The long-predicted splitting of old monolithic ERP into specialized SaaS applications (so-called composable ERP) is well underway, and not always a good thing. When data is spread across multiple silos, it becomes difficult for decision makers to get a complete picture of the enterprise. It also introduces integration challenges, but is more manageable if most business operations are handled by a well-coordinated core ERP system and its central data repository (a vaunted single source of truth). It was.
ERP owners seem keenly aware that most of the information in their enterprise applications is underutilized. For years, they’ve tried to use analytics, AI, and business intelligence tools to glean ideas and insights from mountains of customer and partner data to make better decisions.
But they still don’t get the cross-sectoral business perspective they really need, according to Tom Oliver, product manager at UK-based AI software maker Fertility. In a recent opinion piece, Oliver argued for AI-supported decision intelligence, combining the best of horizontal data and analytics tools with his specialized SaaS applications that best serve user needs. He argues that decision intelligence, both discipline and technology, could even shape the future of enterprise applications.
In the podcast, Oliver elaborated on his discussion and explained how the Faculty’s Frontier Decision Intelligence Platform works.
Decision intelligence connects the dots
Tom Oliver
Previously, he worked as a consultant in the London division of PwC, one of the big four accounting and professional services firms. He has spent nearly five years helping clients answer big questions like whether to buy a company or sell a business unit, and handle more detailed operational and structural issues. said it showed how a typical ERP setup falls short of solving the underlying problem. decision-making problem.
“One poignant theme is really just smacking you in the face,” said Oliver. “It is very difficult to answer moderately nuanced questions about complex organizations and make any decisions.”
He calls the problem partly due to the “massive adoption” of SaaS applications that serve key functions like CRM and HR, but Oliver is a fan of these so-called best-of-breed platforms. There is no change. “They can help people go through workflows that are central to their daily lives and get data about them, which is great,” he said. The problems that Decision Intelligence platforms are designed to solve fall in between these systems.
According to Oliver, Frontier is deployed as “lightweight” on top of enterprise applications and is designed to consolidate data either directly from transactional systems in ERP systems or by integrating with data warehouses. It relies on the concept of computing twins, which provide a real-time digital view of an organization’s operations by analyzing data sources. The department’s website claims that its twin exceeds typical digital twins in its ability to make predictions using machine learning and other techniques.
Other topics include:
- Data scientist’s role in configuring the platform.
- The biggest challenges facing broad adoption of decision intelligence.
- How AI and decision intelligence tools will evolve in the next five years.
Click the link above to listen to the podcast.
