Deep Dive

Current State

Without automated business continuity plan review, companies risk operating with outdated or inadequate contingency plans that fail to address emerging threats or evolving supply chain complexities.

Manual BCP review processes are often infrequent, time-consuming, and prone to human oversight, leading to gaps in preparedness. When a major disruption occurs, an unvalidated or irrelevant BCP can result in prolonged operational downtime, significant financial losses due to missed production or delayed product launches and severe impacts on patient access to life-saving drugs. This reactive posture can also lead to reputational damage, increased regulatory scrutiny and a compromised ability to meet market demand during crises.

Solution

Automated Business Continuity Plan (BCP) Review leverages new technology, in particular generative AI and automation, to systematically assess, update, and validate existing business continuity plans.

This process moves beyond manual reviews to identify internal and external factors that could impact a firm’s resiliency, for example the effect of potential geopolitical shifts, natural disasters and regulatory changes on its supply chains.

The objective of automated BCP review is to ensure that BCPs remain continuously relevant, robust, and immediately actionable, enabling companies to swiftly recover from disruptions and maintain the continuous supply of critical medicines. This “automated red-teaming”, or “AI devil’s advocate” enables the autonomous generation of new scenario and drafting of new response playbooks and plans. Paired with simulation capabilities (e.g. a manufacturing or supply chain digital twin) these newly-generated strategies can also be safely and cheaply tested in-silico before they are passed to humans for review, or ever deployed in the real-world.

Comprehensive data integration is core to successful automated BCP review. This requires breaking down data silos and connecting disparate systems across the pharmaceutical supply chain, including:

• Enterprise Resource Planning (ERP)
• Warehouse Management Systems (WMS)
• Manufacturing Execution Systems (MES)
• Specialized risk management platforms

AI-powered analytics for identifying potential single points of failure and optimizing contingency plans are crucial for collecting, standardizing, and analyzing the vast amounts of data generated across complex businesses and their multi-tiered supply chains.

Benefits of Automated BCP Review

Systems like HASH can analyze vast amounts of real-time and historical data to identify subtle patterns and emerging risks that could impact business continuity, even predicting the likelihood and potential severity of future disruptions.

This enables dynamic adjustment of BCPs based on evolving risk landscapes, automated scenario testing to validate plan effectiveness, and prescriptive recommendations for strengthening resilience.

AI can also facilitate rapid identification of critical dependencies and alternative solutions during a crisis, significantly reducing recovery times and ensuring a more robust and agile business, and supply chain.

Implementation & Enhancement

Selecting A Solution

When building out and utilizing Automated BCP Review, it is important to consider:

• Data quality & latency: is the system based on real-time integrated data?
• Change management: upskilling business leaders in their usage – start by rolling out Automated BCP Review as copilots to humans before relying on them in any autonomous capacity.
• Cybersecurity: ensure the system supports granular permissions and access controls consistent with your business requirements and risk profile.
• Ongoing maintenance costs: does the solution run in the cloud, or must it be hosted internally/on-premises and maintained manually?
• Open-source: is the Automated BCP Review solution open-source, or is there risk of platform/vendor lock-in?
• Incremental adoption: can the solution be used to target specific use-cases initially to prove its value and deliver quick wins (e.g., logistics operations or a single manufacturing site) before broader roll-out?