"Thank you to you and your team for everything, a superb job and a great team." - Programme Director.
Case study: Design, train and handover a new PDM function
Data is the lifeblood of modern manufacturing. Accordingly, inaccurate data coupled with inconsistent processes can have a tremendously detrimental effect on operations in terms of cost, time, and quality.
QR_ was brought in to eradicate inaccurate data and dysfunctional processes, achieving a 25% increase in CR throughput for a leading, high-performance vehicle manufacturer.
Case study: Design, train and handover a new PDM function
Our client, one of the UK's leading high-performance vehicle manufacturers, was experiencing a shortfall in the resources required to roll out and improve their new SAP variant configuration system.
Facing cost, time and quality challenges as a result of misaligned data, they selected QR_ to manage their variant configuration and build-out a new department and develop processes for the post-SAP ‘go live’ environment. The success of the project depended on our ability to develop a new PDM function that could be seamlessly embedded into their operations.
1. Challenge
With training and implementation of the system occurring simultaneously – and the workstream competing alongside other initiatives – the client's upgraded SAP system was plagued by data input errors. Consequently, these errors meant that engineers had a substantially increased workload, with an immense impact on overall engineering efficiency. Knowing the solution lay in remediating inaccurate data and dysfunctional processes, QR_ sought to develop methods and tools that would minimise data faults, streamline workflows and in turn, drive operational improvement.
2. Approach
To achieve these objectives, we defined a solution that was structured into three key phases: NPI process and data migration; data testing and fault finding; and modular modelling setup. As a crucial framework for managing product lifecycle within a company, the first step was to formulate an NPI process that would act as an actionable checklist to streamline operations and confirm robust inputs to VC models. To eliminate data errors and inconsistencies within these models, we developed a suite of time-saving bespoke tools for repeatable tasks such as data format checks and VC model fault-finding. We also ensured that the solution was sufficiently embedded into the client's operations. To achieve this, we developed a series of modular modelling processes to pass knowledge back to internal staff and deliver consistency across operations.
3. Outcome
The client's commitment to making data-driven improvements has translated into tangible results that will continue to have a lasting positive impact on their operations for years to come. As a result of QR_'s approach, the client has seen a 25% increase in CR throughput, as well as the ability to handle twice the workload with a similarly sized team. In addition to enhancing efficiency, significant cost savings have also been delivered, with our tool automation demonstrating effective early error resolution and saving ~£700k in consequential costs.
4. Feedback
"Thank you to you and your team for everything, a superb job and a great team." - Programme Director.