Way to data scientist

In the digital era, enterprise business data no longer merely serves direct commercial objectives; rather, it has become a significant barometer for observing the macroeconomy, social trends, and industry changes.

一 Insights form a transport platform

For example, a platform named “yunmanman” generates a lot of data, and we can have a lot of insights from it

YMM (Yunmanman) was founded in 2013 and operates under Jiangsu Manbang Software Technology Co., Ltd. It is a freight dispatch platform developed using cloud computing, big data, mobile internet, and artificial intelligence technologies. Following its merger with Huochebang in 2017 to form Manbang Group, the platform has further expanded in scale. Currently, it boasts over 5.2 million registered heavy-duty truck drivers and more than 3 million shippers, earning it the reputation as the “Didi” of the freight industry (or “Uber for Trucking”).

1.1 From Logistics Data to Health Trends

The overall volume of soy sauce transported via YMM increased by 6%. This seemingly simple figure, however, holds rich cross-industry insights.

1.2 Foie Gras Transportation – Supply Chain Stability and Commercial Opportunity Identification

The second eye-catching case is the surge in foie gras transportation volume. In the first half of this year, shipments originating from Huoqiu County in Lu’an City, Anhui Province via YMM increased over tenfold compared to last year. More strikingly, last year’s volume had already seen an eightfold increase over the previous year. Most remarkably, this single county now accounts for one-third of China’s total foie gras supply.

This case demonstrates the commercial value of data insights across multiple dimensions:

1. Supply Chain Perspective: The explosive growth indicates a rapid enhancement in the supply chain capability for this premium ingredient within the Chinese market. For restaurant owners, this signifies that foie gras – traditionally viewed as scarce and expensive – can now be sourced for long-term, stable supply with continually decreasing costs.
2. Business Opportunity Perspective: This data insight provides strong evidence of significant market demand expansion for foie gras, highlighting considerable development potential.
3. Strategic Decision Support: Based on this insight, F&B enterprises can make more aggressive business commitments. They can confidently develop large-scale foie gras menus without fearing supply chain instability or significant cost fluctuations. This data-driven decision support empowers businesses to spot opportunities and achieve rapid operational expansion.

二 Insights form a bank

we can see the fortune of a country from the earnings of bank

三 Insights form a food delivery platform

Meituan Waimai, as China’s largest online food delivery platform, offers business data that not only reflects the state of the catering industry but also provides deeper insights into the work-life patterns and societal stress levels of modern Chinese citizens. Analyzing Meituan’s data yields unique perspectives on the hardships within China’s workforce.

The platform currently boasts 3.99 million registered delivery riders, a number growing rapidly. Its daily order volume consistently exceeds 90 million, maintaining a stable market share above 65%. Behind these figures lies the rise of a vast new workforce and the explosive growth of the on-demand delivery economy.

From a sociological perspective, the rapid increase in delivery riders reflects intertwined social phenomena:

1. Rise of New Employment Models: It signifies the emergence of new forms of work and the popularization of flexible employment. Amid relatively scarce traditional job opportunities, food delivery provides a viable alternative for a large segment of the labor force.
2. Accelerated Pace of Life & Increased Work Pressure: It demonstrates the faster pace of modern life and heightened work pressure, leading more people to choose food delivery to save time and energy.

The significant growth in late-night orders is another notable trend. Data shows that peak order times have expanded beyond the traditional “9-to-9” workday into the late-night hours, leading to widespread “overtime” work among riders. This shift not only reflects the development of the urban “night economy” but also indicates a deeper trend of lengthening work hours and increasing life pressures.

From a labor economics perspective, the development model of the food delivery industry also reveals challenges inherent in new employment forms:

• Family Economic Role: 97% of female riders engage in flexible work, and over 60% of delivery personnel are married, highlighting the sector’s critical role in household economies.
• Hardships Beneath Flexibility: However, the physical fatigue from long hours, increased traffic safety risks, and psychological stress stemming from the lack of stable social security benefits mean that the seemingly “free” delivery work is, in reality, fraught with hardship.

The algorithm-driven work model intensifies these difficulties. While platform algorithms optimize delivery routes and times to boost overall efficiency, they simultaneously impose greater time pressure and work intensity on riders. This phenomenon of being a “slave to the algorithm” exemplifies the new characteristics and challenges of labor relations in the digital age.

So, we can get a lot of insights from the operation data of a company

At last

If I want to gauge whether the US economy is robust, which specific enterprise metrics do you think would be valuable to reference?