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2016 Top Data Quality Blogs

Posted by Alison Luna on Dec 21, 2016 1:17:00 PM

 

Convergence Data knows the importance of your part data. We know that part data is a core asset for your company, and the quality of that data is fundamental to the health of the business and the bottom line. Start the new year right with a review of the best ways to get your data clean in 2017. Below is a recap of the top 2016 data quality blogs we published to help you stay on top of your company’s core assets in the New Year.

 Top 5 Data Quality Blogs of 2016:

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Topics: Governance, Cleansing Data, Classification, Duplicate Parts, Manufacturer Parts, Data Cleansing, Part Cleansing, 2016 Top Blogs, Part cost, Benchmarking

4 Key Factors to a Successful Part Cleansing Project

Posted by Alison Luna on Nov 9, 2016 10:47:45 AM

As Steven Covey noted in 7 Habits of Highly effective people  you should begin with the end in mind.  When starting a direct materials data cleansing project, you need to ask yourself, what is the goal of improving the direct materials data?  Cost savings? Sourcing efficiency? Improved insight through reporting and analysis?  To answer these questions and achieve success, engineering and procurement need to work together to obtain the answers. First you need to know what are the overall company goals? From there all the following questions can be answered.

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Topics: Governance, Classification, Product Analytics, Manufacturer Parts, Data Cleansing

4 Critical Steps to Control Duplicates

Posted by Richard Turner on Jul 14, 2016 9:22:25 AM

Duplicate parts are the software bugs of the data world, hard to identify without specific tools and processes in place. If these “bugs” are not found in implementation they can be ultimately time consuming and costly down the road.  For these reasons it is crucial to get ahead of the issue as soon as possible, optimally during a data migration project or switch to a new platform.   For example, an SAP ERP data migration involving cleansing and classifying purchased parts from multiple legacy systems from US and International locations would be the perfect time to detect, isolate and deal with duplicate parts. The best case would be to have lead time of 6 to 12 months prior to the actual cutover to clearly find these duplicates and to give enough time to formulate the best plan to deal with these duplicates. Some may want to remove duplicate parts all together, while others may want to look for ways to consolidate and rationalize this data to help mitigate duplicate inventory, still others may want to associate them for purchaser’s reference for ordering and price comparisons.  Regardless of final goal for your company you first need to identify them through these steps.

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Topics: Classification, outsourcing, Duplicate Parts, Manufacturer Parts, Data Cleansing

Outsourcing Data Cleansing: Top 5 Best Practices

Posted by Richard Turner on Jun 27, 2016 2:14:37 PM

It may seem like a scary proposition to send your data outside your organization to be improved.  Who do you send it too, what do you provide them, how much is it going to cost, how do you know if the data is correct, how can you make it successful.  At Convergence Data we have learned to bridge this gap between outsourced data cleansing operations and US based companies – to make it a successful experience.  There are some basic practices to follow that we have learned we can share.

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Topics: Cleansing Data, Classification, Product Analytics, outsourcing, Data Cleansing

Design Costs Link to Classification

Posted by Ryan Donovan on Aug 19, 2015 10:08:00 AM

1. Classification: - a simple concept saves money and time

Companies can leverage classification to reduce design costs. The scientific community regularly uses classification to understand relations among items, with the plant and animal classification schemes perhaps the most familiar.

A classification scheme groups relevant components in a logical and systematic hierarchy and brings technically similar items together, yet uses attributes to distinguish them by their specific details. A classification scheme embraces all existing items and is able to accept new items into the component population using attributes to create mutually exclusive locations for similar components and excluding dissimilar components.

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Topics: Governance, Classification, Data Cleansing, Benchmarking

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