Successful retailers recognize the value that good data can bring to their business. They also understand how good data can be used to achieve business goals, monitor growth or progress toward those goals, and ultimately measure success. However, as businesses grow in size and scale, so, too, does the volume of data that must be efficiently managed. This volume can lead to a deterioration in data quality, and, coupled with increasing regulatory scrutiny, emphasizes the importance of data governance in the retail industry. 

The need for good data governance isn’t new – any retailer knows how mismanaged data can impact a business. Beyond that, there’s been increasing regulatory guidance, forcing retailers to reassess and reconsider their current data practices. From emerging traceability data regulations to the EU’s General Data Protection Regulation (GDPR) to California’s Consumer Privacy Act (CCPA), current and pending legislation for data privacy and protection poses a threat to how retailers market, share, and utilize collected data. With significant amounts of data coming in from multiple systems and channels, how do you ensure you protect consumer privacy, abide by industry and government regulations, and effectively manage and utilize your data?  

Implementing a data governance program can help manage this growth in volume while reducing challenges in scale.  

Challenges of Data Governance in Retail  

Data governance in retail is a process of managing data availability, usability, integrity, and security. This can include policies, standards, and accountability frameworks that align your business with good data management practices and enable effective decision-making. 

One of the challenges with data in retail, in particular, is that the retail industry has data assets across multiple systems and channels – POS for in-store sales, webstores for online webstores, and ERP for wholesale sales. The omnichannel interactions span these systems, gathering customer data and other personally identifiable information (PII) across each. However, this data isn’t always centrally managed or clearly defined. Each team working through these systems – wholesale, digital, storefront – often operates independently and doesn’t always communicate across channels. This leads to a general lack of organization, a breakdown in effective decision-making, or inconsistency in numbers. 

Take, for example, a retailer using the wrong data or an incorrect definition to develop a forecast. This can have catastrophic consequences, such as overspending on inventory, missed sales, or forced markdowns. Or, imagine marketing and digital webstore teams reporting different sales numbers from separate systems because the definition of a transaction wasn’t clearly defined. Are they including cancelations or excluding returns? How do they account for exchanges? Are they counting from when orders are shipped or placed?  

Disparate groups without good data governance risk losing time and resources.  

Benefits of Strong Data Governance in Retail 

Data governance can help avoid the challenges that retailers see with these assets. Creating accountability for teams and individuals through processes for managing and maintaining data can drastically improve data quality and downstream reporting. Organizations that build data governance frameworks for the onboarding and sharing data reduce confusion on cross-channel reporting, a problem area for most retailers.  

Strong data governance in retail provides a number of other benefits: 

• Efficiency: Knowing what data sets to use, what each means, and the key user groups to follow up with will save your organization time and resources. 
• Improved decision-making: Defining available data sets and users can help avoid costly mistakes of using inaccurate data. 
• Data quality: Better understanding your data can lead to more consistent and accurate information. 
• Enabled insights: Improved sharing and data understanding can help draw new conclusions from assets you already have. 

Getting Started with Data Governance 

Robust data maintenance and governance are essential steps to becoming data-optimized and preventing data debt at any organization.  Even small initiatives for data governance can have a meaningful impact. Consider creating a “data glossary” to define metrics and KPIs to help maintain data and definitions throughout the organization. 

You don’t always need an entire platform; it starts with processes and knowledge. As your organization takes steps toward good data governance, keep these considerations in mind: 

• Identify data assets 
• Standardize terms and definitions 
• Build reusable templates to understand each as you go forward 
• Identify and enable data owners within the organization for each data set 

Data is integral to your retail operations. As such, companies must invest the time and resources into establishing good data governance practices. For more information on best practices in data governance in retail, contact our retail analytics consultants today.