Decades old systems of record uses outdated business assumptions and models. These systems are brittle, cobbled together, and hard to retrofit, and given their outdated assumptions and design, they cannot support the requirements of digital transformation. Connected back office replaces today’s systems of record with new systems of intelligence, which retain the core capabilities while layering in new autonomic and predictive intelligence assets.
Goals and Objectives
To transform the platform tier for core ERP applications to support an information-centric environment; drive cost reduction and process efficiency across the organization (e.g., by cutting cost per transaction); and enable organizational agility (e.g., by allowing the organization more easily to scale up or down).
Machine learning, cloud computing, predictive analytics, process automation, new UX design with natural language processing, and mobile-first design
Use Case Summary
Connected back-office tools are a new platform layer for financial, human capital, supply chain, and customer services core applications. These systems will become more intelligent by leveraging machine learning (ML) and predictive analytics on massive data sets to enable new services and higher employee productivity. The user experience (UX) will change as assistive, collaborative conversational styles (with a mobile-first design) driven by advances in natural language processing (NLP) and machine learning are used.