Increase Product Lifecycle Data Downstream Value
It’s well-known that different product lifecycle phases require different data, and that the data needs to be enriched in all phases. Finding the right information at the right time increases productivity and mitigates the risks of quality issues. One example of when the process is not working properly is when Equipment does not have the required data for customs processing. As a result, a delivery date is missed.
Commonly, a PLM system helps companies keep track of their important product data. However, it can be tricky to motivate the teams to add data that will provide value in later phases, if they don’t see the benefits. It may feel like extra work, and who wants that? In addition, people tend to take shortcuts, or do workarounds, especially if the supporting systems are slow or do not really support the agreed work processes.
Therefore, we want to give some ideas on how to create a motivational environment that encourages the teams to add important data and follow the processes. The goal is to increase the downstream value of the work they put in. While all organizations have different challenges, we have chosen some common areas that often can be investigated and enhanced. The areas are based on the People, Processes, Data, and Technology (PPDT) pillars of Nextage Advisory’s Product Wellbeing* model.
- Train the departments to understand how their roles affect other roles in the organization and provide insights on why to follow the agreed way to operate (processes). Give examples of how the data gives value in later phases of the product’s life cycle.
- Implement KPIs related to data input. For example, a designer will set the correct Tariff and ECCN codes to the design structure items if KPIs related to this are measured.
- To consider: instead of training all the Design Engineers to add for instance sustainability and commercial item data, let a dedicated and trained Item Management team be responsible for data quality and validation.
- Look into the processes and align them throughout all departments.
- Create clear processes to help the organization operate in an agreed common way.
- Create processes that help fulfill regulations that are often mandatory and cannot be bypassed.
- Create a sense of ownership of the data. This can be done as mentioned earlier by setting KPIs that are measured to show the level of success.
- Look into the opportunity of driving your product lifecycle process from the data, as far as it is feasible and beneficial to your Product Wellbeing.
- Once you can rely on the data, you can automate the operations based on it.
- Optimize systems and servers to ensure fast response times.
- Automate the system to a level where user errors are prevented.
- Let the system urge the users to perform the wanted actions.
- Ensure an intuitive workflow and interface.