Enterprise-wide PLM
Reporting starts with capturing the right data – the most important step and, many a time, the least stressed one. When data is not captured in the right format, it results in inconsistent or non-standard data.
Let’s take a simple Workflow process example: Workflow rejection comments are valuable information for companies to understand the repeated reasons for workflow rejection and to improve FTY (First time yield) by developing training plans to address them. Users might not enter rejection comments unless they are made mandatory, so it’s important to have data-model checks and balances to capture the right data and standardize it through categorization and LOVs (List of values).
Since business processes get improved/modified based on different market and performance trends derived from PLM reports, it’s important to have continuous improvement initiatives to fine-tune reporting based on these improved processes and new baselines, from data capture to presentation. That makes it a continuous cycle – business processes need to be designed to support reporting and reports need to help improve the process.
Properly designed reports provide increased visibility into shifting enterprise wide status, reduce time and cost for data analysis, ensure quicker response times and faster product launch cycles and improve product quality and integrity.
How do your reports measure up? Do you have any questions or thoughts? Leave a comment here or contact us if you’re feeling shy.