Cloud, Watson, & Blockchain: Amalgam Insights’ View of IBM Interconnect

From Pixabay
From Pixabay

Amalgam Insights (AI) recently attended IBM Interconnect under the Social Influencer program with the goal of understanding how IBM is planning to position itself in context of technology market changes, investor demands to increase revenue, and the challenges of embracing innovation as one of the largest enterprises on the planet.

In observing IBM over the past few years, AI investigators have noted in the past that IBM faces the challenge of needing to create billion-dollar businesses just to maintain existing revenue. It is not enough for IBM to create a single startup such as Pivotal or Airwatch that ends up becoming a market leader in analytic application development or enterprise mobility. To drive 80 billion+ dollars in annual revenue, IBM needs to grow enough businesses to maintain pace while simultaneously divesting cash cows and declining margin businesses that are not strategic to future growth. Over the past couple of years, this has meant selling off assets such as Salary.com and semiconductor chip manufacturing (and possibly its mainframe division) while investing deeply into systems and capabilities that will drive upcoming business capabilities.

At Interconnect, IBM provided its vision for upcoming success focused on three areas: IBM Cloud, Cognitive computing services highlighted by Watson, and the promise of Blockchain.

IBM in the Cloud

In 2016, IBM’s cloud revenue was up 35% and constituted $13.7 billion in revenue based on IBM’s Q4 and full year earnings results. This increase reflects both IBM’s deep investment into various aspects of the cloud, including infrastructure, platform, video, brokerage, and security. These investments reflect the need for a Cloud that can support proprietary data that is secure, resilient, and supported in a hybrid manner either to be cost-effective in a public cloud setting or to be protected and dedicated in a private cloud or on-premises as necessary.

AI believes that IBM must accelerate cloud revenue even more quickly and has the opportunity to do so as cloud security, multi-cloud brokerage opportunities, cloud video, and cloud platform opportunities continue to grow. Despite the market share advantages that Amazon Web Services and Microsoft Azure have in cloud infrastructure and platforms, it is easy to forget that it is still early days overall in the cloud computing when one considers the percentage of total enterprise data, storage, and compute that is supported on the cloud compared to dedicated computing. IBM is by no means guaranteed victory, but the next generation of cloud computing investment will be based on the trust and viability of cloud vendors that are able to transfer mission-critical, historical and foundational enterprise computing workloads into the cloud.

IBM Watson – What Is Watson?

IBM has made it clear that Watson and cognitive computing are the future and have perhaps been overeager in branding all cognitive-enhanced software and services as “IBM Watson.” Although this re-branding may provide some level of novelty to more traditional IBM offerings, AI believes that this branding has also been confusing at times and led to the fundamental question: “What is Watson?”

From a practical perspective, AI considers Watson to be several different sets of capabilities.

First, IBM Watson is the complex amalgamation of systems that is custom-built to answer questions and must be trained over time. This is the machine that won Jeopardy in 2011. This version of IBM Watson is the product that finds cancer cures, does your taxes, and answers root-cause questions about your business. However, for this to work, IBM Watson must be trained over time based on the expertise that business experts and large bodies of documentation can provide. Because of this need for training, AI believes that IBM Watson as an answering platform is best supported as a consulting engagement where IBM Global Business Services personnel help enterprises to pursue big challenges.

Second, IBM Watson is also offered in a componentized and service-based perspective as the pieces of Watson used to answer questions are offered as APIs. By accessing the Watson Developer Cloud on Bluemix, developers can access specific APIs that provide natural language processing, visual recognition, personality-based insights, speech to text, and other individual capabilities that can quickly insert machine learning and language-based interaction into any application. AI believes that Watson Developer Cloud is still an underutilized toolkit in general that should be more widely adopted as a shortcut for accessing services that would otherwise be unavailable or require significant primary development.

Third, IBM Watson is also available as a variety of custom-built applications used to support technical use cases such as the Internet of Things and analytics, verticals such as Financial Services and Healthcare, and departmental use cases such as Talent, Supply Chain, and Work/Collaboration. These applications consist of multiple services combined to support a specific type of business need, but can be somewhat confusing in that they are typically designed as self-learning and natural language-based applications that are significantly different from other competitive solutions in these enterprise application markets. This paradigm shift is still a battle that IBM is educating the market on. Although these applications tend to be relatively easy to deploy and use as cloud-based and with a Design Thinking foundation, the enterprise as a whole is still learning how to be curious and adopt a discovery-minded approach to business rather than a top-down approach to tracking business metrics. AI believes that this fundamental paradigm shift will need to take place for IBM’s Watson applications to gain their rightful market share in the enterprise. The change is happening and AI believes that the efficacy of assistants such as Alexa, Cortana, and Siri will help lead to the eventual enterprise adoption of question-based interactions.

So, Watson is not one thing. And IBM has actually been startup-like in its innovation and been ahead of the market in selling Watson. Patience will continue to be a virtue as IBM waits for the market to catch up in figuring out how to take the best advantage of Watson. In the short term, AI believes that Watson’s APIs, SDK’s, and services are the most consumable way for companies to take greatest advantage of IBM Watson. As users evolve and become more savvy in understanding the future of self-learning systems in augmenting businesses, IBM Watson will gain adoption at both the application and solution levels as well.

Getting to Blockchain

At IBM Interconnect, CEO Ginny Rometty was quite bullish on blockchain and the Hyperledger as a way to support distributed and trusted transactions. Fundamentally, blockchain allows users, machines, and assets to conduct remote and unregulated transactions that can still be trusted. This abstraction of trust and defined value for transactions are typically handled today either through clunky “handshakes” that define identity or through a medium such as money used to create a standard quantitative value associated with a transaction.

At Interconnect, IBM shared the story of Everledger, which uses blockchain to track diamonds and insure that they are conflict-free. The same process that allows for the independent tracking of diamonds could also be used for fine art, musical instruments, high-performance computing assets, custom vehicles, and other rare assets that can be pooled together into multi-billion dollar inventories that must be tracked over time and space.

AI believes that IBM’s early launch of IBM Blockchain will allow Big Blue to serve as an early standard for this new transactional standard for providing a controlled environment without having to actively manage the environment. As blockchain becomes a de facto standard for transactional governance, AI expects IBM to become a fundamental player in supporting the most important aspect of remote transactions: trust.

Overall, IBM has made its case for the future by demonstrating its plans for Cloud, Watson, and Blockchain. AI is bullish, long-term, on IBM’s future but cautions that IBM basically is developing a variety of startups across blockchain, video, cloud infrastructure, Watson services, Watson platform, Watson-based consulting, and even more future-facing capabilities such as hardware-based cognitive computing and quantum computing. Not everything in the portfolio will pan out as long-term multi-billion dollar businesses and not everyone will be pleased that IBM continues to take risks associated with the long-term future of the company rather than simply doubling down on traditional IBM capabilities. Although AI recommends taking a close look at IBM’s capabilities across cloud, Watson, and blockchain, AI believes that the most immediate opportunities for enterprises to get short-term value are around implementing Watson Services and testing IBM Blockchain for any remote transactions being considered. In the longer term, as enterprises consider the long-term migration to the cloud, AI believes that the hybrid and brokered approach that IBM supports will become the dominant approach to implement cloud services at enterprise-scale.

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