Retailers that use more than one system to collect and store data are becoming increasingly concerned about data quality, data sharing and data persistence.
As data is being shared across many systems, it would be much more pragmatic to adopt a centralized philosophy and approach to manage and share all of this data. Unfortunately, there is no simple solution. The days of Excel spreadsheets with countless rows of Stock Keeping Units (SKUs) are no longer tenable options. A comprehensive method is required, Master Data Management (MDM), which is not just a tool or technology.
MDM defines and manages the critical data of an organization to provide a single, yet holistic point of reference. This includes the processes, governance, policies, standards, and tools within an organization. MDM is extremely critical to retail companies, and they need it to streamline their processes and more efficiently manage their data.
Multi-channel strategy. In today’s digital age, almost all companies use a multi-channel strategy to interact with customers and partners. For retailers, the channels include areas such as: e-commerce, data warehouse, mobile platforms, and catalogs. Unfortunately, these channels are not developed as one unified business strategy at the onset, and there is little to no integration between the complex business application systems. The end result is weak data assimilation, which prohibits full data visibility across the channel. Introducing MDM would be the ideal solution to comprehensively assimilate all these different data points.
Rapidly increasing the number of product types. In the first nine months of 2014, Amazon added 20 million product types to its listings, with a new total of 253 million options. That’s an average of 75,000 products added every day. It’s clear that a traditional IT system would be unable to properly manage this amount of data. Big box retailers can apply MDM to link these products to a centralized master file, which will then be able to properly analyze product visibility and demand. Implementing data governance programs and setting up the right process as a part of MDM is one potential solution for managing categories in a dynamic way. MDM also supports flexible segment management and identifies SKUs not in sync with master data. Recording items at a transactional level is no longer an adequate way to store and manage data. Correctly categorizing products is vital to having useful reference data.
Data analytics begins with data collection and cleaning. Without good data, the value of applying sophisticated modeling, algorithms, and visualizations is greatly diminished. Getting the data right from the onset is far more efficient than correcting errors as you go. A well-built MDM framework prevents errors and provides the holistic point of view needed to inform better decision making.