The ability to ingest real-time digital signals – from external sources such as SNEW (social, news, events, and weather data) can help provide predictive visibility to sense an event/disruption before it happens with the goal of making better and faster decisions.
Published in Chapter:
Cognitive Integrated Business Planning
Salim Shaikh (JDA Software, USA)
Copyright: © 2019
|Pages: 13
DOI: 10.4018/978-1-5225-7700-3.ch008
Abstract
Supply chains of the 21st century are becoming exponentially more complex due to increased mergers and acquisitions, the omni-channel conflict, direct-to-consumer, rapid proliferation of product configurations, same-day delivery, the recall management problem, shrinking product lifecycles, and market volatility. Moreover, today's consumers are increasingly demanding a personalized, consistent, and seamless experience across retail, online, and mobile. To be able to serve this diverse spectrum of customers, products, markets, and channels and at the same time do so in a win-win profitable manner, organizations need a cognitive integrated business planning process, which has the ability to act with speed, agility, responsiveness, and flexibility, leveraging machine learning and artificial intelligence for predictive and prescriptive analytics, thereby enabling organizations to realign their plans quickly through an always-on, self-learning, and autonomous integrated business planning process.