Industry 4.0 is all about the Industrial IoT and big data analytics. According to Forbes, Industrial IoT data analytics is the number one reason for companies to invest in IIoT. With IIoT, manufacturing companies can gain visibility into production stages, identify gaps in business processes and improve them, enable predictive maintenance to reduce downtime and improve production quality.
But while the discussions surrounding IIoT are focused on data analytics, the reality is that most companies are only getting a fraction of the value from the data of their connected systems. A study by McKinsey found that 54% of companies utilized 10% or less of this information.
How do we explain why in a process manufacturing plant with 25,000 sensors, only 4% of data is being used for decision making? This gap between data expectations and reality may seem extreme, but it can be explained.
Understanding the Challenges
Few dispute that organizations have more data than ever at their disposal. However, the data is very siloed and it is not unusual for these lakes of siloed data to “go to waste” due to the lack of platforms that can truly leverage these diverse data sources and extract overarching insights to improve quality, productivity etc. In other words, the pain point is not generating and collecting data, but being able to effectively extract value from it.
Another challenge is the integration of IIoT solutions into business processes. McKinsey recently published a report that calls out the missing integration of IoT solutions into existing business work flows as the top IIoT capability gap. IIoT software vendors may say that their products integrate with business systems, but simply passing data to a business system is not the same as creating an end-to-end business process. It is only when the data from IoT solutions is fully integrated with data from enterprise systems that the biggest benefits can be achieved and advances can be made.
Critical Success Factors
To ensure success, companies must ensure that they collect the right data and get actionable insights from it. A successful data strategy must take into account 3 critical things:
- Business challenge and goals- What are your biggest challenges and what are the benefits you want to get from your IIoT initiative (e.g.: improved quality, reduced unplanned downtime, increased yield)?
- Strategy – How do you plan to put your data to work for solving the challenges and achieving those goals? Which data-driven insights will you need to extract in order to fulfill your needs?
- Assess and define the data gap – Which data sources are required and how do you integrate the required data with your business systems?
Industry 4.0 is a Journey – How can Elisa Smart Factory Help?
Industrial IoT is not a single solution that is implemented by one big project – it is a journey. Getting from today’s practices to tomorrow’s cannot be done in one giant leap; it is an evolutionary process. Elisa Smart Factory can help organizations along the journey with our deep industry insights and technology expertise. We leverage capabilities and experiences from around the globe to customize our solutions to the needs of our clients. Our solutions are designed to help companies overcome the challenges along the digital transformation journey and to advance forward from reactivity, to proactivity, and to predictivity.