Phase 2:
On the road to transformation
When you reach the implementation stage, you’ve decided what technology you want to put in place and whether its deployment will impact an isolated department or location, or if it will be used across the enterprise. As part of this process, you may need to make decisions about:
Sensors for IoT relays on cycle counts or other conditional measuring
Data collection terminals
RFID, 5G or other networks to handle transmissions
At this point, you’re also trying to figure out how to harness the data from Industry 4.0 equipment innovations for analytics, automations, monitoring and optimization. This will allow you to drive further benefits such as:
Adding predictive maintenance on machines
Identifying production bottlenecks
Accessing real-time production information
Adapting and optimizing processes
Sharing data points or other process information to related departments such as customer service, procurement, sales or scheduling
There are several technical and data challenges at this stage. On the technical side, this could include indecision about selecting a broadband provider, a lack of knowledge about how to align technology solutions or the need for additional workforce training.
On the data side, you could have difficulty normalizing data formats for use by other departments or be unable to integrate with other internal or external systems for selective data consumption.
It is quite common for manufacturers to get stuck in this phase. This can happen for various reasons:
The implementation was not seamless
You’ve encountered additional complexities
More investment is needed
You aren’t seeing the returns that were anticipated
Project abandonment often occurs at this point, sending you back to phase one or to develop costly workarounds to justify the cost and effort to date.
Critical questions to ask about your processes and workflows
Can you access real-time data?
Does it show you what you need?
Are there any gaps in the data?
Can you exchange data with other departments, systems or external parties?
Have you improved your workflows?
Do you have control over your data?
It’s important to be mindful of common challenges during the evaluation stage: a data foundation that does not support data sharing across the enterprise; continued use of manual processes; and a lack of central governance that assesses data quality.
One of the benefits of Industry 4.0 is the ability to automate. Not only does this enable you to streamline production and decrease dangerous, error-prone or repetitive tasks, but it also allows you to shift workforce responsibilities to focus on monitoring and other value-added activities. As a result of automation, you’ll see an increased consistency and quality of your operations.
Common challenges with this stage include:
Concerns about the lack of control and transparency that automation brings
Distrust about data quality and the analytics being performed using that data
Role permissions are not yet established or enforced
Additional employee training is needed
There’s no alert system to catch errors
Concerns about employee morale
With digital transformation comes more pressure on your IT infrastructure. At this stage, you need to appropriate additional resources to ensure compliance on data privacy and system security. Once you start to see ROI, you will want to expand the technology to ensure the full benefits of your investment are being realized.
At this point, many manual, offline processes are now online and reliant on digital capabilities. Incompatibility with legacy systems and other technology solutions across the enterprise are a common problem, making it difficult to create seamless workflows.
