Today’s supply networks are global, complex and dynamic – qualities that pose challenges to indirect tax compliance. In the wake of major supply disruptions and global trade volatility in recent years, such as the COVID-19 disruptions and recent trade policy disputes, companies have devoted considerable thought and resources to mounting a more robust defense against supply chain shocks. These developments affect indirect tax groups, many of which are deepening their collaborations with supply chain colleagues and procurement teams.
For example, a few years ago EY explored how a “total landed cost” framework can help optimize procurement, supply chain and trade costs as products move through trading networks. The total landed cost approach calculates all the significant costs involved in physical supply chains, including sourcing, manufacturing, transportation, logistics, direct and indirect taxes and other trade-related expenses.
More recently, McKinsey consultants writing in a Harvard Business Review article address a capability that some supply chain management tools neglect: a mechanism that alerts businesses to potential impacts before they materialize. This approach, which benefits from the input of tax leaders, requires three enabling capabilities:
- Creating an enterprise-wide data repository. This is an integrated, centralized data storage capability that contains quantitative data such as financial and tax information, operational data and business process metrics. It also contains qualitative data such as site visit reports. The early warning system scans this “data lake” to identify risks. The more comprehensive the input, the more effective the results. But, managing the various data sources and standards can be challenging, so companies may want to start with a more restricted set of relevant, high quality, regularly updated data. Key systems that can supply such data include enterprise resource planning (ERP) platforms and quality management systems.
- Leveraging artificial intelligence (AI) to enable actionable alarms. AI thrives at detecting anomalies across seemingly unconnected processes and activities. For example, a pattern of late deliveries could lead to a surge in quality defects. To minimize false-positive results, companies should calibrate their AI tools to identify highly specific conditions, such as a high risk that a given supplier will face shortages of a specific component.
- Revisiting the traditional risk management playbook. Risk management procedures typically classify risks without adequately defining responses. An effective early warning system, by contrast, details the required actions, responsible persons, and steps to be taken (sometimes referred to as “next best actions”). Every alarm should be investigated, with consistent follow-up to mitigate any risks.
With these steps in mind, tax departments can play a vital role in developing a more effective approach to predicting and mitigating supply chain shocks. Tax can supply essential expertise around ERP data. In addition, many tax groups can share their strong working knowledge of analytics, AI and risk management, as well as their knowledge of key suppliers and supply chains.
As the article points out, it’s pretty much a given that supply chains will continue to face disruption, so adaptability is essential. It’s a safe bet that many tax leaders will be working more frequently with supply chain leaders in their companies in the near term to reinforce resilience in their critical supply chains.
Disclaimer
Please remember that the Vertex blog provides information for educational purposes, not specific tax or legal advice. Always consult a qualified tax or legal advisor before taking any action based on this information. The views and opinions expressed in the Vertex blog are those of the authors and do not necessarily reflect the official policy, position, or opinion of Vertex Inc.