How Duplicates Treatment in Your Materials Catalog Impacts Your Stock

The significance of having high-quality customer and product data cannot be overstated. Every consumer is a physical entity with a digital counterpart. Managing that digital twin allows the organization to streamline production processes and create excellent consumer experiences.


Bad customer and inventory data is very destructive for any firm for the same reason.


Duplicate records are a major source of poor data. Every firm, regardless of size, locale, line of business, or industrial sector, faces the problem of duplicate records. Companies have worked hard in this area recently becoming more conscious of the value of high data quality. They are better able to cope with duplication in their IT landscape with master data cleansing technologies.


Let’s have a quick look at duplicate treatment and how the Synopps master data cleansing can improve your materials catalog.

What is Duplicate Data in MDM?

Duplicate data in data management refers to two (or more) records with distinct values yet describing one real-world item. The most typical case is likely to have two entries detailing the same item, for instance:

Product Alpha is located in warehouse 1.
Product A is located on aisle 3, Warehouse 1.

These are the most obvious and typically happen while transferring data across systems. But duplicate data is not limited to precise copies of whole records. They could even be the least destructive of all copies. (Their presence could still cause serious issues down the road).

Partial duplicates are the most prevalent (and destructive) kind of duplicate data. These entries could share names, phone numbers, email addresses, as well as other types of contact information with another record, but may include additional non-matching information in case of a customer, or the two same products with one missing some characteristics in case of inventory.

Why duplicates are harmful to your material catalog

The first step is understanding duplicate data. But to fully comprehend its effects, we should comprehend the issues duplicate data causes in business operations.

1. False Stockouts

Duplicate data can lead to false stock-out situations when a product may be present in your inventory but is reported as unavailable by the system. In addition to the issue of unhappy/lost consumers, you also lose prospective income. Costs will increase as a result of having to pay for pricey expedited delivery or overstocking as a preventative measure.

2. Duplicate Data Causes Excess Inventory

Excess inventory accumulation is a major issue that results in a variety of long-term issues, such as increased expenses owing to additional warehousing needs (or operational challenges), needing to sell at reduced prices by destroying or disposing of when the duplicate errors are detected, and so on. A clean master data collection would help you prevent the problem by anticipating the demands, identifying the surplus immediately, and even automating supply.

3. Duplicate Data Distorts Inventory Visibility

Duplicate data in corporate or warehouse management systems results in an inability to see inventories, which in turn causes overstocking, inventory write-offs, stock-outs, and disruptions in manufacturing activities. In the long run, duplicate materials data becomes a primary factor in cash lock-up, excessive stock, a lack of stock levels visibility within factories, or a decline in worker productivity.

4. Duplicates cause Excessive Purchasing

When there is duplicate materials data in the system, the company often does not know when to purchase materials, what number to order, or what amount to pay. In order to prevent potential part stockouts, incorrect inventory data might lead to overbuying. In the long run, material prices increase as a result of inefficient purchasing, and inventory accuracy decreases.

5. Lack of Critical Stock

Duplicate data leads to inventory levels that are below ideal levels. From too high for some materials to unavailable or low for others.

Whatever your data is telling you might get more problematic when a proportion of all of your data is tallied twice or even thrice. Before you can truly trust the data-backed judgments that your firm takes, you must address those problems.

The Process of Duplicates Treatment

• The first step in the practice involves completing an automatic duplicate search based on recognized blocks. This approach finds all duplicates by comparing each record with every other element. The data manager will select one or more attributes that would be expected to have common values amid similar records;

• The second step involves verifying potential duplicates and confirming with the client. Automatically identified probable duplicates should be manually verified to ensure they are actual duplicates. The decision should be validated by collecting new information from the client;

• The third step includes applying the decision matrix (that is based on warehouse inventory, consumption, requests, and orders data) to merge or block duplicates and cancel a purchase with immediate cash savings. One data record must be created after the duplicate data has been located. By definition, this entry will include the most accurate, full, and up-to-date information on the client;

• Finding the data components and values from duplicate customer records to consider for the "golden record" is the major problem users frequently encounter throughout the merging process.

Results of Duplicates Treatment

The first step is understanding duplicate data. But to fully comprehend its effects, we should comprehend the issues duplicate data causes in business operations.

a. Minimization of Surplus Inventory

By eliminating duplicate data, MRO item stock is reduced by 2–10%. In addition, this will increase turnover while also liberating working capital. With lower levels of duplicate data, the associated unnecessary expenses will decrease. All of this will help to improve margins.

b. Reduction of False Stockouts

Service levels will rise by 5–10% when materials data is reliable and accurate. To add, the likelihood of false stock disruptions will decrease since every stock unit will be visible and accessible. It ensures operations have enough inventory without investing excessive amounts of money in inventory.

c. Decreased Direct Purchases

Data cleansing identifies duplicate, invisible stock. The resulting revenue savings of 1-5% is achieved from the procurement process since unnecessary purchases are avoided.

Conclusion

The detection and elimination of duplicate inventory or customer data is one of the main goals of the Master Data Management process. This is a necessary stage toward obtaining a single version of the truth about consumer data.

This is a necessary stage toward obtaining a single version of the truth about consumer data. Duplicate treatment should begin as soon as client records are combined in MDM from multiple data sources, or, worst-case scenario, when multiple entries are discovered in the same system.

Synopps master data cleansing tools help assess and enhance the quality of your data. The applications will highlight duplicate data and streamline the cleansing process into one easily manageable platform. Get started today on Synopps.

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