Strategic Decision-Making in the Business World

 Strategic Decision-Making in the Business World

In the vast realm of business, decision-making is like a compass guiding a ship, directing the course of an enterprise. The strategic insights of seasoned decision-makers, such as Wang Huaiwen and Wang Xing, offer profound wisdom and acumen. Strategy is not merely planning; it involves finding the highest return on investment (ROI) across different times and spaces, encompassing various regions and businesses. While ROI is difficult to quantify precisely, it objectively exists, and strategies are formed through precise insights and matching action plans.

The scale of an industry, seemingly simple, is a crucial factor that determines success or failure. Many failures stem from misjudging this scale—either overestimating and blindly investing, like the shared bike industry burning money in a market that wasn't large enough, or underestimating and missing opportunities, such as IBM's former CEO Thomas Watson Jr. famously predicting that the world would only need five computers. When Meituan entered the food delivery sector, it initially misjudged the industry scale. However, a product manager's research revealed that Ele.me was achieving a 200% annual growth rate without losing money, indicating significant market potential. Although Meituan still underestimated the market, its assessment was the most aggressive in the industry at the time. Judging market scale can be done through methods like fitting current industry size with growth rates, regressing to fundamental human needs, and analogies. Accurate judgment is vital for entrepreneurs and investors to gain a strategic advantage.

Scale effects are akin to the universal law of gravity in the business world. Their essence has evolved from the traditional notion that selling more products reduces costs to the idea that significant transaction volumes or user engagement can create advantages in customer experience or cost. Different businesses exhibit varying scale effects. For instance, chain hair salons have some scale effects, limited edition products do not, and art pieces may even show reverse scale effects. Scale effect curves come in various shapes: A curves (exponential growth) are typical in social networks like WeChat, where network value grows with the square of the number of nodes, allowing rapid dominance once a critical point is passed. C curves (logarithmic growth) are common in businesses with "two-sided networks and same-side negative effects," such as ride-hailing and food delivery, where growth slows after reaching a certain scale. B curves (linear growth) are seen in platforms like Taobao, where each additional user adds value without competition among users. Scale effects also vary in scope, including global, urban, and cellular types, shaping market landscapes together with curve shapes and parameters. Even with similar curves and scopes, different parameters can lead to vastly different scale effects, as seen in Facebook's success over MySpace due to its strong social network effects. Identifying scale effects in chosen business elements is crucial, as management itself can have reverse scale effects, while strong business scale effects can sometimes offset these negative impacts. Misjudging scale effects in emerging industries can lead to significant challenges.

The Matthew effect, akin to the theory of evolution in business, is prevalent. It arises from people's reliance on experts or majority opinions in various domains, leading to further advantages for those perceived as successful. In venture capital, funds concentrate around top VCs, and startups prefer well-known investors. Yahoo's success was partly due to the Matthew effect, where Sequoia's investment created buzz, attracting traffic and talent. For early-stage startups, initial products may be rough, but forming a Matthew effect can resolve many issues. Meituan's food delivery started with a weak product and research team and a criticized logo but gained momentum through business growth. In almost every field, most decision-makers lack effective information and judgment methods, leading to the Matthew effect. Companies should capitalize on elements with scale effects, reduce reverse scale effects, and quickly form a Matthew effect.

Market concentration, influenced by scale effects, the Matthew effect, and reverse scale effects, is crucial for nurturing large enterprises. High market concentration is essential, even in large markets like China's catering industry. Market concentration is often measured by CR (concentration ratio), and predicting an industry's final concentration is key to strategic decision-making. In highly competitive industries like long-form video platforms, intense competition persists without profitability. If only one player remains, forming a Matthew effect quickly is vital. In most industries with 2-3 leading players, companies must become leaders while balancing ROI to avoid over-investment. In duopolies, long-term preparation and differentiation are crucial from the start. In the internet sector, social networks grow naturally with minimal investment, while group-buying platforms require significant investment, as seen in Meituan's strategy during the group-buying wars.

The industrial chain is complex, with many participants even in large industries. Chain leaders, like Microsoft in the computer industry, hold significant influence during industry transformations. The smiling curve theory suggests that companies closer to core supply resources and consumers fare better. Ecosystem builders like Amazon enhance industry efficiency and create value. Forcing an ecosystem in an industry without one can lead to failure. Porter's Five Forces model highlights the importance of market concentration in supplier-customer relationships, with ideal conditions being high concentration in one's own market and low concentration among suppliers and customers.

First-mover advantages are significant, attracting talent, accumulating resources, and identifying pitfalls early. However, late movers also have advantages, such as clearer paths to success and fewer cognitive biases. For instance, Ele.me, as a pioneer in food delivery, had innovative methods but relied too heavily on its early model, missing out on potential markets. Meituan, as a late entrant, followed conventional business logic and expanded into markets Ele.me had not explored. The differing mindsets of first movers and late entrants shape their development paths.

At any given time, companies must determine whether they are in an incremental or stock market. Stock markets are challenging, especially for late entrants, with high customer acquisition costs and difficult-to-change market structures. However, opportunities exist, as seen in Pepsi's success in differentiating itself from Coca-Cola by targeting younger consumers. High-frequency businesses often use strategies to penetrate low-frequency markets, as Meituan did in online hotel bookings. Low-frequency businesses can maintain competitiveness by deepening their industry chains or collaborating with high-frequency businesses, as seen in Lianjia's second-hand housing market and Meituan's partnership with WeChat.

Timing is crucial for market entry, as entering too early or too late can lead to failure. Community group buying is a current example in the internet industry, with many major companies entering the market. Judging the right time to enter is challenging, as new business lines in large companies may lack influence, leading to chasing trends or abandoning projects too quickly. Small companies may lose talented employees if business progress is slow, often leading to team dissolution by the end of the second year. All significant demands typically emerge after multiple failed attempts, with windows of opportunity opening due to technological and cognitive shifts, such as the proliferation of smartphones driving the growth of the food delivery industry. Early entry allows for the accumulation of correct insights and a better chance of riding the wave of success. Companies should commit to continuous investment rather than hoping for immediate success.

Michael Porter's three generic strategies, while classic, need reinterpretation in the internet age. Cost leadership should be updated to experience leadership driven by scale effects. Differentiation and focus strategies are less effective due to the internet's unique characteristics, requiring assumptions about competitors' weak organizational capabilities. Standardized strategies, while popular, are not universally effective. Successful strategies often result from combining multiple factors, making simple strategies insufficient for complex business operations, organizational situations, and industry conditions. Developing a strategy involves guesswork, assumptions, and validation, with long feedback cycles that can lead to a company's downfall after a few failures. Common misconceptions include determinism and nihilism, where success or failure is attributed to single factors rather than a combination of elements.

In conclusion, making strategic decisions is a complex process that requires considering various factors, including market scale, scale effects, the Matthew effect, market concentration, industrial chains, first-mover and late-mover advantages, incremental and stock markets, high and low-frequency businesses, and entry timing. Through continuous trial and error, companies can make the best strategic decisions to lead their enterprises through the ever-changing business landscape.