SAP IBP Delivers Risk-Resilience with Swift Supply Smartness

A recent McKinsey global resilience survey of over 100 supply chain leaders on their efforts to overcome disruptions, mitigate risks, and build resilience in their operations showed there is less than 20% deep understanding of risks and sufficient budget allocation at board level.

The recent McKinsey Global Resilience Survey showed that two-thirds of the 300 respondents said that CEOs and board teams are indeed responsible for resilience reaction programs. However, 70% of these organizations felt under-prepared for future disruptions.

This is at a time of increased disruptions caused by extreme weather and geopolitical events.

According to the experts at Everstream Analytics, in the 1980s, the U.S. experienced an average of a billion-dollar (€917.1 million) weather event (or greater) every four months (inflation adjusted). Now, a billion-dollar event occurs every three weeks.

During the period from 2018 to 2022, there were 89 billion-dollar events in the U.S. that produced disruptions and damage of $150 billion (€137.6 billion), on average, each year.?

?The cost of global disruption is rising, while many boards are not allocating sufficient funds or organizational training to swiftly and smartly act on supply shortages or disruptions.

In 2022, McKinsey experts identified three ingredients that underpinned the most resilient supply chain systems: end-to-end visibility, high-quality master data, and effective scenario planning. Integrating these capabilities could support swift board risk reviews and resolutions.?

Can an integrated planning suite provide the intelligent insights and agile actions needed for informed executive decisions in today's disruptive environment??

End-to-end Visibility

Visibility across a company’s network and supply chain nodes are a critical starting point for steering supply chain resilience. Many companies focused post-COVID on this visibility.

A secure end-to-end digital twin of the organization’s procurement plans, financials, through to supplier risk and supplier selection processes beyond the third tier, provides visibility for overall risk-resilience in a time of nearshoring and reshoring.

SAP’s Business Network is used by millions of suppliers, so many customers can already access alternative supplier scenarios, with extended visibility of regional preferred suppliers across tiers, transportation partners, and advanced shipping notices, and even material traceability.

The supplier network can remain flexible, while key locations and critical infrastructure should be mapped and monitored by planners, preferably with custom alerts based on risk levels, such as inventory levels at supplier warehouses or hubs. Planning leads then act on tailored information and recommendations.

Integrating incident data from Everstream Analytics into SAP Integrated Business Planning (IBP) across these locations can help monitor unknown risks across the network and raise to risk review boards as required. Speed of responses increases, giving competitive advantage.

Incidents are replicated back from Everstream Analytics to SAP IBP as risk and opportunity master data with a risk score defined as a key figure for the locations and for the validity period of the risk. This alerting and visibility of unknown risks accelerates time to recovery (TTR).

Planners can display the risk score data by location in SAP IBP apps such as Intelligent Visibility and identify events that can have a positive or negative impact on supply chain planning, avoiding crisis management and boost resiliency through driver-based planning.

End-to-end visibility with integrated risk scores then enables risk-aware planning and decisions using real-time external information about events and disruptions affecting the network.

High-Quality Master Data

Proprietary data restrictions traditionally limited the impact analysis and visibility of issues across networks. For example, end-to-end visibility of both internal and third-party inventory.

In addition, organizations face challenges in effectively benchmarking industry risks or opportunities due to limitations in accessing diverse and relevant datasets.

Establishing a data marketplace can address these challenges by providing a platform for organizations to access, exchange, and analyze specialized data, facilitating more accurate and real-time industry risk benchmarking.

Customers can use external factors from providers and partners such as Google, such as the public and commercial data sets that Google Cloud offers, or risk indexes, directly into SAP IBP?demand plans, to steer decisions.

With end-to-end master visibility and fast-track integration to external sources using a data fabric such as SAP Datasphere, companies can bring together data and AI app support from across the enterprise and network for planners to swiftly and smartly react to supply issues.

SAP IBP uses embedded machine learning (ML) to automatically identify likely issues with master data sets and recommend ways to resolve this, leading to higher-quality master data at scale. This helps build trust in statistical forecasting and AI-driven supply optimization.?

Now SAP IBP also has real-time rule-based master data maintenance to populate product-locations, create transportation lanes, and update location regions, supporting accurate actions. So, customers can scale their risk-resilience across locations for known and unknown risk scenarios.

Effective Scenario Planning

Research from MIT Sloan has shown the major impact scenario planning, visibility and organizational agility can have on resilience to irregular operations and disruptions.

Effective scenario planning can use external and internal data sources to find the appropriate balance and actions among resilience, sustainability, responsiveness, and cost. Best practice scenario and supply risk analytics can enhance management business reviews or risk boards.

Though Bain research shows supply chain that is 100% resilient will also likely be too costly, running optimized scenarios across a network to solve known and unknown risk situations can balance service levels, lead-time predictions and inventory costs with a resilient set of suppliers.

Now a sophisticated ML “prediction” of future lead times may be configured in conjunction with one of SAP IBP’s many forecasting algorithms, such as gradient boosting.

Aggregated, time-phased lead times for transportation, production, and procurement are connected from SAP S/4HANA or SAP ECC to SAP IBP. ?ML then identifies outliers and recommends lead times, lead-time variability, and lot-size inputs across multistage networks for each transportation lane, production lane, and vendor lane.

Planners can then collaboratively compare new and old values, validate new values through scenario analysis for use in embedded inventory and supply optimization, or also use recommended values to create supplier score cards to filter or evaluate alternative suppliers in the network.

To validate these selected scenarios, customers can also use Cosmo Tech mass AI simulations in the SAP IBP process to create alternative scenario recommendations at scale.

Conclusion

Consistent risk analytics and scenarios with the agility of an enterprise data fabric enables business users and planners to swiftly and smartly resolve supply issues across the network.

SAP has recently further enhanced the risk-resilience visibility, master data, and scenarios that we orchestrate for planning customers. Please get in touch if you’d like to see more details.

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