The Importance of Data Mapping in PIM
In today’s digital world, businesses are collecting more data than ever before, because there is simply more available and more required (as ESG assumes greater importance). This data is critical to making informed decisions and driving business growth. However, managing this data Product Information Management (PIM) solution comes in. A PIM helps businesses manage their product information from a centralised location. However, implementing a PIM solution is not as simple as just installing the software. It requires a thorough understanding of the data and how it should be structured. This is where data mapping comes in.
What is Data Mapping?
Data mapping is the process of defining how data is transformed from one format to another. When consolidating data to load into a PIM solution, a roadmap is needed to ensure it reaches its destination accurately. In the context of a PIM, you are essentially mapping the data in your existing systems to the new PIM’s data model.
This involves identifying the data fields in your existing systems and mapping them to the corresponding fields in the PIM solution. Data mapping is a critical step in the implementation of a PIM solution because it ensures that the data is structured correctly and can be easily managed in the PIM solution. Mistakes made in a data mapping process can have a knock-on effect on overall quality, leading to replicated errors and ultimately, degraded customer experiences and inaccurate analysis from misleading insights.
What is the purpose of Data Mapping?
The main purpose is to avoid these common pitfalls below! When identifying and transferring various data fields from different sources to the corresponding fields in the PIM system, substandard data mapping can have serious consequences for a PIM implementation project.
Inaccurate and Incomplete Data
The data fed into the PIM system may be inaccurate or incomplete, which can result in inaccurate product listings, incorrect pricing information, or incomplete product attributes to name a few. The bad quality product information which emerges will inevitably lead to customer dissatisfaction and lost sales.
Data mapping streamlines workflows by ensuring that data is organised and structured. Without it, workflows become inefficient and time-consuming, as it may take longer to find and update product information, slowing down the entire process.
Inadequate data mapping has a cost. If reformatting is required, it takes longer to update product information, meaning increased labour costs and a risk of inaccurate or incomplete data slipping through the net. This will impact the bottom line – higher customer returns, lost sales opportunities, and reputational damage.
Poor Data Quality
It is hard to maintain high data quality without proper data mapping. This leads to incorrect product listings, inaccurate and out of date pricing information, and incomplete information. Today’s customer will have very little patience with unreliable and inconsistent information, especially across different sales channels.
Data mapping: best practices
Having identified the risks, what are the best practices for data mapping?
Understand the data: it seems obvious, but before you begin mapping your data, you need to have a comprehensive understanding of its nature. You should identify all data fields in your legacy systems to gain the necessary insights into how they are related.
Define your data model: with that understanding, you can define the data model for the target system (your PIM solution) by defining the data fields required for the PIM solution and how they are related.
Map the Data: with the defined data model, you’re able to start mapping the data. Basically, this means identifying mapping the data fields in your legacy systems to their corresponding fields in the PIM solution.
Test and test the data mapping: Once the data mapping process is complete, you should test, test and test it to ensure data is structured correctly and is easily managed in the PIM solution.
Document the data mapping: documenting the data mapping process is essential, to ensure that it can be easily understood and maintained. This involves information outlining the data fields in your existing systems and how they are mapped to the corresponding fields in the PIM solution.
Typical data mapping use cases
eCommerce businesses often have a large number of products that need to be managed. Data mapping can help ensure that the product information is structured correctly and can be easily managed in the PIM solution.
Retailers often have multiple systems that need to be integrated, such as point of sale systems and inventory management systems. Data mapping can help ensure that the data is structured correctly and can be easily managed in the PIM solution.
Manufacturing businesses often have complex product structures that need to be managed. Data mapping can help ensure that the product information is structured correctly and can be easily managed in the PIM solution.
Imported product data from suppliers frequently comes in a variety of different file formats (such as Excel, CSV, XML) with data structured according to their data models. With a PIM you can import data as you receive it. All you need to do is build an action map for each supplier to map supplier formats to your formats.
In conclusion, implementing a PIM solution is a critical step for businesses that need to manage large amounts of product information. However, it is important to understand that implementing a PIM solution is not as simple as just installing the software. It requires a thorough understanding of the data and how it should be structured. This is where data mapping comes in. By following best practices for data mapping and using it to manage your product information, you can ensure that your business is making informed decisions and driving growth.
At Start with Data, we specialise in all aspects of planning and implementing PIM solutions, as well as maintaining and enhancing existing systems. When it comes to data mapping, we are second to none, so get in touch and we can have a conversation about we can best help you with your product data management needs.