There is much hype these days extolling the virtues of the IIoT (industrial internet of things), thanks to many industrial vendors of automation, communications, and CMMS or other software systems. Although many of you have extensive experience in implementing these systems, some find the latest wave of the IIoT quite daunting, despite the obvious benefits to decision-making capability. The growing quantity and complexity of data requiring integration and compilation for a diverse audience presents many challenges alongside the benefits.
There are so many things that can and do go wrong with asset management IIoT projects. The first step is to recognize that your IIoT project can be quite complex and a lot more involved than just swapping old stand-alone equipment with more modern equipment capable of advanced data collection, analysis, and integration via the internet. Awareness of pitfalls can be one of the first steps toward successful implementation. Take our brief survey to tell us which of the following 15 common causes of IIoT project failure are affecting your ability to execute:
1. Inadequate data security – When it comes to data and the internet, the risk of information falling into the wrong hands through cyber-espionage or even by accident is always an issue worth exploring. Every company’s worst nightmare is equipment malfunction resulting from a data breach, which may jeopardize workers’ and the public’s health and safety.
2. Integration issues – Integrating the myriad islands of automation for any industrial environment has always been difficult. With enough time and money, any two systems can be fully integrated, to be sure, but will the benefits make doing so worthwhile? A cost/benefit analysis typically is recommended to prioritize and determine the optimal level of system integration for each component of your asset management IIoT project. It is always advisable to explore integrating multiple systems using a phased approach to reduce project cost and complexity.
3. Data overload – The problem these days is deciding what to do with all of the data as equipment connectivity is facilitated by cloud technology. Start with a small set of key measures that trade off (e.g., spare parts inventory level and stock availability) for each stakeholder group, from workers to top management. What information do people need to do their job better? What key measures ultimately drive the business? Remember that even with artificial intelligence providing better, more-predictive data, humans still generally make the final decisions, including how to set up a fully automated control system.
4. Poor-quality vendor assistance – Beware of vendors that have few installations in your industry or that do not spend a large percentage of profits on research and development to keep pace with new technology. Also, make sure that there are vendor resources assigned to your project who are not only knowledgeable about vendor products but who also have experience with asset management and CMMS integration. Before beginning your IIoT project, request resumes and check at least three relevant vendor references, visiting at least one. Have a contingency plan if key vendor resources become unavailable.
5. Inadequate staffing of the project team – Whoever is acting as project manager should be well-known and respected in the organization and knowledgeable in how to manage complex change projects. All key stakeholders such as maintenance, operations, IT, finance, human resources, and so on should be represented by fairly senior people on the team. Finally, there should be enough people working full time on the project to ensure that “get-ready” activities are finalized, training is thorough, and installation is completed, all within a reasonable timeline. You cannot rely solely on the vendor for implementation.
6. Unclear roles and responsibilities for implementation – Dilution of responsibility is a common problem with teams that are assembled for a one-off project, such as a more-complex IIoT implementation. Make sure all project team members, senior managers, and the vendor have clear deliverables.
7. Lack of top management support – Senior management must be visibly supportive of the project and must be willing and able to answer questions such as, “What’s in it for me?” If the workers do not understand what is in it for them, then the new capital investment will not be properly used.
8. Unrealistic timeline – If the pace of your asset management IIoT project is too fast, then steps may be missed or done poorly. If a project is delayed or runs too slowly, interest, focus, and momentum will be lost. An IIoT project that drags on is more likely to lose key people to other projects that appear to take precedent.
9. Unrealistic business case – Underpromise and overdeliver in terms of savings. Be conservative in estimating costs. Do not be afraid to recommend shutting down the project if funding proves inadequate. This is especially true when there is a large dependency on integration, given that users typically crave more functionality than needed and budgets can quickly run dry.
10. Poor communication to all stakeholders throughout implementation – You are rarely accused of giving too much open and honest communication. The most effective communication with workers comes from face-to-face interaction with front-line supervisors, from the project’s start until about 3-6 months after installation. Also, don’t overlook other communication tools, such as town hall meetings, newsletters, video briefings, and so on.
11. Poorly articulated goals and objectives – IIoT should fit into a master plan, such as your asset management and/or overall strategy. If you asked a random sample of workers and managers, would they have a consistent explanation of what the project will accomplish?
12. Insufficient rewards/consequences for project success/failure – Clearly defined rewards, monetary or otherwise, will increase the likelihood of success when the project meets or exceeds clearly defined expectations. Senior management must be prepared to carry through on consequences for those people that attempt to shirk their responsibilities.
13. No formal process for issues resolution – Every project requires a simple and efficient way of solving problems. This can involve keeping a formal log of issues, assigning ownership to problems, conducting regular management meetings, etc.
14. Inadequate process design – Business need drives process redesign, which will in turn push out the IIoT specifications, not the reverse. In addition, because procedures change, job functions may change. Therefore, job descriptions may have to be redefined, and user training may be extensive.
15. Inadequate testing – Any system should be subjected to rigorous user acceptance testing prior to implementation to determine whether specifications are adequately met and whether the system is secure.