Introduction
Carhartt Inc., a prominent clothing and sporting goods company, has been into manufacturing and supplying of work wear apparels since 1889. They have been growing over the years and with time have embraced various channels to sell their products. To this end, various underlying IT systems were built catering to each of the sales channels. With this in place, they have an assortment of systems like AS400, SAP & cloud SAS applications like Cloud twist and simple excel files. While the growth and sales from multiple channels did help them diversify their revenue and gain global reach, the company was facing various challenges in terms of operational inefficiency, poor customer support, bloated marketing expenses, minimal analytics, and non-uniform customer experience.
Thus, what was the best way for Carhartt to do so? The best solution was to shift from a multi-channel approach to an Omni channel retail experience. In response to these challenges, Carhartt reached out to Talend to implement a Master Data Management (MDM) to create a rich and satisfying shopping experience across all channels, as well as gain greater control over master data assets. Talend’s implementation partner, Artha Solutions, focused on Carhartt’s data integration and complete data management. It provided Carhartt a 360° view and delivered high data accuracy for operational transactions and analytical reporting. From requirements to implementation, Artha Solutions successfully implemented the complex MDM solution in 4 months flat! This is something that is unheard of in the MDM world. The telling benefit of the complex central rules implemented by Artha was when data of over 4 million customers were brought on to the MDM platform, a total of 50,000 duplicate customers were identified and removed from the system in the first 6 hours itself.
Challenges of a multi-channel approach
While multi-channel e-commerce and retail line up perfectly with how customers already shop, adopting an internal multi-channel approach could be disastrous:
- Difficult for data management and analysis
- Difficult to differentiate each marketing channel
- Does not put focus on creating a consistent shopping experience
- Unavailability of real time data
- Unable to apply common rules on data due to lack of central data
Omni Channel Experience
Important data or information keeps piling up over time, which becomes redundant and needs to be managed. However, when the point of heightened redundancy is reached, businesses start to suffer from operational and efficiency challenges. This leads to a dire need for data accuracy, coherence, accessibility, and uniqueness. Searchable storage becomes very crucial for all types of businesses, highlighting the significance and criticality of master data management.
Advantages:
- Single source of truth
- Improving sales
- Better data collection
- Enhanced productivity
Improvement in Consumers’ Perception & Satisfaction
In Comes Artha Solutions with Their Expert
MDM Implementation Team
Businesses today struggle to become agile by implementing information systems that support and facilitate changing business requirements. As a result, the management of information about products, customers, etc. has become increasingly important.
Additionally, business organizations have systems in place to store and retrieve this data. However, many disparate systems store information, which leads to overlapping, redundant, and inconsistent data. So, where do users go to get valid, accurate, consistent data?
Master Data Management! However, the effectiveness of an MDM solution is as good as the team that is implementing. MDM implementation encompasses wide areas of expertise to do activities such as Talend DI, DQ, Talend MDM, and Talend Data Prep. Master data management (MDM) is critical to achieving effective information governance. Failure to accurately manage information has been the root cause of several incidents, including the leak of sensitive information.
Why is Master Data Management Important?
- Allows smooth functioning of the organization
- Derives meaning out of assembled data
- Improves operations and efficiency
- Reduces process errors by consolidating and controlling data
- Removes duplications
- Avoids missed opportunities and dissatisfied customers
- Data consistency
