How to capture Industrial IoT (IIoT) value through R&D innovation

How to start developing an IIoT R&D project

Step 1: Discover and deploy innovative value-driven use cases that deliver positive impact

Deploying early use cases is an investment, and therefore it is important to think about the deployment in a strategic manner. In most situations, it is recommended to deploy use cases based on value/feasibility.

First, select use cases that create immediate value and avoid use cases that require building databases from scratch or other complex prerequisites.

While the focus is usually on low-effort, high-value use cases, there is a strong case for using use cases with little or no ROI. For example, a use case may not result in immediate impact, but it may allow future use cases to be used.

This decision is pre-analyzed, and the rationale must be clearly stated so that all relevant stakeholders are aware of the investment and its value, even if that value is delayed.

Step 2. Begin collecting and aggregating data while building important features in parallel

Not all items need to be securely fastened before the deployment. In particular, even before the required data is connected, prioritization of use cases provides an overview of the required data sources and an understanding of what data is available and can be connected. The data collection architecture can be customized or defined for specific OT equipment and data sources based on this information.

However, in parallel, the development of the platform core should not be neglected and should start in sync with the development of the use cases. It is necessary to connect sources for automatic data collection as soon as possible. Depending on the implementation state of the target architecture, a use case can be deployed to a local server based on a specific architecture. This assumes the use of frameworks that will eventually be used on the back end.

But it won’t take long to implement the final architecture prioritizing the first use cases, and the migration of the first use cases will be possible in just a few weeks. Further, each use case is implemented in the target architecture. In preparation for this, consider and engage the next wave of use cases by connecting to the required data sources in the previous wave (s).

The point to keep in mind here is that many use cases take longer to prepare simply because some data sources do not yet exist. To compensate for this, it may be necessary to add sensors, change the PLC logic of the machine, update systems, and so on.

Step 3. Establish processes and collaboration that will ensure the required deployment

A standard process of connecting to new businesses should be established to ensure that the team is in place when deployments begin there. Implementation is also about changing how an organization works and thinks; thus, it is important to make informed change management the same priority as the deployment itself. The success of a use case can be undermined if the benefit has not been clearly identified and people are either not using a new application or system in their day-to-day work or are using it incorrectly.

A central IIoT deployment team takes care of the needs across the enterprise, making sure everything is in place prior to deployment. The list of needs includes the skills and the technical background required for a use case. The R&D team identifies the right people on-site to manage the deployment and resolves issues.  The central team also monitors deployment status and emerging issues.

This provides a holistic view of benefits, implementation status and problem solutions to generate best practices for IIoT innovation.

A deeper look at use cases will almost certainly reveal a need for skills that may not currently be available in an organization or individual business. Hiring new talent or training existing employees should begin as early as possible so that skills are in place when they are needed.

Skill development and capacity building is an ongoing effort because deploying use cases never ends. Investing in these areas is a must for an organization that wants to succeed in its Industry 4.0 efforts.

It is also important to have a clear collaboration model that identifies one person for each workstream with clear accountability. Effective communication must be ensured within the organization, such as the exchange of information between enterprises and between the organization and its partners. Important archetypes of value chain partners are industrial equipment suppliers, technology providers and integrators, as well as specialists in functional areas.

Employee training should begin before deployment (or even concurrently) to ensure a shared vision and understanding of each use case capabilities and advantages. Training sessions are critical as time is devoted to answering employee questions and concerns. In addition, getting the people who will be working on a new application or tool into the development process and getting their feedback can create a tool that better suits their needs and provides broader acceptance and interest.

It will also be important to define the expectations and responsibilities of the use case owners as they will define the subsequent sprints within the use cases and report status updates and issues. Consistency of processes is very important, such as how communication occurs and measuring status and progress.

R&D is an integral part of any IoT project, and expanding it can be the first step to project success. By leveraging research and development, your business can optimize costs, reduce risk, and minimize time-to-market for various IoT applications. R&D teams manage both the technical and business elements of the product. Their responsibilities include evaluating both the usefulness of the product and the technology itself.

In addition to this, R&D teams can see future business opportunities. The end result of this should be research, prototyping, and clarification on the IoT product. The R&D team can study the idea before it becomes a product and support the transformation of the concept into a functional asset that solves the user’s problems.

Benefits of utilizing R&D for IIoT projects

Fast time to POC, Prototype, and MVP

IoT technology is evolving at a rapid pace. Why not save time and effort by testing ideas with a Proof of Concept (POC), Minimum Viable Product (MVP), or Prototype before launching a specific product?

POC is the practice of deep product interpretation. This happens before any planning for a product. POC allows you to learn a concept without spending too much time and money.

Prototype has the same basic goal of helping companies understand if a product is potentially good enough to get the job done. 

The R&D team can test the product’s performance, design, and benefits by creating a prototype. This way, you can use the prototype with a limited group of people to test it out before going to market for multiple users.

MVP is a product with a sufficient number of features that can be implemented in the market. The goal of MVP is to provide feedback for the future development of IoT projects. Choosing between one or all of these three can be a little tricky, and doing one of them requires specialists and some IoT equipment.

Enterprise innovation cost optimization

Digital transformation and innovation projects often lead to overhead costs. This includes administrative costs in excess of the total cost of the equipment. Using R&D for IIoT projects will help reduce these costs. Many tech companies provide their R&D services to businesses looking for a variety of outsourcing options. Some of these companies even have entire departments that focus on experimenting with cutting-edge technology. They investigate and scrutinize IoT solutions, deep learning, robotics, digital twin, and other technologies to create solutions, POCs, and MVPs for themselves and their customers.

Better Control and Risk Management

The company must interpret risks and be able to assess or mitigate them immediately. Using R&D for IoT projects can help you mitigate these risks. R&D engineers need to understand well how new IoT devices or functions will work and whether they can meet your business goals and requirements.

Like any other technology, IoT solutions need deep research and development and are best done by professionals. R&D outsourcing allows you to optimize costs, get an idea to market faster, and avoid life-saving risks.

Final Thoughts

Wrapping up, expanding market participation, cost management benefits, developing marketing capabilities, and keeping up with trends are all reasons why companies invest in R&D. Research and development can help a company follow or stay ahead of market trends and keep the company up-to-date.

While R&D requires complex engineering-heavy resources, quality certifications, compliance with the industry standards, and more, the innovations resulting from it may actually work to lower costs through more efficient manufacturing processes or more efficient and higher-quality products.

To accelerate enterprise innovation and create a unique and compelling IIoT value proposition, i’s highly recommended that manufacturing companies establish technology partnerships with companies that already have well-established R&D centers or innovation labs and that have accumulated best practices of leveraging the newest technologies and methodologies.