Case Study

OTIF Scoring

Putting it all together

Combining a Unified Data Platform, Robotic Process Automation (RPA), and Artificial Intelligence (AI) to improve On-Time, In-Full (OTIF) scoring can be seen in the case of a company that used a bot-building platform to overcome challenges related to data consolidation across production, inventory, and sales.

Challenge

The company was struggling to obtain a consolidated view of data across production, inventory, and sales. They often relied on manual reporting to combine sales and production data, which was time-consuming and prone to errors. This lack of consolidated data made it difficult to track key performance metrics, including OTIF, which affected their ability to ensure timely and complete deliveries.

Solution

The company used a bot-building platform, to build a bot named Lucy. Lucy was designed to help the sales team obtain immediate, easy, and anywhere access to data. By connecting to various Line of Business (LoB), reporting, and Customer Relationship Management (CRM) systems, the bot was able to provide a unified view of data across different departments.

Outcome

The combination of a Unified Data Platform, RPA, and AI helped the company improve its OTIF scoring. The sales team was able to access all sales data on a unified platform and track business metrics, including OTIF, more effectively. The real-time processing and predictive capabilities of AI allowed the team to proactively address issues and ensure on-time, in-full deliveries.

Role of RPA and AI

RPA was used to automate the process of data collection and consolidation. This reduced the manual effort involved in reporting and ensured that the data was accurate and up-to-date. AI was used to process large amounts of data in real-time and provide predictive insights. For example, Lucy could notify sales team members if they were off-track in meeting targets or if there were potential issues that could affect OTIF performance.