At a glance

A national grocer needed to bring intelligent automation and AI to their produce supply chain and ensure their stores were stocked with the freshest food for their customers. The client was looking for a trusted Databricks partner with experience applying AI in retail. By modernizing their data platform and applying machine learning to real-time insights, Kforce Consulting Solutions delivered a scalable solution that's driving measurable cost savings, improved inspection results and increased operational efficiency.

From strategy to implementation, we provide the knowledge and leadership our clients rely on to accelerate their business. Our proven team takes a unified approach to driving large-scale change and unlocking new opportunities for growth and success.

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Improving cold-chain management and reducing food waste with Databricks and AI

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Custom solutions to achieve your goals

Together Toward Tomorrow

Challenge

The national grocery chain needed to improve the freshness of perishable food in their stores. The existing systems were not equipped to handle real-time data processing and analytics, leading to inefficiencies in supply-chain operations and lost revenue. Slow response timesThe client didn't have a streaming capability and lacked real-time data ingestion and processing. This limited their ability to respond quickly when perishable food was at risk in transit. Inconsistent data qualityThe data architecture was outdated. Without medallion architecture or a layered data model, it was challenging to trace data lineage and ensure quality. Poor supply-chain insightsThe client lacked a modern data platform. Data was siloed and inaccessible, which made it difficult for the client to understand what was happening across their supply chain in real time. Low trust in data Without proper validation, testing or metadata management, stakeholders had limited confidence in the data for decision-making.

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Unlocking AI and analytics value with modern cloud data platforms

Solution

Project outcomes

The national grocer successfully integrated AI into their business process and saw near-immediate benefits, including enhanced freshness and increased operational efficiency. The work resulted in several qualitative improvements: Improved cross-functional collaboration thanks to a centralized platform for inventory data Accelerated decision making due to self-service enablement that doesn't rely on engineering teams More secure and efficient data access through the Unity Catalog Reduced latency and overhead storage without duplicating data

40%

28%

REDUCTION IN DATA ENGINEERING EFFORT

50%

improvement in data access latency

COST SAVINGS ON STORAGE AND COMPUTE

For example, analytics may reveal that fresh produce like leafy greens and bananas are frequently exposed to high temperatures during transit from distribution centers to stores. With this insight, management can identify critical issues, direct operations to investigate and resolve the root cause, greatly reducing the chance of shoppers coming across wilted lettuce and mushy bananas.

Scalable insights across the supply chainDesigned and implemented an end-to-end, cloud-native architectures for real-time analytics. Trusted, governed dataImplemented Databricks Unity Catalog for centralized data governance, access control and metadata management across domains. Implemented validation, testing and monitoring frameworks to ensure data accuracy and ongoing trustworthiness. High-quality data processingTransitioned to a Databricks Medallion architecture and built Bronze, Silver and Gold data layers to support structured data processing and further data lineage and traceability. Improved supply chain intelligenceDeveloped robust pipelines for ingesting data from Supplier Hub, Coupa (Spend Management) and other internal/external systems. AI use cases & designEnabled machine learning lifecycle with Databricks Managed MLflow, including feature store, model training, tracking, registry, serving and monitoring.

Deliverables

2.5x

INCREASE IN DATA ADOPTION ACROSS TEAMS

Because of the success of the project, the client extended the partnership with Kforce to include a second phase of work. The initiative is ongoing, and outcomes are still being achieved. Estimated quantifiable outcomes, based on results to date, include: 40% reduction in data engineering effort through self-service access and reusable curated datasets, reducing dependency on engineering teams for ad hoc data requests. 50% improvement in data access latency enabled by Unity Catalog's zero-copy data sharing and optimized query performance across workspaces. 28% cost savings on storage and compute by eliminating redundant data copies and streamlining processing through the medallion architecture. 2.5x increase in data adoption across teams due to improved data discoverability, trust and accessibility via centralized governance and documentation.

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MEET THE TEAM

VP CONSULTING SOLUTIONS

DATA & AI

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Ted Horne

SVP BUSINESS PARTNER

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Jim Vyas

PRINCIPAL CONSULTING SOLUTIONS

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MANAGER SOLUTIONS DELIVERY

Brad Boyd

William Lockley

To address these challenges, Kforce implemented a cloud-native data architecture using Databricks. This included streaming pipelines, curated datasets using a Medallion Architecture, and AI-driven quality scoring to help inspectors make real-time decisions. This comprehensive solution optimized cold-chain operations and and gave the grocer the insights needed to reduce the risk of food going bad in transit. Ingestion pipelines The team built robust pipelines to collect data from both internal systems and external applications (e.g., temperature sensors, logistics platforms). Data curation and presentationData was curated, standardized and presented in accessible formats for internal stakeholders to drive actionable insights. Data integrationKforce joined data from multiple systems to create a unified Fresh Domain Data layer, enabling holistic visibility across the cold chain. Data quality managementThe team proactively investigated and resolved data quality issues to ensure accuracy and reliability in analytics and reporting. This is an ongoing, continual activity to ensure data quality remains excellent. Cloud-native architectureLeveraging Azure Data Lake Storage (ADLS) and Databricks, the team implemented a medallion architecture that ensures scalable, high-quality data processing. Unified data governanceUsing Databricks Unity Catalog, Kforce established a single source of truth for sourcing data, enabling consistent access and governance across teams. Platform enablement The team adopted the Databricks Framework and integrated API-driven data sources to enrich the platform with both real-time and historic insights. The project operated off real-time and batch data from the refrigerator supply chain, including temperature sensors, purchase orders, warehousing and transportation. This data informed the AI-driven cold-chain intelligence initiative.

A progressive data journey

Analytics Uncover improvement opportunities

Operational insights Extract meaningful next steps

Real-time adjustments Empower active participation in day-to-day decisions

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