Streamline Global Manufacturing

This global powerhouse is a leading player in nearly every major sector of the economy including energy, healthcare, consumer products, industrial automation, transportation and financing. Over its 172-year history, this industrial conglomerate has gr own from a 10-person operation to a workforce of 3 80,000 spread across the globe.

Challenge

Like all companies that operate on this scale, this means expertise and data are now scattered around the world.

The company knew they needed a solution to make expertise and information widely available. They built search-based applications starting over ten years ago. But the previously purchased products, didn’t have the depth of capabilities needed to support the company’s deep search-based application needs. A reusable platform that could become the powerful core of all of their search-based applications was required.

Solution

This is a story of how one of the worlds most respected companies is using Sinequa to develop information-driven applications using data mining, natural language processing (NLP) and machine learning to process massive data sets to find indicators of known and unknown answers to problems and queries. This approach brings significant automation that is particularly helpful when evaluating unstructured data. Because of machine learning, information-driven applications were developed that surface emerging patterns that humans could never detect, allowing them to:

• Win more business vs global competition
• Create industry-leading solutions
• Secure restricted data, meeting the world’s toughest privacy regulations
• Facilitate product repair
• Improve customer service
• Lower cost

Future Annual Results

The Sinequa solution included identifying and quantifying the benefit of solving manufacturing specific business issues. The following results include the corresponding annual benefit :

• 230,000 out of 3 80,000 employees save time daily, increasing productivity | €1.25B / $ 1.42B
• Reduced cost of compliance | € 83M / $ 94.3M
• Increased productivity of 3,000 field engineers saving | €27M / $30.6M
• Expert finder increases profit from revenue | €6.9M / $ 7.84
• Produce cost a voidance within the IT team | €288k / $327k
• Reduced the need for 16 FTEs in the call center sa ving | € 1.6M / $1.81M
• 2% more effective at winning new business when responding to massive RFPs
• Anticipate future efficiency of 3,500-person online customer suppor t team | €31.5M / $35.7M