Tag: cloud

Thinking about Robotic Process Automation (RPA) – What Can You Learn from Your Cloud Journey? | Sherpas in Blue Shirts

Everyone is talking about the emerging disruptive technology that is the next transformational solution…

Tales of massive cost reductions and time-to-market improvements that will leave your competitors in the dust abound…

You are getting pressure from the C-Suite about what you’re doing about it…

The vendors have lots of slideware, but precious few production examples at scale…

Everyone is launching pilots or proofs of concept…

Hmmm…is this recounting the cloud services situation of 5 to 7 years ago, or today’s RPA situation?  Well, I think it is both. Our discussions in the market – encompassing both enterprises that are commencing their RPA journey and services and technology providers jockeying to deliver solution to those enterprises – suggest a picture that is eerily similar to a number of patterns we saw as the “last” disruptive trend was gaining its footing a few years ago. It got us thinking about what those wishing to capitalize on the emergence of RPA might learn from the trials and tribulations many firms went through as cloud services emerged.

 RPA
today
Cloud Services during emerging phaseFast forward: what happens next for RPA
Market maturity
  • Every conversation begins with “here is what we mean by RPA…”
  • Every conversation began with “here is how we define cloud…”
  • As enterprise-wide usage patterns emerge, nomenclature will converge to drive clarity on the value levers
Adoption patterns
  • Lots of pilots; slow to scale across processes/ enterprise
  • Focus on “no brainer” use cases
  • Lots of pilots; slow to scale to enterprise workloads
  • Early focus on “spiky” workloads where cloud yielded extraordinary benefit
  • Many “red herring” barriers (“cloud can’t be secure”)
  • Business users will continue to drive siloed initiatives until market reconciles buyer needs with provider business models (see below)
Solutions
  • Targeted at specific use cases with value enabling providers to extract maximum profit surplus
  • Not oriented toward enterprise value
  • Targeted at “low hanging fruit” use cases where benefits were unassailable
  • Broad enterprise-wide solutions limited to niche players (private cloud-led for most larger enterprises)
  • Solutions evolve from “bolt-on’s” to serving as a foundation/primary dimension of the environment
  • ROI driven by impact across processes and internal organizational boundaries
  • Enterprise software vendors build automation capabilities into their products
Market leading solution providers
  • Bifurcated market structure with leading software providers and business process services providers
  • Software firms struggling to align a software business model with market needs
  • BPO players conflicted with cannibalizing installed base
  • Tradeoffs embedded in software and BPO business models hinder adoption
  • “New entrants” exploited unique cloud business model
  • “Incumbents” that attempted to leverage their historical business model made compromises and fell behind
  • New RPA business model must emerge to fully align with market needs and drive enterprise-wide value
  • Solution providers will emerge with approaches that align interests (rather than create conflicts)
Value levers
  • Cost reduction with the ability to replace human capital with robots

 

  • Cost control by tying  cost structure to usage patterns
  • Value levers emerge that supplant cost reduction such as accuracy, flexibility, agility and compliance 

That’s not to say there aren’t some key differences in how these two disruptive trends are playing out. For example, while both sets of key early players created their business models from a blank sheet of paper, the cloud leaders (Amazon Web Services, Google, Microsoft Azure, etc.) clearly had deeper pockets than emerging RPA leaders and they leveraged that ability to invest ahead of demand to drive a market share-driven pricing strategy that secured and continues to protect distinct advantages.

Notwithstanding the differences, it sure feels like many enterprises (and service providers) have been down this path of pursuing the next disruptive technology before.

As you contemplate your RPA strategy, it probably makes sense to step back and gauge how your organization responded to the emergence of cloud services. The steps you took that worked for your cloud initiatives – and those that didn’t work so well – will provide a good path forward.


Photo credit: Flickr

IBM’s Watson Ups the Ante in Healthcare | Sherpas in Blue Shirts

The recently announced acquisition of Merge is one in a string of initiatives by IBM to increase both its market presence and depth of offerings to the healthcare sector. With birth rates increasing in many parts of the world and the aging population growing in developed countries, the race is on for data driven and highly efficient healthcare.

IBM is clearly targeting this market. Its recent activities have included:

  • Entering into new partnerships with companies such as Apple, Johnson & Johnson, and Medtronic for health-related data collection, analysis, and feedback
  • A partnership with CVS Health to develop care management applications for chronic diseases
  • Acquiring Explorys, a healthcare data provider, and Phytel, a hospital care coordination information provider
  • Buying AlchemyAPI to include text analysis and computer vision capabilities into Watson’s computing platform
  • Establishing a dedicated business unit called IBM Watson Health, headquartered in the Boston, MA, with the specific remit of growing its healthcare business
  • Collaborating with leading hospitals and research institutes including Memorial Sloan Kettering Cancer Center, University of Texas MD Anderson Cancer Center, the Cleveland Clinic, and the Mayo Clinic to leverage Watson’s healthcare capabilities at the cutting edge of medical research
  • Setting up IBM Watson Health cloud to bring together data for healthcare and research

The US$1 billion acquisition of Merge brings IBM a medical imaging platform to combine with Watson’s image data and analytics capabilities and an extended client base. Excellent and Elementary, Dr. Watson.

With these initiatives, IBM is building specialist competences, to capture, analyze, and recommend treatments or actions that would help healthcare providers, payers, pharmaceuticals, as well as individuals achieve positive health outcomes.

Gaining a wide range of capabilities in specific areas has helped IBM generate specific segment revenue in good and bad times. For example, its large number of information management and WebSphere portfolio acquisitions (e.g., Cognos, Netezza, and SPSS, to name but a few) has seen segment-specific revenues maintain steady growth over the years.

If IBM was to successfully combine its deep specialization in healthcare with Watson’s cognitive computing to enhance its services, it could gain a big edge over competitors at a time when demand is set to grow. At the moment we are seeing more of IBM in healthcare IT infrastructure modernization contracts than data-driven care provisioning and support services. Recent examples include:

  • A contract to update the UK NHS’ electronic staff record (ESR) system, adding mobile access and self-service capabilities for 1.4 million employees
  • A contract to provide mainframe and data center server and storage infrastructure services for Anthem Inc, a U.S.-based health benefits company, for the next five years at TCV of US$500 million

These types of contracts give IBM opportunities to tap into new solution and services openings at existing clients.

Other challenges for IBM’s intelligent and data driven healthcare offerings include:

  • Collecting enough data for its solutions to be relevant to, as well as accessible in, different parts of the world
  • Data protection barriers in Europe
  • Poor cloud infrastructure in emerging economies.

IBM is going all out when it comes to showcasing Watson as a competitive differentiator. In an uncharacteristic move (and a sign of the times), it has launched Watson Developer Cloud, an open platform for developers to build apps on top of Watson for industry-specific solutions (through a set of APIs and SDKs). It is also working with app developers such as Decibel, Epic, Fluid, Go Moment, MD Buyline, TalkSpace, and Welltok to build apps embedded on Watson technology, thereby, rounding up a robust ecosystem. It is abundantly clear that IBM views healthcare as the principal vertical where Watson’s computing prowess can make its mark. In the meantime other service providers are likely to build or acquire their own cognitive capabilities to challenge IBM on pricing and specialist offerings.


Photo credit: Flickr

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