Transforming Organizations with People and Technology
Lean as the Foundation: A Stepping Stone to Excellence
Mike Parkins emphasizes the significance of lean as the bedrock of organizational transformation. He believes that while lean should remain the baseline, it is essential to supplement it with new tools and capabilities. By doing so, organizations can enhance productivity and performance beyond what lean alone can offer. This approach ensures that the organization builds on a solid foundation while constantly evolving to meet the challenges of a changing business environment.Lean principles not only provide a structured way of working but also instill a culture of continuous improvement among employees. When people are trained in lean practices, they become more efficient and effective in their tasks, leading to better overall outcomes for the organization.The People Factor: The Heart of Transformation
Kimberly Borden highlights the central role of people in any transformation. She argues that if organizations do not address the needs and concerns of their people, the transformation effort is likely to fail. This means investing in people's skills, providing feedback, and creating a supportive work environment.Managers play a crucial role in this regard. They need to be comfortable giving supportive feedback and having conversations with their teams. By doing so, they can help employees grow and develop, which in turn contributes to the success of the organization. Additionally, having the right metrics in place allows people to understand how they are performing and what areas need improvement.Technology as an Enabler: Bridging the Gaps
Technology plays a vital role in enabling next-generation operational excellence. Kimberly Borden discusses how technology can bring together collaboration platforms and provide data visibility. This instant knowledge of what is happening, where, and when allows organizations to make more informed decisions and connect the dots across different data sources.One of the key benefits of technology is that it takes away the tedious aspects of work. Instead of focusing on repetitive tasks, employees can focus on more strategic and creative activities. Technology also helps to automate processes, reducing errors and increasing efficiency.Technology and Feedback Culture: A Powerful Combination
Kimberly Borden explains how technology can enable a feedback culture. By using tools like copilots, organizations can provide constant feedback to their employees. This feedback not only helps employees improve in their jobs but also creates a culture of continuous learning and improvement.In many organizations, there is a gap between performance dialogues and individual contributors. Technology can help to bridge this gap by providing a platform for regular feedback and performance discussions. This ensures that employees are aware of their performance and can take steps to improve.Process Reengineering: The Key to Success
Kimberly Borden emphasizes the importance of reengineering processes fundamentally end-to-end. She argues that even with the best technology tools, if the processes are not transformed, the impact of the transformation will be limited. By reengineering processes, organizations can eliminate inefficiencies, reduce waste, and improve overall performance.This requires a holistic approach that looks at processes from end to end and identifies areas for improvement. It also requires the involvement of all stakeholders to ensure that the changes are sustainable and lead to long-term success.Get to Know and Engage with Senior McKinsey Experts on AI Guardrails
Lareina Yee, a senior partner in McKinsey's Bay Area office, along with Roger Roberts (a partner), Mara Pometti (a consultant in the London office), and Stephen Xu (a senior director of product management in the Toronto office), are here to guide us through the world of AI guardrails.Benefits of AI Guardrails
Privacy and security are crucial aspects. AI systems are vulnerable to attacks by malicious actors who can manipulate AI-generated outcomes. Guardrails act as a shield, safeguarding organizations and their customers. Regulatory compliance is another key benefit. As government scrutiny of AI increases, guardrails help organizations ensure their AI systems adhere to existing and emerging laws and standards, reducing the risk of legal penalties. Trust is paramount, and guardrails enable continuous monitoring and review of AI-generated outputs, minimizing the risk of errant content being released.For instance, imagine a healthcare organization using an AI system to diagnose patients. Without proper guardrails, the system might generate inaccurate or misleading diagnoses, putting patients at risk. But with guardrails in place, the system can be monitored and corrected in real-time, ensuring the accuracy and reliability of diagnoses.
Another example is in the e-commerce industry. Guardrails can prevent the sale of counterfeit products by filtering out inappropriate or inaccurate product information generated by AI. This helps build trust with customers and protects the reputation of the business.
Main Types of AI Guardrails
Appropriateness guardrails check for toxic, harmful, biased, or stereotypical content and filter it out before it reaches customers. For example, in a social media platform, these guardrails can prevent the spread of hate speech and offensive content.Hallucination guardrails ensure that AI-generated content is factually correct and not misleading. Say a news organization uses an AI to generate articles; these guardrails would prevent the inclusion of false information.Regulatory-compliance guardrails validate that generated content meets regulatory requirements. In the finance industry, for instance, these guardrails would ensure that financial advice generated by AI complies with relevant regulations.Alignment guardrails ensure that generated content aligns with user expectations and maintains brand consistency. For a brand's customer service chatbot, these guardrails would ensure that the responses are in line with the brand's tone and values.Validation guardrails check if generated content meets specific criteria. If a piece of content fails the validation, it can be funneled into a correction loop. This helps maintain the quality of AI-generated content.Take a content management system as an example. By implementing these different types of guardrails, the system can ensure that the content published is appropriate, accurate, compliant, and aligned with the organization's goals.
Another instance could be in an educational setting. Guardrails can prevent AI-generated educational materials from containing biases or incorrect information, providing students with high-quality learning resources.
How Guardrails Work
Guardrails are built using various techniques, from rule-based systems to LLMs. Most guardrails are fully deterministic, meaning they produce the same output for the same input. They work by performing a range of tasks such as classification, semantic validation, and detection of personally identifiable information leaks.The checker scans AI-generated content to detect errors and flag issues like offensive language or biased responses. It acts as the first line of defense. Once an issue is identified, the corrector refines, corrects, and improves the output. The rail manages the interaction between the checker and corrector, triggering corrections when needed and logging the processes for analysis. The guard interacts with all components, coordinating and managing the entire process.For example, in a chatbot application, the checker might detect a misspelled word in the AI's response. The corrector would then correct the spelling, and the rail would ensure that the corrected response is sent back to the user. This iterative process ensures the quality of the chatbot's responses.
In a legal document generation system, the guardrails would ensure that the generated documents are accurate, compliant with legal requirements, and free from biases. This is crucial in ensuring the fairness and integrity of legal processes.
How AI Guardrails Generate Value
AI guardrails not only help meet compliance and ethical requirements but also create a competitive advantage. They help build trust with customers and avoid costly legal issues. By using AI more responsibly, organizations can attract and retain top talent.For instance, a manufacturing company that implements AI guardrails in its production processes can ensure the quality and safety of its products. This builds trust with customers and gives the company a competitive edge in the market.ING, a financial-services company, developed an AI chatbot with guardrails to ensure accurate and safe customer interactions. The guardrails filtered out sensitive information and risky advice, while ensuring compliance with regulatory standards. This not only protected the customers but also enhanced the company's reputation.Another example is in the logistics industry. AI guardrails can optimize delivery routes and ensure the timely and accurate delivery of goods. This improves customer satisfaction and increases the efficiency of the logistics operations.
How to Deploy AI Guardrails at Scale
Design guardrails with multidisciplinary teams that include legal experts. Define content quality metrics tailored to business goals and regulations. Adopt a modular approach to build reconfigurable components that can be easily embedded and scaled in existing systems. Take a dynamic approach by setting up rule-based guardrails with dynamic baselines that can change based on different variables. Steer with existing regulatory frameworks and develop new capabilities and roles for practitioners accountable for model outcomes.For example, a large e-commerce company can form a team consisting of engineers, legal experts, and ethicists to design and implement AI guardrails across its platform. By defining specific metrics for content quality, such as product descriptions' accuracy and compliance, the company can ensure the consistency and reliability of its offerings.
In a healthcare system, deploying AI guardrails at scale requires collaboration between IT teams, medical professionals, and compliance officers. This ensures that the AI systems used in healthcare are safe, accurate, and compliant with medical regulations.
The rapid growth of AI has made compliance more complex for companies. Guardrails can help companies manage risks and foster innovation. By incorporating guardrails into various processes like product development, organizations can better handle AI-related crises and create a safer environment for AI-related activities.Transforming Field Service with Generative AI
The Opportunity
In an era where machinery is becoming more complex, Ascendum recognized the need to enhance field service support. By collaborating with McKinsey and Salesforce, they aimed to find value areas and cross-impact with feasibility. Time is of the essence for customers, and even diagnosing an issue can take up to 30 minutes as agents search through vast amounts of data. Building a solution to these challenges has the potential to create significant customer value by reducing equipment downtime.
The company's operations involve distributing and maintaining over 25 different brands of machinery and equipment. With a team of dedicated field and service agents, Ascendum is committed to rapid mobilization and swift issue resolution.
The Solution
Ascendum initiated a transformation to harness the potential of generative AI. Through strategic collaboration with McKinsey and Salesforce, they identified and evaluated 30 potential use cases where generative AI could deliver significant value. For instance, one use case involved using generative AI to help agents quickly pinpoint equipment repair instructions from a large body of technical documents.
Ascendum led the mobilization of its business organization and provided essential customer and industry insights. QuantumBlack brought deep industry knowledge and advanced AI capabilities, along with integration support for Salesforce technologies. Salesforce delivered a seamless user experience through its development tools, giving access to customer data. Over five weeks, McKinsey's QuantumBlack team built the generative AI engine on the Salesforce platform, working closely with field agents to ensure model output was trusted and useful.
The Impact
The partnership resulted in a generative-AI-powered solution seamlessly integrated with Ascendum's Salesforce Service Cloud. The pilot solution implemented in just four weeks led to significant improvements. It enhanced first-time resolution by streamlining access to information and providing more accurate troubleshooting diagnoses. This freed service teams from repetitive tasks and allowed them to focus on adding value to customer relationships and driving business growth.
Faster issue resolution directly translated into reduced equipment downtime, saving customers between $5,000 to $12,000 per hour. Construction workers and other operators no longer lose as much time to technical delays, experiencing less disruption to their daily work. This initiative has set a new benchmark in the industry, leveraging cutting-edge technology to redefine service standards and deliver unparalleled value to customers.
As McKinsey senior partner Peter Dahlstrom said, "Technology enablement offers a new approach to field operations, making the process faster and saving significant time for agents." This work is a prime example of how their partnership with Salesforce drives real impact at scale.