Real outcomes, not slide decks.

Challenge

Critical operations were running on disconnected manual Excel files and systems, making reporting on production yields and financial forecasting slow and error-prone.

Outcome

Implemented Chobani's first cloud data warehouse (Snowflake), uniting their demand planning (TILLIT) and ERP (Dynamics AX) systems. Pivot embedded their sole data engineer into the project team to build long-term internal capability.

Challenge

A high-volume data environment (millions of transactions) that made traditional BI tools sluggish. The transition to the cloud had stalled due to a BAU backlog and a lack of specialised senior resources.

Outcome

Delivered a production-ready use case in record time, moving from a stalled project to a major business outcome. Implemented an AI-driven search interface (ThoughtSpot) to allow users to ask complex logistics questions in simple business language.

Challenge

Needed to level the playing field for independent retailers by providing the same real-time intelligence used by national retail giants.

Outcome

Developed a robust, real-time transaction processing system that provides the 'data edge' needed to outperform larger competitors.

Challenge

The existing BI solution could not cope with massive transaction-level data, leading to multi-minute dashboard load times even after data aggregation. Business users were forced to rely on the analytics team for deep-dive analysis, resulting in delays and lost opportunities.

Outcome

Pivot Analytics successfully deployed a ThoughtSpot search and AI platform, allowing category and operations managers to ask their own questions in plain language. This shifted the culture from static reporting to real-time decision-making during live meetings.