The platform ecosystem business model: A blueprint for enterprises. Part 2

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The platform ecosystem business model: A blueprint for enterprises. Part 2

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Platform ecosystems are defined as open or closed networks where an orchestrator mediates relationships between a diverse set of complementary stakeholders. Orchestrators receive benefit from both accrued value in the platform ecosystem and in barriers to entry that ecosystems create for potential competitors. Platform ecosystems are also defined by a collaborative strategy that aims to create value for all stakeholders, including customers, partners, suppliers, and competitors.

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What’s inside

  1. How are ecosystem business models helping enterprises?
  2. How do enterprises mastering ecosystems drive transformational growth?
  3. How to build ecosystem in eight steps
  4. Transformative trends redefined

How are ecosystem business models helping enterprises

Ecosystem business models offer diverse benefits, as described in part one. A brief summary can be found below:

  • Agility and adaptability: Ecosystems can adapt swiftly to shifting market circumstances due to effective collaboration across a broad set of partners.
  • Access to innovation and technology: Diverse set of collaborators enables access to new ideas, technology, and innovation.
  • Improved customer experience: Seamless integration of services and goods provides ease in creating value and results in better customer experience and satisfaction.
  • Cost reduction and operational efficiency: Shared resources, distribution networks, and economies of scale reduce redundancies, create cost savings and optimize operations.
  • Market expansion: Leveraging the reach of a given ecosystem, businesses can increase their total market reach and gain access to new clients.
  • Additional income streams: Ecosystems offer the potential for additional income streams through cross-selling and value-added services. Download Complete Research

How do enterprises mastering ecosystems drive transformational growth?

For enterprises seeking to adopt an ecosystem model, the key factors of success are listed below:

How to build an ecosystem in eight steps

The following are the identified eight steps to develop an ecosystem business model:

Transformative trends redefined

The key trends in ecosystems business models being adopted by enterprises at present are as follows:

  1. Collaboration among competitors: More businesses are collaborating with their rivals to expand their ecosystems.
    Example: Apple and IBM collaborate to create business apps, and General Motors and Lyft collaborate to create autonomous ride-sharing services.
  2. The emergence of consortium-based platform-based ecosystems: Many firms are shifting towards platform-based ecosystems to interact and collaborate with their partners and clients.
    Example: AWS offers a platform for enterprises to host their apps and data.
  3. Increased focus on customer experience: A smooth, intuitive, and appealing customer experience across all touchpoints is a growing area of enterprise focus.
    Example: Apple has created an ecosystem that integrates its devices, software, and services seamlessly.
  4. Adoption of AI and autonomous systems: Automation and AI are used more frequently in business ecosystems to boost efficiency and streamline procedures.
    Example: Siemens leverages AI to instantly improve the operation of its gas turbines within its broader ecosystem.
  5. Rise of open innovation: More enterprises are embracing open innovation to collaborate with external customers, suppliers, and startups.
    Example: GE’s Ecomagination program, which collaborates with entrepreneurs to hasten clean energy technology development.
  6. Emphasis on sustainability and social impact: Businesses are incorporating sustainability and social impact into their ecosystem strategy as ESG becomes more prevalent across enterprises.
    Example: Unilever has a Sustainable Living Plan that aims to improve stakeholder health and well-being and minimize the company’s carbon footprint. Download Complete Research

Credits
Author@lab45: Poonam Pawar
Contributing Author: Hussain S Nayak

Latest stories

Business process services in the era of generative artificial intelligence

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Business process services in the era of generative artificial intelligence

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In today's fast-paced business landscape, staying ahead requires more than just keeping up with the latest trends—it demands innovation. This is particularly true in the realm of BPS, where efficiency, accuracy, and adaptability reign supreme. In our latest special report, we delve into the transformative power of GenAI and its profound implications for the future of BPS.

What's Inside

  1. The current state of BPS
  2. How GenAI can solve current BPS challenges
  3. Quantifying the financial impact of GenAI
  4. How GenAI can transform BPS
  5. Addressing GenAI implementation challenges
  6. How to measure the financial impact of GenAI
  7. Current state of GenAI adoption in BPS
  8. How GenAI may reshape the BPS industry
  9. The future: The GenAI-Enhanced evolution of BPS

In today's fast-paced business landscape, staying ahead requires more than just keeping up with the latest trends—it demands innovation. This is particularly true in the realm of Business Process Services (BPS), where efficiency, accuracy, and adaptability reign supreme. In our latest special report, "Business Process Services in the Era of Generative Artificial Intelligence," we delve into the transformative power of Generative Artificial Intelligence (GenAI) and its profound implications for the future of BPS.

Current state of BPS

We analyze the current state of BPS, highlighting its strengths and limitations. Traditional approaches have undoubtedly improved operational efficiency, but they often fall short in handling complex tasks that require nuanced decision-making and adaptability.

Unlocking solutions with GenAI

Enter Generative AI—a game-changer in the world of BPS. We explore how GenAI offers innovative solutions to longstanding challenges, from streamlining repetitive tasks to enhancing decision-making processes. By harnessing the power of machine learning and natural language processing, GenAI empowers organizations to automate workflows, optimize resource allocation, and drive unprecedented levels of efficiency.

GenAI implementation challenges

Navigate hurdles of GenAI adoption with strategies for data governance, technical integration, and fostering a culture of AI acceptance. Our paper equips readers to overcome obstacles, ensuring successful implementation and maximizing the transformative potential of AI in BPS.

Reshaping BPS

We delve into how GenAI is reshaping BPS as we know it. From revolutionizing customer service with chatbots to automating document processing tasks, the potential applications are limitless. By augmenting human capabilities with AI-driven insights, organizations can elevate their BPS capabilities to new heights, unlocking untapped value and gaining a competitive edge in the process.

Measuring financial impact

But how do we quantify the financial impact of GenAI adoption? We explore this question in detail, outlining key metrics and methodologies for assessing ROI. Whether it is through cost savings, revenue generation, or enhanced customer satisfaction, the benefits of GenAI are tangible and far-reaching.

The future of BPS

Looking ahead, we paint a compelling picture of the future of BPS with GenAI at its core. As organizations embrace AI-driven automation and innovation, we envision a landscape where BPS becomes synonymous with efficiency, agility, and strategic value creation. By leveraging GenAI to its fullest potential, businesses can future-proof their operations and thrive in an era of unprecedented digital transformation.

" Business Process Services in the Era of Generative Artificial Intelligence " offers a comprehensive exploration of the transformative potential of GenAI in the realm of Business Process Services. From addressing current challenges to envisioning future opportunities, this paper serves as a roadmap for organizations looking to harness the power of AI to drive meaningful change and unlock new possibilities. Join us on this journey as we redefine the future of BPS together.

Credits
Author@lab45: Ankit Pandey

Top trending insights

Hey AI, welcome to the team: Emergence of algorithmic enterprise

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Hey AI, welcome to the team: Emergence of algorithmic enterprise

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Do we fully understand what it means to be an AI-enabled enterprise? If a company does give primacy to Artificial Intelligence, what does that company look like? What does it take to be such an enterprise? How does it behave? What does its growth path look like and where is it headed? Who will it take along for the ride, and crucially, who will it leave behind? We unpack it for you here.

What's inside

  1. Transitioning to an AI-enabled businesses
  2. What if we humans stopped designing processes for humans to execute? Would we design processes differently if we had the limitless computing power of an algorithm to execute it?
  3. What becomes of humans in an AI enabled enterprise
  4. How comfortable are you with the Idea of a AI-Coworker
  5. The Algo-xperience

Transitioning to AI-enabled businesses

Companies today will begin their journey by becoming the AI-First Virtual Enterprise, evolving into the Autonomous Enterprise and finally into the Agent-enabled Enterprise

AI is now asserting its place as the cornerstone of the modern enterprise: an engine that brings alive a grand human vision by driving innovation, crafting strategy, and powering execution across every business function. To make this happen we are likely to see gigantic leaps in the way innovations scale up to become disruptions.

This point of view evaluates these disruptions, and distills the insights you need to embrace this oncoming change. Download Complete Research

What if we humans stopped designing processes for humans to execute? Would we design processes differently if we had the limitless computing power of an algorithm to execute it?

Today’s AI executes tasks designed for humans, better than what humans can do. What if, we start designing tasks to be executed by AI.

What becomes of humans in an AI enabled enterprise

We will see a proliferation of new roles that human beings will be required to play in an AI-Enterprise as it evolves. From AI psychologists who understand AI behavior, AI ethicists who guide the ethical aspects of AI behavior, to even AI trainers who train AI in much the same way as we train human apprentices today.

How comfortable are you with the idea of a AI-coworker

On a scale of 1 to 5, how comfortable are you with having an AI co-worker, or even an AI boss? As AI develops personhood, we will need to grapple with these questions as the culture of organizations evolve within the AI-enabled enterprise. This point of view explores this evolution.

Algo-xperience

If humans are hired today based on the quality of their 'work experience', how will AI algorithms be hired in the not too distant future? Enter the 'Algo-xperience' - a quantifiable measure by which you can evaluate one AI agent over another. A tangible metric of their past accomplishments, personality, biases and acquired knowledge. This point of view explores how Algo-xperience will play a role in the AI-enabled enterprise. Download Complete Research

Credits
Author@lab45: Nagendra Singh
Contributing Author: Jishnu Dasgupta

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