More and more consumers are conducting online research before they buy a specific product. To gather information about products, consumers will visit different channels. In 2018, 22% of all purchases by consumers took place online. As organizations are required to provide consumers with relevant product data, many departments are involved in the processing of product data. We see numerous organizations using different systems, such as ERP- and DAM systems, to record and coordinate the flow of data. There is, however, a great chance that errors will occur when product data is processed on self-contained systems.
Every department in an organization needs specific pieces of product information to carry out their tasks. In most organizations, each department is responsible for its own data — and that means specific data is often stored in separate locations across the organization.
These organizations, meanwhile, need to have the data from all departments at their disposal, in order to provide customers with the right information across all channels (for example, the webshop). When product data is stored separately via Excel files or in separate databases, data governance will become very hard. It also has direct consequences for product data consistency, completeness and accuracy. Finding the right product data in all systems and files in order to get all your data up-to-date, has proven to be an arduous and time-consuming process.
Consequences of fragmented data
Besides using different, self-contained systems for storing data, manual processing of product information increases the likelihood that different (Excel) files are spread across the organization.
When product data is spread across the organization, it is hard to know if all systems are up-to-date, or whether data is being processed according to the right standards. To illustrate, the sales department might use centimeters to describe the dimensions of a product, while the logistics department uses millimeters. This type of error is a common occurrence when departments are processing data separately from each other.
The effects of errors in product data can be felt in every layer of an organization. The logistics department, for instance, needs to know the correct dimensions of a product for packaging, storage, and transport. But these types of errors can also directly cost money to an organization. When, for example, an incorrect price or product information is displayed, a consumer could have the wrong expectations about a product and end up dissatisfied.
How to prevent data fragmentation
Fragmentation of product data can be prevented by no longer processing your data manually – that means no more Excel files! In other cases, databases like an ERP system are used for all departments to store their specific product information. However, an ERP system has its limitations and won’t be able to save all necessary commercial product data, such as SEO texts or pictures for the website.
An optimal solution to prevent data fragmentation is to create a single-source-of-truth, by using a Product Management Information (PIM) system. A PIM system is a central point within your organization where all product information is stored – when using a single-source-of–truth, you are guaranteed that your product data is always up-to-date and reliable.
A PIM system allows for more detailed product information and, by integrating with the other systems of an organization, provides all relevant channels — such as the website, ERP and POS — with the right data, all the time.
How to prevent data fragmentation in your organization?
The most significant cause of data fragmentation is the manual processing of data in separate locations. To prevent fragmentation, you need to abandon this processing of data by hand, and start working towards a centralized solution.
Want to know more about how you can optimize the processing of data? This e-book tells you everything you need to know!