How Decision Intelligence Drives Decision-Centric Integrated Business Planning

In today’s fast-paced business environment, many Integrated Business Planning (IBP) cycles rely on processes defined 30 years ago and supported by planning concepts that are over two decades old. This traditional approach to IBP is increasingly inadequate in a world where the speed and accuracy of decision-making determine competitive advantage.

The Limitations of Traditional IBP

Traditional IBP faces significant constraints, including sequential process steps, arbitrary periodic planning and decision cycles, excessive preliminary meetings, poor integration of strategy, cumbersome data management, wasted analytics, and, most critically, an overemphasis on information rather than decision-making.

Although IBP aims to support high-impact business decisions, little attention has been paid to the quality and speed of those decisions. Furthermore, IBP stakeholders often fail to effectively manage decision-making biases, document decisions, or learn from their outcomes. Addressing these gaps requires a shift toward decision-centricity, which can be achieved through decision intelligence.

Rethinking IBP with Decision Intelligence

Decision intelligence refers to the digitization, augmentation, and automation of decision-making processes. Planning decisions can be categorized into highly automated Sales and Operations Execution (S&OE), where humans play a minimal role, and augmented IBP decisions, where humans remain actively involved (“in-the-loop”). For example, since 2017, Aera has automated short-term S&OE decisions, and Gartner predicts that by 2026, 65% of short-term supply chain decisions will be autonomous.

While IBP decisions are less frequent than S&OE decisions, they tend to recur across cycles. As illustrated by a 10-year-old schematic from a global beverage company, a projected demand-supply imbalance triggers a limited set of possible decisions to address the issue. These recurring decisions can be digitized into decision trees and augmented with cognitive tools like Aera skills. As intelligent agents, Aera skills analyze the environment, detect issues, evaluate options, and either recommend solutions or act autonomously within predefined thresholds, all while learning from their outcomes.

The application of skills to augment IBP decisions is not confined to long-term demand and supply balancing. These skills can support decisions across every stage of the IBP cycle, including sourcing, product portfolio management, pricing, margins, promotions, gap closures, and risk and opportunity assessments.

The Need for Decision-Centric Technology

IBP managers and planners often rely on Enterprise Resource Planning (ERP) and Advanced Planning and Scheduling (APS) systems, which, while useful, are not designed to focus on decision-making. ERP systems act as systems of record for enterprise data, while APS systems serve as systems of record for schedules, plans, and planning assumptions. These tools primarily facilitate inputs such as data, forecasts, and scenarios, but they fall short of focusing on the decisions themselves.

In contrast, decision intelligence technology is centered on orchestrating decision-making as a measurable, data-driven business process. Aera skills, for instance, digitize IBP decisions and capture their context. This creates a system of record for decisions, documenting the decision-maker, steps taken, value generated, and overall impact. These data points can then be analyzed and monitored, enabling continuous learning and improvement.

In the context of IBP, this means that all open, pending, and closed decisions can be digitized, visualized, and monitored in a control room. This provides IBP managers and senior stakeholders with a real-time view of outstanding decisions, gaps to plans, and risks and opportunities. Such decision-centric capabilities necessitate updates to traditional planning models and workflows.

A Changing Role for the IBP Manager

Decision intelligence is giving rise to new roles, such as supply chain decision intelligence managers and lead decision architects. For IBP managers, decision-centricity means shifting from discussing planning outcomes to facilitating decision streams. The focus will be on improving decision velocity, quality, and institutional learning.

Using an IBP control room, managers can monitor unresolved decisions by sorting the decision log based on function, impact, urgency, or other criteria. By simply sorting the IBP decision log by function, value impact, likelihood of success, or other criticality criteria, the IBP manager can prioritize critical decisions and escalate them to leadership without waiting for the next IBP cycle, thereby accelerating decision velocity.

When strategic shifts occur, digitized IBP decisions and their supporting skills may require adjustments to align with the new direction. It becomes the role of the IBP manager to facilitate updated assumptions, decision policies, decision goals, and targets across functions. Decision boundaries, as well as automation and augmentation thresholds for the skills, might need cross-functional renegotiation. After facilitating these updates, the IBP manager can maintain IBP skills in the control room to ensure decision-making stays aligned with the company strategy.

Conclusion

Despite its focus on strategic decision-making, traditional IBP has yet to embrace advanced decision-making practices. A decision-centric approach to IBP, supported by decision intelligence, is no longer optional but essential. Besides the need for decision intelligence technology, it necessitates a new mindset and approach for companies and their IBP managers.

Integrating decision intelligence into IBP enables faster, higher-quality decisions with fewer meetings, reduced analytics waste, and greater employee engagement in the decision-making process. It fosters a learning organization that remains continuously aligned with company strategy. Decision-centric IBP represents not just an evolution of planning but a transformation that equips businesses to thrive in an increasingly complex and dynamic world.