Data project helps consumer goods company save $1.5M
A consumer goods company undergoing massive transformation was ready for a transportation management solution, but faced a significant hurdle.
Employees had little trust in inventory volumetric data, so the company turned to NTT DATA’s supply chain experts for master data verification, consolidation and management. The team quickly kicked off a master data improvement project to help the transportation and warehouse program move forward confidently with one source of truth.
Necesidad empresarial
The company’s information sat in two separate systems, which led to inconsistent data and product information gaps. Across multiple locations, employees couldn't obtain the accurate consolidated packaging, volume, weight, unit load and stack pattern data they needed for optimal warehouse and transportation capacity planning. Lack of quality data led to significant inefficiencies and higher costs.
The company partnered with NTT DATA’s Packing Optimization services to evaluate its existing transportation management system and look for significant cost savings, packaging efficiencies and sustainability benefits.
Resultados
- Gains significant cost savings and packaging efficiencies
- Acquires a consolidated, single source of truth for item-level package data
- Builds uniform controls across all business units for better data governance
The completed analysis revealed the company could ship 1,000 fewer truckloads per year, save an annual $1.5M in freight costs and reduce its carbon footprint by more than 1,800 metric tons of carbon dioxide.
Solución
NTT DATA started the process by collecting prioritized SKUs from eight business units — each with data from multiple products with various storage and handling requirements. Next, the team custom-developed an interactive data collection tool to compare data measured on-site against data stored in the enterprise resource planning (ERP) system. They benchmarked the approach and measuring methods against Global Standards 1 (GS1) to identify acceptable product variance levels.
NTT DATA trained on-site teams to perform standardized package measurements for size, weight, and volume. They developed consistent approaches for other essential data elements such as unit load data of pallet size, stack pattern and load height. The team focused on all levels of packaging, from shelf-level “inner packs” for retail to pallet-level configurations. Then, using the interactive data collection tool, they compared data measured on-site with ERP data in real time, revealing which products required updates.
The result: only one-third of the ERP data was accurate, another one-third required volume updates, and one-third required weight updates.
ERP and TMS data consolidation
With the analysis in hand, the team uploaded the accurate volume and weight data into its ERP system, providing the company with a consolidated, single source of truth for its item-level package data. The completed analysis and updated product data revealed the company could ship 1,000 fewer truckloads per year, saving an annual $1.5M in freight costs. In addition, the company’s team was happy to realize the sustainability impacts of 1,000 fewer trucks on the road, which meant reducing its carbon footprint by more than 1,800 metric tons of carbon dioxide. Finally, because of the improved master data project, the company was more confident in programming the system to make the right decisions during truckload planning.
Transportation process improvements
NTT DATA’s master data improvement project helped the client recognize significant cost savings, packaging efficiencies and sustainability benefits, but it also uncovered additional process gains for each location. Throughout the project and on-site training, the client’s teams uncovered inefficiencies and differences in the packaging processes across sites. This discovery helped the company fine-tune its standardization protocols for more uniform controls across all business units for better data governance going forward.
About this case study
A master data improvement plan helped a leading consumer goods company recognize significant cost savings, packaging efficiencies and sustainability benefits.