Free Building Watson: Not So Elementary, My Dear! (Abridged) Case Study Solution | Assignment Help

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Harvard Case - Building Watson: Not So Elementary, My Dear! (Abridged)

"Building Watson: Not So Elementary, My Dear! (Abridged)" Harvard business case study is written by Willy Shih. It deals with the challenges in the field of Strategy. The case study is 17 page(s) long and it was first published on : Oct 22, 2015

At Fern Fort University, we recommend IBM continue its aggressive investment in Watson, focusing on a disruptive innovation strategy to transform its business model. This involves leveraging Watson's capabilities to create new value propositions across various industries, expanding beyond its current focus on healthcare and financial services. IBM should prioritize strategic alliances with key players in emerging markets, particularly in sectors like education, agriculture, and manufacturing, to accelerate market penetration and build a robust business ecosystem. Furthermore, IBM must actively engage in digital transformation initiatives, fostering a culture of innovation and leadership development to ensure the successful implementation of its ambitious vision for Watson.

2. Background

This case study explores the journey of IBM's Watson, a revolutionary cognitive computing platform. The case highlights the challenges IBM faced in transitioning from a traditional hardware and software company to a leader in artificial intelligence (AI) and machine learning. The main protagonists are:

  • IBM: A technology giant seeking to redefine its business model and leverage its expertise to capitalize on the burgeoning AI market.
  • Watson: IBM's flagship AI platform, initially developed for the healthcare and financial services sectors, with potential for broader applications.
  • Industry Players: Competitors like Google, Microsoft, and Amazon, all vying for dominance in the AI landscape.

3. Analysis of the Case Study

To analyze IBM's strategic challenges, we can apply several frameworks:

  • Porter's Five Forces: The AI market is characterized by high barriers to entry due to the need for significant investment in research and development. The threat of substitutes is moderate, with other technologies like cloud computing potentially offering alternative solutions. The bargaining power of buyers is high, as customers are increasingly demanding customized AI solutions. The bargaining power of suppliers is moderate, with access to talent and data being crucial. Finally, rivalry among existing competitors is intense, with companies like Google and Microsoft aggressively pursuing AI dominance.
  • SWOT Analysis: IBM possesses strengths in its established brand, vast research capabilities, and extensive customer base. However, it faces weaknesses in its slow adoption of new technologies and its struggle to adapt to the rapidly evolving AI landscape. Opportunities lie in the immense growth potential of AI across various industries, while threats include increasing competition and the potential for regulatory hurdles.
  • Value Chain Analysis: IBM's core competencies lie in its ability to develop and deploy complex technologies, manage large-scale IT projects, and leverage its global network of experts. However, the case highlights the need for IBM to strengthen its value chain by focusing on product development, marketing, and customer service tailored to the specific needs of AI applications.

4. Recommendations

  1. Disruptive Innovation Strategy: IBM should adopt a disruptive innovation strategy to create new markets and disrupt existing ones. This involves leveraging Watson's capabilities to develop innovative solutions for industries beyond healthcare and finance, such as education, agriculture, and manufacturing. This approach requires a shift in focus from selling software to providing AI-powered services, creating a more value-driven business model.
  2. Strategic Alliances: IBM should prioritize strategic alliances with key players in emerging markets, particularly in sectors like education, agriculture, and manufacturing. This approach allows IBM to leverage local expertise and accelerate market penetration. Partnering with established players in these sectors can also help IBM overcome cultural and language barriers, fostering a more inclusive and globally integrated approach to AI adoption.
  3. Digital Transformation: IBM must actively engage in digital transformation initiatives, embracing a culture of innovation and leadership development. This involves investing in talent acquisition, training, and fostering a collaborative environment where employees are empowered to experiment and explore new ideas. IBM should also leverage social media and other digital platforms to build a strong brand presence and engage with potential customers.
  4. Open Source and Collaboration: IBM should embrace an open-source approach to AI development, encouraging collaboration with the broader developer community. This fosters innovation, accelerates the development of new applications, and strengthens IBM's position as a thought leader in the AI space.
  5. Focus on Emerging Markets: IBM should prioritize emerging markets where the potential for AI adoption is high and competition is less intense. This requires tailoring Watson's capabilities to address specific needs and challenges in these markets, ensuring a more localized and relevant approach.

5. Basis of Recommendations

Our recommendations are based on the following considerations:

  1. Core Competencies and Consistency with Mission: Our recommendations align with IBM's core competencies in technology development and its mission to innovate and drive progress. By leveraging its existing strengths, IBM can effectively capitalize on the potential of AI.
  2. External Customers and Internal Clients: Our recommendations prioritize the needs of both external customers and internal clients. By focusing on value creation and customer experience, IBM can build long-term relationships and foster a culture of innovation within the organization.
  3. Competitors: Our recommendations consider the competitive landscape and aim to position IBM as a leader in the AI market. By embracing a disruptive innovation strategy and focusing on emerging markets, IBM can differentiate itself from competitors and capture a significant market share.
  4. Attractiveness: The potential for AI adoption across various industries is immense, offering significant growth opportunities for IBM. Our recommendations are based on a long-term strategic vision that focuses on sustainable growth and value creation.

6. Conclusion

IBM is well-positioned to become a leading player in the AI revolution. By embracing a disruptive innovation strategy, focusing on strategic alliances and emerging markets, and prioritizing digital transformation, IBM can leverage Watson's capabilities to create new value propositions and achieve sustained growth. However, success requires a commitment to continuous innovation, leadership development, and a culture of collaboration.

7. Discussion

Other alternatives not selected include:

  • Focusing solely on existing markets: This approach carries the risk of being outmaneuvered by competitors in a rapidly evolving market.
  • Adopting a purely defensive strategy: This could lead to stagnation and a loss of market share as competitors innovate and disrupt the industry.

Key assumptions of our recommendations include:

  • Continued growth of the AI market: This assumption is based on the increasing demand for AI solutions across various industries.
  • IBM's ability to adapt and innovate: This assumption is based on IBM's history of innovation and its commitment to investing in research and development.

8. Next Steps

To implement our recommendations, IBM should:

  • Develop a comprehensive digital transformation strategy: This strategy should outline the key initiatives and investments required to achieve a successful transition.
  • Establish a dedicated team to oversee the implementation of the strategy: This team should be composed of experienced professionals with expertise in AI, digital transformation, and strategic planning.
  • Develop a clear communication plan to engage stakeholders and build support for the strategy: This plan should ensure transparency and address any concerns or resistance.

By taking these steps, IBM can position itself for success in the rapidly evolving AI landscape and create a more sustainable and prosperous future for its stakeholders.

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Case Description

This case is set inside IBM Research's efforts to build a computer that can successfully take on human challengers playing the game show Jeopardy! It opens with the machine named Watson offering the incorrect answer "Toronto" to a seemingly simple question during the championship match. Was the answer a reflection of a strategic weakness, or was it actually consistent with design principles established by the development team? The case seeks to expand students' view of the product development process. Traditional software development projects begin with the gathering of requirements and analysis of the problem, and the writing of a detailed specification. The Jeopardy! problem is different-it requires a probabilistic approach where there is no closed form solution. Instead statistical patterns in the data are important and there is no obvious mapping to the way queries are expressed. Such problems are increasingly common in data mining, optimization problems, or Internet applications where the goal is to find an acceptably good solution in a short amount of time, when a deterministic approach might be less fruitful or impractical. We aspire for students to recognize that product development can take many forms, and that these are enabled by creativity and the right organizational flexibility and mindset. This abridged version of the case focuses on the choice of Jeopardy! as the development target, and the approach taken by the development team. The original case is HBS No. 612-017, and has much more detail on the design strategy for the Watson system.

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