IBM CEO Declares Chapter 2 of Cloud and AI at IBM Think 201…
In 2013, IBM had a wakeup call.
It lost an important cloud deal at the CIA to AWS. IBM protested the contract exposing previously confidential details. In a high profile decision, Judge Thomas Wheeler ruled against IBM despite the apparent higher price bid submitted by AWS. The bottom line is AWS’ cloud offering was viewed as superior to IBM’s.
Less than twenty-four months into her tenure as IBM’s CEO, Ginni Rometty understood the imperative. IBM had to make a move to get into the public cloud game or it would be left out in the cold, much like HP, Cisco, EMC, VMware, and other large tech firms at the time. IBM paid $2B to acquire Softlayer and has since transformed the platform into a viable offering from which it intends to re-write the cloud narrative.
Here’s a paraphrase of the premise put forth by IBM’s Chairman and CEO at this week’s IBM Think conference in San Francisco:
Chapter one of the cloud represented about 20% of the workload opportunity. It was largely about moving a lot of new and customer-facing applications to the cloud. Chapter two is about the hard stuff. It’s about scaling AI and creating hybrid clouds. It’s about bringing the cloud operating model to all those mission-critical apps and enabling customers to manage data, workloads, and apps and move them between multiple clouds. This is a trillion dollar opportunity and IBM intends to be #1.
IBM is not alone in its aspiration. Large companies like Cisco, VMware, and even HPE have somewhat similar aspirations. As does ServiceNow and a host of smaller specialist firms. And of course, the public cloud giants including AWS and Microsoft have their own ideas about Chapter 2 of the cloud era.
To claim a leadership position in Chapter 2, IBM is spending $34B to acquire Red Hat. This is a huge move on the chess board and underscores that the IBM Cloud and a decade of trying to commercialize Watson aren’t enough to win the day. Rather it sees open source, Kubernetes, containers, microservices, and developers as a lynchpin to success in the next chapter of the cloud.
A Quick Review of Chapter One
There’s much debate about who first created the term cloud computing. There’s little doubt however that Jeff Barr’s blog post in the summer of 2006, announcing AWS’ Elastic Compute Cloud, ushered in the modern era of cloud – so-called Chapter 1. In his post, Barr wrote:
With Amazon EC2, you don’t need to acquire hardware in advance of your needs. Instead, you simply turn up the dial, spawning more virtual CPUs, as your processing needs grow.
His assertion underscored the most fundamental value proposition of cloud – pay for only what you use model. This, of course, was the first of numerous innovations and functions – all available with the swipe of a credit card, to be dialed up on demand. Startups flocked and tapped world-class data center services previously only available to large companies.
The economic downturn of 2007-2009 led CFOs to mandate a shift from Capex to Opex and when the economy turned up, businesses realized that their cloud experience enabled much greater agility. Shadow IT-powered the next phase of growth and as “cloud creep” permeated the market – IT hopped on board and hasn’t looked back.
Notably, Microsoft transformed itself to the cloud using the formula of: 1) An open source mindset – alignment and support (open compute, linux on .net, etc.); 2) Cloudify all things Microsoft and making Azure, not Windows, the center of its universe; and 3) bundling office 365 to show revenue from not only IaaS but SaaS.
Joined by Google, which used its dominant global search infrastructure to stake its claim in the cloud, the big three paved the way for a new economic model based on scale, innovation and automation, applying software economics to the concept of infrastructure deployment and management services (See Figures 1 & 2 below).
Enterprise IT Economics 1990-2010SiliconAngle.com
Enterprise IT Economics 2010-2030SiliconAngle.com
Key Points in the Charts:
Traditionally, the marginal cost of software approaches zero while services have negative economies of scale;
With cloud – infrastructure services track more closely to software economics – enabling massive scale (and profitability) for those with volume (i.e. AWS, Microsoft, and Google);
Traditional infrastructure companies struggle to hang on to legacy installed bases;
Cloud companies with a SaaS portfolio (Oracle, IBM, Microsoft) have “up-the-stack” value advantages they can use as a bulwark against the commoditization of their businesses.
IBM’s Prospects for Chapter 2 Leadership Rely on Data
Before diving into the Red Hat piece of the puzzle, we have to point back to data. In our view, IBM is working closely with customers to build a digital business fabric where data remains the underpinning of its strategy to drive a new era of analytics based on AI. IBM sees data as a fundamental ingredient in bringing contextual relevance to business applications. What we’re seeing is because of IBM’s massive services business and deep industry expertise it’s earned the right to help customers build digital networks and transform business models. IBM’s large customers are getting this. They’re not looking to IBM to simply deliver services or secure their infrastructure or sell them SaaS – rather they’re looking for IBM to help them transform and deliver new business models. We’re seeing this in healthcare, financial services, agriculture, energy, insurance and virtually all industries in which IBM has a presence globally.
IBM’s opportunity as we see it is to help companies understand how to make money using data. Not necessarily by directly selling their data but figuring out how to monetize data. What we see IBM doing is taking what has been largely piecemeal, data-oriented AI projects and creating what Rometty calls “Outside / In” – i.e. customer experience oriented applications and “Inside / Out” – i.e. workflow and new ways to work applications – both which contribute to bottom line results. More importantly, IBM wants to help the customer completely transform their business operations.
To accomplish this, IBM is delivering a business platform – fueled by data, and a machine intelligence platform – i.e. tooling and capabilities to extract value from data and operationalize AI.
Enter Red Hat
IBM didn’t release any new details about Red Hat at Think, presumably because of regulatory concerns. But with Red Hat, IBM can enable a new breed of application developers – for businesses – using cloud-native tooling. Data is the key ingredient to emerging business applications and with Red Hat in its portfolio, IBM can “cloudify” and “Data-fy” businesses and position itself as modern and relevant. More importantly, it can dramatically scale Red Hat’s business globally.
Red Hat for IBM emerges as a vehicle for generating derivative leverage out of IBM ecosystem software and industry knowledge. With RHEL, OpenShift and eight million Red Hat developers, IBM can help its customers modernize their application portfolios and transform business operations…creating a new breed of digital business developers.
Consider statements made by Ginni Rometty and Jim Whitehurst during their mini roadshow after announcing the Red Hat acquisition. Ginni kept saying “this isn’t a backend loaded deal.” What did she mean? In our view, she was essentially explaining the business case for IBM paying a 60%+ premium over Red Hat’s stock price prior to the deal being announced. Specifically, IBM has a huge installed base of services clients (a $20+B captive opportunity in our estimate) at which it can point Red Hat PaaS tooling to modernize application portfolios and build the future digital business platform for/with customers.
So out of the chute, IBM can immediately begin scaling Red Hat’s business, marrying deep industry expertise, the sprawling IBM SaaS portfolio, the IBM Cloud (where applicable), AI infused everywhere and Red Hat PaaS to connect customer data, workloads, and applications to any cloud or on-prem installation.
Longer term, IBM can, along with its clients, fully adopt modern application development practices to codify its deep industry expertise and build out transformative business and AI platforms to help incumbent companies compete in the digital era.
The Competitive Landscape
If you don’t own a public cloud, you go hard after multi-cloud. To wit: VMware exited public cloud after years of trying to commercialize VCloud Air. It finally settled on a deal with AWS and sold off its public cloud. VMware is Dell’s ace in the hole for multi-cloud. Cisco recently announced its multi-cloud strategy at Cisco Live Barcelona which comes at the problem from a strong position in networking. As networks flatten – Cisco can be the glue between clouds with software management and orchestration framework for networked data– not a bad strategy. HP tried and failed in the public cloud game and HPE is trying to be a provider of multi-cloud services but is largely relying on packaging its hardware, services and some minimal software content.
Of these players, only Cisco has any meaningful presence with developers. IBM with Red Hat gets access to eight million devs.
As such, IBM has a stronger position than these players– albeit more complex. It owns a public cloud presence and while not nearly as large as AWS in IaaS, IBM has a large SaaS portfolio. Like Oracle, it doesn’t have to compete for commodity business against AWS, rather it can sell value “up the stack” using SaaS as a high-value play. As well, it’s AI runs on the cloud and it just announced at Think that it’s opening up Watson to run on any on-prem, public or hybrid cloud (a long overdue move in our opinion). Previously, if you wanted Watson you could only get it on IBM’s cloud.
Microsoft clearly will have its say in Chapter 2 of the cloud. With its acquisition of GitHub and large software estate, combined with a leading cloud at scale, Microsoft holds a lot of cards. It is investing in AI and has a strong data angle.
Google Cloud is resetting with new management and is playing the long game. It clearly has AI chops and a strong data angle.
Then there’s AWS. Amazon’s announcement of Outposts shows that it can and will evolve and change its spots. Today, AWS makes a strong case for a single versus a multi-cloud approach – arguing that multiple clouds are less secure, more complex and more expensive. While credible in its position, the reality is multi-cloud is like multi-vendor. There’s not a procurement czar inside of every company that will dictate a single cloud. As such if AWS sees an opportunity to manage multiple clouds it will enter the space in our view.
The new “innovation cocktail” combines Data + AI + Cloud. A common data model brings a competitive advantage in the digital world. Machine intelligence (AI) applied to data drives insights and cloud enables scale and attracts innovation through ecosystems. IBM is combining these three elements to compete in the next chapter of technology industry growth.
IBM, like Microsoft, is cloudifying its offerings to support its clients’ digital transformations. By bringing the cloud to its products, building data networks with customers, applying AI everywhere and leveraging Red Hat, it can catalyze a new class of business developers and go hard after the multi-cloud opportunity that exists.
We believe, however, that the multi-cloud world will be messy. Today, multi-cloud is as much a multi- (cloud) vendor occurrence versus a deliberate strategy. Nonetheless, buyers will continue to choose horses for courses – meaning the right cloud for the right workload – and that will inevitably lead to multiple clouds and opportunities for simplified management, security, governance, and data leverage.
Today, about half of IBM’s revenue comes from so-called Strategic Imperatives. That piece needs to grow faster than the other half declines. Moreover, about sixty percent of IBM’s revenue comes from consulting and professional services. The good news there is it gives IBM deep visibility and relationships into virtually all global industries. The downside is that business doesn’t scale as well. As such IBM’s greatest strength is its greatest challenge. The unique opportunity facing IBM is to codify that deep industry expertise in software, using data as the key ingredient for new business applications built on cloud-native PaaS tooling – and scaling to the cloud, any cloud.
That is a differentiable story and one that protects IBM from getting Amazon’d while at the same time allowing the company to drive margin improvements over time. IBM’s Rometty has spent the last 5-6 years preparing the company for this next chapter.
Now Big Blue needs to show that Elephants can dance, sprint and run marathons.