📅 2025-07-05
🕒 Reading time: 7 min
🏷️ Promotional Support 🏷️ Retail 🏷️ Operational Efficiency 🏷️ AI Document Generation 🏷️ BPM 🏷️ Value Proposition
"By month-end, over 50 instruction sheets. And each is slightly different."
So spoke Mercadix Supply Co.'s Sales Planning Manager. The company providing promotional planning to nationwide retailers created all sales floor proposal documents manually.
"Now, individual staff expression ability determines promotional results. We're too dependent on experienced personnel's intuition—we can't even reproduce it."
Listening to him, I recalled yesterday's warning from Professor M: "the real game begins now."
"By the way," I carefully inquired, "how did you learn about us?"
The manager answered naturally:
"At an industry information exchange meeting, the brand manager from Velvette & Co. referred me. She said 'they do wonderful analysis.'"
My blood ran cold. Velvette & Co.—the company representative we saved yesterday was now involving another company.
But thinking about it... she didn't know our true identity. She probably just referred us as good consultants.
No, that's wrong.
This is Professor M's trap. He anticipated we'd gain confidence from yesterday's incident and set up the next move.
"Hypothesis: Promotional instruction sheets appear to be 'creative work' but might actually be a 'structure repetition' aggregate."
ChatGPT began conventional analysis but retained tension from yesterday.
"Could we convey this more through 'feeling'?—Sales floor people are 'customer advocates.' So documents should begin with 'empathy,' not 'instructions.'"
Claude continued analysis while carefully observing the consultant's reactions.
"First, let's map the workflow. And the gap between provided value and recipients can be visualized with Value Proposition Canvas."
But this time there was a suspicious point.
The materials the manager brought included detailed data on nationwide retail stores—store names, sales scale, employee numbers, even personal characteristics.
This was information absolutely unnecessary for normal consulting.
"This store data is very detailed," I said. "Where did you collect it?"
The manager answered somewhat proudly:
"Actually, we recently contracted with an excellent market research company. 'Nexus Market Research'—they provide detailed store analysis for free."
Holmes and I froze.
Nexus Market Research—clearly a Nexus Advisory Group affiliate.
Process | Effort | Personalization | Automation Potential | Information Collected |
---|---|---|---|---|
Theme Confirmation | Low | Low | Complete | Planning strategy information |
Instruction Creation | High | Very High | High | Store individual data |
Store Delivery | Medium | Medium | Medium | Distribution route information |
Content Confirmation/Addition | High | High | Medium | Field reaction data |
Reaction Confirmation/Compilation | High | High | Medium | Sales/behavioral data |
I was horrified. This was an information collection system.
Professor M was using promotional support as pretext to collect detailed information on nationwide retail stores.
But the true purpose was different.
"This story could be interesting if expanded further."
ChatGPT began analyzing sentence patterns as usual, but I was concerned about something else.
The "Nexus Market Research" materials the manager showed included competitor strategic information.
This was industrial espionage level information gathering.
"By the way," I inquired, "what other companies does that market research company contract with?"
The manager answered happily:
"Including competitors, quite a few apparently. They share information 'for industry-wide development.'"
Information sharing—I shuddered.
Continuing analysis, I understood the full picture of Professor M's real game.
He was simultaneously collecting corporate decision-making systems and detailed business data from seven industries (apparel, retail, manufacturing, medical, regional organizations, restaurants, promotional support).
And using that information to...
"Holmes," I said in a trembling voice, "this is economic espionage."
Holmes was also pale:
"Systematic collection of major Japanese industries' confidential information."
"And that information—"
"Is sold to foreign companies and used to rob Japanese companies' competitive advantages."
Mercadix's manager was satisfied with our analysis:
"Wonderful! This will enable efficiency improvements. I'll share this with Nexus Market Research immediately."
"Please wait," I said hastily.
"What's wrong?"
Holmes stood up quietly:
"I apologize, but we must prohibit sharing our analysis results with third parties."
The manager looked confused:
"But information sharing is mandatory in our contract..."
Contract—that word made me fully understand Professor M's methods.
He imposed information sharing obligations on companies in exchange for "free services." In other words, our analysis results would automatically fall into Professor M's hands.
"Sorry," the manager said apologetically. "If we break the contract, all previous free services will be stopped. That would be problematic for the company."
I was in despair.
Professor M was luring companies with "free services" and binding them with contracts forcing information sharing. He'd built a system to legally steal analysis results provided by sincere consultants like us.
"This is..." I murmured, "a perfect information collection system."
Holmes gazed out the window:
"So we've been made part of Professor M's information collection apparatus."
That night, we held an emergency meeting.
"The situation is serious," Holmes said. "Professor M is using us to collect Japanese industrial information."
"What should we do?" I asked.
"First, we must free Mercadix from their contract. And we need to check if other companies are caught in similar traps."
Claude proposed:
"But direct warnings would reveal our movements to Professor M."
Gemini organized structurally:
"Then let's use legal methods to invalidate the contract. Illegal information collection contracts likely violate laws."
ChatGPT added:
"That story will probably require collaboration with public agencies."
Next day, we made a crucial decision.
"We can no longer handle this alone," Holmes said. "We need collaboration with public agencies."
I nodded:
"Let's consult with economic security specialists."
"And we need to coordinate the affected companies."
We decided to carefully convey the truth to the seven companies we'd consulted with:
Surprisingly, all seven companies immediately offered cooperation.
Espol's Brand Strategy Director: "I thought something was strange. We'll cooperate."
Oceantrail's Sales Operations Manager: "Let's involve regional partners too."
Voltbridge's Business Innovation Manager: "We'll provide technical support."
Civitas's General Affairs Manager: "We'll utilize medical industry networks."
Riverstone Chamber of Commerce's General Affairs Manager: "We'll bridge with administration."
Veritage's Field Operations Manager: "We'll gather information through nationwide store networks."
Mercadix's Sales Planning Manager: "We'll spread warnings throughout the retail industry."
That weekend, the 7-Company Alliance's first meeting convened.
Holmes stood up and declared:
"From today, we are not mere victims. We are a counterattacking alliance."
I was moved. Professor M's conspiracy had conversely created Japanese corporate unity.
"We counter information theft with information."
Our battle entered a new phase.
Sales floor execution precision dwells in instruction sheet design philosophy. Beyond personalization, to the intersection of empathy and structure.
But when someone seeks to control that intersection, we must create new intersections.
7-Company Alliance VS Professor M
The true decisive battle was about to begin.
"Who conducts the sales floor—the answer to that question determines the future"—From the Detective's Notes