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Digitize your engineering governance system to help mitigate risks

Thomas Richter, Log in to subscribe to the Blog

The diesel emissions scandal, which began in 2015, has shown quite plainly how a lack of control and compliance in the automotive product lifecycle process can become an existence-threatening crisis for an organization. In that particular scenario, even if the auto manufacturer can avert the immediate financial implications of the scandal, they will still have to fight to earn back trust and confidence.

The episode underscores how fundamentally important the creation and delivery of innovative products and services is to automotive manufacturers and Tier-1 suppliers, but also how important it is that manufacturers ensure the compliance of their new innovations in the face of massive legal requirements (such as low carbon objectives) and an increasing complexity of new technologies and growing ecosystems – all while striving for significant improvements in quality and cost targets, and providing the highest level in customer orientation by speeding time to market.

It is the management of these varied, complex, and interconnected manufacturing systems that has heightened the need for integrated engineering governance systems.

Engineering governance – more than a policy recommendation

Engineering governance is an essential component of overall corporate governance. In short, it’s the management and optimization of design, development, and operational systems. It’s the set of clearly defined structures, processes, and policies that direct and control how organizations align their investments and incentives to the best interests of the organization, including risk mitigation. It also informs the development and deployment of hardware, electronics, and software within the entire automotive product creation process (Idea-to-Offer), with the purpose of maintaining or improving business value in time to market, costs, product quality, and compliance. For today’s high-tech manufacturers, engineering governance is critical.

Professional engineering governance and the critical need for quality engineering advice relative to identification and management of risk is an increasingly important part of the modern engineer’s skillset. This is especially true for government systems, where engineering advice is vital early in the policy planning and target agreement stage – not just at the point of delivery.

Engineers who can look holistically at interconnected systems and processes and understand the risks within that end-to-end lifecycle will be able to help organizations optimize their operations to avoid risk. To achieve that holistic vision and understanding, manufacturers will need to be able to analyze disparate sets of data throughout the organization, then understand the potential effect of this data on the workforce and operational systems. Intelligent technologies can help engineers in this engineering governance process.

Engineering governance systems combine process and digitization to mitigate risks

Digital technology is a core element of any future-proof engineering governance system, as it needs to support a much faster and more flexible deployment of products and services. For automotive companies, the ability to control and update the governance for management systems and business operations is essential. Manufacturers need to be able to shape and run a set of structures, processes, and policies that align interests and incentives within the entire engineering value chain. Governance systems that integrate digital technologies and process-improvement capabilities with compliance requirements are better equipped to alert engineers and managers to risk, and provide information that highlights opportunities for process optimization.

Build future-proof IT architectures and governance models

As I mention in my earlier article on digitizing the product lifecycle value chain, digital tools like case management, AI, and robotic automation can be integrated within a layer-based modular architecture to leverage existing legacy system investments, automate complex processes from end-to-end, and support flexible and reusable technologies. This Digital Process Automation approach orchestrates enterprise systems to govern, among others, functions for development, maintenance, and communications, to help ensure compliance.

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Industry: Manufacturing Topic: Digital Transformation

About the Author

As Director and Industry Principal for Automotive Manufacturing in Germany, Thomas Richter helps carmakers and Tier 1 suppliers shape new business and operating models for tomorrow, driving exceptional customer engagement and operational excellence through accelerated digital transformation.

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