digital ecosystem essay

Ecosystem 2.0: Climbing to the next level

As COVID-19 accelerates customers’ migration to digital , with consumers of all ages going online for everything from food to cars to doctor visits, some companies may feel that the channels, platforms, and approaches they have relied on for years are burning up faster than ever.

The pandemic has magnified a previous trend in which many traditional corporations tried to create or participate in digital ecosystems, only to fall short. These ecosystems consist of interconnected sets of services through which users fulfill a variety of cross-sectoral needs in one integrated experience. Today’s dominant ecosystems were launched by ascendant tech companies, which have used hyperscale platforms  to compete with, disintermediate, and often substitute for the offerings of traditional competitors by controlling customer interfaces and control points such as search, advertising, and messaging.

The market understands this power. Most of the companies with the world’s highest market capitalizations are tech companies that generate much of their revenue from the digital ecosystems they created (Exhibit 1). Many of these ecosystems are B2C plays. Others, such as Jabil’s, represent B2B spaces. Some companies tackle both: Amazon, for example, ties together e-commerce, cloud computing, logistics, and consumer electronics, while China’s Tencent provides services including social media, gaming, finance, and cloud computing.

Can more traditional competitors play this new game? To shed light on that question, we recently looked at the ecosystem strategies of 100 incumbent companies. Our findings suggest there is a path for more established players to use ecosystems to level the playing field. This path has been opened up, in part, by the ubiquity of digitization and data and the emergence of advanced analytics, tools that give companies better insight into customers and market niches, allowing them to personalize products as never before. The path has also been clarified by the mistakes incumbent companies made in their early efforts to participate in digital ecosystems, during an era that might be called Ecosystem 1.0. Absorbing those lessons while making the most of new digital technology can help companies move up their industry’s power curve  in a hurry, executing on practices that turn so-so ecosystem plays into markedly better ones. That’s the promise of Ecosystem 2.0.

An evolving model

How do ecosystems work? For starters, they create value along two dimensions. They allow participants to consolidate a range of customers , often across sectors. Think of this as the horizontal vector. On the vertical vector, ecosystem participants strengthen or even dominate touch points along customer journeys (both B2C and B2B). Of course, ecosystem participants don’t try to do this by building everything they need in-house. Instead, ecosystem organizers provide incentives to and partner extensively with other participants, who may be within their traditional industry boundaries or outside of them. These moves can unleash distributed innovation and create new efficiencies along value chains to improve customer experiences while opening new avenues of value creation for a wide range of participants.

To participate successfully in ecosystems, traditional companies must often change the way they think about customers. Instead of limiting themselves to services within their historical industry borders, they may venture beyond in an effort to serve customers from one end of the customer journey to the other. For instance, opportunistic companies in the housing market—such as the United Kingdom’s ZPG—are trying to create end-to-end ecosystems that may span search, property comparisons, mortgage shopping, household moving, switching phone and cable companies, and access to home-improvement professionals. In fact, we estimate that at least a dozen sectors, including B2B services, mobility, travel and hospitality, health, and housing, are reinventing themselves as vast ecosystems , networks of networks that could add up to a $60 trillion integrated network economy by 2025.

To participate successfully in ecosystems, traditional companies must often change the way they think about customers.

These ecosystems develop in virtuous cycles through network effects. By offering products and services that individual companies could not create on their own, ecosystems draw in more and more customers, which creates even more data, which allows artificial intelligence (AI) to fashion even better offerings, which in turn further improves processes and wins more customers. As ecosystems bridge openings along the value chain, they create a customer-centric, unified value proposition in which users can enjoy an end-to-end experience for a wide range of products and services through a single access gateway. Along the way, customers’ costs go down even as they gain new experiences, all of which whets their appetite for more.

Consumers and companies understand the appeal. Seven in ten consumers we surveyed said they value ecosystem offerings that simplify their purchase journey. Perhaps more surprisingly, 60 percent of US banks we surveyed said they were likely to form or join an ecosystem.

Major technology vendors and suppliers are fueling the growth by keying their strategies to ecosystem players. They furnish hardware and software for platform building and set up data exchanges (application programming interfaces) for ecosystem partners. The growth of 5G  communications is helping to make interconnections faster and more seamless, while “as a service” cloud offerings have multiplied the ways partners can plug into ecosystems. Advanced technology providers are also providing the tools to manage vast databases and using AI to improve how ecosystems understand and attract customers.

Regulators also may be helping out, as they start to sort through the risks and benefits of a more networked economy. In several regions of the world, regulators are looking at ways to level the playing field between digital platforms and traditional companies. The frameworks emerging from their work could ensure data security, portability, and interoperability for consumers and ecosystem partners.

There is a path for established players to use ecosystems to level the playing field. This path has been opened up by tools that give companies better insight into customers and market niches, allowing them to personalize products as never before.

The lessons of Ecosystem 1.0

These technology enablers and regulatory patterns hold considerable promise for incumbent players looking to play the ecosystem game. No, not every company is going to be an Amazon or a Tencent. The ecosystem strategies that companies pursue will vary in scope and ambition, as they should. But our analysis suggests that the efficiencies and potential of ecosystems are such that even a moderate success built on a moderate budget can lead to measurable gains.

To evaluate the success of existing strategies and operating models, we studied 100 traditional companies that have launched ecosystem strategies. 1 Some companies in our sample have announced plans for ecosystems and provided details of their strategies. While there is a lot of activity across this group, few incumbents have achieved significant financial gains. About half have merely started experimenting with ecosystems, perhaps via a low-risk experiment or cross-sector partnership. Some 40 percent have gone far enough to gain customer traffic and clear a viable path to meaningful economic impact. No more than 10 percent of incumbents have established ecosystems that have gained sufficient scale to deliver 5 percent or more of company revenues (Exhibit 2).

The fact that relatively few incumbents have registered big gains may not be surprising. All these companies began in the nondigital world, and most have been experimenting with ecosystems for only a few years. As they do, many encounter organizational hurdles in addition to technological ones. As we dug into their experiences, though, we were able to carve out four lessons from Ecosystem 1.0.

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Lesson 1: go deep or go home.

Going deep does not mean that every incumbent should make a bet-the-company move into organizing or participating in an ecosystem. It does mean that companies should understand the complexities and unfamiliar opportunities that ecosystems present. Many companies are constrained by their own incrementalism. To protect existing lines of businesses, they think small. But the very reason ecosystems exist is to mobilize and incent diverse participants to collectively address the end-to-end needs of consumers.

Doing so requires deep strategic thinking about the key touch points along relevant customer journeys. It means probing value chains for areas where smart shifts can drive big improvements, the way Amazon revolutionized customer experience with one-click shopping and one-day delivery. Even if your company’s participation and investment in an ecosystem are small, your thinking about the customer journey must go deep.

Lesson 2: Move strategically, not conveniently

In launching an ecosystem, incumbents too often covet revenue pools that are on the doorstep of their core businesses. They believe that making small, intuitive moves, such as adding a few clever features or apps to their website, is sensible and sufficient. For example, one bank buffed up its online-lending app, trusting that design tweaks and an advertising push would lure borrowers from beyond its core lending businesses and geographies. Executives were disappointed: few customers even tried the app, much less used it to secure a loan. Why? Because the app didn’t lower borrowing costs or make interactions easier—two key elements of any ecosystem’s value proposition to customers.

The bank’s team hadn’t thought deeply about what would be necessary to shift new customers to their offering. It never invested in the digital talent or capabilities needed to discern user pain points and deliver products that addressed those problems at scale.

Lesson 3: Partner with vision

We know of many cases where two CEOs, keen on duplicating the marquee successes of digital leaders, launched ecosystem initiatives with a burst of enthusiasm and bold visions of combining forces along value chains or pursuing attractive new markets. Invariably, however, their plans foundered on details such as which points along the value chain the company is best positioned to control versus those that partners should own, how participants could mesh capabilities, or how they will jointly manage the novel operating model of their ecosystem.

This kind of failure to develop a deep shared vision prevented an online advertising company and a financial institution from trying to build an ecosystem with breakthrough potential for both. The advertiser rejected the revenue-sharing proposal, and the financial player ended up spending heavily on a gap in its value chain that could have readily been filled with the advertiser’s analytics skills. Neither company had a clear notion of how pooling their expertise would bring in additional customers or revenue. Nor, perhaps, did they share a convincing long-term vision of where their market was headed, a vision that would clarify who would do what while lowering perceived risk for the rest of the potential participants they would need to fully build an end-to-end offering for customers. As a result, both companies failed to expand from mere regional players to national powers.

Lesson 4: Clear the path to impact

Some incumbents do the hard work of deliberating carefully about where to play along horizontals and verticals, assemble all the necessary capabilities for the task, and yet fail to achieve scale or meaningful financial returns. One reason this can happen is that companies don’t get the organizational model right, which itself represents a failure to integrate the lessons of experiments and trials of Ecosystem 1.0.

Here’s what can go wrong inside the four walls of your company: functions or business units may resist change because they aren’t persuaded of the potential value; incentives aren’t tailored to nurture ecosystems; data are siloed; leaders aren’t role models who mobilize change. Ecosystems require strategic and financial foresight, but to succeed they also require careful design and governance planning within the organization to serve the new ecosystem approach.

In the emerging world of Ecosystem 2.0, data are the holy grail, the breakdown of sector borders is a given, and successful players try to lock in control points to expand horizontally and vertically across the grid.

The principles of Ecosystem 2.0

When embarking on ecosystem strategies, many companies use standard frameworks to determine which new revenue pools to pursue. As a result, they rarely look beyond the obvious adjacencies. What’s needed for the evolving world of Ecosystem 2.0, however, is a holistic approach guided by the following three principles:

Use strategic mapping to identify control points. Holistic ecosystem strategies spring from a top-down view of the potential span of impact, as well as a nuanced approach designed to nurture multiple initiatives by the many players participating in an ecosystem. The first step, whether you are organizing or participating in an ecosystem, is mapping against your existing business the horizontal and vertical dimensions of the large ecosystem in which you operate or would like to operate. The map will illuminate “control points,” or places on the map where the company could maximize impact on the value chain by deploying or attracting the right capabilities into the ecosystem. The map will also reveal how far removed your business is from these control points. Companies that find themselves closer to a control point might look to organize an ecosystem around it. If they find themselves further away, they might look to move closer or choose instead to participate in ecosystems formed by more natural owners of a given control point.

In general, control points are where capabilities can best be deployed to remove pain points and smooth the course of customers’ journeys. Mastery of one or more of these control points provides the base for horizontal and vertical moves that can propel your company into new sectors, new sets of customers and business partners, and even new businesses.

Lock in impact with precise capabilities. Mapping is a forcing mechanism for prioritizing control points. Companies that want to create value from the control points they have identified must then assemble and attract the capabilities needed to improve customer journeys. To do so, they may have to invest in reworking and tailoring existing capabilities, or they may need to attract partners that can fill the gaps. The elements that incumbents often lack are advanced digital skills such as AI, functional know-how such as digital marketing, high-level supply-chain and logistics skills, and innovation capabilities to increase the value of products and services. As we mentioned, tech companies have made it easier than ever for incumbents to find appropriate partners to deliver such digital expertise. Articulating the right vision for where the market is headed, combined with creating a platform that, by lowering interaction costs and boosting learning, lowers the investment costs for other companies, helps make the whole greater than the sum of its parts and promotes distributed innovation.

Locking in impact with appropriate capabilities at these control points is how ecosystems and the companies in them extend their reach and create value. Successful companies work on control points with focus and intentionality to align ecosystems precisely with what customers want and expect—and to attract into the ecosystem the partners they need to accomplish that.

• Design the organization for many participants and customers. Successful ecosystems are designed to win market gains and create value for all participants. That’s certainly what investors want to see. But companies that intend to orchestrate or participate in ecosystems must balance a tricky set of issues both within and beyond their own boundaries. Internally, they have to find the right organizational model. Here, companies typically err by going to extremes. One extreme approaches too narrowly, through an organizational silo—say, tackling the entire housing ecosystem through the department or function that works on mortgages. In this model, capabilities will be lacking, and achieving scale difficult. At the other extreme, companies use the venture-capital model to buy companies they think are needed, such as technology-platform providers, and then struggle to integrate the acquisition with their current capabilities, go-to-market approaches, and data systems. The right model will fall somewhere in the middle, tailored to both internal and market context.

Externally, orchestrating companies must encourage collaboration, in part through transparent sharing of data, in part by being careful to leave value on the table for all participants (rather than hoarding all of it), and in part by thinking through and designing mechanisms for dispute resolution and the cross-ecosystem learning that collaboration enables. Particularly for companies in the orchestrator’s position, success requires protocols and designs from which all participants benefit and profit. That includes benefiting customers, of course, which is perhaps the most difficult piece of all. One financial-institution CEO girding for the challenge told us, “We proved we can do this for 20,000 customers. Now we need to scale it to 20 million.”

Ecosystem 2.0 in action

In theory, participating successfully in ecosystems or orchestrating them can sound like a high-wire act. In practice, it may not feel as daunting. Let’s look at the experiences of three incumbents that successfully applied the principles from the previous section.

Mastering control points

At one global bank, leaders decided they would finally confront a problem that had bedeviled them for years: how it could better serve the small-business market. A marketing push and the addition of a small-business area to their well-regarded website had done little. Executives realized that if they were ever to make a successful horizontal move into a market crowded with sophisticated competitors, they needed a much better understanding of the needs of small-business customers. They assembled a team from business development and lending operations to map out small-business journeys and identify the biggest pain points. The much-needed exploration returned valuable discoveries. The team found that their traditional value-chain strengths, which served large corporate clients well, were a poor fit for small-business owners. But their efforts did identify two potential control points: small businesses needed help initiating new business propositions and managing their ongoing businesses effectively.

Bank leaders took an Ecosystem 2.0 approach to the problem. To get an edge in the first control point, they went outside to partner with a company specializing in company registration and launch-related services. But for the second control point—delivering targeted services to help improve business administration—the team found that they had many of the relevant assets and expertise in-house. Senior management authorized a substantial investment to ensure that this in-house group could deliver a set of distinctive small-business services. The team then forged a partnership between an outside invoicing and accounting-services player and an in-house design team to integrate its partnership offerings with its existing banking services.

When it had armed itself with substantial services at critical small-business control points, the bank tested its offerings in a small market and quickly began attracting new customers. Top leaders authorized the significant investment needed to scale the new business line, sweetened the revenue-sharing agreement with its partner to secure this critical alliance, and approved plans to further develop the nascent ecosystem.

In theory, participating successfully in ecosystems can sound like a high-wire act. In practice, it may not feel as daunting.

Reworking the value chain

An industrial-products manufacturer faced new global competition and slowing growth. During a yearly strategic review, senior leaders asked the strategy team whether there were opportunities along its value chain that could capitalize on the company’s sizable base of loyal customers. The manufacturer’s products were equipped with sensors to create data to evaluate performance, which supported an existing after-sales service business. Strategists reasoned that there might be additional control points to exploit and, in collaboration with marketing and sales, discovered that many of its customers were relatively inexperienced in leveraging data analytics to guide businesses decisions and were eager for better insights. The company decided to offer its own data-analytics services, and it set about creating an ecosystem of partners who could make that happen.

The central challenge was combining the company’s proprietary data from equipment sensors with outside data and number-crunching skills. To add a macro lens, the company teamed up with a well-regarded forecaster of economic and industrial business conditions. It partnered with a start-up and a large global transportation company that both had expertise in AI-backed logistics. It brought in another promising start-up that used AI to generate B2B end-customer insights for buyers of its industrial gear. This cobbled-together data-services business delivered significant share gains in its very first year, helped defer a planned move into the space by a major digital player, and attracted users beyond the company’s core product lines. The company eventually partnered with a global manufacturer to expand into new niche markets.

From vertical to horizontal

An emerging-market bank had successfully expanded into several new segments. Wherever it went, the bank had a commanding ecosystem control point: thanks to its superior analytics capabilities, it could introduce seamless digitized banking journeys that were very popular. With strong brand recognition across its markets and an increasing number of customers reaching middle-class status, the bank’s top leaders decided the time had come to exploit that control point horizontally. Believing that their proven platform might attract customers in other sectors, they led a mapping exercise looking at consumer journeys in sectors well beyond traditional banking and finance. Combining that research with analytics that discerned purchasing trends among its banking clients, leadership decided that a bold lateral move into e-commerce, travel, food and dining, and even health services might pay off.

They had no illusions about their own organization; they knew it lacked the entrepreneurial capabilities for such an effort. So they set up a new entity to build and manage a platform that came to include dozens of partners. A few years later, the company is attracting several million customers each month to its nonbanking ecosystem offerings, while its banking and finance businesses have grown rapidly as the ecosystem has expanded.

Just a few years ago, incumbent companies were only awakening to the shifts in competition and organization that ecosystems might bring. Since then, players have accumulated lessons and notched successes. The focus now is on proven practices that lead to scale and improved returns. In the emerging world of Ecosystem 2.0, data are the holy grail, the breakdown of sector borders is a given, and successful players try to lock in control points to expand horizontally and vertically across the grid. Every company needs to be watching this trend closely, since the players that first master the new architecture are likely to capture sizable benefits.

Violet Chung is a partner in McKinsey’s Hong Kong office, Miklós Dietz is a senior partner in the Vancouver office, Istvan Rab is a solution manager in the Budapest office, and Zac Townsend is an associate partner in the San Francisco office.

The authors wish to thank Venkat Atluri, Nicolaus Henke, Vinayak HV, Xiang Ji, Tamas Kabay, Hamza Khan, Nemanja Predojevic, Hamid Samandari, Imre Szilvacsku, and Hugo Tong for their contributions to this article.

This article was edited by Rick Tetzeli, executive editor of McKinsey Quarterly, who is based in the New York office.

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Four Strategies to Orchestrate a Digital Ecosystem

September 09, 2020  By  Nikolaus Lang ,  Christoph Lechner ,  Charline Wurzer , and  Maximilian Dexheimer

There is something sublime about a well-played symphony. The woodwinds and the strings, the brass, and even the percussion hang so well together, offering a leading tone, a moment of emphasis, or complementary counterpoint and harmony. It’s easy to get lost in the sweep of the composition and simply overlook the orchestrator who made it possible. This leader painstakingly coordinated the mélange of disparate sounds and timbre from each section, arranging them into a cohesive whole. In many ways, these orchestrators are the difference between coherence and failure.

The impact of arranging symphonic ensembles to produce a rich and desirable outcome has an apt analogy in today’s digital ecosystems. Consider a vacuum cleaner manufacturer collaborating with companies that make sensors, cameras, and AI software to produce a fully autonomous smart vacuum robot. The small ecosystem of companies responsible for this feature-rich vacuum cleaner creates a popular product, but the ecosystem’s value is limited (like a single section in an orchestra) if it is not integrated into a larger platform-based ecosystem (with other instrument families). In this case, an orchestrator is needed to integrate the vacuum with a smart home platform that combines disparate household electronics into a single network.

• The Emerging Art of Ecosystem Management
• What Does a Successful Digital Ecosystem Look Like?
• How Chinese Digital Ecosystems Battled COVID-19

There are numerous well-known orchestrators managing platform-based ecosystems engaged in social media, e-commerce, transportation, banking, and even mining. These include tech leaders Google, Amazon, Facebook, and Apple, as well as longer-established companies, such as Maersk and Cisco. And there are many emerging leaders among new startups, including the Switzerland-based credit platform MoneyPark, and GlobalSpec, a US-based information platform serving the engineering, industrial, and technical communities.

In the realm of digital platforms, orchestrators are the pivotal players.

In the realm of digital platforms , orchestrators are the pivotal players and therefore stand to gain significantly as platform-based ecosystems increase market share and eat into the profits of traditional companies. Still, while many companies participate in platform-based ecosystems—approximately 40% of the world’s top-30 highest-valued brands and 70% of startup unicorns—few have been able to reap the benefits. Orchestrators often face challenges with scaling the ecosystem, expanding it beyond its initial use case, or simply with monetization and value extraction.

There are ways, however, to overcome these challenges. And orchestrators that do this successfully will gain from embracing and leading a digital business model built upon a platform, while also ensuring that ecosystem partners (call them “complementors”) benefit, enhancing the scope and attractiveness of the ecosystem. What follows is a step-by-step strategic guide for orchestrators, which will help them grow their platform-based ecosystems, attract and retain partners and customers, and maximize their share of the pie generated by the digital ecosystem. (See Exhibit 1.)

Step One: Grow the Platform

The first step is to expand the ecosystem by increasing the number of complementors on the platform and widening the user base. Orchestrators can grow existing business by using network effects. These players can broaden their reach by moving into adjacent areas.

Stimulate network effects . Leveraging network effects is the most potent method for amplifying the range and influence of an existing ecosystem quickly. The theory governing network effects is relatively straightforward: new members are attracted to the ecosystem by a growing user base producing more and better content and by a larger variety of product offerings from new complementors seeking to reach these members. The growth, in turn, is exponential. Network effects also function as an entry barrier for potential platform rivals. Studies of the competitive dynamics of platform-based ecosystems suggest that it is extremely difficult for challengers to topple established, dominant ecosystems that have strong network effects in place.

There are two ways for an orchestrator to build up a critical mass of users and complementors in a short span of time. First, orchestrators can deploy pricing strategies, subsidizing one side of the ecosystem (customers or complementors) with sharp discounts in the hopes of enticing the other side to participate. For example, many recruiting platforms, including the popular German site Monster, charge hiring firms to place ads, but they are free for job seekers because these platforms benefit from a large talent pool. When e-commerce giant Alibaba launched in China in 1999, it faced intense competition from incumbent players like eBay. To attract businesses to its platform, Alibaba did not charge membership fees to Chinese merchants, and its marketplace, Taobao (a C2C e-commerce platform), still doesn’t. Instead, Taobao makes money by taking a percentage from sales, advertising, display marketing, and storefront services.

Second, an orchestrator can use “smart” marketing, through which specifically designed algorithms are used to drive relevant buyers or sellers to the platform. SkinVision, a Dutch skin cancer detection platform, is a good example. To use it, a person takes a photo of a potentially cancerous spot on their skin, which the app then analyzes and—within 30 seconds—suggests a level of cancer risk based on a comparison with millions of other skin images in the company’s database. On the strength of its algorithm, SkinVision has been able to expand its platform’s reach to more than 1 million users globally.

Expand into adjacent markets . Another option for expansion is to offer adjacent (usually complementary) offerings to new and existing users.

Some companies choose to develop adjacent products or services organically. Meituan, a Chinese firm that debuted as a Groupon company in 2010, leveraged its existing user base to move into food delivery and hotel reservations in 2013, and into ride-hailing in 2017. Alipay, which began as an online payment service, has since offered its customers wealth management services, insurance, consumer lending, and credit score reviews.

Orchestrators may instead decide to acquire an adjacent ecosystem.

Orchestrators may instead decide to acquire an adjacent ecosystem. Facebook’s purchase of Instagram in 2012 was a natural step into a new social network sector. Sharing photos (and the stories behind them) on a smartphone-driven platform wasn’t the tech giant’s forte, but Facebook had a huge number of engaged subscribers, a robust engineering team, a global web-based infrastructure, and a strong financial backbone, all of which could support Instagram’s growth trajectory. Indeed, Instagram’s user base has ballooned to more than 1 billion today from 30 million at the time of the acquisition.

Step Two: Improve the Platform

In a competitive environment, a platform can only prosper if it is maintained at the highest level of quality. This means that a platform must be technologically sound and persistently innovative—using technology to respond to the needs and preferences of its users and complementors.

Provide best-in-class functionality and services . From a technical standpoint, platform quality depends on reiterative innovation targeted at achieving the highest standards for speed, information-processing capacity, and frictionless interfaces with other relevant platforms. These benchmarks can serve as a foundation for an orchestrator to add advanced features and functions to improve the platform’s overall experience.

As an example, tech-savvy Alibaba describes its mission as, “make it easy to do business anywhere.” The company has accordingly added multiple services over time to support its merchants and to make online shopping seamless for merchants and consumers alike. For one thing, Alibaba has moved into logistics services through its Cainiao Network to improve delivery proficiency, especially during high-volume periods like the “11.11 Global Shopping Festival,” held in China in November. Alibaba has also expanded its cloud-computing offerings to ensure consistently high site-service levels at a relatively low cost. Additionally, the platform is offering a full suite of technologies and tools, such as livestreaming, short videos, and interactive games, to help merchants reach Chinese consumers in an appealing way.

Decide on an open or closed structure . Orchestrators may choose one of two technical approaches to attract the right type, number, and quality of complementors: open or closed interfaces, with the level of openness measured by access to the ecosystem and its relevant resources.

In certain platform-based ecosystems, quality depends on having uniquely reliable complementors on the platform. When that’s the case, a relatively closed structure is the right choice. This is true, for instance, in Cisco’s smart city and smart mining platforms, on which a network glitch or mishap could have disastrous consequences. Thus, to ensure the safety and security of its platform services, Cisco uses a stringent vetting process for complementors and limits the number of companies able to participate on the platform.

By contrast, platforms that decide on a more open approach are often interested in encouraging many partners to join to boost customer variety and service. Such is the case with Grab, a Singapore-based ride-hailing and food delivery platform, which relies on having many drivers and restaurants in the network to provide an appealing and wide-ranging consumer experience. Grab has adopted an automated system to simplify the sign-up process for new complementors and offers an always-available support hotline to deal with customer issues, freeing up drivers and food outlets to focus on their jobs.

Another reason for having an open-platform architecture could be to encourage innovation that would benefit the entire ecosystem. For instance, in Baidu’s Apollo autonomous vehicle ecosystem, programming and application-development architectures are left virtually unsealed to make it easy for high-caliber partners (including BMW, Intel, and Softbank) to join and accelerate the design of new components, parts, and products for self-driving cars. While the development platform itself is open, the final product, the autonomous vehicle, is heavily protected against cyber attacks.

Create tailored experiences . Orchestrators can use technology to provide a distinctive experience for users and improve the platform’s performance by leveraging “learning effects,” which stem from using advanced analytics to examine user activities and customizing content and recommendations based on people’s specific interests. In turn, this move will increase user activity and provide the orchestrator with additional forward-looking insight into consumer behavior and preferences. Orchestrators that have benefited from network effects to build an enormous customer base can gain particularly from such learning programs.

An excellent example is Netflix, which among subscription-based streaming services has the highest number of paying users in the world and, therefore, the most voluminous and detailed data on user activities. By making specific product recommendations based on this data, as well as demographics and other statistics, and then observing how people react to their recommendations, Netflix can deliver even more precise evaluations. The company can generate better decisions about programming, content development, and subscriber preferences. The combination of network and learning effects enables Netflix to invest more in new productions than its rivals, such as Hulu and HBO, while effectively paying less per hour and per user.

Step Three: Control the Platform

Users and ecosystem partners can be fickle. In many cases, they are seeking high platform quality at the lowest cost, based on such factors as convenience, variety, reliability, and beyond. Orchestrators must be proactive about managing relationships with their customers and complementors to ensure they don’t stray.

Orchestrators must be proactive about managing relationships with their customers and complementors to ensure they don’t stray.

Minimize multihoming . The phenomenon of multihoming entails complementors participating on several platforms simultaneously to provide the best profit potential and largest customer base. Complementors jump between platforms as conditions change. Likewise, users are not shy about switching between platforms that offer the best service or deal. In either case, multihoming is a big problem for orchestrators. It’s commonplace when barriers to ecosystem entry are relatively low, such as in the ride-hailing sector, where passengers generally opt for the provider that offers the best deal and shortest waiting time for a given trip. Drivers are partial to services with the most active customers in the region, and they may actively drive for more than one provider.

Multihoming can result in severe and damaging price wars among platforms, and orchestrators must take steps to avoid this issue.

Multihoming can result in severe and damaging price wars among platforms, and orchestrators must take steps to avoid this issue. The most effective approach is an exclusivity arrangement, which is common in the video game industry. Nintendo, for example, uses strict exclusivity clauses to ensure that certain top game developers only offer their best sellers on Nintendo's gaming consoles. This of course strengthens the Nintendo platform by increasing the size and loyalty of its user base, whose members cannot get these popular games elsewhere. It also lessens the need for developers to adapt their games for multiple platforms.

Another way to reduce the effect of multihoming is to incentivize complementors to remain highly active on the platform. For instance, orchestrators can offer gift certificates or additional services to ecosystem participants that achieve certain sales targets. A similar program can also be set up for users.

Own the value chain . An additional threat to ecosystem loyalty is disintermediation—that is, complementors and users connecting directly after their first interaction, bypassing the platform and thus depriving it of income from future transactions. Platforms that provide handyman referrals, physical services (such as cleaning, gardening, and the like), and the exchange of used goods are among the most likely to be affected by disintermediation. They are particularly vulnerable because the lion’s share of their transactions involves offline interactions, allowing users and complementors to develop a relationship outside of the platform and make alternative contact and payment arrangements.

Protecting against this practice isn’t easy. One method would be for an orchestrator to provide services that add value to the transaction, which users or complementors will find appealing. Another approach involves using technology to make it impossible for buyers and sellers to communicate directly. Airbnb does both. It offers insurance and other protections to hosts that would be forfeited if they dealt directly with customers. Airbnb routes all contact between the two parties exclusively through the platform until a transaction fee has been paid.

Step Four: Maximize Ecosystem Monetization

Although an ecosystem is made up of partnerships (albeit a loose set), of all its participants, orchestrators have the most to gain or lose. They make the most substantial financial investment and allocate significant resources to ensure the platform’s survival and growth. Naturally, they would be seeking ways to enhance their share of the profits generated by the platform. Four actions for improving platform monetization stand out as the most effective (see Exhibit 2):

• Increase fees . Generally, such increases are only effective when linked to new ecosystem features or when complementors are bound to the platform because there aren’t any others on which they could market their offers successfully. Orchestrators should raise fees when complementors would incur switching costs (from the technology adjustments needed to go elsewhere) or the services provided by a competitor platform are significantly inferior. Apple has been able to charge developers both an annual fee to access the iOS ecosystem and a commission on every app sold—all while raising its rates more frequently than its rival Android—thanks to its loyal, higher-spending users.
• Encourage competition among complementors. Give technical support and incentives to ecosystem partners or would-be partners for the development of highly competitive applications on the platform. This step would result in more and higher quality offerings, which in turn render the platform more attractive to consumers, driving greater hardware and software sales and allowing the orchestrator to enjoy an ever-expanding revenue pool. Both Apple and Android have adopted this approach, providing promising app developers with free advertising (for instance, a listing in their top-ten charts), an early rollout of new features, and greater technical assistance.
• Compete with complementors. By moving into the product space of its complementors, orchestrators can squeeze the complementors out and take their share of revenue. One example is Twitter’s acquisition of Periscope, an app that enabled Twitter users to broadcast live video streaming to their followers. After Twitter integrated Periscope into its services, all other third-party offerings with similar functions were pushed off the Twitter platform. This tactic is only advisable when the orchestrator can increase revenue by replacing a complementor or complementors without diminishing the breadth and attractiveness of the platform to users and other members of the ecosystem.
• Drive cross-selling. Orchestrators can drive additional platform sales through cross-selling and upselling to existing users. In order to do this effectively, orchestrators must understand the needs of users in near real-time and make relevant recommendations based upon this understanding. Amazon has been using powerful and complex algorithms for over two decades to provide its customers with helpful and relevant product recommendations based on previously purchased and rated products. This system has historically generated approximately 35% of Amazon sales. In a similar fashion, Toutiao, the news and information content platform from ByteDance, has employed algorithms to analyze users’ content preferences to produce customized lists of additional material that they might want to explore. With this service, ByteDance is now second only to Alibaba in China in user time and advertisement revenues.

Overall, the relative interdependency between an orchestrator and its complementors generally determines the distribution of profits.

Overall, the relative interdependency between an orchestrator and its complementors generally determines the distribution of profits. If an individual complementor is central to the success of a platform, it will accordingly demand and receive a higher-than-average share of added value. However, if the platform is not dependent on "star" complementors, but instead is able to support a broadly diversified offer, orchestrators can retain most of the profits while the complementors receive less—but still enough to stay engaged.

The Way Ahead

Virtually every industry has been digitized due to the emergence of a wide variety of digital platform-based ecosystems. By now, companies see the value of these partnerships, which provide users a broader palette of services and products under one digital roof. But despite knowing the potential of platform-based ecosystems, orchestrators often struggle to scale, cultivate, fully monetize, and expand them so that all participants can benefit. And in the end, many platforms fail to reach their potential, especially as the competition among ecosystems heats up.

Solving this problem is not easy, but it is essential for executives. The strategies shared here outline a pathway to begin to turn struggling platforms into profitable businesses. The role of the orchestrator, however, is crucial. The quality of the orchestrator’s leadership, ability to forge successful collaborations, and creativity will ultimately determine whether an ecosystem is harmonious and successful, or otherwise out of tune.

For more on this topic, please see the following:

Zhu, F., Iansiti, M., “Why Some Platforms Thrive and Others Don't” (Harvard Business Review, 2019).

Dexheimer, M., Lechner, C., “Ökosystem-basierte Wettbewerbsstrategien” (Die Unternehmung, 2019).

Eisenmann, T., Parker, G., Van Alstyne, M., “Platform Envelopment” (Strategic Management Journal, 2011).

Jacobides, M., Lang, N., Louw, N., von Szczepanski, K., “ What Does a Successful Digital Ecosystem Look Like? ” (BCG, 2019).

Lang, N., von Szczepanski, K., Wurzer, C., “ The Emerging Art of Ecosystem Management ” (BCG, 2019).

Ozalp, H., Cennamo, C., Gawer, A., “Disruption in Platform‐Based Ecosystems” (Journal of Management Studies, 2018).

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Digital Ecosystems: Principles and Semantics

2007, 2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference

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We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures (EOA) where the word ecosystem is more than just a metaphor.

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Digital Ecosystems Essay

• Author: arsalan
• Posted on: 24 Aug 2019
• Paper Type: Free Essay
• Subject: Business and Finance
• Wordcount: 1378 words
• Published: 24th Aug 2019

Digital Ecosystems models help in co-creating, capturing, and distributing value in businesses. They base and reorganize the ancient ecosystems removing the limits of geographical proximities and providing tools for cross-system collaborations. Firms that have transformed to use digital systems enjoy the comprehensive, rich knowledge and offer excellent solutions to their customers’ needs. Structuring digital ecosystems have won immense attention from researchers due to its applicable strategic significance. The streaming has assisted many firms to gain vital insights, more so on leveraging the IT/IS abilities to reconstruct business and technology ecosystems, and other types of the systems. Although the ecosystems can fail at times, they provide invaluable aids in running the businesses.

The diverse ecosystems have effects on the co-creating, capturing, and distributing value in and outside digital ecosystems. This digital fusion with the technological inventions change the ecosystems and transform the business landscapes. It is such an alignment that we will be reviewing in this paper, commonly referred to as conglomeration of digital ecosystems. These ideas have been discussed in the article we are examining here in, The Formation Process towards Conglomeration of Digital Ecosystems: A Hybrid Organizing Perspective by Wenchi Ying and Suling Jia. The duo conducted a three-phase study to unveil the hybridization mechanisms of combining the traditional, emerging, and the future strategies on IT/IS to bring a large and diverse ecosystem in action.

The analysis herein will comprise of an introduction then critically review the mentioned article above. Afterward, it will examine three articles referenced in the cited paper, which enrich the paper with related content. Also, it will review the literature to elucidate research gaps identifies in this area. These gaps open for further research.

Keywords: Ecosystems, conglomeration, hybrid organizing,

Critical Review

The scope of the article.

Merging the traditional, emerging, and the future issues in IT/IS in the business environment lay the foundation for Ying and Jia’s work. They also focus on hybrid organization in a theoretical aspect. The article conceptualizes on aligning and combining the ecosystems referring to conglomerations of digital ecosystems.

Business, Technology, and Digital Ecosystems

Business ecosystem emphasized efficiency and flexibility of the relevant sources to co-create a thriving economy. It is the central coordinator for the products and structures of ecosystems. The technology/industry ecosystem focuses on innovations and the external benefits of the sources and the products. It is the product platform which defines the relevant components and products in the business world. The digital ecosystems thrive on fusing the relations between business and industrial technologies from various resources. Ying and Jia in their article define the digital conglomeration as the fusing between companies and industrial technologies from varied resources and IT/IS capabilities. They argue that it is a collective inter-link between the stakeholders with shared interests in an interactive environment. The pair claims that conglomerating systems break the geographical proximity bounds and advocate for cross-system collaborations. Once the stakeholders have secured the collective activities, it gives an intelligent approach to align to ensure operations for a holistic ecosystem. Digital ecosystems bring into line with single, multiple, and diverse ecosystems. Firms should deal with digital boundaries and compatibility challenges to make a distinct organization.

Hybrid Organization towards Digital Ecosystems

A hybrid organization is combining several organizational structures to improve the quality of services provided. However, not all elements in the organizational structures are compatible. Incompatibility may cause tension and strain in the hybrids in the process of combining mutually conflicting procedures and practices required by varied organizational forms in the hybrid contexts. Coalescing regulatory aspects of the locus in innovating and creating new reforms like the digital ecosystems combining diverse ecosystems. The primary research question in the article is: how do the core firms adopt hybrid-organizing approaches in the conglomeration of digital ecosystems?

Nevertheless, hybrid organizing comes with challenges due to the structural elements of numerous forms as diverse ecosystems which are incompatible. The adoption strategies need to address the internal and external forces caused by these hiccups of the structures. The duo consolidated the four policies of hybrid organizing from the research articles in existences. These are; (1) Dismissal refers to reject the elements or demands of organizational forms explicitly. (2) Separation of refers to the compartmentalization of components or claims from varied organizational structures. (3) Cumulation relates to retention and linkage to different rudiments of organizational forms. (4) Creation refers to the forgery of new idiosyncratic institutional orders.

Research Methodology

The authors used the case research method approach to carry out the study due to three reasons. One, the mode of the research question based on ‘how’ which is best answered via the inductive method. The second one is that the study focuses on building new theoretical models thus the case study is more efficient due to it assertiveness in the exploration of new concepts. Lastly, the case study method works out very well for process-based analysis.

Data Collection

Ying and Jia collected data in two steps. First, they collected data from secondary sources and industry seminars. Collecting secondary data on adopting digital ecosystems concepts and hybrid-organization perspective guided them for the subsequent on-site data collecting and analysis. Secondly, they collected data from RCG’s headquarters and its factories via telephone interviews for nine months. They embraced the top-down interview procedure where they gathered data from 25 interviewees. They recorded the interview digitally then transcribed it.

The researchers studied the Red Collar Group (RCG) where they interviewed the executive management down to the subsidiary workers totaling to 25 informants. One interview lasted between 50 and 120 minutes comprising of customized questions. RCG has its headquarter in Qingdao Shandong, China with about 3,000 staff members. It produces individualized and personalized suits, apparels, and accessories to the international market. RCG has embarked on digital transformations and innovations journey for ten years before acquiring necessary competencies in the digitally personalized production of suits. RCG came up with a novel digital platform and business models which they termed as C2M model (Customer-to-manufactory). The model helped in integrating customers, sales, suppliers, designers, former competitors, and producers. The study’s focus question was, by far RCG has conglomerated digital multi-win ecosystems, how did they achieve this?

RCG built the digital infrastructures to exploit internal systems of personalized and customization of suits. This was achieved by integrating diversified stakeholders and the related resources to minimize the complexities and costs of customization. They also delivered digitals solutions for the exploration od consultation services to the external stakeholders. Such assisted in popularizing RCG as the role model of smart productions in China. Lastly, they leveraged the digital platform to conglomerate the internal and external stakeholders

Additional references

Literature Gaps

Although Ying and Jia achieved their objectives by presenting the ideas on conglomeration and hybrid organizing, they left some issues unsolved. The human beings’ interactions with computers should not overshadow the interactions with other aspects of production in a study. It is thus crucial that each research applies realistic settings with minimal hitches.

For instance, the use of the representative sample of 25 informants to represent the other 3000 staff is misrepresentative. It is impractical to generalize the findings to other large companies without conducting a more significant sampling. For quality research, at least 30 people give a better representation. Those embarking on future research must find out how and why managers interact with the digitalization and hybrid organizing. The analysis should also incorporate the theoretical generalization approach for better findings. Since Ying and Jia are dealing with digitalization, they should have included some cognitive ideas in the models to assist in contextualizing the varied requirements in a better way.

Today, digital firms face disruptive technological progressions in innovating and creating new ideas. In the process of evolving to embrace the reforms, several challenges are met. These, Ying and Jia did not discuss in depths to make the involved companies aware. Several challenges should be addressed from a study and practically. They just mentioned one problem with hybrid organization, which is the incompatibility of the organizational structures. They did not give a glimpse of the trends in technology and the visionary scenes.

Ying and Jia tend to have overlooked the fact that, RCG walked the journey for ten years before achieving their goals in a conglomeration of the digital systems. The duos did not explain to us why to take such a long route in attaining this yet there can be shorter ways. What these two authors did not tell us is that background and experience are critical factors in achieving the goals. Echoing Green brings out these aspects out in an elaborate way in his article where he presents the research findings on hybrid organizing issues. The research sampled 700 responses to carry out a survey. He states that background and environment coerces one into the adoption of particular ways of thoughts and internalization of specific values dominating this specific environment.

Green also discusses how the educational background exposes an individual to particular content that he or she internalizes and makes the necessary actions. With work experience, he elaborates further by arguing that it creates hybrid social ventures rather than the traditional nonprofit ones. Experience makes one incorporate the social enterprise into the business’ errands. According to Lee and Battilana (2014) people who stay in one organization type for long become rigid in their ways of thoughts regarding organizational possibilities.

It is evident that the diverse ecosystems have effects on the co-creating, capturing, and distributing value in and outside digital ecosystems. Hybrid organization in a theoretical aspect which conceptualizes on aligning and combining the ecosystems referring to conglomerations of digital ecosystems. The conglomeration involves the merging of ecosystems to come up with one. The mergeable ecosystems include the business, technological, and the digital ecosystems. Firms should deal with digital boundaries and compatibility challenges to make a diverse organization. The hybrid organization is combining several organizational structures to improve the quality of services provided. Conglomerating systems break the geographical proximity bounds and advocate for cross-system collaborations and advocates for cross-system collaborations. The hybrid organization is combining several organizational structures to improve the quality of services provided. Not all elements can be conglomerated into the structures of interest. Incompatibility is the source of tension and strain in hybrid organizing. Its challenges arise due to the structural factors in the diversified ecosystems. The strategies adopted in addressing these internal and external forces help in solving the challenges.

Ying and Jia, in their article they carried out a case study on Red Collar Group (RCG) where they carried interview using the top-down approach. Its headquarters are in Qingdao Shandong, China with about 3000 staff members. It is taken the RCG about ten years to acquire the needed competencies in digitally personalized productions of suits.

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Mapping Antitrust onto Digital Ecosystems

By cpi | may 9, 2024.

The assessment of “ecosystem power” has come to occupy centerstage in antitrust cases involving large digital firms, as regulators are finding traditional market-by-market analysis increasingly inadequate to capture how competition…

The assessment of “ecosystem power” has come to occupy centerstage in antitrust cases involving large digital firms, as regulators are finding traditional market-by-market analysis increasingly inadequate to capture how competition works between firms holding multiple “assets and capabilities”. While antitrust economics is lagging behind in developing usable tools for the analysis of “ecosystems”, this is an established and growing area of study for strategic management and business

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PYMNTS’ latest report on  paycheck-to-paycheck consumers Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. sources. Cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

This is a part of the fact This is a bold part of the fact AS OF FEBRUARY 2023

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Drill down a bit, and our research found that 23% of consumers overall had side jobs, and 30% of these consumers with issues paying their bills have embraced additional employment. The extra income runs into the billions of dollars, as seen in the chart below, where tips and gratuities run nearly $12 billion. Informal tasks might conceivably fall within the confines of gig economy work, too — one-off jobs that might be found through online platforms and sites that match supply and demand, though not on a dedicated, hourly setup.

Methodology

This is an example where you can call out text in a circle. consumers conducted from Feb. 7 to Feb. 23, as well as analysis of other economic data. The Paycheck-to-Paycheck Report series expands on existing data published by government agencies, such as the Federal Reserve System and the Bureau of Labor Statistics, to provide a deep look into the core elements of American consumers’ financial wellness: income, savings, debt and spending choices. Our sample was balanced to match the U.S. adult population in a set of key demographic variables: 51% of respondents identified as female, 31% had college educations and 36% declared incomes of more than $100,000 per year.

If paycheck-to-paycheck consumers are bringing in billions of dollars from these side gigs, and a significant percentage of these households are depended on these active forms of income to help offset the monthly struggle of making ends meet, any turbulence in the gig economy will have negative ripple effects.

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Separate data from PYMNTS and LendingClub show that consumers are recalibrating their spending, and reconsidering discretionary vs. essential expenses. In a few notable examples, we’ve found that among grocery shoppers who say they have noticed price changes, 59% have cut down on nonessential grocery items, while 35% are buying cheaper alternatives. And, as seen here , consumers think that restaurant prices are as much as three times higher than inflation.

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These are areas where it would be “low hanging” fruit to cut back on delivery, which in turn cuts back on demand for orders across platforms such as DoorDash, which lessens the need for drivers … you get the picture. What winds up happening is that tip volumes, and the delivery work, itself, face headwinds.  Companies such as Instacart are broadening their business models to expand their addressable markets (in this case, to boost its business clientele).

We note that, depending on where you look, freelance demand in other areas is volatile, too. Fiverr’s recent results showed only slight growth in clients hiring the talents of gig workers, though spending across that client population is up.

CEO Micha Kaufman made note in remarks on the analyst conference call that the macro challenges resulted in “headwinds to overall freelance demand.” All, told, in the most recent period, Fiverr has said that active buyers (who buy gig services from “sellers”) were 4.3 million. That was up 1% year over year, according to company materials. There are, of course, pockets of notable growth in the gig economy.

In one example, Uber has said in its most recent results that active mobility drivers also reached an all-time high in Q4, up 35% year on year — 5.4 million people are earning across the platform on a global basis and growth had been continuing into 2023.  CEO Dara Khosrowshahi said that 70% of drivers are coming onto the platform to earn money to help combat inflation. PYMNTS’ gig economy app provider rankings released just last week show that Uber has remained the most popular app in that pantheon.

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https://www.nist.gov/news-events/news/2024/05/chips-america-announces-285-million-funding-opportunity-digital-twin-and-0

CHIPS for America Announces $285 Million Funding Opportunity for a Digital Twin and Semiconductor CHIPS Manufacturing USA Institute

Today, the Biden-Harris administration issued a Notice of Funding Opportunity (NOFO) seeking proposals from eligible applicants for activities to establish and operate a CHIPS Manufacturing USA institute focused on digital twins for the semiconductor industry. Digital twins are virtual models that mimic the structure, context and behavior of a physical counterpart. The CHIPS for America Program anticipates up to approximately $285 million for a first-of-its-kind institute focused on the development, validation and use of digital twins for semiconductor manufacturing, advanced packaging, assembly and test processes. The CHIPS Manufacturing USA institute is the first Manufacturing USA institute launched by the Department of Commerce under the Biden administration.

Unlike traditional, physical research models, digital twins can exist in the cloud, which enables collaborative design and process development by engineers and researchers across the country, creating new opportunities for participation, speeding innovation and reducing costs of research and development. Digital twin-based research can also leverage emerging technology like artificial intelligence to help accelerate the design of new U.S. chip development and manufacturing concepts and significantly reduce costs by improving capacity planning, production optimization, facility upgrades and real-time process adjustments.

“Digital twin technology can help to spark innovation in research, development and manufacturing of semiconductors across the country — but only if we invest in America’s understanding and ability of this new technology,” said Secretary of Commerce Gina Raimondo. “This new Manufacturing USA institute will not only help to make America a leader in developing this new technology for the semiconductor industry, it will also help train the next generation of American workers and researchers to use digital twins for future advances in R&D and production of chips.”

“Digital twin technology will help transform the semiconductor industry. This historic investment in the CHIPS Manufacturing USA institute will help unite the semiconductor industry to unlock the enormous potential of digital twin technology for breakthrough discoveries. This is a prime example of how CHIPS for America is bringing research institutions and industry partners together in public-private partnership to enable rapid adoption of innovations that will enhance domestic competitiveness for decades to come.” —Under Secretary of Commerce for Standards and Technology and NIST Director Laurie E. Locascio

Read the entire news release on the Department of Commerce website.