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Why Most Industrial IoT Implementations Fail

The IoT Revolution is picking up speed to change the manufacturing world forever. But digital transformation doesn’t happen overnight: it’s an evolutionary journey from today’s practices to tomorrow’s that requires a roadmap to follow.

Posted: May 14, 2018

In Industry 4.0 (IoT), instruments and machines in the factory connect through cyber and physical system components of the Internet, creating a smart factory network. But many IoT projects go over budget, deployment times run long, interoperability issues occur across legacy platforms or planning and resources aren’t allocated appropriately, leading to their cancellation. This failure rate leads to greater hesitation for manufacturers to embark on their digital transformation journeys. So what's the key to success?

The IoT Revolution is picking up speed and as it does, it is changing the manufacturing world forever. The Industrial Internet of Things (IIoT) brings together machines, advanced analytics and people. It’s the network-connected assets and devices by communications technologies that results in systems that can monitor, collect, exchange, analyze, and deliver valuable new insights like never before. These insights can then help drive smarter, faster business decisions for manufacturers.

Despite the undeniable impact IIoT is having on the manufacturing sector, how seriously are manufacturers about moving forward with IIoT implementations and what do their IIoT roadmaps look like? Look no further than the findings from Accenture’s latest IIoT trend study (Digital Industrial Transformation with the Internet of Things, 2017):

  • 72 percent of the companies will increase their IoT spending in the next three years. A solid amount of companies plan to keep this increase between 10 percent and 30 percent, while some of them are willing to raise spending by more than 30 percent.
  • 60 percent of the companies are already involved in IoT initiatives. More than half of these, however, are still in the early stages of deployment and have some ongoing IoT projects.
  • Cost reduction is seen as the biggest driver of moving IoT initiatives forward for 69 percent of the companies. However, the fact that product improvement and development of new business models took second place on the list of drivers shows how IoT investment can be channeled towards driving top line growth rather than just reducing costs.
  • Investment decisions for IoT solutions are mostly made within IT departments but line of business executives also have considerable influence. This, however, largely depends on the country in question and the scale of the projects under consideration. Data security and privacy concerns top the list of challenges that are slowing down IoT adoption for 70 percent of the companies. Apart from fears of cyber attacks, there are also mounting regulatory burdens, especially ahead of the General Data Protection Regulation (GDPR).
  • Companies cannot bear the fruit of the IoT on their own, and will require assistance along the way. More than 50 percent of them are strongly involved with IT services companies and consulting firms, which is reasonable bearing in mind that successful IoT requires significant expertise both from a solution delivery and business advice perspective.

Aside from the above insights, of the many manufacturers that are in pursuit of digitization, a large number of these projects are unlikely to succeed according to a 2017 Cisco study finding 74 percent of companies that begin an IoT initiative fail. More often than not, projects go over budget, deployment times run long, interoperability issues occur across legacy platforms or planning and resources aren’t allocated appropriately, leading to their cancellation. This failure rate has lead to a greater hesitation for manufacturers to embark on their digital transformation journeys.

To build a successful roadmap to digital transformation, having the right pieces in place, setting reasonable expectations, and a dedication to project initiatives may be the best approach to applying Industrial IoT technology. We often talk to companies who have predictive and preventative aspirations but who still don’t have machines networked, the necessary IT infrastructure to capture and aggregate machine data, or the internal organizational resources required to decipher the data and implement continuous process changes. Thus, like any good action plan, it’s all about the preparation. Here are a few areas of focus for any company to consider when readying themselves for digital transformation:

  • Organization: To understand what you are solving for, it’s essential firstly to be aware of what the problems are, and then to become capable of not just solving those problems but to ready ourselves for the greater problems in the journey ahead. Transformation requires buy-in at all levels, from the front office and on the shop floor, but it also requires internal leadership. It’s critical for manufacturers to recognize the important role organizational attributes play in long-term project success and begin discussions about how the odds of project success can be increased by evaluating organizational gaps. Ask yourself: Where do we stand now? Does your team have the right people in place to implement new technology? Are there project leaders capable of owning this project?
  • Communication: The information we need is available, but the hard part is actually applying it. Avoiding an “us vs. them” mentality is critical in this transition stage.  It is vital to build trust between everyone involved in the manufacturing process so problems can be quickly identified, and new solutions can be effectively implemented as a team. Don’t let a lack of communication stand in the way of change. Ask yourself: Does your team have an environment capable of communication and applying process changes not just from the top down but from the bottom up?
  • Waste Reduction: Before you embark on our digital transformation journey, it’s important to get as lean as possible with your current capabilities. The goal of lean manufacturing is continuous improvement of production processes, while eliminating waste and cutting costs. However, setting the stage for a lean process is just the first step; implementing a system that allows you to maximize your manufacturing productivity results will take your lean model to the next level. Ask yourself: Are we lean? Do we know what our top areas of waste are? Have we embraced lean manufacturing principles?
  • Key Performance Indicators (1): Depending on the systems and processes you have in place on your factory floor, you may face one of two problems; either you don’t know which key performance indicators (KPIs) you should track to enable you to improve your factory performance, or you are unable to collect sufficient data to accurately measure the KPIs you want to track. Having specific KPI’s will allow you to assess, analyze and track our manufacturing processes, as well as to evaluate success in relation to goals and objectives. Ask yourself: What are our key performance indicators that we want to measure as a benchmark for our improvement? Do we have any information now that we can use for this benchmarking? Some of our top suggestions to get started? OEE, Machine Utilization, Set Up Time, Cycle Time, and Scrap Rate.
  • Tools: Digital manufacturing will transform every link in the manufacturing value chain, from research and development, supply chain, and factory operations to marketing, sales, and service. Having tools to measure your efforts, for designers, managers, workers, consumers, and physical industrial assets will unlock enormous value and change the manufacturing landscape forever. What tools are in your toolbox right now? What tools do we need to measure our success? What tools do we need to upgrade?
  • Key Performance Indicators (2): Of course, every company will need tools to help them optimize their capabilities, but for this job some tools will make more sense than others. Your KPI’s will help you assess which tool will allow you to capture the information you are looking for that best fit your company’s needs. Ask yourself: What tools do we want to use to measure our efforts? What tools are we already using that we can leverage?
  • Digital Connectivity: In 2018, the cloud can be your best friend, and with security being better than most on-site solutions systems, the benefits are . Increasingly more companies are developing or moving their workloads to the cloud by the day, aiming to migrate everything onto the cloud over the next few years. This digitization of data will enable you to deliver competitive advantages in an ever-competitive landscape. Networking your machines and ensuring that all production data can be captured is one of the most essential capabilities for real-time analytics. Ask yourself: Are you ready to digitize our assets? Do you have the technical assets in place to capture and store the data?

Finally, once you’ve readied your company to start your journey, it’s essential to avoid the many pitfalls made by previous teams who were unable to move their IIoT implementations past POC. According to Cisco’s Scot Wlodarczak in his article entitled “Don’t Let Your Industrial Internet of Things Project Fail,” here are a few tips to optimize your chances of success:

  • Start small: If you focus on your entire plant, you will make success much less likely. Try starting with a smaller project in a key focus area.
  • Define success: Determine what you are trying to achieve, then measure it before and after any IoT project.
  • Gain internal company IT and operations alignment: The days when operations can implement network-related projects without IT are gone, or at least close to extinction. Success is much more likely achieved by working closely together.
  • Understand and address security risks: Connecting to data from the factory to the enterprise, or opening up remote access all the way down to the plant floor, can potentially open up security risks. Carefully evaluate the potential risks and impact of those risks, then focus on the most serious.
  • Free up data from disparate networks: Make sure you fully understand the different networks in use all the way down to the data you want to capture for analysis.
  • Avoid data overload: Keep your data set manageable and use basic statistical analysis to look for outlier data.
  • Cultivate a technology-focused culture and IoT expertise: You need new technology to achieve the promise of many IoT benefits, and you need the expertise of people, vendors, and partners to get there.

Remember, digital transformation doesn’t happen overnight, it’s a journey. Getting from today’s practices to tomorrow’s cannot be done in one giant leap; it is an evolutionary process. Readying your team’s capabilities and learning from the mistakes of others will best prepare your team for a successful implementation.

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