A classic supply chain moves from upstream to downstream, where the raw material is transformed into products, moved through logistics and distributed to final customers. A data supply chain moves in the opposite direction. The raw data is “sourced” from the customer/user. As it moves downstream, it gets processed and refined by proprietary algorithms and stored in data centers.
The supply chain is the set of steps between the sourcing, manufacturing, distribution of a product up to the steps it takes to reach the final customer. It’s the set of step it takes to bring a product from raw material (for physical products) to final customers and how companies manage those processes.
In a traditional, and physical supply chain, we move from upstream to downstream, as we go from raw materials to the finished good, distributed in the hands of customers and consumers.
While the physical supply chain is structured by starting from sourcing, manufacturing and logistics. Distribution (intended as the finished product ready to be sold) comes at the end of this process.
There is another kind of supply chain, which for tech and AI companies is integrated within their business models, that is the data supply chain.
From physical to data supply chains
Let’s take a simple example. When Google manufactures its phone, the Pixel, while the phone is designed by Google, its manufacturing is outsourced in China (even though Google is moving it to Vietnam).
This means that up to sourcing and manufacturing, the process is outsourced, where Google instead takes control of the process as the phones produced are shipped to Google and ready to be distributed, either through its online stores, through carriers or other indirect channels.
So the whole physical supply chain might look like the following:
Yet, if we flip the perspective and look at the data side of Google, as an AI company, the whole “data supply chain” changes.
Data supply chains: flipping upside down the physical supply chain
In a data supply chain the closer the data to the customer the more we’re moving downstream. For instance, when Google produced its own physical devices. While it moved upstream the physical supply chain (it became a manufacturer) it moved downstream the data supply chain as it got closer to consumers using those devices, so it could gather data directly from the market, without intermediaries.
Where the Pixel phone moves from upstream to downstream, as we saw, it follows a classic supply chain path.
However, once the device is in the hands of customers/consumers/users, they suddenly become the sources of data, and the whole supply chain flips upside down.
A few things to notice here:
In the Google’s Pixel case, the whole data supply chain is controlled by Google.
Customers become also the sources of raw data.
As the raw data move downstream it gets refined by Google’s algorithms and it gets used for several purposes (from products’ personalization, to monetization of its assets through advertising).
That data gets stored in the Google data centers
And the Google data centers will need to source renewable energies and materials to maintain, and run its facilities, that keep the whole infrastructure going.
From traditional supply chain to AI supply chain
AI supply chains start with the sourcing of data. This flips them upside down.
Where a traditional supply chain would start with sourcing and manufacturing with a top-down approach, an AI supply chain starts bottom-up.
The source of raw data is the customer/user, as the raw data moves downstream the supply chain, it gets processed, refined and stored.
Key Highlights
Traditional vs Data Supply Chain: A traditional supply chain involves the movement of physical products from raw materials to final customers, while a data supply chain involves the movement of data from customers/users to data centers, where it’s processed, refined, and stored.
Direction of Movement: In a physical supply chain, the movement is upstream to downstream – from raw materials to customers. In a data supply chain, the movement is reversed, with data moving downstream from customers to data centers.
Components of Traditional Supply Chain: A traditional supply chain encompasses steps like sourcing, manufacturing, logistics, and distribution, ultimately reaching the final customer.
Data Supply Chain for Tech Companies: Tech and AI companies often integrate a data supply chain into their business models. For example, Google’s Pixel phone follows a physical supply chain for manufacturing, but a data supply chain for gathering and processing user data.
Flipping the Data Supply Chain: In a data supply chain, the closer the data is to the customer, the further downstream it is considered. Once devices are in the hands of users, they become sources of raw data, and the entire supply chain flips, with data moving from customers to the company.
Google’s Data Supply Chain: Google’s data supply chain is controlled by the company. Customers/users provide raw data as they use devices. This data is refined by Google’s algorithms, utilized for personalization and advertising, and stored in Google’s data centers.
Renewable Energy and Materials: Google’s data centers require renewable energy and materials to sustain their operations, which adds an environmental aspect to the data supply chain.
Transition to AI Supply Chain: AI supply chains start with data sourcing from customers/users, taking a bottom-up approach. Raw data moves downstream, undergoing processing and refinement, which is a reversal of the traditional supply chain.
Google is primarily owned by its founders, Larry Page and Sergey Brin, who have more than 51% voting power. Other individual shareholders comprise John Doerr (1.5%), a venture capitalist and early investor in Google, and CEO, Sundar Pichai. Former Google CEO Eric Schmidt has 4.2% voting power. The most prominent institutional shareholders are mutual funds BlackRock and The Vanguard Group, with 2.7% and 3.1%, respectively.
Google (now Alphabet) primarily makes money through advertising. The Google search engine, while free, is monetized with paid advertising. In 2023, Alphabet generated over $175B from Google search, $31.51B billion from the Network members (Adsense and AdMob), $31.31B billion from YouTube Ads, $33B from Google Cloud, and $34.69B billion from other sources (Google Play, Hardware devices, and other services). And $1.53B from its other bets.
Google is an attention merchant that – in 2022 – generated over $224 billion (almost 80% of revenues) from ads (Google Search, YouTube Ads, and Network sites), followed by Google Play, Pixel phones, YouTube Premium (a $29 billion segment), and Google Cloud ($26.2 billion).
Of Google’s (Alphabet) over $307.39 billion in revenue for 2023, Google also generated for the first time, well over 1.5 billion dollars in revenue from its bets, which Google considers potential moonshots (companies that might open up new industries). Google’s bets also generated a loss for the company of over $4 billion in the same year. In short, Google is using the money generated by search and betting it on other innovative industries, which are ramping up in 2023.
In 2023, Alphabet’s (Google) Cloud Business generated over $33 billion within Alphabet’s Google overall businessmodel, and it was also profitable, with over $1.7 billion in profits. Google Cloud is instrumental to Google’s AI strategy.
Google is an attention merchant that – in 2023 – generated $237.85 billion (over 77% of its total revenues) from ads (Google Search, YouTube Ads, and Network sites), followed by Google Play, Pixel phones, YouTube Premium (a $31.5 billion segment), and Google Cloud (over $33 billion).
The traffic acquisition cost represents the expenses incurred by an internet company, like Google, to gain qualified traffic – on its pages – for monetization. Over the years, Google has been able to reduce its traffic acquisition costs and, in any case, to keep it stable. In 2023 Google spent 21.39% ($50.9 billion) of its total advertising revenues ($237.8 billion) to guarantee its traffic on several desktop and mobile devices across the web.
YouTube was acquired for almost $1.7 billion in 2006 by Google. It makes money through advertising and subscription revenues. YouTube advertising network is part of Google Ads, and it reported more than $31B in revenues by 2023. YouTube also makes money with its paid memberships and premium content.
In 2023, Google’s search advertising machine, generated over 175 billion dollars. Whereas Microsoft’s Bing generated 12.2 billion dollars. Thus, as of 2023, Google’s search advertising machine is over 14x larger than Microsoft’s search advertising machine.
Google makes most of its money from advertising. Indeed total advertising revenue represented nearly 78% of Google’s (Alphabet) overall revenues for 2023. Google Search represented nearly 57% of Google’s total revenues. Google generated $307.39B in revenues in 2022, and $73.79B billion in net profits.
In 2023, Google generated $307.39 billion, comprising $175B in Google Search, $31.51B in YouTube ads, and $31.31B in Google network revenue. $34.69B in other revenue, $33B in Google cloud, $1.53B in other bets.
In 2023, Google generated 237.85B in revenue in advertising, which represented over 77% of its total revenues of $ 307.39 B. In 2022, Google generated $224.47B in revenues from advertising, which represented almost 80% of the total revenues, compared to $282.83B in total revenues. Therefore, most of the revenues from Alphabet, the mother company of Google, come from advertising.
At the end of December 2022, Google had over 190,000 employees. On January 20, Google announced the layoff of 12,000 employees within the company, thus bringing the number of total employees by December 2023 to 182,502 full-time employees.
Google generated $1,684,332 per employee in 2023, compared to $1,486,779 per employee in 2022. As of January 2023, as the company announced a mass layoff, it brought back its revenue per employee at $1,586,880, still behind the peak in 2021, for $1,840,330.
The supply chain is the set of steps between the sourcing, manufacturing, distribution of a product up to the steps it takes to reach the final customer. It’s the set of step it takes to bring a product from raw material (for physical products) to final customers and how companies manage those processes.
A classic supply chain moves from upstream to downstream, where the raw material is transformed into products, moved through logistics and distribution to final customers. A data supply chain moves in the opposite direction. The raw data is “sourced” from the customer/user. As it moves downstream, it gets processed and refined by proprietary algorithms and stored in data centers.
Distribution represents the set of tactics, deals, and strategies that enable a company to make a product and service easily reachable and reached by its potential customers. It also serves as the bridge between product and marketing to create a controlled journey of how potential customers perceive a product before buying it.
A distribution channel is the set of steps it takes for a product to get in the hands of the key customer or consumer. Distribution channels can be direct or indirect. Distribution can also be physical or digital, depending on the kind of business and industry.
In business, vertical integration means a whole supply chain of the company is controlled and owned by the organization. Thus, making it possible to control each step through customers. in the digital world, vertical integration happens when a company can control the primary access points to acquire data from consumers.
Horizontal integration refers to the process of increasing market shares or expanding by integrating at the same level of the supply chain, and within the same industry. Vertical integration happens when a company takes control of more parts of the supply chain, thus covering more parts of it.
By definition, a horizontal market is a wider market, serving various customer types, needs and bringing to market various product lines. Or a product that indeed can serve various buyers across different verticals. Take the case of Google, as a search engine that can serve various verticals and industries (education, publishing, e-commerce, travel, and much more).
A vertical or vertical market usually refers to a business that services a specific niche or group of people in a market. In short, a vertical market is smaller by definition, and it serves a group of customers/products that can be identified as part of the same group. A search engine like Google is a horizontal player, while a travel engine like Airbnb is a vertical player.
When entering the market, as a startup you can use different approaches. Some of them can be based on the product, distribution, or value. A product approach takes existing alternatives and it offers only the most valuable part of that product. A distribution approach cuts out intermediaries from the market. A value approach offers only the most valuable part of the experience.
Backward chaining, also called backward integration, describes a process where a company expands to fulfill roles previously held by other businesses further up the supply chain. It is a form of vertical integration where a company owns or controls its suppliers, distributors, or retail locations.
A market type is a way a given group of consumers and producers interact, based on the context determined by the readiness of consumers to understand the product, the complexity of the product; how big is the existing market and how much it can potentially expand in the future.
Psychosizing is a form of market analysis where the size of the market is guessed based on the targeted segments’ psychographics. In that respect, according to psychosizing analysis, we have five types of markets: microniches, niches, markets, vertical markets, and horizontal markets. Each will be shaped by the characteristics of the underlying main customer type.
According to the book, Unlocking The Value Chain, Harvard professor Thales Teixeira identified three waves of disruption (unbundling, disintermediation, and decoupling). Decoupling is the third wave (2006-still ongoing) where companies break apart the customer value chain to deliver part of the value, without bearing the costs to sustain the whole value chain.
Disintermediation is the process in which intermediaries are removed from the supply chain, so that the middlemen who get cut out, make the market overall more accessible and transparent to the final customers. Therefore, in theory, the supply chain gets more efficient and, all in all, can produce products that customers want.
Reintermediation consists in the process of introducing again an intermediary that had previously been cut out from the supply chain. Or perhaps by creating a new intermediary that once didn’t exist. Usually, as a market is redefined, old players get cut out, and new players within the supply chain are born as a result.
As startups gain control of new markets. They expand in adjacent areas in disparate and different industries by coupling the new activities to benefits customers. Thus, even though the adjunct activities might see far from the core businessmodel, they are tied to the way customers experience the whole businessmodel.
The bullwhip effect describes the increasing fluctuations in inventory in response to changing consumer demand as one moves up the supply chain. Observing, analyzing, and understanding how the bullwhip effect influences the whole supply chain can unlock important insights into various parts of it.
Dropshipping is a retail business model where the dropshipper externalizes the manufacturing and logistics and focuses only on distribution and customer acquisition. Therefore, the dropshipper collects final customers’ sales orders, sending them over to third-party suppliers, who ship directly to those customers. In this way, through dropshipping, it is possible to run a business without operational costs and logistics management.
Consumer-to-manufacturer (C2M) is a model connecting manufacturers with consumers. The model removes logistics, inventory, sales, distribution, and other intermediaries enabling consumers to buy higher quality products at lower prices. C2M is useful in any scenario where the manufacturer can react to proven, consolidated, consumer-driven niche demand.
Transloading is the process of moving freight from one form of transportation to another as a shipment moves down the supply chain. Transloading facilities are staged areas where freight is swapped from one mode of transportation to another. This may be indoors or outdoors, depending on the transportation modes involved. Deconsolidation and reconsolidation are two key concepts in transloading, where larger freight units are broken down into smaller pieces and vice versa. These processes attract fees that a company pays to maintain the smooth operation of its supply chain and avoid per diem fees.
Break bulk is a form of shipping where cargo is bundled into bales, boxes, drums, or crates that must be loaded individually. Common break bulk items include wool, steel, cement, construction equipment, vehicles, and any other item that is oversized. While container shipping became more popular in the 1960s, break bulk shipping remains and offers several benefits. It tends to be more affordable since bulky items do not need to be disassembled. What’s more, break bulk carriers can call in at more ports than container ships.
Cross-docking is a procedure where goods are transferred from inbound to outbound transport without a company handling or storing those goods. Cross-docking methods include continuous, consolidation, and de-consolidation. There are also two types of cross-docking according to whether the customer is known or unknown before goods are distributed. Cross-docking has obvious benefits for virtually any industry, but it is especially useful in food and beverage, retail and eCommerce, and chemicals.
The Toyota Production System (TPS) is an early form of lean manufacturing created by auto-manufacturer Toyota. Created by the Toyota Motor Corporation in the 1940s and 50s, the Toyota Production System seeks to manufacture vehicles ordered by customers most quickly and efficiently possible.
Six Sigma is a data-driven approach and methodology for eliminating errors or defects in a product, service, or process. Six Sigma was developed by Motorola as a management approach based on quality fundamentals in the early 1980s. A decade later, it was popularized by General Electric who estimated that the methodology saved them $12 billion in the first five years of operation.
Scientific Management Theory was created by Frederick Winslow Taylor in 1911 as a means of encouraging industrial companies to switch to mass production. With a background in mechanical engineering, he applied engineering principles to workplace productivity on the factory floor. Scientific Management Theory seeks to find the most efficient way of performing a job in the workplace.
Poka-yoke is a Japanese quality control technique developed by former Toyota engineer Shigeo Shingo. Translated as “mistake-proofing”, poka-yoke aims to prevent defects in the manufacturing process that are the result of human error. Poka-yoke is a lean manufacturing technique that ensures that the right conditions exist before a step in the process is executed. This makes it a preventative form of quality control since errors are detected and then rectified before they occur.
A Gemba Walk is a fundamental component of lean management. It describes the personal observation of work to learn more about it. Gemba is a Japanese word that loosely translates as “the real place”, or in business, “the place where value is created”. The Gemba Walk as a concept was created by Taiichi Ohno, the father of the Toyota Production System of lean manufacturing. Ohno wanted to encourage management executives to leave their offices and see where the real work happened. This, he hoped, would build relationships between employees with vastly different skillsets and build trust.
Jidoka was first used in 1896 by Sakichi Toyoda, who invented a textile loom that would stop automatically when it encountered a defective thread. Jidoka is a Japanese term used in lean manufacturing. The term describes a scenario where machines cease operating without human intervention when a problem or defect is discovered.
The andon system alerts managerial, maintenance, or other staff of a production process problem. The alert itself can be activated manually with a button or pull cord, but it can also be activated automatically by production equipment. Most Andon boards utilize three colored lights similar to a traffic signal: green (no errors), yellow or amber (problem identified, or quality check needed), and red (production stopped due to unidentified issue).
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
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