GVIA Insights | The Casual Conversation Method: How to Understand a Company Through Informal Channels

In capital markets where information is highly transparent, investors seem closer to corporate truth than ever before. Financial reports, announcements, earnings calls, industry databases and research reports are readily available, and artificial intelligence can organize materials in just a few minutes. However, the increase in information volume has not eliminated cognitive biases. Content disclosed by companies is usually filtered, and financial figures only record operating results. Many factors that determine long-term value — whether customers are willing to repurchase, whether channels are overstocked, whether suppliers trust the company, whether employees endorse management — remain difficult to obtain directly from standardized documents.

This also explains why the Global Value Investment Association, in practicing "focusing on value, focusing on investment, and taking a global perspective", has always attached importance to continuous observation of companies’ real operating conditions. Judging a company’s long-term value requires not only analyzing financial statements and valuation, but also understanding how products enter the market, why customers are willing to pay, and whether competitive advantages can withstand the scrutiny of all parties in the industrial chain. Only by moving from paper data to real business relationships can investment research approach the source of corporate value formation.

The "scuttlebutt method" proposed by Philip Fisher is precisely a bridge connecting paper research with the real business world. It is not about prying for gossip, but about observing a company’s performance in actual operations through different channels such as customers, suppliers, distributors, competitors, industry experts and employees, and verifying whether the future depicted by management has a realistic foundation.

I. Beyond Financial Reports, There Is a Real Business World

Financial statements can tell investors how much a company’s revenue has grown, whether its gross margin has improved, and whether its cash flow is sufficient, but they can hardly explain why these changes occurred. A company’s rapid revenue growth may stem from enhanced product competitiveness, but it may also come from price-cut promotions, relaxed credit terms, or pre-pressuring goods onto distributors. A rise in gross margin may result from technological upgrading, or it may simply be a short-term decline in raw material prices. A sharp increase in orders may mean strong real demand, but it may also hide risks such as customer concentration, delivery delays or order cancellations.

Fisher realized that to judge whether a company can maintain long-term growth, it is not enough to merely listen to management’s explanation of itself. Management knows the company’s strategy and operations best, but it also naturally has the motive to maintain the company’s image. In contrast, why customers buy, whether suppliers are willing to prioritize supply, whether distributors actively restock, and how competitors evaluate its products often better reflect the company’s real position in the market.

Therefore, what the scuttlebutt method pursues is not a single piece of "exclusive news" enough to trigger stock price fluctuations, but to restore the process of a company’s revenue, profit and competitive advantage formation through a large number of scattered, mutually independent operating clues. Financial reports present the answer sheet a company has already completed; the scuttlebutt method studies how the company answers the questions.

II. Finding Answers in the Behavior of Stakeholders

Customers are one of the most important sources of information in Fisher-style research. Customers know best whether a product can truly solve problems, and they can best explain whether a company’s competitive advantages can be translated into sustained revenue. Instead of asking generically whether the product is easy to use, it is better to understand why customers chose this company, whether they compared other suppliers, whether they are still willing to purchase after price increases, and how much it would cost to switch products or systems.

These actual behaviors can help investors distinguish between "customer satisfaction" and "customer dependence". The former may just be a positive evaluation, while the latter may form pricing power, repurchase rates and stable cash flow. If customers buy only because of lower prices, the company’s growth can easily be replicated by competitors. If the product has been embedded in customers’ production processes, data systems or core businesses, with high switching costs, its competitive barrier deserves more attention. What truly has investment value is not just customers expressing satisfaction with the product, but customers being willing to buy continuously and being unable to switch easily.

Suppliers can help investors observe a company’s procurement rhythm, payment ability, quality requirements and order stability. If a company delays payments for a long time, frequently changes procurement plans, or continuously suppresses supplier prices to maintain profits, its short-term financial performance may still look good, but supply chain relationships are unlikely to be stable for long.

Conversely, if suppliers are willing to reserve capacity for a company, jointly develop new products, or even prioritize meeting its demand when industry supply is tight, it usually means the company has good credit, stable orders or a strong industry position. The real behavior of suppliers is often more persuasive than a phrase like "establishing long-term strategic cooperative relations".

Distributors and channel partners provide a critical perspective between "company shipments" and "terminal sales". For consumer goods, pharmaceutical, automotive and industrial product companies, the company may have sold products to distributors and recognized revenue, but the goods are still piled up in channel warehouses. If distributors mainly rely on rebates to maintain purchases, terminal discounts continue to expand, or inventory continues to rise while restocking willingness declines, then the growth in financial statements needs to be re-evaluated.

Products entering channels does not mean terminal demand has been realized, and inventory transferring from the company to distributors does not mean sales are truly completed. Therefore, channel research should not only focus on how many products the company has shipped to distributors, but also observe terminal sales speed, inventory turnover days, discount levels, return rates and distributors’ active restocking willingness.

Competitors’ evaluations also have reference value. Although peers may have their own positions, they usually know best a company’s capability boundaries. If competitors generally admit that a company is hard to catch up with in R&D, delivery, cost control or customer relations, such evaluation often carries more weight than the company’s self-promotion. Conversely, if the company repeatedly emphasizes technological leadership, but peers believe its products are easy to replicate, investors need to re-examine the so-called moat.

Employees and former employees can further help investors understand how the organization operates internally, including whether R&D and sales are coordinated, whether decision-making processes are efficient, whether management can accept different opinions, and whether performance assessment encourages long-term innovation. However, employees’ evaluations may be influenced by position, interests and personal emotions. Investors should focus on verifiable specific facts rather than directly accepting emotional praise or criticism.

III. Amid the AI Boom, Do Huge Orders Equal Real Revenue?

As of July 2026, artificial intelligence remains one of the most important investment themes in global capital markets. Chip, server, data center, cloud computing and power equipment companies continue to disclose huge orders, and the market is continuously raising growth expectations for related industries.

For example, Super Micro disclosed that it received new orders exceeding $60 billion in the fourth quarter of fiscal 2026, and expected quarterly gross margin to reach 15% to 17%, significantly higher than the previous guidance of 8.2% to 8.4%. After the news was announced, the company’s stock price rose significantly in after-hours trading.

On the surface, huge orders are enough to prove strong demand for AI servers. But Fisher-style research does not stop at order size; it further understands customer structure, payment ability, contract constraints and the supply of key components. Whether orders come from a small number of large customers, whether customers have sufficient financing ability, whether contracts can be postponed or cancelled, and whether the company can obtain chips, memory and liquid cooling equipment in a timely manner will all affect the speed and quality with which orders are ultimately converted into revenue.

The expansion of artificial intelligence infrastructure is also constrained by power systems and engineering cycles. In July 2026, U.S. power companies and data center developers were still competing for key equipment such as transformers, and the delivery cycle for some large equipment had exceeded 160 weeks. A Reuters investigation showed that utility companies had to lock in capacity in advance, refurbish old equipment and expand overseas procurement.

This means that even if a data center company signs a huge contract, it may not be able to complete construction and grid connection on schedule. By understanding project progress through grid operators, equipment manufacturers, engineering contractors and park customers, investors may identify delivery bottlenecks earlier than simply reading order announcements. Orders represent business opportunities, while the supply chain determines whether opportunities can be converted into revenue.

This kind of research is particularly important for hot industries, because different companies in the industrial chain may expand based on the same set of long-term demand. Server manufacturers include potential projects in their sales pipelines, data center operators expand capital expenditure based on customer plans, and power equipment companies increase capacity based on data center plans. Once project financing, grid connection progress or terminal demand changes, growth expectations in multiple links may be revised down simultaneously.

What the market sees may be multiple sets of strong data, but these data may not correspond to multiple sets of mutually independent demand. Facing hot industries, investors need to judge not only how large demand is, but also whether demand is independent, whether funds are in place, and whether projects can be delivered.

IV. Understanding Companies in Continuous Change, Rather Than Being Driven by Single-Quarter Figures

Graham’s influence on Buffett was first reflected in investment discipline. Buffett studied under Graham at Columbia University and later worked at Graham-Newman Corporation. In his early years, he was accustomed to looking for companies whose stock prices were significantly lower than their asset values, and profiting from valuation repair, asset disposal or corporate liquidation.

Such investments were later vividly called "cigar butt stocks" — the company itself may have lost growth potential, but the price is low enough that there is still a chance to get the last bit of residual value. For investors with small capital scales and many undervalued securities in the market, this method was once very effective.

However, cheap securities often come with obvious flaws. Some companies, despite large asset discounts, lack the ability to improve operations. Some enterprises take a long time to complete value regression, during which they may continue to consume cash. Other investments, even if profitable, must be sold after price repair, unable to form long-term compound interest through corporate operations.

Buffett later reflected that buying cheap enterprises with operational difficulties is like struggling in quicksand — even if one can eventually escape, it often consumes a lot of time and energy. Low prices can provide one-time profit opportunities, but they cannot automatically create a continuously growing compound interest machine.

V. Turning "Scuttlebutt" into Disciplined Research

Informal channels do not mean unprofessional. On the contrary, for the scuttlebutt method to generate investment value, it first needs to transform vague judgments into verifiable questions. When researching a company, instead of asking generically whether it has development prospects, it is better to specifically understand whether customer purchase volume has increased, whether renewal prices have changed, whether delivery cycles have lengthened, and whether the product has entered new usage scenarios. The closer to actual operating behavior, the more judgmental value the answer has.

Information sources should also cover different positions in the industrial chain. Researching a manufacturing company cannot only involve visiting a few suppliers; researching a consumer company cannot only listen to distributors’ evaluations. A single group often has similar positions, and may even repeat the same set of market narratives. Only when information provided by customers, channels, suppliers, peers and employees complements each other can a complete corporate portrait gradually be formed.

Attention should also be paid to contradictions between information during the research process. If management says products are in short supply, but distributors reflect high inventory, one should not immediately choose to believe one side, but continue to check statistical caliber, regional differences, product structure and time cycles. Many operational risks do not initially appear directly in financial reports, but are manifested as inconsistent information across different links of the industrial chain.

Ultimately, all research conclusions must return to financial statements. An increase in customer repurchase rates should theoretically gradually be reflected as enhanced revenue stability or declining customer acquisition costs. An improvement in a company’s bargaining power should leave traces in gross margin and cash conversion cycle. A continuous rise in channel inventory may be manifested as increased accounts receivable, return provisions or sales expenses. Industrial research explains business logic, while financial data verifies whether the logic is realized.

VI. Artificial Intelligence Improves Efficiency, Real Relationships Provide Depth

Artificial intelligence can quickly compare financial reports, extract key points from earnings calls, organize industry materials, and also help investors develop interview outlines. But it mainly processes information that has already been recorded and expressed, and it is difficult to fully capture subtle changes in business relationships.

Customers’ hesitation about price increases, the reasons why distributors are unwilling to restock, suppliers’ concerns about payment rhythm, and employees’ real feelings about organizational efficiency usually do not appear completely in public texts. This information may not be enough to form an investment conclusion alone, but it can help researchers discover problems worth further investigation.

When a large number of reports and content are generated by artificial intelligence, different information sources may just repeat the same set of public narratives. On the surface, investors have read a lot of materials, but in fact they may just have received the same set of information multiple times without obtaining new independent evidence. Therefore, artificial intelligence is more suitable for material organization, text comparison and anomaly identification, while the scuttlebutt method is used to access real operating scenarios. The former improves research efficiency, while the latter supplements cognitive depth.

As information generation becomes easier and easier, procurement, delivery, usage and payment behaviors in the real world become more precious.

VII. Moving from Information Quantity to Cognitive Quality

The reason Fisher’s scuttlebutt method remains relevant over time is not because it provides a shortcut to finding investment secrets, but because it requires investors to maintain skepticism, patience and independent judgment. Facing a company sought after by the market, what truly matters is not collecting more praise, but understanding who is paying for its products, why customers are willing to pay continuously, whether growth relies on price cuts and subsidies, and what competitive advantages the company can retain when industry prosperity declines.

The entrepreneurs, investment institutions and industry experts connected by the Global Value Investment Association provide a foundation for exchanges between different markets and industries. But from the perspective of value research, the significance of a relationship network is not to obtain undisclosed information, but to help investors observe the same company from more positions. From customer demand, one can understand revenue quality; from supply chain status, one can judge delivery capability; from the competitive landscape, one can verify the company’s market position.

These feedbacks from real business scenarios must ultimately be tested against public information, financial data and long-term operating results. Only by maintaining the independence of information sources and continuously excluding positions, emotions and short-term noise can scattered industrial clues be transformed into reliable value judgments.

Global Value Investment Association True value research requires not only understanding how a company introduces itself, but also understanding how the entire industrial chain evaluates it.