CASE STUDY

Data Management Assists a Leading Retail Industry Client Reduce Data Redundancy and Create a Consistent Workflow

Apr 7, 2018

The client: A leading player in the retail industry

Area of engagement: Data management

The global retail landscape has seen drastic changes in the last decades or two. Initially, the retail industry was dominated by small, local stores, and traditional department stores, whereas it is currently being dominated by mass merchandisers and specialty and online retailers.

Typically, the retail industry deals with different types of goods that are essentially divided into durable goods, such as furniture and large appliances and nondurable goods, which include food, clothing, and other such products. The data generated from this sector is huge owing to their involvement in various kinds of products. Also, since most of the retailers use many systems to collect and store data they are increasingly concerned and are focusing on maintaining data quality, data persistence, and data sharing by implementing a centralized system.


Speak to our analytics experts to learn more about Quantzig’s data management solutions for companies in the retail industry.


The following are some of the significant challenges faced by organizations in the retail industry:

  • Lack of processes and systems: Extracting data from disparate databases results in data inconsistencies and loss of valuable information if the information is not analyzed accurately. Therefore, the lack of accurate data management strategies and processes contributes towards inaccurate data.
  • A reactive approach to data management: Several organizations have adopted a reactive approach to data management, which leads to data inconsistencies as they often wait until specific issues arise. This is the biggest challenge for the retail firms as they are unaware of the problems associated with their data.
  • Sheer volumes of data: The huge amounts of data that is generated by firms operating in the retail sector, makes it difficult for them to manage, aggregate, and creating value from data. The sheer volume of data being created, and the abundant collection channels make good data management an important, yet elusive goal.
  • Fragmented data ownership: In most organizations, data ownership is still predominantly fragmented, with the management of data quality and consistency being driven by multiple stakeholders and frequently measured at a department level, rather than across the entire business unit.

It is important for retailers to ensure that they have good data governance underpinning all the other processes. But it is harder than you’d think to get the process of measuring and managing data right. Considering today’s retail scenario, while most businesses strive for gaining data-driven insights, the others are relatively unaware of such challenges.

Want to know more about our approach to data management and how we help retail companies identify and adjust to the latest market trends? Request a FREE proposal today!

The Business Challenge:

A client, a prominent player in the retail industry approached our team of experts to help them devise an effective system across their business units. The client was finding it difficult to manage and extract accurate details from their customer’s data in a dynamic retail environment. They were looking at maximizing revenue and customer loyalty by delivering consistent, tailored customer experiences.

The Solution and the Business Impact:

Quantzig’s solutions helped the client develop a data governance framework to reduce data redundancy. It also assisted them in improving the transparency and clarity in information. Additionally, the client was able to develop a repository or databank for meta data management. This, in turn, helped them take advantage of the metadata management services that were offered.

Data Management Solution Predictive Insights:

As organizations across the globe begin to adopt a more data-centric approach, they recognize the importance of managing and maintaining the quality of data. From building healthier customer relationships to overcoming internal and external data management challenges, organisations will need to overhaul and evolve their data management practices.

In addition, retailers are also increasingly understanding the need to employ a standard meta data management framework, which acts as an end-to-end process for creating, managing, and maintaining data. However, for players in the retail sector, the ability to use high-quality data to make critical business decisions that improve the bottom line should be the main area of focus.

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