No Parts Management without data services!
Very few companies have reliable and comprehensive data on the parts that they use. Before starting any Parts Management project, it is therefore vital that they commit to a “data services” process.
This process is generally divided into 3 stages:
- Data cleansing
- Class designing
- Data harvesting
Data cleansing
Data cleansing consists of “cleaning up” basic parts-related data so it can be read and used during the following stages. It mainly involves verifying the names and references of the manufacturer, standard, and identifications.
Artificial intelligence tools are not yet able to cleanse data automatically, so the task is either performed by our data analysts or completed by your staff internally.
Class Designing
Class designing consists of using the information that was cleaned during the data cleansing stage to come up with the most efficient classification system for your parts.
As in a bookstore, this system is based on shelves (the classification), classification criteria (the attributes), and a final element that is often overlooked: a dictionary to understand and restrict the terms that are used.
Once this analysis has been completed by our teams, you can then choose a specific classification system for your activity, a standard system (eClass, ICS, UNSPSC, ETIM, etc.), or a combination of systems.
Data Harvesting
Without a doubt the most tedious phase, data harvesting consists of collecting all the missing information, checking it, and entering it as attributes.
This final step is usually performed by our team of 200 data entry operators and verified by our analysts, after which time the data is reintegrated into the PLM and/or ERP databases of our customers.
No Parts Management without data services!
Very few companies have reliable and comprehensive data on the parts that they use. Before starting any Parts Management project, it is therefore vital that they commit to a “data services” process.
This process is generally divided into 3 stages:
- Data cleansing
- Class designing
- Data harvesting
Data cleansing
Data cleansing consists of “cleaning up” basic parts-related data so it can be read and used during the following stages. It mainly involves verifying the names and references of the manufacturer, standard, and identifications.
Artificial intelligence tools are not yet able to cleanse data automatically, so the task is either performed by our data analysts or completed by your staff internally.
Class Designing
Class designing consists of using the information that was cleaned during the data cleansing stage to come up with the most efficient classification system for your parts.
As in a bookstore, this system is based on shelves (the classification), classification criteria (the attributes), and a final element that is often overlooked: a dictionary to understand and restrict the terms that are used.
Once this analysis has been completed by our teams, you can then choose a specific classification system for your activity, a standard system (eClass, ICS, UNSPSC, ETIM, etc.), or a combination of systems.
Data Harvesting
Without a doubt the most tedious phase, data harvesting consists of collecting all the missing information, checking it, and entering it as attributes.
This final step is usually performed by our team of 200 data entry operators and verified by our analysts, after which time the data is reintegrated into the PLM and/or ERP databases of our customers.