
A consistent same-part strategy avoids duplicate work and creates synergies. With the DUPLICATE SEARCH extension, you identify duplicates across systems and locations and clean up your systems without much effort. The list of duplicates is exported from SIMILIA for processing in other systems. The matching process takes place in the background and saves an enormous amount of time and effort compared to conventional methods.
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With the SIMILIA software, you have access to all relevant data in the shortest possible time, without having to search through your inventory manually as you used to. See for yourself how leading companies are already using the software solution. Download now our free Use Cases.
DATA CLEANSING - CLEANSING THE ITEM INVENTORY WITH SIMILIA
Using modern and established methods, data cleansing, or the cleansing of drawing parts, is an efficient approach to detecting and permanently eliminating duplicates in the article stock. From this, short-term potential benefits can be mobilized for all industrial companies. The beneficiaries of clean and fast data cleansing are distributed differently throughout the company. They can be users in purchasing and procurement, in warehousing, in AV or even in design and development. Once the clean room is created, the creation of duplicates in inventory can be automatically avoided. Data cleansing is a profitable business.
Find duplicates & consolidate inventory data - this is how it works
Duplicates in inventory data are a horror for any company. Duplicate development costs, duplicate master data management, duplicate inventory, duplicate procurement costs, duplicate costs everywhere you look. Duplicates in inventory also create confusion. This occurs more often than one would like. Manufacturing, assembly and service are often confronted with these situations, which lead to errors and complicate processes. Why make things so difficult for yourself? Read the following blog to learn how you can efficiently avoid duplicates in the future and consolidate your inventory data.