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Edge is the new core fueled with democratized data

The Kinetic Enterprise: Unleashing innovation with AI and machine learning

The maturity of intelligent technologies continues to grow by leaps and bounds. And industry leaders are taking advantage of the latest artificial intelligence and machine learning solutions to innovate, drive their businesses forward, and gain an edge.

But with limitless possibilities for intelligent automation, determining where to place your bets can be challenging. For many organizations, finance and the supply chain will be obvious starting points for innovation—rich with opportunities to automate tedious processes, increase information visibility, and deliver exceptional service.

Three Deloitte transformation professionals discuss the latest artificial intelligence technologies and how you can strategically deploy them to make an impact.

Building resilience

“Supply chains were already fragile, the pandemic didn’t make them fragile,” said Jagjeet Singh, Senior Manager, Deloitte Consulting LLP, kicking off the discussion. While it is important to be risk aware in supply chain management, the movement now is towards risk sensing, insourcing and decentralization to build in resilience using AI and Machine Learning. The best place to start? Obsolete Platform and Siloed Processes. “If companies are running archaic platforms with outdated capabilities, they need to modernize their core and processes to build a robust digital platform with new and differentiated capabilities.”

Data to develop processes

For Hernan Krymkiewiez, Managing Director, Deloitte Consulting LLP, data plays an essential role in a stronger, more resilient supply chain, because when an entire ecosystem is working with the same data, “you can start growing into different processes.” As supply chains faltered globally, consumer tolerance for inefficiency plummeted during the pandemic. With the right volumes of data informing right processes, companies can adapt and respond.

But the conversation around a resilient supply chain comes back around to modernization. Organizations can’t react on processes that were built years ago and with a built-to-last mentality. “There is no such thing as ‘build to last forever’ anymore,” he says. “Technology is changing every six months. Technology is changing every year. You have to be able to adapt that quickly.”

Democratization of intelligent data

Long gone – thankfully – are the days when reporting meant binders full of spreadsheets, charts, and pages upon pages of data that took too long to generate by just a few people. “Data is democratized and reporting is more about storytelling,” says Denise McGuigan, Principal, Deloitte Consulting LLP, “It’s readily available, therefore companies have to understand how to standardize and automate reporting in a way that's flexible, user-friendly and self-service.”

Machine learning can depict trends, propose results, and uncover issues – things that once required a human. Deploying that kind of technology for intelligent, real-time, flexible, interactivity, says McGuigan, is table stakes. “If you don't have it you're going to find a very, very hard time just keeping up with the fast change of technology and business.”

Singh cautions that companies need to stay focused on storytelling with data, and avoid getting bogged down with creating pre-defined reports with static drill-down and deep-dive features. “You have to bring the pool of data and the slice & dice capabilities to the people who want to tell the story so that they can use the tools and capabilities to weave a story that conveys the key message.”

With newer companies building differentiated capabilities in the Edge cloud platforms using intelligent AI and ML technologies surrounding modern digital core, Edge innovations are becoming table stakes in today’s business environment. Fueled by democratized data and intelligent innovations propelled by AI and ML technologies, Edge is becoming the new Core.

Want more transformation insights from enterprise leaders? Visit deloitte.com/SAP to download future podcast episodes or listen to previous ones.