Advances in data management and analytics use cases are helping enterprises across industries focus on business outcome-oriented Data & Analytics (D&A) initiatives. Process improvement, asset management, cost efficiencies, and better customer experience are some of the major enterprise objectives driving the adoption of analytics and AI use cases. Enterprises have also started focusing on monetizing data and providing data-driven products and solutions to customers to differentiate themselves in heavily saturated markets. Further, the pandemic has led to a significant shift among organizations to focus on digital initiatives that ensure workforce safety and build operational resilience.
In this report, we assess the current state of analytics adoption in the manufacturing industry, deal characteristics in the space, emerging themes driving the adoption of analytics, and advanced analytics and AI use cases that support manufacturers across the value chain. Further, the report discusses how enterprises are rationalizing and building agility across the value chain through analytics to ensure business continuity, protect their workforce, and tackle demand and supply volatility in the next normal.
Scope
Industry: manufacturing
Services: D&A
Geography: global
Sources: publicly available information (120+ D&A case studies), Everest Group’s survey of 100+ midsized and large enterprises, and Everest Group’s proprietary transaction intelligence database
Contents
In this report, we study the following topics:
Manufacturing market overview – current state of analytics and deal characteristics
Emerging themes in manufacturing driving D&A adoption
Analytics adoption and use-case analysis by value-chain segment
Following an exponential rise in data volumes over the past decade, there isa pressing need for enterprises to gain data-backed insights. This need has driven rapid scaling of ArtificialIntelligence (AI) and Machine Learning (ML) systems across orga…
