Master Data Management (MDM) for CPGs

Master Data Management (MDM) in CPG: An introduction

In the consumer packaged goods (CPG) industry, data is a business-critical asset. Forecasting demand, managing inventory, understanding consumers, and monitoring trends are aspects of a viable CPG business that require data for precise planning and decision-making.

Data is also a competitive advantage in CPG, with retailers increasingly using data to inform their purchasing decisions, often prioritizing relationships with suppliers who can bring valuable insights to the table.

In order to become data-driven, brands face the challenge of ingesting datasets from many diverse sources with unique formatting, naming conventions, and organizational structures. To make data actionable, it needs uniformity.

The process of collecting and organizing data to align with internal business standards and ready it for analysis and decision-making is known as Master Data Management (MDM).  Read on to understand why MDM is important for a CPG and how the process works.

The process of collecting and organizing data to align with internal business standards and ready it for analysis and decision-making is known as Master Data Management (MDM). 

What is master data?

“Master data” is core information identified as essential to operating a business. It is typically divided into “domains,” or categories of data. For a CPG supplier, master data might include the following domains:

• Product data – SKU-level information, including ingredients, weights and dimensions
• Retail data – Performance metrics, product distribution, inventory flow, POS data 
• Customer (retailer) data – Retail customer contracts, store locations, order history
• Consumer data – Demographics, purchase history
• Marketing data – Campaigns and KPIs
• Financial data – Invoicing, credit transactions
• Regulatory data – Quality and safety certifications

Because master data serves as the single source of truth for the entire CPG organization, it must be consistent and standardized so that every function within the organization can understand and evaluate master data in the same way. 

Aligning master data uniformly to the organization's internal conventions and categorization calls for MDM.

What is Master Data Management (MDM) in CPG?

MDM is the process of applying a CPGs business-specific rules, nomenclature, and specifications to their master data. For example, an organization may want to customize terminology in their master data, create more streamlined or more granular product categories and sub-categories, or otherwise tailor their data to be more useful for decision-makers and stakeholders. 

MDM helps to ensure that internal analytics and reporting tools are comparing apples to apples. Here’s how this might look in the real world. 

Imagine a granola bar company that sells its products at Whole Foods, Target, Walmart, and Dollar Tree locations across the US. Each retailer passes retail data about granola bar sales, pricing, and inventory back to the supplier via its own unique data pipeline, and each retailer uses its own formatting standards. One may use a five-digit format for store location zip codes while another uses nine.  Units of measurement (ounces, kilograms, pack sizes) might differ. Walmart uses the term ‘choco-nut granola’ bar to describe a certain product, while Target uses the term ‘chocolate nutty bar’ for the identical item.

For the CPG to use the data for internal analysis and reporting once it has been aggregated, they must ensure a consistent format for zip codes, product names, and so on. 

While the process of data normalization eliminates variability, errors, and duplication during the retail data ingestion process, MDM tailors the master data to standards the CPG uses across its business and business tools. In the master data, a ‘chocolate nut bar’ is a ‘chocolate nut bar’.

An organization may want to customize terminology in their master data, create more streamlined or more granular product categories and sub-categories, or otherwise tailor their data to be more useful for decision-makers and stakeholders. 

How MDM solves CPG data challenges

MDM helps CPG suppliers better leverage data to address business challenges they face in a highly competitive market with complex supply chains.

Many CPG suppliers reckon with siloed data and a lack of integration between data sources and databases, and might rely on manual data extraction and reporting methods. These extra steps and fragmentation lead to higher costs for the company and mean that teams are often working with outdated and disorganized data when making strategic decisions. 

In addition, the CPG industry is an increasingly competitive landscape that requires quick response to fast-moving market shifts and evolving consumer preferences. CPG brands must remain agile and innovative to thrive in this environment. With immediate access to actionable and decision-ready master data, CPGs can more easily stay attuned to consumer preferences, embrace new trends, and seize opportunities ahead of competitors.

Finally, there’s the essential challenge of visibility. CPGs can’t act on what they don’t see. Without consistency, uniformity, and accuracy across data domains, CPG analysts may make incorrect calculations regarding inventory and sales velocity, for example, which could lead to out-of-stocks and waste. Marketing teams may allocate budget to retail locations that underperform. And problems can domino across the organization. 

By standardizing master data for use throughout the organization, MDM improves data accuracy, streamlines data organization, and provides a single source of truth for diverse functions and departments.

Many CPG suppliers reckon with siloed data and a lack of integration between data sources and databases, and might rely on manual data extraction and reporting methods. These extra steps and fragmentation lead to higher costs for the company and mean that teams are often working with outdated and disorganized data when making strategic decisions. 

Benefits of MDM

A more automated and sophisticated data strategy can help CPGs better tackle data challenges, and MDM is an essential step in that process.

MDM allows a CPG to reduce data fragmentation, identify and act faster on data insights, and improve visibility across their data domains. Even for a relatively small CPG company, product data alone may comprise multiple product categories, subcategories, identifiers (SKUs, UPCs), pack sizes (1pk or 3pk), case sizes (eg. sold in 24ct cases), and more. For large, global CPG organizations with thousands of products and numerous retail partners, MDM is vital to keeping data consistent throughout the enterprise. 

The benefits of MDM are both operational and strategic and can include:

• Ensuring product information, customer data, and other critical information is accurate and consistent across all internal systems and channels
• Streamlining internal processes such as product data management, inventory management, and order processing
• Providing improved customer insights and a better retailer-supplier experience 
• Enabling better demand forecasting, inventory management, and collaboration with partners
• Ensuring regulatory compliance by maintaining accurate and up-to-date product information
  

Clean retail data can also be used to implement multi-domain MDM across back-end tools and databases. Multi-domain MDM involves aggregating data verticals for deeper business analysis and insights. For example, store-level retail data and marketing data can be combined so that CPGs can target digital campaigns to areas that have more product in stock. The organization can then analyze marketing performance metrics alongside retail POS data to measure sales lift and campaign efficacy. 

Even for a relatively small CPG company, product data alone may comprise multiple product categories, subcategories, identifiers, pack sizes, case sizes, and more. For large, global CPG organizations with thousands of products and numerous retail partners, MDM is vital to keeping data consistent throughout the enterprise. 

How to implement MDM in CPG

Implementing a successful Master Data Management (MDM) system within a CPG organization requires a structured approach. Here's a breakdown of the steps involved.

1. Assess Data Environment

• Analyze the existing data infrastructure. Which data sources are most important (retail data, customer information, product specifications, etc.)? How is the data currently stored and managed?
• Determine what the CPG aims to achieve with MDM. Improved data accuracy? Better decision-making? Increased operational efficiency?
• Pinpoint the core data domains essential to achieving the defined goals. Retail data is a cornerstone for any CPG.

2. Clean and normalize data

• MDM is significantly more effective when implemented with data that has been cleaned and normalized to ensure consistency and eliminate redundancies.  
• This initial process of data normalization is necessary to eliminate duplicate information, formatting issues, bugs, and incomplete data.
• In addition to normalization, harmonization refers to the process of streamlining data conventions across retailers, for example, so MDM rules will only need to be applied to the master data as a whole.

3. Apply master data rules

• Define how product names, attributes, and other data will be consistently written.
• Create custom categories and hierarchies that align with the CPG's internal reporting and analysis structures.
• Apply these rules manually or with a streamlined software solution.

4. Integrate master data into systems for Master Data Management

• To implement MDM across an organization, data domains need to be centralized in a repository, providing a single source of information for teams.
• For CPGs, master retail data can be regularly integrated into a database leveraging an API connection or reliable data pipeline.

MDM for CPGs: Crisp can help

MDM traditionally involves manually extracting, normalizing, organizing, and reconciling master data, which can be time-consuming, error-prone, and unsustainable for a growing organization. As CPG suppliers expand their product lines, manual MDM becomes increasingly difficult to manage. It can be challenging to maintain data quality and consistency across a large number of products and channels without automated workflows.

Starting with automating data normalization for each retail data connection, Crisp exports clean retail master data with our Master Data Manager, which allows CPGs to precisely control and organize how data is structured in Crisp dashboards, as well as in data warehouses and BI tools like Snowflake, Databricks, Power BI, and more, which Crisp maintains automated connections to. 

Using Crisp for MDM enables CPGs to:

• Automatically normalize and harmonize data across retailers
• Customize and create new product names and categories
• Easily remove categories and attributes from Crisp, such as when a SKU has been discontinued  
• Combine data efficiently, such as to combine the sales of two products after a packaging change

As experts in CPG data visibility, Crisp can help you at every stage of the data management process. Reach out to learn more about the Crisp platform, Crisp MDM tools for CPG, and how we help CPG brands get the most from their retail data.