KEY VALUE CHAIN ANALYSIS: IDENTIFYING PAIN POINTS TO IMPROVE BUSINESS PERFORMANCE

WHAT IS A KEY VALUE CHAIN?

The concept of the value chain was first introduced by Michael Porter, a professor at Harvard Business School, who “opened the black box” of enterprises by breaking down the process of value creation into a series of distinct but interrelated economic activities (Porter, 1985). The value chain serves as the foundation of enterprise operations, offering a perspective through which to understand a company’s business logic and the underlying reasons for its profits or losses. Porter’s value chain includes not only primary activities, such as logistics, operations, marketing, sales, and services, but also supports activities like procurement, technology development, and human resource management. For decades, Porter’s value chain has remained an essential tool for strategic planning and business analysis (e.g., Hart & Milstein, 2003; Gereffi et al., 2005; Porter & Teisberg, 2006; Srivastava et al., 1998).

The fundamental logic of Porter’s value chain is equally applicable to performance improvement practices. Analyzing activities along a value chain enables managers and consultants to quantify the contributions of each activity and identify performance gaps and growth opportunities to improve business results. However, Porter’s value chain operates at the macro level, addressing issues at the levels of industries, corporations, and strategic business units. In contrast, most business performance improvement projects focus on specific tasks and job performance at the individual and departmental levels. Therefore, it is important to develop a value chain analysis methodology at the micro level for business performance improvement initiatives.

The KVCA methodology introduced in this paper is such a tool. It is a micro-level method, focusing on activities associated with job performance at individual, departmental, and organizational levels. To illustrate this method, Figure 1 depicts a retail store value chain, which can be used to improve business performance in areas such as sales revenue, profit, and market share. We will provide more detailed discussions of figures like this one in subsequent sections.

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Based on these understandings, we define a value chain as a set of continuous activities and sequential processes that contribute to achieving goals and job performance at individual, departmental, and organizational levels. It can be expressed as an equation that includes all key factors related to growth, demonstrating how these factors collectively drive desirable business outcomes. The value chain represents a linear relationship where all factors are connected using the four basic mathematical operations: addition, subtraction, multiplication, and division. Multiple value chains can be drawn for each desired business outcome. Among these, the key value chain is the one with the most direct and critical impact on business results.

WHY DO WE NEED KEY VALUE CHAIN ANALYSIS?

To fully understand the rationale behind developing this tool, we can begin by examining the Human Performance Technology (HPT) model, which provides performance improvement professionals with essential standards and guidelines (Van Tiem et al., 2012). As illustrated in Figure 2, the first phase of performance improvement should be “Performance Analysis of Need or Opportunity.” In this phase, professionals must conduct both organizational analyses and environmental analyses to identify performance gaps before moving on to cause analyses and intervention design (Van Tiem et al., 2012). Engaging in root cause analyses or solution design without first identifying and clarifying existing performance deficiencies would be contrary to the principles of system thinking within performance improvement (Kaufman, 2014).

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Not surprisingly, the field of performance improvement has long advocated the importance of conducting thorough analyses before rushing to implement interventions such as training (e.g., Ripley, 2016; Van Tiem et al., 2012). For example, Harless (1975) argues that a small investment in analysis upfront can prevent wasted time and resources on incorrect solutions later, cautioning against selecting a cure without fully understanding the problem. Similarly, Kaufman (2014) emphasizes the importance of assessment and encourages performance improvement professionals to go beyond quick but premature fixes. He argues that quick fixes, though often costly, are neither effective nor efficient (Kaufman, 2014). In the business world, however, many executives and professionals tend to rush to popular solutions without fully assessing the situation. For example, in sales management, Zoltners et al. (2012) revealed sales management’s addiction to financial incentives as a quick fix and the undesired consequences it caused.

In fact, jumping to conclusions is quite common among many people. Nobel Prize winner Daniel Kahneman developed the Dual System Theory to explain this phenomenon (Kahneman, 2013). According to this theory, the human mind operates using two distinct systems of thinking: a fast, intuitive, and automatic System 1, and a slower, more deliberate, and analytical System 2. It is estimated that human decision making operates 70% in System 1 and only 30% in System 2 (Clark, 2014). However, rushing to quick fixes without fully understanding the situation can lead to suboptimal decision making and expose individuals to various biases, such as overconfidence bias, confirmation bias, and status quo bias, etc. (Guerra-López & Hicks, 2017; Guerra-López, 2021). These biases and suboptimal decision making may partially explain why more than 70% of organizational change initiatives fail (Al-Haddad & Kotnour, 2015; Balogun & Hailey, 2016; Hornstein, 2015).

The KVCA methodology is designed precisely to address this issue. This systematic and data-driven approach helps shift decision-makers’ attention from System 1, which is easy but prone to biases, to System 2, which can be slow but more rational. Specifically, by following the principles and steps of this methodology, business professionals can visualize the value creation process and business logic, demonstrate the series of business activities through linear relationships, and identify pain points and potential growth opportunities. In summary, the principles of the KVCA are consistent with the guidelines of the HPT model. Both promote a disciplined strategy that avoids simpler heuristic approaches, which are intuitive but often flawed mental shortcuts that may lead to premature conclusions. Like the HPT framework, the KVCA helps reduce common cognitive biases, such as confirmation bias, overconfidence bias, and status quo bias (Guerra-Lopez & Hicks, 2017; Guerra-Lopez, 2021). By making decisions grounded in rigorous upfront assessment, professionals are better equipped to design interventions that are not only effective but also aligned with actual business needs (Kaufman, 2014).

HOW TO DRAW A KEY VALUE CHAIN?

The KVCA is a systematic tool. Although there are potentially many different ways to draw value chains, based on our practices and experience accumulated over the past decade, we suggest three general steps for drawing a key value chain. We believe that when managers and practitioners follow these steps, they are more likely to thoroughly analyze and visualize business logic, identify pain points, and reveal potential growth opportunities. By following these three steps, we can quantify causal relationships between business needs and activity needs, building a foundation for identifying key leading indicators for business performance improvement.

Let’s use a real case to demonstrate the steps. This case involved one of the sales performance improvement projects we conducted with M & Z Furniture, a furniture manufacturer and marketer. Riding the growth trends of China’s real estate boom over the past decade, M & Z Furniture shifted its business model from mass production to custom furniture. Although both the manufacturing and selling processes were transformed to meet market needs, the store sales of custom furniture were disappointing and dragged down the sales of other furniture. To make matters worse, unsatisfactory sales outcomes led to low sales commissions, which eventually resulted in high salesperson turnover. Management did not know what had gone wrong, so they decided to conduct a KVCA, a methodology typically suited for this type of situation.

To use the KVCA, it is crucial to understand the company’s business model and, in the process, how desirable outcomes are generated. M & Z Furniture employs a multi-channel marketing strategy, integrating telemarketing, social media marketing, and channel partnerships to enhance customer engagement and promote its products and services. In addition to these proactive marketing efforts, customers may independently visit a M & Z Furniture store. Upon arrival, they are welcomed by sales representatives who provide product information and address inquiries. When customers perceive a match between their needs and the features and benefits of the products, they develop an interest in learning more, transitioning into potential buyers. A critical stage in the sales process involves encouraging customers to schedule an appointment for in-home measurements, enabling the customization of furniture to meet their specific spatial and functional requirements. Once an appointment is confirmed, sales representatives visit the customers’ residences to take precise measurements of their living spaces. These measurements inform a tailored product proposal, which is then presented to the customers upon their return to the store. At this stage, negotiations take place regarding pricing, payment plans, accessory options, and delivery schedules, ultimately facilitating the final purchase decision.

Step 1. Stems and Trunks

With a good understanding of the firm’s business model, we start to explore its Key Value Chain. As a first step, we need to identify the stems and trunks, which are the major components of the value chain and the key factors that impact the expected business results and outcomes. These key factors are connected through the four basic mathematical operations: addition, subtraction, multiplication, and division. A function using these four basic operations represents a linear relationship and demonstrates how the main components contribute to business outcomes. One of the principles we follow is to ensure that the relationships remain linear throughout the value chain.

In the example of M & Z Furniture, the total sales revenue of a furniture store can be expressed as the multiplication of the number of units sold and the average unit price. As shown in Figure 3, the number of units sold and the average unit price represent the stems and trunks of this value chain. Furthermore, the total number of units sold is equal to the number of customers’ negotiations at the store multiplied by the percentage of customers who make a purchase. The average unit price is calculated by multiplying the customized unit price by (1 + accessory%). Combining these relationships leads to the following equation:

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$$\text{Total\hspace{0.17em}sales\hspace{0.17em}revenue}=\text{number\hspace{0.17em}of\hspace{0.17em}customer\hspace{0.17em}negotiations}\hspace{0.17em}\times \hspace{0.17em}\text{percentage of customers who purchase}\hspace{0.17em}\times \hspace{0.17em}\text{customized unit price}\hspace{0.17em}\times \hspace{0.17em}(1+\text{accessory}\hspace{0.17em}\%)$$

The left-hand side of the equation is the outcome indicator, whereas the right-hand side includes all major activity indicators connected by the four basic mathematical functions. Defining the major activity indicators enables business managers to visualize the linear relationships and offers them opportunities to optimize these activities. Typically, these activities are organized in a time order sequence, with customers negotiating at the store, deciding to purchase, then customizing unit prices and determining whether to purchase accessories. Understanding the sequential order of the activities is critical for managers to prioritize their efforts on business performance improvement.

Step 2. Branches and Twigs

The ultimate purpose of a KVCA is to understand, reveal, and demonstrate business logic to identify pain points and potential growth opportunities for business performance improvement purposes. To achieve these goals, it is important to thoroughly draw and analyze the value chain until we see specific actions. Following the same analogy as in Step 1, we treat these specific actions as branches and twigs connecting to the branches and visualize the whole picture of the value chain tree. Let’s use the same example of M & Z Furniture to demonstrate this step.

A critical component identified in the first step is customers’ negotiations at the store. It is therefore important to understand what contributes to this performance indicator. As shown in Figure 4, the number of customers’ negotiations at the store is the result of the number of measurements made multiplied by the percentage of customers who decide to visit the store for the second time and negotiate with salespeople. Further, the number of measurements comes from the number of appointments multiplied by the percentage of measurements out of all appointments, where the number of appointments is the product of the number of customers’ initial visits and the percentage of customers who agree to make appointments of measurement.

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Please note that many factors, such as store location, advertising and promotion, may have significant effects on store traffic. However, these effects are typically non-linear since they cannot be easily expressed as multiplication, division, subtraction, and addition. Instead of trying to incorporate their effects into the equation, the KVCA focuses directly on the sources of store traffic. As shown at the bottom of Figure 4, the total store traffic may be divided into either proactive store traffic or passive store traffic. The terms of proactive and passive store traffic are from the company’s perspective, whether they take any active actions to attract customers or not. The proactive store traffic refers to customer visits to the store due to the company’s promotional efforts or sales calls. In contrast, passive store traffic refers to customer visits that occur spontaneously or as a result of peer recommendations, without any direct promotional efforts or interventions initiated by the firm.

Step 3. Pain Points and Opportunities

After drawing the entire value chain, the next and final step is to identify pain points that influence performance. This process involves pinpointing three types of pain points: shortcomings, critical items, and opportunities. Shortcomings refer to areas where significant efforts have been made but results remain unsatisfactory. Critical items are areas that constitute a large proportion of or have a substantial impact on job performance. Although these items are performing reasonably well, there is still room for improvement. Opportunities can arise from two sources: previously unnoticed areas or areas that were acknowledged but not adequately addressed. Among the three types of pain points, opportunities are the most significant and typically offer the best chances to improve performance, sometimes dramatically.

To identify pain points including opportunities, we need to fill data into each point along the key value chain. The data should be real and objective data collected directly from reliable sources such as company records and databases. Using objective data instead of personal assessment avoids bias and prejudice typically associated with subjective data, thus enabling managers to identify pain points based on credible data. Afterwards, data at each point along the key value chain will be compared with benchmarks, which can be based upon predetermined standards, best practices, and average numbers at industry and organizational levels.

There is no guarantee that pain points and opportunities will automatically emerge after the first attempt. For example, after analyzing the initially drawn value chain, the managers of M & Z Furniture would say, “Our store traffic isn’t a concern, and we’ve thoroughly mapped out the in-store selling process. This is our standard way of operating, and each step is carried out effectively. However, we’re simply not seeing any opportunities.” One way to address situations like this is to look at how customers are categorized and analyze whether there are differences in their business actions based on these categories. Although M & Z Furniture’s business actions are almost identical when categorizing customers based on demographic variables, the business actions are significantly different when categorizing customers based on their housing conditions, that is, unfinished condominium customers and finished condominium customers. As the term suggests, unfinished condominiums include only the basic structural elements, such as walls and ceilings, and are delivered without interior finishes. This type of unit is prevalent in many Chinese housing markets, where buyers often favor the lower purchase price and the flexibility to customize the interior according to personal preferences.

This discovery is an eye-opener and enables the project team to redraw the Key Value Chain. As shown in Figure 5, the revised Key Value Chain separates the two categories of customers and adds detailed activities to the branches and twigs. After comparing with benchmarks, the project team identifies “the percentage measurement appointment” as a pain point. The leading indicator measures the percentage of unfinished condominium customers who make appointments to have their condominiums measured after discussing with the store salespeople. It is a growth opportunity since improving this percentage leads to more customer negotiations at the store and eventually increases sales of furniture in unfinished condominiums.

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FINAL THOUGHTS

This paper introduces the KVCA methodology, designed to systematically identify pain points and opportunities within business value chains. Drawing from the literature on HPI and marketing management, the three-step KVCA methodology enables business executives to transition from heuristic, overly simplistic approaches to comprehensive, data-driven analysis (Clark, 2014; Kahneman, 2013). This paradigm shift mitigates cognitive biases that often lead to suboptimal decisions and unintended consequences (Guerra-López, 2021; Zoltners et al., 2012). Documented successes across various industries in China demonstrate that KVCA can help business executives enhance revenue, profitability, customer satisfaction, and operational efficiency, addressing a critical gap in the performance improvement and business management literature.

Future research on KVCA methodology could explore several promising directions. First, scholars, consultants, and practitioners may apply KVCA to performance improvement initiatives across diverse organizations and industries. Investigating the best practices in utilizing KVCA to analyze business logic, identify pain points and opportunities, and publishing these insights as case studies would contribute to both academic and practical knowledge. Second, as data analytics continues to gain prominence, its alignment with KVCA principles presents opportunities for integration. Leveraging data mining and data science techniques can facilitate the identification of key value chains and uncover critical inefficiencies. It is important to emphasize that KVCA does not require advanced computing resources or large datasets. Even small businesses without extensive data analytics expertise can manually analyze their data and apply the methodology effectively. Finally, the evolving capabilities of artificial intelligence, such as ChatGPT and DeepSeek, offer potential enhancements to KVCA. AI-driven tools can support various stages of the analysis process, making the methodology more accessible and impactful for business professionals. These applications will further extend the reach of KVCA, equipping organizations with more effective strategies to improve business performance.