Mitre 10

About the Company

Mitre 10, New Zealand’s largest home improvement and garden retailer, is a local co-operative of small and medium-sized businesses owned by Kiwi families. Today, Mitre 10 has 84 stores across the country along with a national support center. Collectively, it employs over 8,000 people nationwide and supports over 500 local suppliers.

As a proud Kiwi business, Mitre 10 is dedicated to enhancing the communities it serves. Its mission: to inspire Kiwi to love where they live, work, and play.

Project Background

Mitre 10 initiated a business transformation journey with the goal of delivering superior customer experiences. Given its sizeable presence and ecosystem across New Zealand, Mitre 10 recognized the critical need to establish a solid core of trusted data to achieve this goal which would help to future-proof the co-operative. The technology aspect of the program aims to modernize systems, streamline processes, and enable better information access, creating efficiencies and ultimately empowering Mitre 10 team members to deliver exceptional customer experiences

Challenges

The primary objective of our work was to consolidate all data into SAP S/4 HANA, establishing it as the cornerstone central repository and core engine. However, harmonizing data across Mitre 10’s expansive network of 84 independent stores was no small feat as there were differences in how each store managed their data and inventory systems.

Central to the success of this consolidation journey was the critical need to stabilize Mitre 10’s Extract, Transform, Load (ETL) process — a crucial first step to ensure the underlying quality and integrity of its data. The sheer volume of data flowing in from its stores nationwide meant that this was a substantial and complex project. Recognizing the imperative for stability, security, and scalability within its underlying data infrastructure, Mitre 10 sought the expertise of Syniti, an expert in SAP S/4 HANA transformations.

Solution & Implementation

Combining its unique data migration methodology with its strong expertise in SAP data migrations, Syniti kicked-off the project with the implementation of the Syniti Knowledge Platform, a silo-free centralized data management solution. Integrated with migration, data quality, and data replication capabilities, the platform delivered value in a number of areas.

Firstly, it helped to centralize and simplify the overall data migration process within a single solution, delivering Mitre 10 complete visibility and transparency throughout the project.

To that end, the platform’s in-built data quality assessment and matching engine helped devise a comprehensive plan and roadmap for the successful migration to SAP S/4 HANA.

Secondly, the solution significantly transformed the ETL process by delivering more intelligent code auto-generation, which meant that Mitre 10’s teams no longer had to spend hours on ETL alone. Since the implementation of the platform, Mitre 10 saw an improvement in the accuracy of its ETL output by 96% from its first data release prior to engaging Syniti.

Lastly, the solution enabled better data governance through intelligent matching, deduplication, and harmonization. This ultimately helped to preserve the integrity of Mitre
10’s data and instill internal confidence in its accuracy and reliability. The final result was one core system with trusted data across Mitre 10’s ecosystem.

Outcomes

“Syniti’s Data First approach set the data foundation we needed to ensure a successful migration to SAP S/4 HANA. The Syniti team not only had unparalleled technical knowledge on SAP, but a deep understanding of our data needs and how it ties into our overall business,” said Chris Waterman, Project Manager for Data Transformation at Mitre 10. This has not only helped the co-operative realize data as a true business asset but also set them up for success as they look to implement new processes and enhance the experiences of its team members and customers.

Future Plans

With a solid core of trusted information, Mitre 10 is now looking at how it can intertwine data value across levels of its day-to-day processes, from onboarding new customers all the way to compliance. This will warrant a strong data governance model that can be tailored to the creativity and business needs of its teams at each store — so they can deliver the best customer experiences.