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With everything connected, will humans be even needed in logistics and supply chain? Will connected supply chain technology applications simply speak to each other and update all the data? Will we usher in an era of no process and all strategy? We surely hope that strategy for transportation management is the focus. Who has time and money for human INPUT error? After all, the internet of things is all about process efficiency to decrease costly human error.

TMS integrated to ERP which talks to the Robotics picking items and the WMS and the YMS and so forth and so on. The Internet of Things, like the White Walkers in Game of Thrones, is coming to manufacturing, supply chain, and logistics. Are you and your fellow “Night’s Watch” supply chain and logistics managers watching the Internet of Things and how it will affect the world of logistics as we know it? We certainly are here at Cerasis, and we found this great list and video of 10 things you should know about the Internet of Things today from The Digitalist Magazine. 

10 Things about the Internet Of Things that Supply Chain and Logistics Managers Should Know

The Internet of Things (IoT) is becoming a hot-button issue for the C-suite. Many senior leaders are concerned whether implementing IoT-based technology and processes is worth the time, money, and effort involved. Others worry they risk being left behind and losing their customers to competitors if they avoid it altogether.

In fact, Gartner found that 64% of large enterprises plan to implement big data projects. Sounds promising, right? Not really – considering 85% of them will be unsuccessful.

All of this data needs to go somewhere – but where?

During the America’ SAP Users Group (ASUG) IoT webcast “Operationalizing IoT Data for Predictive Analytics, Dave Roberts, OSIsoft fellow specializing in cities and industrial clusters, observed that complexity in the IoT is attributed to technologies that support a wide variety of standards that seem to be emerging in the IoT space. “There’s AllJoyn, Thread, IEEE, Open Internet Consortium (OIC), Industrial Internet Consortium (IIC), among others, that are promoting different standards on how sensors and assets will communicate with gateways and routers,” he explained.

As a result, businesses are spending 50%–80% of their development time just prepping their data – collecting, cleansing, shaping, backfilling, and timestamping all of this information. Some are even going as far as creating a new job title –“data engineer”– responsible for getting this data together and shaping it so data scientists can accurately answer critical business questions with this information.

10 things Manufacturing Companies Need Consider when Operationalizing the Internet of Things

If so many companies understand the value of the IoT and are investing considerable time, money, and effort to realize its potential, why are so many still failing to achieve it? Dave Roberts sheds some light on why they are missing the mark by offering his Top Ten list of what every company should know about successfully operationalizing the IoT.

1. The value of the IoT is not technology. The real value lies in the creation of new value propositions and potential revenue streams. The key is taking this technology and using it to move toward new business models and services that will help realize them. According to leading analysts and thought leaders, the growth potential is significant. IDC believes the IoT market will hit $7.1 trillion in revenue by 2020. Gartner foresees the IoT install base growing to 26 billion units by 2020. And Cisco predicts that the IoT is poised to become a $19 trillion market.

2. IoT data will be more democratic than SCADA data. Historically, SCADA data has been locked away in somebody’s process control network. To access this information, update it, and revalidate it, people needed a miracle. With IoT, you can freely and quickly bring up this information when and where you need it. This one aspect is revolutionizing business models, allowing businesses to enhance their services in real time.

3. Businesses outside of your industry may know something you don’t. For example, highly powerful tools developed for clickstream analysis, fraud detection, cyber security, and genome sequencing are now coming to process industries. Don’t snub other industries, thinking that you are different from them. They may have a few tricks in their pocket that you need.

4. Standardization leads to repeatability. The more comparable assets are in your organization, the better your forecasts will be. Machine learning is better with more, similar data. Anything less leads to misconstrued information and inefficiency.

5. IT and OT are converging – deal with it. Data engineering can take significant time and resources. However, it shouldn’t stop you from moving forward with IoT initiatives. Instrumentation and controls engineers from the world of operational technology (OT) have to bridge the gap between the analytics and IT communities.

6. Sensors will not live forever. In other words, cheap sensors are not going to be 100% reliable, 100% of the time. Physical damage during normal maintenance and operation in hostile industrial environments (such as dust, vibration, water, and caustic materials) will occur. Even sensor batteries can discharge. Ultimately, all sensors fail either instantaneously or slowly degrade. Processes must be established to make sure sensors are fully operational and deliver correct data.

7. Your information is as good as your sensors. Reliability of predictions is only as good as the data feeding them. If you are going to run analytics based on sensor data, you better make sure that the sensor is in good working order. At times, you even have to go as far as validate the sensor data before it is reported or analyzed to answer critical business questions.

8. Data needs context. To develop a model that forecasts behavior, data scientists require context and time-series data. Otherwise it becomes very difficult to consume this information and truly see what happening now and in the future. People need real-time data to make the best possible decisions. With pervasive monitoring, this information is captured and delivered for business intelligence analysis.

9. The IoT brings a tsunami of data. IoT rollouts bring a proliferation of cheap, distributed sensors – resulting in a huge volume of data in a short amount of time. Is your infrastructure ready to support it?

10. Don’t forget what powers the IoT. Data integration and actionable information are the heart of collection and analysis of IoT data. Invest in the technologies, expertise, and processes that support integration, reporting, decision making, and action – and maintain them well.

How are you looking at using the Internet of Things for your manufacturing company? Tell us in the comments below!

The list of relevant applications of the Internet of Things (IoT) era technology across multiple industries and market segments continues to grow. Current and future applications have the potential to provide new methods of value creation and sources of revenue streams for companies in the digital age. For supply chains, this advancing technology enables the building of a framework in which rapid responses and solutions in an increasingly intricate network can be designed and implemented quickly and easily. This advancement is based on the potential to integrate relevant data at any point in the value chain, define inter-dependencies from the data almost instantaneously, and utilize advanced analytics to develop highly targeted solutions.

11 Improvements by the Deployment of the Internet of Things in the Supply Chain

Thus, in the global supply chain, exploiting the opportunity presented by the Internet of Things technology can improve:

1. revenue growth,
2. asset utilization,
3. waste reduction,
4. customer service,
5. profitability,
6. sustainability,
7. security,
8. risk mitigation,
9. working capital deployment,
10. agility and
11. equipment uptime.

For many businesses, this means partnering with a third-party logistics service provider (3PL) such as Flash Global that has already integrated evolving technology into its holistic, comprehensive logistics services.

Cerasis embraces IoT-type technology, such as integration, as an interconnected, intelligent network that combines together many tiers of contract manufacturers, suppliers, service providers, customers, and distributors, regardless of their geographical location. Data created, processed and analyzed by strategically distributed devices and systems in the chain significantly reduces visibility gaps and introduces tremendous flexibility into the production chain. Deployment of the Internet of Things technology within the chain has significant potential to drive advancement in:

• Evolving solutions support to simulation.
• Predictive capabilities and modeling to reduce costs.
• Improve service levels.
• Improve quality levels in real-time.

Smart devices and systems with embedded intelligence can make critical decisions and adjustments in response to complex scenarios, and this in turn enables managers to focus on improving global capabilities through better orchestration within the network. Currently, business processes that use static data structures and analysis will need to adapt in order to maintain the competitive edge and pursue new value creation. The Internet of Things devices and systems have the ability for continuous monitoring that can sense constraints and produce intelligent responses almost instantly with the guidance of an intelligent network or autonomous system. This leads to greater opportunities for cross-enterprise and cross-industry process innovation and optimization, which contemporaneously drives cost containment while decreasing time to market.

Ability for Decision Making in the Internet of Things Supply Chain

The decision-making capacity of smart devices within an IoT-enabled network also affects the overall supply chain structure. Traditional supply chain tasks in procurement, planning, logistics and supplier management would be streamlined by intelligent, data-driven systems in a collaborative multi-enterprise environment. While logistics managers may need to acquire an enhanced skill set, their primary functions would be focused on designing capability and network optimization, inter-enterprise collaboration, disruption and risk mitigation, and supply chain orchestration in an effort to exploit competitive advantages and differentiation.

Having the capability to track raw or finished materials and the associated features such as count, type and geographical data with the Internet of Things technology through an entire life cycle from a tier-n supplier to the final consumer will have a positive influence on inventory management, sourcing strategies and logistics costs. For instance, when a supplier cannot deliver on time, that event could trigger an automatic search for an alternate supplier within the interconnected intelligent system. This would ensure no disruption in the production schedule, customer service or revenue stream.

Another example might be a situation in which production constraints might delay delivery of raw materials by 3 days to a proprietary supplier. The IoT-enabled system would sense the upcoming delay and make adjustments to the material delivery schedule to include other suppliers. Those suppliers would have the opportunity to route the raw material to other clients, thus enhancing the revenue stream and working capital for the network. The production site would obtain automatic data regarding the delay in raw material, and it could adjust production and machine schedules for optimization. Raw material and fixed asset utilization would be enhanced as asset demand and availability are matched more consistently. Moreover, supply chain risk mitigation would improve through the continuous monitoring of supply status, and disruptions would receive a response in real time.

In addition, the capability to sense demand for finished product by using embedded intelligent devices will enable the supply chain to automatically match available finished product across multiple distribution facilities with sales channels indicating current demand. If no inventory is currently available, the system can check raw material availability and manufacturing capacity, leading it to send an automatic production trigger to the appropriate site. This continuous, seamless matching of supply and demand will positively affect profitability, revenue, and customer service while concurrently optimizing the inventory of finished goods. Moreover, areas of the supply chain such as spare parts and maintenance would see significant streamlining and improvements, and real-time monitoring of machines and equipment would drive predictive maintenance schedules and minimize machine downtimes.

Thus, as standards and technology advance, the Internet of Things devices and systems provide a critical competitive edge through linking actuators, sensors, embedded intelligence, advanced analytics, systems and people. Supply chains that embrace this technology will differentiate themselves easily and quickly from the rest of the crowd.