Operational Excellence
Are efficiency and effectiveness a double-edged sword when it comes to customer value?
By Moss M.Jacques
At what point can a company deem itself efficient, effective, or both? Efficiency and effectiveness are two core principles of operational Excellence, but they are a double-edged sword in customer value creation. What do we mean by that?
Operational Excellence refers to the ongoing effort of a company to improve its products, services, and processes. The goals are straightforward: higher productivity, lower costs, improved quality, and faster service. No business is immune to failing customer value, regardless of efficiency and effectiveness. Failed products, those that do not meet the criteria of customer demand, needs, and satisfaction, can originate from both established companies and startups alike; even successfully well-known companies lost multimillions of dollars in product failure, Microsoft, Google, Amazon, MC Donald’s, Apple, Ford, coca cola, Colgate, Starbucks, Sony, Samsung, Meta, and we can go on and on.
In a business context, efficiency refers to how well a company uses its resources to achieve its objectives. It’s about doing things right, optimizing processes, and eliminating waste. It’s often measured in terms of output per unit of input. It might involve streamlining workflows and automated tasks or reducing resource consumption. The benefit is clear: lower costs and faster turnaround times. Conversely, effectiveness is about doing things right that align with business objectives and customer needs. It involves making strategic decisions that drive value creation, such as developing new products, entering new markets, or enhancing customer service.
While both are pillars of operational Excellence, though crucial, they can impede the very goal they aim- to achieve -creating maximum customer value. This dichotomy, this intriguing paradox, explains why pursuing these objectives might enhance and potentially hinder customer value creation.
Initially, pursuing efficiency and effectiveness is a win-win for businesses and customers. Efficient operations can lower costs, translating into more competitive customer pricing. Additionally, effective processes ensure that customer needs are met precisely, enhancing satisfaction and loyalty. For Instance, in the e-commerce sector, efficient logistics and effective inventory management can lead to faster delivery times, directly impacting customer satisfaction.
Highlighting The Double-Edged Nature
However, an overemphasis on efficiency and effectiveness can sometimes lead to a narrow focus that overlooks other critical aspects of customer Value. For Instance, excessive cost-cutting measures in the name of efficiency can result in reduced product quality or proper service, ultimately diminishing customer satisfaction. Similarly, a rigid focus on effectiveness defined by internal goals might ignore customer preferences or market trends.
Case in point: the tech industry, where companies often streamline operations for maximum efficiency and effectiveness. While this approach can lead to innovative products being released quickly, it may also result in over-engineered products or a need for meaningful customer features. An example is Apple’s initial reluctance to create a larger-screen iPhone, favoring design efficiency over market demand. Apple adjusted its strategy only after recognizing the customer preference for larger screens, illustrating the need to balance operational Excellence with customer insights. A custom solution for every client may delight them in the short term, but if it’s not economically viable, the long-term sustainability of the business is at risk.
Efficiency can lead to standardization. While this ensures consistency, it also strips away the personal touch that customers value. In a world where customer experience is king, over-standardization can make a brand feel impersonal and disconnected from its consumer base. The drive for operational efficiency often leads to increased automation. While automation can improve speed and reduce errors, it can also diminish the human element in customer service. In an industry where customer experience is paramount, lacking human interaction can be a significant drawback. For Instance, while efficient, an overly automated customer service system or automated customer service line can frustrate customers who seek human interaction for complex issues. Here, efficiency in reducing human resource costs contradicts the effectiveness of customer satisfaction and loyalty.
Striking the right balance
The key is to find a balance where efficiency and effectiveness coexist harmoniously. This balance is not static but a dynamic equilibrium that responds to market changes, technological advancements, and customer expectations.
Businesses need to measure metrics reflecting efficiency/effectiveness and customer satisfaction. This dual focus ensures that operational improvements do not come at the expense of customer value. By implementing a customer-centric process design, businesses ensure that processes are designed for operational efficiency and with the customer in mind. This involves designing processes that deliver value at every customer touchpoint. Many companies launch products they claim to be innovative but find out later that customers don’t want them. In banking, financial institutions use Customer Due Diligence(CDD), a risk-based approach, to evaluate the nature and purpose of customer relationships. Maybe it seems advisable before launching a new product; businesses owe themselves to do some “customer due diligence.” In a competitive market, instead of obsessing about pushing new products to the customers, it is best to incorporate long-term relationships and strong brand value in your product launch strategy that can buffer the negative impacts of excessive focus on efficiency and effectiveness. Operational decisions should be guided by a long-term strategy focused on sustained customer value creation. This involves continually reassessing and realigning operational goals with customer needs and market trends. Leveraging technology smartly can also serve this purpose. For example, AI and data analytics can provide insights into customer behavior, enabling businesses to meet customer needs while effectively identifying areas for efficiency improvements.
Entering the stage: AI, the disruptor
In the age of AI, measuring efficiency and effectiveness is a combination of traditional and AI-specific Key performance indicators(KPIs). For AI projects, organizations establish KPIs to track progress and impact. Classic AI implementations typically use machine learning to create refined models and algorithms over time and measure predicted results against training data.
Business and IT-relevant KPIs applicable to AI include mean time to repair (MTTR), first contact resolution rate (FCRR), and IT support ticket volume. Indirect metrics derived from these can include customer satisfaction and net promoter scores. ROI is critical, reflecting the tangible returns of time, money, or labor savings due to AI initiatives. Businesses also gauge qualitative benefits, ensuring that metrics are observable and measurable, with technical metrics like mean-squared error(MSE) and business-oriented metrics such as MTTR and FCRR.
In intelligence analysis, for example, the effectiveness of AI systems can be measured using a taxonomy of roles that AI systems can play, such as automated analysis, collection support, evaluation support, and information prioritization. Effectiveness is evaluated based on how well these systems perform these roles in their mission context. Quantitative analyses, like the mathematical modeling of information prioritization systems, help understand the impact of errors and the consequential efficacity of these systems.
The military and intelligence communities have shown particular interest in developing AI systems for national security, emphasizing the importance of selecting the right metrics before system development and considering the resources devoted to the mission outside of building the system.
The measurement of AI’s efficiency and effectiveness is multifaceted, involving a strategic selection of metrics that reflect the system’s real-world impact, continuous evaluation and tuning post-deployment, and a combination of direct and indirect KPIs that together provide a comprehensive view of an AI system’s value and return on investment. As AI technology evolves, So do the standards and benchmarks for measuring efficiency and effectiveness. Keeping up with those changes is a challenge for organizations. Ensuring that AI systems are fair and unbiased is essential for their effectiveness. However, measuring, and mitigating biases in AI systems is complex and ongoing. Measuring AI’s efficiency and effectiveness requires a blend of technical, business, and ethical considerations, necessitating a multidisciplinary approach. Furthermore, the effectiveness of AI is often measured by the value it generates for a business, which can be quantified in terms of cost savings, revenue growth, and improved operational efficiency.
Efficiency and effectiveness, though sometimes seemingly at odds, are not inherently contradictory in creating customer value. The challenge for business is to foster an environment where both are given due diligence, and a synergy between them is actively sought in a dynamic that maximizes value for both the company and customers. This delicate balancing act, when mastered, can lead to sustainable growth and a loyal customer base that sees true value in what the business offers.
As a transformative force in operational Excellence, AI can significantly improve efficiency and effectiveness in delivering customer value. AI-driven automation, predictive analytics, personalization, quality control, efficient resource allocation, and risk management enhance customer service efficiency and effectiveness as businesses continue to embrace AI technologies, those that successfully leverage AI not only as a technological evolution but also as a strategic imperative to implement operational optimization position themselves to thrive in today’s highly competitive business environment. As AI continues to evolve and become more accessible, it will undoubtedly play an increasingly pivotal role in shaping operational Excellence and delivering superior customer value across various industries.