Skip to content

Archive for

Roundup of Cloud Computing Forecasts Update, 2013

tunnel-of-speed-forecast-of-saas-cloud-computing-final-300x201Time-to-market, more flexible support for business strategies by IT, and faster response time to competitive conditions are combining to accelerate cloud computing adoption today.

Of the enterprises I’ve spoken with over the last several months including several Fortune 500 corporations to small businesses just beginning to evaluate cloud-based CRM and manufacturing systems, one message resonates from all of them: they need enterprise applications that keep pace with how fast they want to move on new business strategies. The latest round of cloud computing forecasts reflect the urgency enterprises have of making IT a foundation for strategic business growth.

The following is a summary of the latest cloud computing forecasts and market estimates:

McKinsey Analysis

  • IDC predicts public IT cloud services will reach $47.4B in 2013 and is expected to be more than $107B in 2017. Over the 2013–2017 forecast period, public IT cloud services will have a compound annual growth rate (CAGR) of 23.5%, five times that of the IT industry as a whole. The growing focus on cloud services as a business innovation platform will help to drive spending on public IT cloud services to new levels throughout the forecast period. By 2017, IDC expects public IT cloud services will drive 17% of IT product spending and nearly half of all growth across five technology categories: applications, system infrastructure software, platform as a service (PaaS), servers, and basic storage. Software as a service (SaaS) will remain the largest public IT cloud services category throughout the forecast, capturing 59.7% of revenues in 2017. The fastest growing categories will be PaaS and Infrastructure as a service (IaaS), with CAGRs of 29.7% and 27.2%, respectively.  Source: IDC Forecasts Worldwide Public IT Cloud Services Spending to Reach Nearly $108 Billion by 2017 as Focus Shifts from Savings to Innovation.

IDC Forecast Public IT Spending

  • Informatica’s presentation titled Enable Rapid Innovation with Informatica  and MicroStrategy for Hybrid IT by Darren Cunningham, Informatica Cloud  and Roger Nolan, Informatica Data Integration and Data Quality contains a useful series of cloud market overviews supported by 451 Research Gartner, Forrester and IDC data.  A summary of the statistics section is shown below:

Informatica

adoption graphic from KPMG

  • Gartner predicts that in the next five years enterprises will spend $921B on public cloud services, attaining a CAGR of 17% in the forecast period.  Darryl Carlton, Research Director, APAC with Gartner recently presented Cloud Computing 2014: Cloud Computing 2014: ready for real business?  His presentation is full of insightful analysis and market forecasts from Gartner, with specific focus on Asia-Pacific.
  • Visiongain predicts the Platform-as-a-Service (PaaS) submarket is valued at $1.9B in 2013 growing to $3.7B in 2018, attaining a 14.3% CAGR for the period 2013-2018.  The following figure shows the firm’s forecast.  Source: Visiongain on Slideshare.
  • Gartner predicts that in the next five years enterprises will spend $921B on public cloud services, attaining a CAGR of 17% in the forecast period.  Darryl Carlton, Research Director, APAC with Gartner recently presented Cloud Computing 2014: Cloud Computing 2014: ready for real business?  His presentation is full of insightful analysis and market forecasts from Gartner, with specific focus on Asia-Pacific.
  • Visiongain predicts the Platform-as-a-Service (PaaS) submarket is valued at $1.9B in 2013 growing to $3.7B in 2018, attaining a 14.3% CAGR for the period 2013-2018.  The following figure shows the firm’s forecast.  Source: Visiongain on Slideshare.

visiongain forecast

marketscape

  • Boston Consulting Group writes that SaaS is a $15B market, growing at three times that rate of traditional software.  BCG estimates that SaaS is 12% of global spending on IT applications.  BCG interviewed 80 CIOs and found they were willing to consider SaaS solutions for 35% to 60% of their application spending.  BCG also evaluated how the economics of cloud software adoption vary for on-premises versus SaaS customers.  The following two charts from the completed study. Source: (Free, opt-in required) Profiting from the Cloud: How to Master Software as a Service

Profiting_Cloud_Ex1_lg_tcm80-138310 BCG Categories

Profiting_Cloud_Ex2_lg_tcm80-138309 BCG Economics

Asia Pacific Cloud Market Growth

Cloud Predictive Analytics Most Used To Gain Customer Insight

AnalyticsUsing analytics to better understand customer satisfaction, profitability, retention and churn while increasing cross-sell and up-sell are the most dominant uses of cloud-based analytics today.

Jim Ericson and James Taylor presented the results of Decision Management Solutions’ cloud predictive analytics survey this week in the webinar Predictive Analytics in the Cloud 2013 – Opportunities, Trends and the Impact of Big Data.  The research methodology included 350 survey responses, with a Web-based survey used for data collection.  The survey centered on the areas of pre-packaged cloud-based solutions, cloud-based predictive modeling, and cloud deployment of predictive analytics.  You can see a replay of the webinar at this link.

Key takeaways of the study results released during the webinar include the following:

  • Customer Analytics (72%), followed by supply chain, business optimization, marketing optimization (57%), risk and fraud (52%), and marketing (58%) are the areas in which respondents reported the strongest interest.
  • When the customer analytics responses were analyzed in greater depth they showed most interest in customer satisfaction (50%) followed by customer profitability (34%), customer retention/churn (32%), customer management (30%), and cross-sell/up-sell (26%).
  • Adoption was increasingly widespread and growing, with over 90% of respondents reporting that they expected to deploy one or more type of predictive analytics in the cloud solution.
  • Industries with the most impact from predictive analytics include retail (13% more than average), Financial Services (12%) and hardware/software (4%). Lagging industries include health care delivery (-9%), insurance -11%) and (surprisingly) telecommunications (-33%).  The following graphic illustrates the relative impact of cloud-based predictive analytics applications by industry.

Adoption of Cloud-based Predictive Analytics by Industry

  • The most widespread analytics scenarios include prepackaged solutions (52%), cloud-based analytics modeling (47%) and cloud-based analytic embedding of applications (46%).  Comparing the 2011 and 2013 surveys showed significant gains in all three categories, with the greatest being in the area of cloud-based analytic modeling.  This category increased from 51% in 2011 to 75% in 2013, making it the most likely analytics application respondents are going to implement this year.

Comparison of Analytics Applications Most Likely To Deploy, 2011 versus 2013

  • 63% of respondents report that when predictive analytics are tightly integrated into operations using Decision Management, enterprises have the intelligence they need to transform their businesses.

Impact of Predictive Analytics Integration Across The Enterprise

  • Data security and privacy (61%) followed by regulatory compliance (50%) are the two most significant concerns respondent companies have regarding predictive analytics adoption in their companies.  Compliance has increased as a concern significantly since 2011, probably as more financial services firms are adopting cloud computing for mainstream business strategies.

Concerns of Enterprises Who Are Using Cloud-based Predictive Analytics Today

  • Internal cloud deployments (41%) are the most common approach to implementing central cloud platforms, followed by managed vendor clouds (23% and hybrid clouds (23%). Private and managed clouds continue to grow as preferred platforms for cloud-based analytics, as respondents seek greater security and stability of their applications.  The continued adoption of private and managed clouds are a direct result of respondents’ concerns regarding data security, stability, reliability and redundancy.

Approach To Cloud Deployment

  • The study concludes that structured data is the most prevalent type of data, followed by third party data and unstructured data.
  • While there was no widespread impact on results from Big Data, predictive analytics cloud deployments that have a Big Data component are more likely to contribute to a transformative impact on their organizations’ performance.  Similarly those with more experience deploying predictive analytics in the cloud were more likely to use Big Data.
  • In those predictive analytics cloud deployments already operating or having an impact, social media data from the cloud, voice or other audio data, and image or video data were all much more broadly used as the following graphic illustrates.

Which Data Types Deliver The Most Positive Impact In A Big Data Context

Making Analytics Pay In The Enterprise

global-analytics-300x2001With analytics and big data being so heavily hyped today, it is ironic the majority of business analysts often lack access to data and tools they need.

But things are changing with the next generation of analytics software coming to market.  A recent study by The Economist, “Big Data and the Democratisation of Decisions,” shows the severity of the big data analytics problem and which departments need the most support: customer service, human resources, marketing, strategy and business development.  The following is an infographic based on the study’s key findings. To be clear, all companies mentioned in this post are not and never have been clients of mine or companies I have worked for.

Unleashing Greater Insight in the Enterprise

The real analytics payoff in the enterprise begins when business analysts can achieve customer and market insights faster than their competitors.  In the consumer packaged goods industry, every week counts in a new product launch and product lifecycle.  In healthcare, lag times in customer service lead to patients seeking more responsive treatment alternatives.  The net result in each is lost revenue.

Analytics applications and platforms are increasingly being designed for self-service and the needs of business analysts first.  Instead of having to rely on IT for analytics, big data and advanced statistical analysis support, business analysts need to be able to complete projects on their own. Analytics applications are advancing quickly on this self-service dimension, making it possible for business analysts to get complex projects done in a fraction of the time it would have taken IT to staff and complete them.

Alliances and partnerships between analytics software providers are focused on getting business analysts the tools they need so they don’t have to rely on IT so much to get their work done.  The recent partnership announced between Alteryx and Revolution Analytics puts R-based predictive analytics directly in the hands business analysts is a case in point.

What’s noteworthy about this partnership above all others is the option it gives enterprises to integrate big data and other 3rd party sources into a common system of engagement. Business analysts can then use tools to design analytics and reporting workflows that align and stay in step with line-of-business needs over time.

alteryx-gallery1-300x1691Once an application or workflow is complete, business analysts can publish and distribute their analytics applications enterprise-wide. The Alteryx Analytics Gallery (shown to the right) gives customers the opportunity to share their analytics applications with each other.  The gallery is helping business analysts learn from each other, serving as a catalyst for broader analytic consumption.

This is the same model ServiceNow (NYSE:NOW) has been so successful with in the area of IT Service Management.  I attended Knowledge13 earlier this year and found their customer base to be one of the most enthusiastic I’ve ever met.  What ServiceNow has done IT Service Management, Alteryx is on its way to accomplishing in analytics.

Why All This Matters For Customers

Getting analytics applications and tools in the hands of business analysts significantly improves the customer experience and reduce errors at the same time. At Kaiser Permanente, business analysts focus on cost saving projects that improve customer service.

Kaiser has a continual stream of customer interactions across multiple channels going on daily.  Supported by legacy IT systems, Microsoft Excel spreadsheets and manual processes to keep the entire system working, the healthcare provider was seeing patient satisfaction levels drop as they didn’t have a clear view of their customers.  The legacy and manual systems also made coordinating customer service teams very difficult and replicating analytics tools very difficult.

Alteryx-Workflow-21

Kaiser Permanente was able to aggregate and cleanse the myriad of data sources they rely on and gain greater insights into their customer’s needs. Creating analytics and reporting workflows that business analysts and lean leaders in their Service Organization use to stay on top of customer needs has led to a five-fold increase in customer service performance according to Greg Hall, Senior Service Optimization Leader.

%d bloggers like this: