As retail businesses keep growing, data sources grow with increasing sales channels (web, app, store, phone, etc.). Businesses also start integrating third-party SaaS products (ERP, PIMS, CMS, etc.) into their tech stack to fulfill their operational needs, data from them is mostly stored in their proprietary warehouse running on legacy data technology. As a result data gets stored across different data silos, in rigid formats, under different technology stack.
Challenges of Data Silos in Retail
Departments such as marketing, sales, supply chain, logistics, and customer service frequently rely on separate systems to manage and store their data. This gives rise to data silos posing unique challenges for an industry that is heavily reliant on data.
Limited visibility and insights
Data silos prevent retailers gaining insights about their customers, operations, and business performances under one umbrella. This makes it difficult to run comprehensive analytics on customer behavior, market trends, and make informed decisions.
Inefficient operations
Since data is separated across different warehouses and technology stack a lack of transparency and coordination arises. Data inconsistency can be detrimental to the performance of highly coordinated departments like supply chain management, inventory management, and post sales support.
Prevent Omnichannel Marketing
Data is the fuel to today’s marketing strategy and data silos stand as obstacles to that path. The lack of complete data over a customer journey makes it difficult to build omnichannel experiences. Similarly it is also difficult to build targeted campaigns based on customer preferences, geography, and demography.
Limited access control
Data silos lead to lack of data ownership especially, when it is stored in some third-party SaaS providers warehouse. This makes it difficult to ensure the compliance and security of data as no consistent control policy can’t be enforced.
The answer to all these inconsistencies and challenges arising from data silos is to build a data mesh.
What is a Data Mesh?
A data mesh is an architectural framework that integrates disparate data sources through a self-served data platform. It involves a decentralized approach to data ownership oriented towards the business domain that creates the data. In this model, each entity provides its data in the form of an interoperable “data product.” Every domain owns their data and sets up a pipeline to clean, filter, and share data as a product for consumption by others. This increases the attachment and sense of responsibility of managing data by the owners and improves data governance. Business functions are created to control the access of data and the format it is delivered in.
How Data Mesh is Solving Challenges of Data Silos in Retail?
In retail, despite having access to vast proprietary data, organizations find it challenging to sort, filter, process, and analyze the data in making this data work for them. Typically, a centralized team of data engineers and data scientists processes data from various business units. The team relies on a central data platform for the following:
- Gathering data from various business units or domains.
- Standardizing the data into a reliable and consistent format. This might involve ensuring uniform date formats or summarizing daily reports.
- Getting the data ready for users, whether by creating human-readable reports or preparing XML files for applications.
However, as data grows, maintaining agility becomes expensive with the existing monolithic system. There are also other challenges to this centralized approach of one team being responsible for the entire data.
The central data team, comprised of skilled data scientists and engineers, lacks in-depth business knowledge and struggles to align data provision with diverse operational needs. Making changes to the data processing pipeline, managed by this team, is a slow and complex process, hindered by conflicting priorities and limited understanding of the business domains. This can lead to delays in adapting to changes. Additionally, the disconnect between business units and the central data team results in data that may lack accuracy and relevance. A more agile and interconnected approach is required to ensure that the data serves the specific needs of a business operation effectively.
Data Mesh emerges as a solution, offering a more scalable and cost-effective approach to handling the expanding volumes of diverse data in retail.
Imagine your data as a giant warehouse filled with products (information) organized by department (data domains). Instead of having a single gatekeeper controlling who gets what, each department manages its own section with clear labeling and easy access. This is the idea behind data mesh for your retail business, and it solves 3 major challenges you might be facing with a centralized data platform:
Democratic Data Processing
Imagine your marketing team struggling to find insights buried deep in the warehouse or waiting for the “gatekeeper” to grant access. Data mesh empowers each department to own and manage their data (products), making it easily discoverable and accessible to others who need it (like marketing). Think of it as clear signage and self-service checkout for your data warehouse!
Increased Flexibility
Imagine silos forming within your departments, each hoarding their data and making it difficult for others to see the bigger picture. Data mesh encourages collaboration and data sharing by establishing a central directory, like a product catalog for all your data assets. This breaks down walls between departments, allowing them to leverage each other’s insights and optimize processes together.
Improved Data Management
Imagine your IT team drowning in requests for data access and struggling to keep everything running smoothly. Data mesh distributes ownership of data management, so each department takes responsibility for their own section of the warehouse. This frees up your IT team to focus on strategic initiatives and ensures smoother operations overall.
The benefits don’t stop there! Data mesh can also:
Boost agility: Respond faster to market changes with readily available data.
Increase cost-efficiency: Avoid bottlenecks and optimize resource allocation with real-time data insights.
Improve data security: Enforce clear access controls and track data usage across departments.
Think of data mesh as a modern way to organize your data warehouse, making it work for your business, not against it.
The Practical Implementation of Data Mesh in Retail
Data mesh is a revolutionary approach that unlocks the full potential of your data, transforming your retail operations. Some of the interesting use cases are:
Enhanced Customer Experience
Personalized recommendations
Data mesh empowers marketing and sales teams to access and analyze customer data across different domains (e.g., purchase history, product browsing, loyalty programs). This unlocks insights to create personalized product recommendations, targeted promotions, and loyalty rewards, leading to happier and more engaged customers.
Improved customer service
Support teams can access a holistic view of each customer across all touchpoints, enabling faster issue resolution and a more personalized service experience. Imagine agents having instant access to a customer’s past purchase history and preferences, leading to quicker and more relevant solutions.
Optimized Operations & Inventory Management
Demand forecasting
Data mesh allows seamless integration and analysis of internal sales data with external factors like weather patterns and social media trends. This leads to more accurate demand forecasting, reducing stockouts and overstocking, optimizing inventory levels, and ensuring the right products are available at the right time.
Streamlined supply chain
Imagine real-time data visibility across your entire supply chain, from suppliers to warehouses to stores. Data mesh enables this by connecting disparate data sources, allowing for proactive management of deliveries, stock transfers, and potential disruptions, improving efficiency and reducing costs.
Data-Driven Marketing & Promotions
Targeted campaigns
Data mesh breaks down silos between marketing, sales, and customer data, enabling marketers to create highly targeted campaigns based on specific demographics, purchase behaviors, and preferences. This leads to a significant increase in campaign effectiveness and return on investment.
Dynamic pricing and promotions
Data mesh allows for real-time analysis of pricing trends, competitor offerings, and customer behavior. This empowers retailers to implement dynamic pricing strategies and personalized promotions, maximizing profits and attracting more customers.
Conclusion
Data mesh is not just technology; it’s a cultural shift that empowers your teams to leverage data as a strategic asset. Imagine your retail business thriving on data-driven insights, unlocking new levels of customer satisfaction, operational efficiency, and market competitiveness.
