Data is a key component of today’s retail strategies. This allows organizations to make smart analytics based business decisions. From refining individual marketing efforts to improving logistics operations, to improving their overall retail strategies. The retail sector has become increasingly data-rich thanks to ecommerce and other technological advances. Despite having this data, retailers are still under pressure to adapt to the changing economic environment, including the ongoing effects of the pandemic and uncertain global economic conditions.
Retail has seen a shift from bankruptcies towards buyouts since the outbreak of the pandemic. The global retail M&A volume has increased significantly. Increasing 59% between 2020 and 2021. This increased M&A has resulted in more dispersed data. Companies now have to manage and grant access to large volumes of data spread across new teams.
Retailers are also facing challenges due to the pandemic. Customers now expect seamless and tailored experiences from companies such as Amazon and Netflix, thanks to companies like Netflix and Amazon.
Retailers must develop data strategies that allow them to better understand consumers and make informed business decisions to meet these expectations. Companies need to adapt to ever-changing environments and their data and analytics strategy must grow with them.
The Data-Driven Environment: The Challenges
Global ecommerce sales are expected to reach $2.5 trillion in 2022 Expected to reach$5 trillion and by 2025 it will be more than $7 trillion. The potential growth in retail and ecommerce shows how critical it is to address data management issues businesses currently face. It has been a key requirement for retailers to have quick and easy access their data. However, it has now become apparent that the data warehouse model is not the best approach to data management.
This centralized model does not always make it clear who has access to the data. This leads to a disorganized architecture in which key insights and data can be lost. Data warehouses are unable to keep up with the pace of change in modern organizations. Retailers cannot afford to make mistakes when it comes time to monetize their data.
Change Privacy regulationsRetailers will face another challenge as consumers demand greater transparency about their personal data. As data privacy laws are becoming more stringent around the world, it has become a time-consuming task to ensure compliance. This can lead to data consumption and analysis being delayed.
Data Mesh Approach
Retailers may query data for many reasons, including cart abandonment rates, item return rates, and geographical preferences. This data can be used by retailers to identify problems and then find solutions that will improve the business and product areas. The Data Mesh approach to data management allows retailers to quickly deploy data strategies that help them better understand customers and make more business decisions.
Data Mesh architecture, a decentralized approach to data administration, can help retailers gain more data-driven insights faster and share them more easily. Data is treated as a product, not a byproduct, and data ownership is distributed instead of being held in one IT department.
Businesses will have less chance of losing key data if they give the experts more control from the beginning of the data management process. They will also be able bypass common bottlenecks that can occur when using a central approach. This approach is more agile and beneficial for the business. It will allow for more time for analysis and less dependence on data transfers or the constraints imposed by a central IT function.
Data Mesh Adoption in Retail: Benefits
Retailers continue looking for deeper insights to help them improve customer service and build relationships with key stakeholders. For retailers to remain competitive in the retail industry, they must have more data at their disposal. The Data Mesh approach allows them to access data more quickly and cost-effectively, enabling them to make more informed decisions.
With the rise of online shopping and the distribution across channels and platforms of shopping, data volumes have increased. The Data Mesh architecture allows companies to keep control of their data, regardless of its distribution and scale.
The pandemic is affecting how consumers shop. Retailers must be able and willing to adapt to the changing environment and implement innovative data-driven strategies. The Data Mesh architecture will allow retailers to bypass some of the data management and analysis challenges they face and instead focus on the power of their data.
Andy Mott, EMEA Head of Partner Solutions Architecture & Data Mesh Lead is at StarburstWith more than 20 years of experience in the IT industry. With a deep technical background and experience across a number of industry verticals and international geographies, Mott is an expert in considering how an organization’s use of analytics, analytical culture and analytical processes can be optimized through technologies such as self-service data tools, cloud, and streaming analytics. He is also an expert Data Mesh, a new architectural approach.
