployment of the GPS field site is done by teams of 3-4 staff using a combination of sledges and skidoo, or Twin Otter aircraft, depending on the distance and the abundance of ice features such as crevassing. As such, wireless equipment needed to be lightweight and easy to install and configure because of obvious human and material resource constraints.

In addition, the solution has to revolve around low power consumption. FreeWave radios have more than two decades of military application and many of the technical advancements made in collaboration with its military partners have led to innovations around low power consumption and improved field performance. The below image shows an example of a BAS remote GPS site, powered by a combination of batteries, a solar panel and a wind turbine (penguin not included).

FreeWave Technologies has been a supplier to the BAS for nearly a decade and has provided a reliable wireless IoT network in spite of nearly year-round brutal weather conditions. To learn more, visit: http://www.freewave.com/technology/.

You must have heard about the global cyberattack of WannaCry ransomware in over 200 countries. It encrypted all the files on the machine and asked for payment. Ransomware, which demands payment after launching a cyber-attack, has become a rising trend among hackers looking for a quick payout.

Recent events have highlighted the growing need for enhanced cybersecurity.

It’s not uncommon to drive about any major city at night and see many buildings illuminated despite the fact that the workers went home hours earlier. Likewise, manufacturing plants the world over often have equipment unnecessarily consuming energy during idle periods. Power plants create and store energy everyday and use energy distribution grids to distribute energy to users, but are they doing it “smartly?”

With rising concerns about global warming, this immense waste of energy undoubtedly hurts the environment, but it also hurts business. Offices, manufacturing plants, commercial spaces and power grids all stand to benefit financially from better and “smarter” energy management.

How IoT Reduces Energy Usage for Businesses and Manufacturing

In his article, “Report: Lofty Energy Management Goals Far Ahead of Reality,” (Panoramic Power, August 5, 2015) Jon Rabinowitz points out that most companies receive data on their energy usage only at the end of each billing cycle, which is usually a month at a time. By incorporating Internet of Things (IoT) technology, energy consumption data will be available in real-time, and energy-reducing measures can be implemented as soon as a problem gets detected (rather than waiting until the end of the month). Integrating smart devices through IoT technology will provide greater visibility into energy usage and help both industrial and commercial enterprises save energy, and as a result, save money.

Starting with simple, smart and low cost sensors, like User to User Information (UUI) and Feature Driven Development (FDD) devices, businesses can reduce energy usage and cost by dimming lights, turning off unnecessary equipment and improving the use the cooling/heating apparatus. Software that collects and correlates granular usage data, performs analytics and then converges information to increase efficiency will make manufacturing plants “smarter,” and thus more cost-effective.

Local and remote sensors that detect points of inefficiency quickly and perform triage to decrease waste will also reduce the need for maintenance as constant monitoring will detect small issues before they become big problems. Continuous optimization through 24/7 monitoring will assure that energy is not wasted during slow periods in between high-usage spans, while maximizing the use of energy-demanding equipment at critical times.

Specific Use Cases – Energy Production and Management

• General Electric’s Asset Performance Management software connects disparate data sources in power plants, enabling data analytics to guide energy usage and to increase efficiency (“10 Real-Life Examples of IoT Powering the Future of Energy,” Internet of Business, Freddie Roberts, Oct. 7, 2016).

• Duke Energy, a Florida-based electric power holding company, has developed a self-healing grid that automatically reconfigures itself when power goes out. Using digital smart sensors at sub stations and on power lines, the system automatically detects, isolates and reroutes power in the most efficient way when problems occur (Roberts).

• Pacific Gas & Electric Company is testing drones as a means to monitor and evaluate electric infrastructure systems in hard-to-reach areas. The ease of access will allow more frequent and consistent monitoring and drastically reduce the amount of methane leaks and other unwanted disruptions. (Roberts).

Energy Saving in the Auto Sector

Nissan (manufacturer of the world’s best-selling electric car, the Leaf) and ENEL (Europe’s second largest power company) have teamed to develop an innovative vehicle-to-grid (V2G) system that creates mobile energy hubs, which also integrates the electric cars and the power grid. The system allows Leaf owners to charge at low-demand, cheap-tariff periods, while allowing owners to use the energy stored in the car’s battery to power their home during peak periods, or when power goes out. Owners can store excess energy, or return it to the grid, making the entire system more efficient for everyone (“Nissan and ENEL to test first Grid Integrated Vehicles in Denmark,” Copenhagen Capacity, December 11, 2015).

Conclusions

As evidenced by these specific use cases, IoT technology is making energy-intensive systems in power generation and in manufacturing far more efficient. It’s good for the environment, but it’s also good for business. Intelligent implementation of energy saving technology stands to benefit every business, from small commercial enterprises to the largest power producing utility companies in the world. It’s time to make the move to smarter energy usage, for both the environment and for your bottom line.

Originally published on the Unified Inbox blog

About the Author

Richard Meyers is a former high school teacher in the SF Bay Area who has studied business and technology at Stanford and UC-Berkeley. He has a single-digit handicap in golf and is passionate about cooking, wine and rock-n-roll.

The widespread use of the Internet of Things (IoT) is systematically impacting worldwide growth in online transactions, and research from Gartner underscores that this trend shows no signs of waning.

This compounding growth in connected devices and their use in online transactions has created new challenges for merchants trying to stay compliant with a complex web of global ecommerce regulations that vary by country and state.

As merchants bear the burden of regulatory compliance, they need to be able to quickly adapt to changes to ensure competitive advantage and sustained success.

Take the popular “driver for hire” company Uber. A few years ago in India, Uber’s largest market behind the U.S., the government closed a loophole in a 2009 law. The amended law required two-step authentication (with verification codes sent via text or email) for any “card not present” transaction. In other words, the ease of the Uber app’s payment system was now illegal for the sake of added consumer protection.

This not only put the company at risk of noncompliance in India, but the change could have shut down the company’s operations in India altogether. Even though Uber acted quickly and updated its app, consider the potential negative consequences had it not been able to pivot: heavy fines, potential lawsuits or, even worse, allowing an opportunistic competitor to strategically enter the region. The ability to nimbly pivot when facing unexpected changes is what has, in part, given industry leaders like Uber market dominance.

This past November, the EU introduced legislation banning unjustified geo-blocking between European member states to boost ecommerce across the region.

Geo-blocking is a discriminatory practice preventing customers from making online purchases outside of their resident nation. With the new legislation, a consumer in France, for instance, can purchase goods off a German ecommerce site instead of being re-routed to the French site, where prices may be higher.

This measure was made to promote – rather than restrict – commerce in the EU , forbidding traders from blocking or limiting customer access to their online interface based on nationality or place of residence. And while the new legislation provides a tremendous advantage for the consumer, it forces merchants to adjust how they’d previously done business. Opening up the market, merchants not only lost their price discrimination leverage, but also had to ensure they updated their payment processing and other systems to avoid business disruption and remain compliant. Ultimately, those that are flexible enough to address these requirements will thrive over less nimble competitors.

One thing is certain for merchants: as consumers buy more online, merchants need to prepare for the unexpected. The previous examples just scratch the surface when it comes to adjusting for new ecommerce regulations. Many questions remain unanswered when it comes to commerce and consumer protection, namely: 

• Will products enabled with automated subscription services (think Tide detergent ordering replenishment pods) have a required notification period before an order is placed?

• Will a consumer’s electronic signature be required before an order is authorized, as in the Uber example above?

• Does information that is collected and related to health and wellness, such as fitness tracker/health band data, fall under the protection of additional medical regulations like HIPAA (in the United States)?

How merchants navigate this murky regulatory landscape is critical. Each new regulation can reset the competitive playing field, making flexibility a company’s most important asset.

Companies have every reason to be opportunistic as regulations shift and new opportunities arise. The trick is to put your company in a position to turn the inevitable complexity of global commerce compliance into a competitive advantage – something that may be giving merchants headaches now, but will be well worth the pain once the groundwork has been laid.