1. Background of Data Analysis

1-2. Who Conducts Data Analysis

Diagram Content: Conducting Entities of Data Analysis

Regarding who should lead data analysis and who should bear the costs, the gap between principle (ideal) and reality, as well as future direction, is organized from three perspectives.

• Principle (Ideal):
  Ideally, the "customer" themselves, who should define the preconditions, ought to conduct it. If customers cannot perform the analysis on their own, they pay consultants, engineering companies, or logistics manufacturers to do so. However, as a general rule, the reality is that customers often lack awareness of data analysis or do not understand analytical methodologies.
• Current Reality:
  In reality, "companies creating proposals"—such as IT vendors and logistics manufacturers—conduct the analysis on their behalf. The reasons are as follows:
  • To undertake time-consuming and costly tasks as a "customer service."
  • To set preconditions themselves in order to make their own proposals advantageous.
  • When aiming to clarify preconditions in systems where interfaces between preceding and succeeding processes are delicate.
  • To appeal to customers by the act of performing data analysis itself.
• Future Direction:
  It concludes that 3PL (third-party logistics) operating companies "should make this data analysis capability their own competitive weapon."

【Explanation】

While data analysis—the foundation of system design—is inherently the customer's role, the current situation reveals that system vendors and manufacturers undertake it free of charge as part of customer service due to a lack of specialized knowledge. However, the proposal side's motivation also includes setting preconditions that favor their own offerings. The message implies that if 3PL operators managing actual operations equip themselves with advanced data analysis capabilities, it will become a powerful competitive advantage (weapon).

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Another Perspective: Division of Roles Among Three Parties in Actual Projects

Apart from the previous perspective of "who bears responsibility and costs," at the field level executing actual projects, a collaborative process where the three parties—"Customer (User)," "Sales (Proposer)," and "Design (Engineer)"—advance with respective initiative is indispensable.

• Customer Initiative:
  As the party understanding their business environment and future outlook best, they provide historical performance data (raw data) and present field-specific irregular operations and constraints. They evaluate whether final analysis results satisfy their business requirements.
• Sales Initiative:
  They listen to customer "concerns" and "requests," formulating analytical goals and policies. They act as a "bridge (mediator)" translating customer business requirements into engineering requirements for the design team, aligning overall project direction.
• Design Initiative:
  They process and cleanse provided data, executing specialized tasks such as actual EIQ analysis and scale calculation (simulations). Based on objective numerical data, they logically derive required equipment capacities and system specifications.

【Explanation】Why Three-Party Collaboration is Necessary

If data analysis is dumped solely on "design personnel (such as data scientists)," it easily turns into "armchair theory" lacking operational reality. Conversely, proceeding solely on customer intuition or rule of thumb risks excessive investment or capacity shortfalls lacking objective grounds.

Only when all three parties verify and evaluate numbers from their respective domains of expertise (field operational insights, project coordination capabilities, and data analytical capabilities) do "firm, highly accurate preconditions for system design" get completed.