S U C C E S S I N IOT MACHINE LEARNING
C A P I TA L I Z I N G O N IOT CONNECTIVITY HOW TO TRANSFORM M A N U FA C T U R E R S I N T O SERVICE PROVIDERS
THE REAL VALUE OF PA R T N E R I N G W I T H A N IOT E N A B L E R
ISSUE FOCUS
K E E P Y O U R IOT S Y S T E M S FROM ENDING UP ON S E C U R I T Y B LO G S
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The Kopis Edge
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From the CEO's Desk A N D R E W K U R TZ
Success in IoT Machine Learning K E V I N W E N TZ E L
Keep Your IoT Systems From Ending Up On Security Blogs
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Captializing on IoT Connectivity How to Transform Manufacturers Into Service Providers AD AM D R EWES
C H R I S S M I TH
Copyright @2018 by Kopis and The Brand Leader. All foreign and U.S. rights reserved. Contents of this publication, including images, may not be reproduced without written consent from the publisher. Published for Kopis by The Brand Leader.
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The Real Value of Partnering with an IoT Enabler B Y A N D R E W K U RT Z
In its simplest form, the Internet of Things ( IoT ) enables devices to collect data, provide information, and respond to requests for action. •
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A N D R E W K U RT Z P R•E S I D E• NT &• C E O andrew.kurtz@kopisusa.com
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IoT then connects these smart enabled devices via the Internet to a centralized place where all of the data can be easily viewed, digested, and acted upon, either by people or AI. Through this ongoing collection and distribution of data, the devices become smarter about the way they function and how they’re used. Smart thermostats are a common example. We used to set our thermostats to a certain point. Perhaps we could bump the set point up or down if we were going out of town—but only if we remembered. Now, with smart thermostats like Nest on the market, we can control temperature remotely, set timers for the temperature based on our daily routines, get information back from the device, see data trends, and make decisions that increase the home’s energy efficiency. More and more devices are becoming smart enabled and being added to the IoT—working together, manufacturers and IoT enablers like Kopis are discovering value where people would not have imagined that value existed even five years ago.
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3 Strategies to Enter the IoT Space with Maximum Results and Minimum Risk. Of course, exponential growth creates growing pains. As manufacturers attempt to convert more traditional devices into the IoT space, concerns about data management, data visualization, device security, and network security are also on the rise. Kopis developers, and our partners at Zipit Wireless, work alongside manufacturers who want to explore the possibilities of smart enabled devices, helping them get their devices to market quickly with the least possible risk.
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In our work as IoT enablers for clients such as Hitachi and even our own company, Vigilix, we’ve come up with a few tips that help companies enter the IoT space with fewer challenges along the way. Prioritize Security.
First tip: Practice the Lean Startup concept. Instead of spending your time trying to understand all aspects of IoT, partner with knowledge experts so you can focus on what you do best and get to your first product iteration quickly.
There is no cookie-cutter approach to creating an IoT device. I’ve mentioned that Kopis helps make the information you’ve gathered consumable, but that means vastly different things depending on the device. A smart thermostat will need to collect and report much different data than a smart camera, for example. Some IoT devices may need to summarize massive amounts of data and respond on their own, while other devices should only respond to user input.
Finally, security is, perhaps, even more important than figuring out visibility and how to consume data. Manufacturers need to make their devices as secure as possible upfront; you can iterate through software updates and visualization as you learn what your users are doing with the data and how they’re interacting with the device, but it’s difficult to regain trust after a security breach.
As an example, Kopis, and our partners at Zipit, are both IoT enablers, and together we can offer clients a fully integrated platform to test, build and run their products with as little investment as possible each step of the way. Having someone like Zipit to handle connecting your device to the internet and managing the carriers means you are focusing on what features on the physical device will be most valuable to customers. Similarly, on the software and cloud side, building a new software product from the ground up to be secure, scalable, and have all the functionality your users expect is a daunting challenge—let alone if you need to pivot after the first customers get their devices. Essentially, partnering with companies that bring a platform & experience to the table, help you iterate quickly to a successful version 1 product without the startup shortcuts.
When creating a new IoT device, it’s important to consider the best way to consume the data. This is an area where a knowledge partner like Kopis can be a true valueadded to the final product. We can help you figure out what you have, what data is meaningful, and what should be made visible and actionable—which, again, will be different for each device. As more devices become smart enabled, the real value will be in figuring out how to use the data that’s created to improve lives, improve finances, and find more economical, efficient ways to work.
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Consider the Goal—And the End User.
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If data security isn’t your area, then you need to partner with an expert to secure your device. Zipit partners with manufacturers to secure the device itself, while Kopis can work with you to connect the device to a centralized infrastructure and secure the user portal. That is a critical place to secure, because an attacker who accesses the portal can get access to multiple devices.
By following these three best practices, manufacturers can enter the IoT space and find success without having to build a development team from the ground up or risking their customers’ data.
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Success in IoT Machine Learning BY KEVIN WENTZEL
"Big Data" was one of the hottest terms in business technology a few years back. One of the major drivers behind "big data" was the increase of internet-connected devices that allowed businesses to grow and diversify complex datasets around device usage.
Machine Learning Since this time, there has been an accelerated boom in the number of internetconnected devices worldwide. In fact, it’s gone from approximately 15 billion in 2015 to more than 23 billion in 2018! This growth has major value implications for businesses, and many businesses are already using their vast data repositories as means of setting valuation and leveraging further financial gain through data-sharing partnerships and reselling analytics to suppliers and customers. However, managing this "Internet of Things" (IoT) is quite challenging, as these types of datasets are often too complex, large, and fluid for a human to effectively interpret.
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The solution to this problem is one of the most significant advances in recent business technology: machine learning, which allows businesses to understand, interpret, and act on these vast datasets. Create Customer-Centric Product Roadmaps allows you to effectively crowd-source your ongoing development without expensive user research studies. Another example would be to use machine learning algorithms to adapt to changing market conditions on the fly. As new trends and conditions are detected, machine learning can help you identify these trends and make recommendations for improvement— for example, recommending new configurations to the end user based on the success of others.
For example, device data can be collected and analyzed by machine learning algorithms to pinpoint the mostand least-used features of a software application or mobile app. This insight is especially effective when it comes to releasing new updates and features, as it
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When it comes to implementing machine learning in your business, the key to success is to create a product roadmap that meets the needs of the customer.
Use Machine Learning to Detect Anomalies Early For example, machine learning could help you detect whether devices on a particular software version or connection type tend to fail faster, allowing you to perform predictive maintenance to patch or upgrade systems before they fail.
Nine times out of ten, keeping devices and equipment up and running revolves around telemetry data—things like log messages and measurements (connection speed, battery status, temperature, etc.).
Security is probably the most relevant way that machine learning can help businesses today detect intrusion or fraudulent activity. For example, the temperature of businesses sensors may all vary in a similar manner. So when one sensor is too static, it could indicate a security compromise or other anomaly. Or, for example, machine learning could detect a device sending massive amounts of data significantly above the activity of similar devices.
The ability to detect issues and problems without manually monitoring telemetry data is hugely valuable for businesses, and allows you to be proactive in resolving issues before you hear about them from your customers.
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Energize Data-Driven Decision Making Techniques like NLP, unstructured data, and the digitizing and consuming paper documents are only useful if a real person can ultimately use these methods and make decisions based on the results. This is a key driver behind why machine learning is now focusing not just on the data analysis but also on how to make human interaction with data easier. Natural language processing has become a larger part of solution design and now allows humans to ask relevant and compelling questions of machinelearning algorithms. For example, a user might ask which product line generated the highest profits in Q2 of 2018, and machine learning could generate a chart of profitability by product in Q2 2018. Another exciting area developing in machine learning is through helping improve the ability to make data-driven decisions through the breakdown
and consumption of unstructured data. For example, this would typically involve something like a Facebook feed or other highly varied text-based information source. Machine learning can take unstructured data like this and identify common elements and trends in the text. This is useful for monitoring things like user sentiment towards your products and services. Finally, an obvious, but often-overlooked, way that machine learning can energize a data-driven culture is by helping your business digitize without disrupting normal business operations. The primary mechanism for this is using optical character recognition (OCR) to turn scanned documents into digitally readable and searchable documents. This allows for digital archiving, which saves physical space and creates a reliable method for future retrieval.
Develop 21st Century Thinking Every business needs to have a plan for how digital information can help drive decision making. Hardware is rapidly becoming cheaper and more readily available through cloud providers, and software is becoming more powerful and efficient. Leveraging machine learning to analyze data even just 5–10 years ago would have been a major undertaking, but today implementing a machine learning solution takes relatively little upfront capital and can sometimes be implemented in as little as a few days.
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The trend towards data-driven decision making started decades ago with the development of softwares like Microsoft Excel, and more recently through concepts like data warehousing. As with most technologies, data analysis is evolving rapidly, and businesses that refuse to evolve and adopt a new mindset will eventually lose ground to more forward-thinking competitors who know how to use solutions like machine learning to their advantage. So, how will your business adapt?
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Machine learning can help energize a data-driven culture by helping your business digitize without disrupting normal business operations."
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Recently a popular IP camera vendor discovered a major vulnerability. A complaint alerted the company that users could see other camera feeds when they logged in to view their own.
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Security researchers found that the cameras used serial numbers to authenticate to the user dashboard, and an assembly line glitch had given two cameras the same serial number. Even worse, security researchers found they could manipulate serial numbers so their camera mimicked any other camera. This slip speaks to a larger problem in the industry: Too often, security is assumed when there’s no screen or browser. While there are some special considerations for IoT, most of these hard-won rules and practices can be carried over from the web world. Fortunately, the National Institute of Standards and Technology has a helpful framework for evaluating different aspects of cybersecurity, comprised of 5 parts: Identify, Prevent, Detect, Respond, and Recover.
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Identifying the risks in each part of the system should be the first consideration. For IoT systems evaluating the risks can be broad, including the device operating system, the application software, the network that the device runs on, and finally the system that takes in data. Really, we need to be honest about these risks, not because we're pessimists (I swear I'm not!), but so we can move on to the next part: Prevention.
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Encrypt Data Most organizations claim to encrypt, but I find many encrypt data only at rest. This isn't enough, since the value of an IoT system is data flowing in and out. Data should be encrypted on-device (if possible), in transit from the device, at rest, and in transit to end-users. Each stage gives an attacker opportunity to view things they shouldn't, especially on someone else's network. Segment User Data Another major issue for the camera company— each camera wasn't strictly associated with a user. Any user could view any camera by knowing its serial number. This may seem like decent security if serial numbers aren't sequential, but it wouldn't take long for attackers to write a script to cycle through and test all the possible combinations.
Prevention Now that you’ve identified risks, how can you mitigate them? There are several effective steps: Streamlined Workflows This simple process saves so many headaches. Keeping an inventory of all the devices you have online allows you to prevent two devices from having the same serial number and track of what kind of device, and capabilities, are associated with each. A good Device Management System would have helped our camera company avoid overlapping serial numbers. Taking this step also helps later, in Detection.
You may not be able to completely prevent compromised data, but by segmenting both the input and output, you can minimize the damage.
Detect This is where the rubber meets the road. You cannot respond to a breach or attack without knowing it exists!
Authenticate Devices The old adage trust, but verify applies. How do we know it's actually our device talking to the system? Typically, authentication requires two parts: Who you claim to be and proof for that claim. For most websites, this is accomplished through a username and password. However, in the device world we don't have the luxury of a user sitting in front of a keyboard. Both Azure and AWS give devices a unique ID which identifies the device so the system knows the who part.
Monitor Errors Logging errors is low-hanging fruit that pays huge dividends. In the camera example, the end user website displayed an error when the two different users tried to use cameras with the same serial number. If this was being logged and reported, it could have been caught earlier. Monitor for Anomalies Both cloud IoT platforms include basic monitoring; with a little work you can also display any anomalous readings. For example, is the device sending a lot more data than usual? It may have been hacked and is now part of a botnet that's DDoSing some poor website. Is it sending readings that are out of the norm? It may have been physically tampered with. Was it using an IP address in the US a couple hours ago and now one from China? Someone may be imitating the device and probing for vulnerabilities.
For the password, devices are usually given a cryptographic certificate. This is like a more secure password, verified by a chain of trust. For additional security and ease of management, you can provide your own certificate authority (CA) that verifies only you are allowed to provide certificates to devices. In our camera example, this would have prevented users from being able to claim they were device 12345 when they had credentials for device 67890.
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A good response usually takes the form of closing one of the avenues of attack: the device itself or the system used to manage it.
I hope that IoT vendors follow this step most of all. Making security mistakes is easy, but what matters is how you respond and learn from them.
Deprovision Devices Just like taking a compromised server offline, you should be able to stop a device from communicating with your system. This allows you to minimize the damage that a rogue device can do, both to your own system and any other systems in the case of a DDoS attack. Cameras with duplicate serial numbers should have been immediately deprovisioned until further analysis was performed. Revoke User Access On the other side, you should be able to revoke access to bad actors if your system has been compromised. This capability cannot be understated. Do you want to be scrambling to figure out how to remove bad data quicker than an attacker can add it? Both users in the camera scenario should have had access revoked as soon as it was detected that they were accessing something they shouldn't have, giving researchers more time for investigation and mitigation. Practice All of the Above The best responses are useless if your team isn't adept at running them. On the teams I've managed, we regularly run practice drills for these and other operational scenarios in a test environment. It makes the real thing much less stressful for all involved, which in turn leads to fewer mistakes when it matters most. In our camera scenario, it was clear by the PR confusion and lax response that this company had not practiced responding to a security vulnerability.
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Your team should do a postmortem, determine the root cause, and incorporate changes to the Prevent and Detect stages. Changes should happen iteratively each time an issue arises. Make it part of your organizational culture to incorporate these processes and you dramatically reduce the chances that your IoT system will end up on a security blog.
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Over the past few years, it has been a common theme to see product creators and manufacturers transforming, pivoting, and constantly re-inventing themselves to achieve digital transformation and modernization. One of the biggest drivers behind this evolution is the reduction in the physical size and cost of sensors, devices, and connectivity that now make it easier to create "smart products" and "smart devices". For example, you may have seen a smart toaster released last year.
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How Product Creators and Manufacturers are Capitalizing on IoT Connectivity From a consumer’s perspective, buying a smart product really only matters if there is something to be gained from its connected nature, and product manufacturers would do well to always keep this in mind. A device or product has to be easy to use and connect and should be quick to demonstrate its value. Many times a product’s value is simply in its ability to deliver superior convenience to the end user.
One of the key requirements in all of these product developments has been that they require an interface to allow access for internal and external users. For example, this access would be required when provisioning a new device to bring it online or in exposing analytics and received data to relevant users.
So how are you leveraging the power of IoT connectivity in your products and business? And how are you ensuring that you deliver value to the end user while gleaning commercial value in return? Here are some ways that IoT connectivity is benefiting product creators and manufacturers today.
Other business forces behind this trend include:
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Simplification Through Remote Management One of the most basic use cases for the value of IoT connectivity is the ability to manage products and devices remotely. It can be as simple as being able to see a device’s status, interact with it in some way, or push an update to it. For example, there are huge benefits in being able to remotely manage things like thermostats, security cameras, lights, locks, and more. Remote management has significant commercial applications as well.
For example, businesses may need to access devices in difficult-to-reach places or highly distributed networks of sensors that would be difficult and time-consuming to manage individually. The ability to pull telematics for troubleshooting and performance measurement, as well as pushing automated software updates, will drive the overall efficiency of a commercial product line.
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Delivering Value Through Asset and Activity Tracking Activity tracking has become extremely popular in recent years through the proliferation of fitness trackers and smart watches. For these types of devices, the focus is on tracking steps, heartbeats, and—in some cases—a user’s location. End users use this data to help monitor and improve their physical fitness, while the data collected can be used to further improve the product and deliver valuable data on usage. Commercially, there are far more implementations of asset and activity tracking that are viable than in the consumer space. For example, consider the value in being able to track a package or shipment. Fedex, UPS, and USPS are now all offering services that show you not only an estimated delivery date, but also the stages and progress of the transport. This same concept has a major influence on manufacturing and distribution organizations. Data can be used for inventory management efficiency.
For example, based on sales forecasts and historical delivery times, new items can be ordered automatically when needed to ensure adequate stock at all times. There are even applications that use direct location tracking. For example, it is now fairly typical for a golf clubhouse to be able to see on a map every golf cart’s location, battery level, originating tee time, and expected pace. Consider the implications of this same model in businesses like IT managed services, HVAC, and electrical or in organizations like EMS and law enforcement. Safety is another area where data collected from IoT devices and products can deliver value. Consider being able to monitor where a vehicle or piece of equipment has gone (restricted or unapproved areas) or accelerometer data to determine whether harsh braking or cornering has occurred. Vehicles can also be equipped with speed sensors, and some can even monitor how loud the music in the vehicle is.
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Continuous Improvement Through Performance Measurement Manufacturing companies have been using IoT performance measurement since before IoT became a popular term. For decades, they have been pulling information from production lines based on speed and quality, seeking to optimize both. A more modern innovation in performance measurement is now taking manufacturing to new levels via gamification. This is currently more common for consumer applications, but can also be relevant in B2B. Fitness trackers commonly show
your step counts against your peers or similar users. This is designed to motivate behavior and further improve perceived health and fitness. Similarly in manufacturing, data can be collected and aggregated in near real-time across multiple plants and locations and show on dashboards designed to drive motivation and competition within an organization. This need not apply only to companies that make and ship widgets, but can even be implemented in industries like retail. It’s becoming easier and easier to combine data between points of sale, ERP systems, and other secondary systems across multiple locations to build real-time visibility into performance. Imagine the benefits of an owner of several franchise locations being able to quickly see the total sales, expenses, transactions, and inventory in near real-time across all locations.
Maximum Productivity Through Predictive Maintenance
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A recent trend in business technology is to use IoT connectivity to help prevent unexpected downtime through preventative maintenance. For example, consider how a car’s computer collects data. There are a multitude of data points that can be collected to monitor the mechanical performance of a vehicle, from acceleration to coolant temperature, engine load, miles per gallon, and more.
models to continuously monitor and predict when maintenance should be performed. Some vehicles are already self-diagnosing. But imagine your car— or more likely an app connected to your car—letting you know that the transmission fluid needs to be flushed. By knowing exactly what needs to be done, you can rest assured that you are not unnecessarily spending money at the service center.
These devices typically have access to the car’s computer and the relevant fault and error codes that cause check engine lights to come on. Today, these errors and their meanings can also be fed into AI/ML
Now think about how this model of IoT connectivity can be applied more broadly in other applications and products. The opportunities are truly limitless!
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Your Opportunity is Knocking Industries across the globe are being disrupted by unique applications of IoT that are leveraging data collection and AI/ML. Hardware and software have progressed to such a point that
unique solutions are now only limited by our own imaginations. Innovation always leads to opportunity. What opportunities can IoT connectivity help you realize in your business?
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• • • Transform Manufacturers • • • Into Service Providers
The Internet of Things (IoT) has become a lot of things to a lot of people. For consumers, IoT can mean smarter homes, energy savings, better security, convenience, and more responsive services. For Smart Government, it can mean connected cities, better transportation, and a stronger infrastructure that creates jobs and attracts business.
U S I N G
g IoT to sform
I O T T O T R A N S F O R M
Manufacturing is one industry where IoT-enabled devices have opened up the possibility of an entirely new business model addition: Service Provider.
Service for enterprise equipment, such as industrial AC units, has traditionally been managed through a large Enterprise Asset Management system (EAM). Asset management has always been expensive and inefficient. Work tickets, planned maintenance, unplanned maintenance, and all of the other service activities that ensure your assets are operating at their best took a lot of time and required a lot of testing and guesswork.
The Rise of IoT in Manufacturing and Asset Management Enabling technologies makes it easier for manufacturers to also service the devices they sell, driving a new revenue stream. Gathering the data means that the manufacturer can now manage the devices they install more efficiently.
Through IoT-connected devices and user-friendly data visualization dashboards, manufacturers can monitor all of their devices close to real-time and take action quickly if something goes wrong. At the same time, the cost of the hardware and the software for connecting products has been steadily dropping, making connecting products to the IoT more and more attractive, even for lower cost products. For example, 20 years ago enterprises may have only invested in sensors for their most expensive or most risky assets, such as Internetenabled nuclear plant data. Now, consumers are buying Internet-connected refrigerators, and the Raspberry Pi computer, which costs just a couple hundred bucks, has plugs and pins that can connect nearly any device to the Internet. It should come as no surprise that the B2B and manufacturing worlds are following suit.
Through IoT-connected devices, manufacturers can monitor all of their devices close to real-time and take action quickly if something goes wrong.
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Improve Service Quality Over Time. AI plus human ingenuity is a powerful thing. With IoT-enabled devices, manufacturers can look at the trend analysis, look at the data, and deliver a better value and more efficient service to the customer. In my industrial AC example, a manufacturer who decides to provide ongoing service may discover that the service interval is not optimal. In a more mild climate where the unit gets minimal use, they may decide to extend the time between service, whereas in a hot climate or at a plant with poor air quality, they may decide to increase service. In either case, they are now able to tailor their service to the environment and needs of the customer.
Create Monthly or Yearly Recurring Revenue. In addition to creating a new revenue stream, becoming a service provider gives your business a new kind of revenue stream. Recurring revenue is not only a primary driver of valuation, it’s also helpful from a cash flow standpoint, delivering a consistent, flat source of income.
Want to learn more about how IoT can transform your organization? Contact Kopis for a consultation or go to www.kopisusa.com/iot.
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Stay in Contact With Customers.
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Deliver a Better Customer Experience and Eliminate Risk.
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T O
In addition to opening up a new business model for manufacturers, enabling IoT devices has additional potential benefits to consider:
Becoming a service provider also has tremendous business benefits, such as the ability to develop an ongoing relationship with your customers. If a manufacturer sells a commercial AC unit with a mean time to failure of 15 years, it’s unlikely that any relationship will form. With a service contract, the manufacturer can be in frequent contact, stay in touch with clients, and lay the necessary groundwork for future sales.
Perhaps most importantly, becoming a service provider can improve business operations for your customers. From the customer’s perspective, it’s much better to have steady, predictable service costs—the service contract becomes a win-win as long as the value hits the right point. Selling commercial AC as a service, for example, means that the customer won’t have to capitalize any equipment and eliminates surprise costs that could otherwise kill their month or their quarter.
The Bottom Line Due to the better, more tailored service and the elimination of risk, many businesses are willing to pay a little bit more for their service upfront, knowing it will save them time and frustration later. If you’re a manufacturer, enabling IoT devices can help you deliver the kind of experience B2B customers are beginning to expect and transition toward opening a service revenue stream or automating and enhancing the one you already have.
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411 University Ridge, Suite 230 • Greenville, SC 29601 kopisusa.com
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