Technology Category
- Analytics & Modeling - Process Analytics
Applicable Industries
- Life Sciences
- Mining
Applicable Functions
- Logistics & Transportation
- Procurement
Use Cases
- Last Mile Delivery
Services
- System Integration
About The Customer
Johnson & Johnson is a multinational corporation that develops medical devices, pharmaceuticals, and consumer packaged goods. Founded in 1886, the company has grown to become one of the world's largest and most diverse healthcare companies, with operations in more than 60 countries. Johnson & Johnson's products are sold in over 175 countries, and the company employs approximately 132,200 people. The company is committed to innovation and continuous improvement, and is always looking for ways to optimize its processes and deliver better value to its customers.
The Challenge
Johnson & Johnson, a global healthcare and life sciences company, was seeking to digitize its continuous process improvement and bring its process mapping and discovery efforts into the 21st century. The company was facing challenges in identifying inefficiencies in their processes and understanding the value of Process Mining. The traditional methods of process improvement were not providing the desired results, and the company was looking for a more efficient and effective way to optimize their processes. The challenge was to find a solution that could be easily adopted by their global teams and provide consistent and rapid value creation.
The Solution
Johnson & Johnson identified Celonis as the perfect partner to help them digitize their process improvement efforts. They embarked on a proof of value exercise using Celonis to analyze data from a single system, uncover inefficiencies, and understand the value of Process Mining. This exercise quickly became a source of ongoing value, leading to the creation of global templates. These templates, enabled by Celonis, provided a strong foundation for Johnson & Johnson’s Process Center of Excellence. The company adopted a 'crawl, walk, run' methodology, getting users into the system and into their data as quickly as possible, refining user stories and analysis over time. The company also moved to a team-based methodology, creating metrics that could be leveraged upstream and downstream from the team that created them, while remaining tied to that team’s objectives.
Operational Impact
Quantitative Benefit
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