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Posts from the ‘Cisco’ Category

Nov 30

86% Of Enterprises Increasing IoT Spending In 2019

  • Enterprises increased their investments in IoT by 4% in 2018 over 2017, spending an average of $4.6M this year.
  • 38% of enterprises have company-wide IoT deployments in production today.
  • 84% of enterprises expect to complete their IoT implementations within two years.
  • 82% of enterprises share information from their IoT solutions with employees more than once a day; 67% are sharing data in real-time or near real-time.

These and many other fascinating insights are from Zebra Technologies’ second annual Intelligent Enterprise Index (PDF, 25 pp., no opt-in). The index is based on the list of criteria created during the 2016 Strategic Innovation Symposium: The Intelligent Enterprise hosted by the Technology and Entrepreneurship Center at Harvard (TECH) in 2016. An Intelligent Enterprise is one that leverages ties between the physical and digital worlds to enhance visibility and mobilize actionable insights that create better customer experiences, drive operational efficiencies or enable new business models, “ according to Tom Bianculli, Vice President, Technology, Zebra Technologies.

The metrics comprising the index are designed to interpret where companies are on their journeys to becoming Intelligent Enterprises. The following are the 11 metrics that are combined to create the Index: IoT Vision, Business Engagement, Technology Solution Partner, Adoption Plan, Change Management Plan, Point of use Application, Security & Standards, Lifetime Plan, Architecture/Infrastructure, Data Plan and Intelligent Analysis. An online survey of 918 IT decision makers from global enterprises competing in healthcare, manufacturing, retail and transportation and logistics industries was completed in August 2018. IT decision makers from nine countries were interviewed, including the U.S., U.K./Great Britain, France, Germany, Mexico, Brazil, China, India, and Australia/New Zealand. Please see pages 24 and 25 for additional details regarding the methodology.

Key insights gained from the Intelligent Enterprise Index include the following:

  • 86% of enterprises expect to increase their spending on IoT in 2019 and beyond. Enterprises increased their investments in IoT by 4% in 2018 over 2017, spending an average of $4.6M this year. Nearly half of enterprises globally (49%) interviewed are aggressively pursuing IoT investments with the goal of digitally transforming their business models this decade. 38% of enterprises have company-wide IoT deployments today, and 55% have an IoT vision and are currently executing their IoT plans.

  • 49% of enterprises are on the path to becoming an Intelligent Enterprise, scoring between 50 – 75 points on the index. The percent of enterprises scoring 75 or higher on the Intelligent Enterprise Index gained the greatest of all categories in the last 12 months, increasing from 5% to 11% of all respondents. The majority of enterprises are improving how well they scale the integration of their physical and digital worlds to enhance visibility and mobilize actionable insights. The more real-time the integration unifying the physical and digital worlds of their business models, the better the customer experiences and operational efficiencies attained.

  • The majority of enterprises (82%) share information from their IoT solutions with employees more than once a day, and 67% are sharing data in real-time or near real-time. 43% of enterprises say information from their IoT solutions is shared with employees in real-time, up 38% from last year’s index. 76% of survey respondents are from retailing, manufacturing, and transportation & logistics. Gaining greater accuracy of reporting across supplier networks, improving product quality visibility and more real-time data from distribution channels are the growth catalysts companies competing in retail, manufacturing, and transportation & logistics need to grow. These findings reflect how enterprises are using real-time data monitoring to drive quicker, more accurate decisions and be more discerning in which strategies they choose. Please click on the graphic to expand to view specifics.

  • Enterprises continue to place a high priority on IoT network security and standards with real-time monitoring becoming the norm. 58% of enterprises are monitoring their IoT networks constantly, up from 49%, and a record number of enterprises (69%) have a pre-emptive, proactive approach to IT security and network management. It’s time enterprises consider every identity a new security perimeter, including IoT sensors, smart, connected products, and the on-premise and cloud networks supporting them. Enterprises need to pursue a “never trust, always verify, enforce least privilege” approach and are turning to Zero Trust Privilege (ZTP) to solve this challenge today. ZTP grants least privilege access based on verifying who is requesting access, the context of their request, and ascertaining the risk of the access environment. Designed to secure infrastructure, DevOps, cloud, containers, Big Data, and scale to protect a wide spectrum of use cases, ZTP is replacing legacy approaches to Privileged Access Management by minimizing attack surfaces, improving audit and compliance visibility, and reducing risk, complexity, and costs for enterprises. Leaders in this field include Centrify for Privileged Access Management, Idaptive, (a new company soon to be spun out from Centrify) for Next-Gen Access, as well as Cisco, F5 and Palo Alto Networks in networking.

  • Analytics and security dominate enterprise’ IoT management plans this year. 66% of enterprises are prioritizing analytics as their highest IoT data management priority this year, and 63% an actively investing in IoT security. The majority are replacing legacy approaches to Privilege Access Management (PAM) with ZTP.  Enterprises competing in healthcare and financial services are leading ZTS’ adoption today, in addition to government agencies globally. Enterprises investing in Lifecycle management solutions increased 11% between 2017 and 2018. Please click on the graphic to expand to view specifics.

Jul 2

10 Ways Machine Learning Is Revolutionizing Manufacturing

machine learningBottom line: Every manufacturer has the potential to integrate machine learning into their operations and become more competitive by gaining predictive insights into production.

Machine learning’s core technologies align well with the complex problems manufacturers face daily. From striving to keep supply chains operating efficiently to producing customized, built- to-order products on time, machine learning algorithms have the potential to bring greater predictive accuracy to every phase of production. Many of the algorithms being developed are iterative, designed to learn continually and seek optimized outcomes. These algorithms iterate in milliseconds, enabling manufacturers to seek optimized outcomes in minutes versus months.

The ten ways machine learning is revolutionizing manufacturing include the following:

  • Increasing production capacity up to 20% while lowering material consumption rates by 4%. Smart manufacturing systems designed to capitalize on predictive data analytics and machine learning have the potential to improve yield rates at the machine, production cell, and plant levels. The following graphic from General Electric and cited in a National Institute of Standards (NIST) provides a summary of benefits that are being gained using predictive analytics and machine learning in manufacturing today.

typical production improvemensSource: Focus Group: Big Data Analytics for Smart Manufacturing Systems

  • Providing more relevant data so finance, operations, and supply chain teams can better manage factory and demand-side constraints. In many manufacturing companies, IT systems aren’t integrated, which makes it difficult for cross-functional teams to accomplish shared goals. Machine learning has the potential to bring an entirely new level of insight and intelligence into these teams, making their goals of optimizing production workflows, inventory, Work In Process (WIP), and value chain decisions possible.

factory and demand analytics

Source:  GE Global Research Stifel 2015 Industrials Conference

  • Improving preventative maintenance and Maintenance, Repair and Overhaul (MRO) performance with greater predictive accuracy to the component and part-level. Integrating machine learning databases, apps, and algorithms into cloud platforms are becoming pervasive, as evidenced by announcements from Amazon, Google, and Microsoft. The following graphic illustrates how machine learning is integrated into the Azure platform. Microsoft is enabling Krones to attain their Industrie 4.0 objectives by automating aspects of their manufacturing operations on Microsoft Azure.

Azure IOT Services

Source: Enabling Manufacturing Transformation in a Connected World John Shewchuk Technical Fellow DX, Microsoft

  • Enabling condition monitoring processes that provide manufacturers with the scale to manage Overall Equipment Effectiveness (OEE) at the plant level increasing OEE performance from 65% to 85%. An automotive OEM partnered with Tata Consultancy Services to improve their production processes that had seen Overall Equipment Effectiveness (OEE) of the press line reach a low of 65 percent, with the breakdown time ranging from 17-20 percent.  By integrating sensor data on 15 operating parameters (such as oil pressure, oil temperature, oil viscosity, oil leakage, and air pressure) collected from the equipment every 15 seconds for 12 months. The components of the solution are shown

OEE Graphic

Source: Using Big Data for Machine Learning Analytics in Manufacturing

  • Machine learning is revolutionizing relationship intelligence and Salesforce is quickly emerging as the leader. The series of acquisitions Salesforce is making positions them to be the global leader in machine learning and artificial intelligence (AI). The following table from the Cowen and Company research note, Salesforce: Initiating At Outperform; Growth Engine Is Well Greased published June 23, 2016, summarizes Salesforce’s series of machine learning and AI acquisitions, followed by an analysis of new product releases and estimated revenue contributions. Salesforce’s recent acquisition of e-commerce provider Demandware for $2.8B is analyzed by Alex Konrad is his recent post,     Salesforce Will Acquire Demandware For $2.8 Billion In Move Into Digital Commerce. Cowen & Company predicts Commerce Cloud will contribute $325M in revenue by FY18, with Demandware sales being a significant contributor.

Salesforce AI Acquisitions

Salesforce revenue sources

  • Revolutionizing product and service quality with machine learning algorithms that determine which factors most and least impact quality company-wide. Manufacturers often are challenged with making product and service quality to the workflow level a core part of their companies. Often quality is isolated. Machine learning is revolutionizing product and service quality by determining which internal processes, workflows, and factors contribute most and least to quality objectives being met. Using machine learning manufacturers will be able to attain much greater manufacturing intelligence by predicting how their quality and sourcing decisions contribute to greater Six Sigma performance within the Define, Measure, Analyze, Improve, and Control (DMAIC) framework.
  • Increasing production yields by the optimizing of team, machine, supplier and customer requirements are already happening with machine learning. Machine learning is making a difference on the shop floor daily in aerospace & defense, discrete, industrial and high-tech manufacturers today. Manufacturers are turning to more complex, customized products to use more of their production capacity, and machine learning help to optimize the best possible selection of machines, trained staffs, and suppliers.
  • The vision of Manufacturing-as-a-Service will become a reality thanks to machine learning enabling subscription models for production services. Manufacturers whose production processes are designed to support rapid, highly customized production runs are well positioning to launch new businesses that provide a subscription rate for services and scale globally. Consumer Packaged Goods (CPG), electronics providers and retailers whose manufacturing costs have skyrocketed will have the potential to subscribe to a manufacturing service and invest more in branding, marketing, and selling.
  • Machine learning is ideally suited for optimizing supply chains and creating greater economies of scale.  For many complex manufacturers, over 70% of their products are sourced from suppliers that are making trade-offs of which buyer they will fulfill orders for first. Using machine learning, buyers and suppliers could collaborate more effectively and reduce stock-outs, improve forecast accuracy and met or beat more customer delivery dates.
  • Knowing the right price to charge a given customer at the right time to get the most margin and closed sale will be commonplace with machine learning.   Machine learning is extending what enterprise-level price optimization apps provide today.  One of the most significant differences is going to be just how optimizing pricing along with suggested strategies to close deals accelerate sales cycles.

Additional reading:

Cisco Blog: Deus Ex Machina: Machine Learning Acts to Create New Business Outcomes

Enabling Manufacturing Transformation in a Connected World John Shewchuk Technical Fellow DX, Microsoft 

Focus Group: Big Data Analytics for Smart Manufacturing Systems

GE Predix: The Industrial Internet Platform

IDC Manufacturing Insights reprint courtesy of Cisco: Designing and Implementing the Factory of the Future at Mahindra Vehicle Manufacturers

Machine Learning: What It Is And Why It Matters

McKinsey & Company, An Executive’s Guide to Machine Learning

MIT Sloan Management Review, Sales Gets a Machine-Learning Makeover

Stanford University CS 229 Machine Learning Course Materials
The Economist Feature On Machine Learning

UC Berkeley CS 194-10, Fall 2011: Introduction to Machine Learning
Lecture slides, notes

University of Washington CSE 446 – Machine Learning – Winter 2014

Sources:

Lee, J. H., & Ha, S. H. (2009). Recognizing yield patterns through hybrid applications of machine learning techniques. Information Sciences, 179(6), 844-850.

Mackenzie, A. (2015). The production of prediction: What does machine learning want?. European Journal of Cultural Studies, 18(4-5), 429-445.

Pham, D. T., & Afify, A. A. (2005, July). Applications of machine learning in manufacturing. In Intelligent Production Machines and Systems, 1st I* PROMS Virtual International Conference (pp. 225-230).

Priore, P., de la Fuente, D., Puente, J., & Parreño, J. (2006). A comparison of machine-learning algorithms for dynamic scheduling of flexible manufacturing systems. Engineering Applications of Artificial Intelligence, 19(3), 247-255.

Aug 27

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How Google is Driving Mobile Video Market Growth

Google’s top advertising customers are pushing for convergence of mobile and video quickly, which is turning into a strong catalyst of growth of the global mobile video market.  With their largest advertising customers wanting greater flexibility in bringing video to mobile devices, Google will make significant strides this year to make that happen.

During their latest earnings call, Google execs said that Android, Chrome and YouTube are the highest priority areas of their business. I’ve been following the last year of earnings calls closely, and it’s clear that Google’s largest advertising customers are pushing the company to bring video to mobile at a level of performance and usability not accomplished yet.  The Q2, 2012 earnings call transcript makes this point clear which can be accessed here Google’s Management Discusses Q2 2012 Results – Earnings Call Transcript.

 Mobile and Video: Transforming Convergence Into Cash

Over the last year, Google executives have mentioned the growth of YouTube and its quick evolution from a content management system to a profitable advertising platform.   During the Q1, 2012 earnings call held on April 12, 2012 the following points were made:

  • Google reported they had over 800 million monthly users uploading over an hour of video per second
  • U.K. mobile operator O2 used YouTube as the foundation of a brand launch that year with support for 100 new original channels completed and launched
  • Global product launch plans from GM, Toyota and Unilever and several other large advertising accounts are also underway

During the Q2, 2012 earnings call, Nikesh Arora, Senior Vice President and Chief Business Officer started his comments regarding the YouTube business with the statement “I think in 2007 it was when newspapers frequently said YouTube is groping for an effective business model. I think we can declare we found our model.” Immediately after making this statement, Mr. Arora mentioned that yearly account signups have doubled year-over-year and users are uploading over 72 hours of video every minute.  He also mentioned that  “thousands of partners are making six figures and we’re proud to work with major record labels in Hollywood studios on this platform.”

The call continued with the points made of Danish advertisers shifting their television advertising dollars to YouTube and other Google branding solutions.  Additional companies mentioned on the call using YouTube-based advertising include Denon, Shire, and Intel.  Clearly these companies have major product introductions coming up and see mobile video as perfect for reaching more potential customers than ever before.

Google’s Challenge: Keep Content Quality and User Experience Constantly Improving

If Google is going to attain the full revenue potential of YouTube as an advertising platform, they’ll need to focus on the following factors:

  • Create Application Programmer Interfaces (APIs) and easy-to-use programming tools for quickly creating mobile-optimized sites.  As Gartner studies have shown, video on telephones is most often used as a time-filler, with a median length of 2 minutes, 46 seconds.
  • YouTube will need to support more optimized mobile-based video browsers that can support contextual search.  This will be a core requirement for the enterprise, specifically in the areas of mobile customer care, mobile commerce and mobile health.
  • More extensive analytics in YouTube than are available today, specifically tying into to major marketing strategies including product introductions.  It is becoming common knowledge that videos improve viewer engagement and prospects attribute a more positive shopping experience when they are used.  Luxury brands are investing heavily in this technology including BMW, Burberry, Channel, Louis Vuitton and many others.
  • A Google/Ipsos OTX MediaCT smartphone users study completed in April, 2011 shows that 77% of smartphone users said that their most visited site was a mobile search engine.

Mobile Video: The Market YouTube Built

The size of the worldwide mobile video market was comprised of 429 million mobile video users in 2011, projected to grow exponentially to 2.4 billion users by 2016.  Smartphones and tablet sales will contribute 440 million new mobile video users during the forecast period.  These market estimates are from the recently published Gartner report, Market Trends: Worldwide, the State of Mobile Video, 2012.

Additional take-aways from this report include the following:

  • Allot Communication’s reports that mobile streaming grew 93% in the first half of 2011; Allot also reports that the usage of YouTube’s mobile channel grew by 152% and YouTube generated 22% of all mobile video traffic in the first half of 2011.  YouTube reports getting 400 million video views a month globally.
  • Gartner reports from a survey completed in the 4th quarter of 2010 that 32% of mobile enterprise users watch short videos from YouTube and other sites optimized for video streaming.
  • The fastest growth for mobile video will be in Latin America as smartphone adoption continues to accelerate, replacing traditional cell phones in these markets.  Asia/Pacific will have the highest number of mobile video users at 541 million by 2016.  Both of these markets will benefit from low-cost smartphones being produced by contract manufacturers who are becoming the dominant production strategy of brand leaders globally. The following graphic shows the Mobile Video User Forecast by Region, Worldwide, 2008 – 2016.

  • By 2016, close to 60% of professionally developed mobile video content will be delivered via mobile-optimized websites that also have enhanced contextual search functionality included in the content management systems.
  • Mobile customer care, mobile commerce and mobile health will be the three primary industry drivers in the near-term of mobile video market, emerging as growth catalysts of this emerging market.
  • Cisco’s Visual Networking Index study reports that last year, mobile video accounted for 56% of all mobile data traffic.
  • 3G/4G connections are emerging as a powerful catalyst of mobile video growth.  Gartner is forecasting that the worldwide share of mobile video connections on 3G/4G will increase from 18% in 2011 to 43% in 2015.  In more established markets incouding North America and Western Europe, the percentage of 3G/4G connections is expected to be as high as 80% and 96% respectively.
  • Gartner projects that 70% of mobile video users will use only Wi-Fi to view mobile video, with the remainder of the market relying on a mix of cellular and Wi-Fi networks to gain access and also upload content.   The following figure shows the Mobile Video User Forecast by Network Type, Worldwide, 2008 – 2016.

Source: Market Trends: Worldwide, the State of Mobile Video, 2012. Gartner Group. Published: 10 February 2012 ID:G00223693 Author: Shalini Verma.   Link: http://www.gartner.com/id=1920315

Aug 3

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Gartner Releases Their Hype Cycle for Cloud Computing, 2012

Enterprises are beginning to change their buying behaviors based on the deployment speed, economics and customization that cloud-based technologies provide.  Gartner cautions however that enterprises are far from abandoning their on-premise models and applications entirely for the cloud.

Based on an analysis of the Gartner Hype Cycle for Cloud Computing, 2012, the best results are being attained by enterprises that focus on a very specific strategy and look to cloud-based technologies to accelerate their performance.  Leading with a strategic framework of goals and objectives increases the probability of cloud-based platform success. Those enterprises that look to cloud platforms only for cost reduction miss out on their full potential.

The Hype Cycle for Cloud Computing, 2012 is shown below:

Cloudwashing and Inflated Enterprise Expectations

While the hype surrounding cloud computing may have peaked, cloudwashing continues to cause confusion and inflated expectations with enterprise buyers.  This just slows down sales cycles, when more straightforward selling could lead to more pilots, sales and a potentially larger market. Cloud vendors who have the expertise gained from delivering cloud platforms on time, under budget, with customer references showing results are starting to overtake those that using cloudwashing as part of their selling strategies.

Additional take-aways from the Gartner Hype Cycle for Cloud Computing include the following:

  • Cloud Email is expected to have a 10% adoption rate in enterprises by 2014, down from the 20% Gartner had forecasted in previous Hype Cycles.  This represents modest growth as the adoption rate of this category had been between 5 and 6% in 2011.
  • Big Data will deliver transformational benefits to enterprises within 2 to 5 years, and by 2015 will enable enterprises adopting this technology to outperform competitors by 20% in every available financial metric.  Gartner defines Big Data as including large volumes processed in streams, in addition to batch.  Integral to Big Data is an extensible services framework that can deploy processing to the data or bring data to the process workflow itself. Gartner also includes more than one asset type of data in their definition, including structured and unstructured content.  The Priority Matrix for Cloud Computing, 2012 is shown below:

  • Master Data Management (MDM) Solutions in the Cloud and Hybrid IT are included in this hype cycle for the first time in 2012.  Gartner reports that MDM Solutions in the Cloud is getting additional interest from Enterprise buyers as part of a continual upward trend of interest in MDM overall.  Dominant vendors in this emerging area include Cognizant, Data Scout, IBM, Informatica, Oracle and Orchestra Networks, are among those with MDM-in-the-cloud solutions.
  • PaaS continues to be one of the most misunderstood aspects of cloud platforms.  The widening gap between enterprise expectations and experiences is most prevalent in this market.  Gartner claims this is attributable to the relatively narrow middleware functions delivered and the consolidation fo vendors and service providers in this market.
  • By 2014 the Personal Cloud will have replaced the personal computer as the center of user’s digital lives.
  • Private Cloud Computing is among the highest interest areas across all cloud computing according to Gartner, with 75% of respondents in Gartner polls saying they plan to pursue a strategy in this area by 2014.  Pilot and production deployments are in process across many different enterprises today, with one of the major goals being the evaluation of virtualization-driven value and benefits.
  • SaaS is rapidly gaining adoption in enterprises, leading Gartner to forecast more than 50% of enterprises will have some form of SaaS-based application strategy by 2015.  Factors driving this adoption are the high priority enterprises are putting on customer relationships, gaining greater insights through analytics, overcoming IT- and capital budget-based limitations, and aligning IT more efficiently to strategic goals.
  • More than 50% of all virtualization workloads are based on the x86 architecture. This is expected to increase to 75% by 2015.  Gartner reports this is a disruptive innovation which is changing the relationship between IT and enterprise where service levels and usage can be tracked.

Bottom line: Gartner’s latest Hype Cycle for Cloud Computing  shows that when cloud-based platforms are aligned with well-defined strategic initiatives and line-of-business objectives, they deliver valuable contributions to an enterprise.  It also shows how Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) are the catalysts of long-term market growth.  The following slide from the presentation  High-Tech Tuesday Webinar: Gartner Worldwide IT Spending Forecast, 2Q12 Update: Cloud Is the Silver Lining (free for download) also makes this point.

Jan 17

25 Comments

Roundup of Cloud Computing Forecasts and Market Estimates, 2012

The latest round of cloud computing forecasts released by Cisco, Deloitte, IDC, Forrester, Gartner, The 451 Group and others show how rapidly cloud computing’s adoption in enterprises is happening.  The better forecasts quantify just how and where adoption is and isn’t occurring and why.

Overall, this year’s forecasts have taken into account enterprise constraints more realistically  than prior years, yielding a more reasonable set of market estimates.  There still is much hype surrounding cloud computing forecasts as can be seen from some of the huge growth rates and market size estimates.  With the direction of forecasting by vertical market and process area however, constraints are making the market estimates more realistic.

I’ve summarized the links below for your reference:

  • According to IDC, by 2015, about 24% of all new business software purchases will be of service-enabled software with SaaS delivery being 13.1% of worldwide software spending.  IDC further predicts that 14.4% of applications spending will be SaaS-based in the same time period. Source: http://www.idc.com/getdoc.jsp?containerId=232239
  • The cloud computing marketplace will reach $16.7B in revenue by 2013, according to a new report from the 451 Market Monitor, a market-sizing and forecasting service from The 451 Group. Including the large and well-established software-as-a-service (SaaS) category, cloud computing will grow from revenue of $8.7B 2010 to $16.7B in 2013, a compound annual growth rate (CAGR) of 24%. https://451research.com/
  • Forrester forecasts that the global market for cloud computing will grow from $40.7 billion in 2011 to more than $241 billion in 2020. The total size of the public cloud market will grow from $25.5 billion in 2011 to $159.3 billion in 2020. Link to report excerpt is here.
  • Deloitte is predicting cloud-based applications will replace 2.34% of enterprise IT spending in 2014 rising 14.49% in 2020.  The  slide below  is from an excellent presentation by Deloitte titled Cloud Computing Forecast Change downloadable from this link.

  • Gartner predicts Small & Medium Business (SMB) in the insurance industry will have a higher rate of cloud adoption (34%) compared to their enterprise counterparts (27%).  Gartner cites that insurance industry’s opportunity to significant improve core process areas through the use of technology.  The following figure from the report, 2011 SMB Versus Enterprise Software Budget Allocation to Annual Subscriptions indicates the differences in software budget allocation for annual subscriptions by vertical market from the report:

2011 SMB Versus Enterprise Software Budget Allocation to Annual Subscriptions

  • Gartner is predicting that the cloud system infrastructure (cloud IaaS) market to grow by 47.8% through 2015. The research firm advises outsourcers not moving in that direction that consolidation and cannibalization will occur in the 2013 – 2014 timeframe  The providers named most often by respondents were Amazon (34%), SunGard (30%) and Verizon Business (30%). Of the global top 10 IT outsourcing market leaders, only CSC appears on the list. Source: User Survey Analysis: Infrastructure as a Service, the 2011 Uptake  Claudio Da Rold,  Allie Young.

External Service Providers Being Considered for IaaS (or Cloud IaaS)

Mar 7

Evolving the Data Center to the Private Cloud

[tweetmeme source=@LouisColumbus only_single=false]

According to what Cisco is seeing in the market, the transition to private clouds starts with consolidation of systems and applications to reduce costs, followed by a targeted virtualization strategy.

Cisco sees this as a step to making their customers’ businesses more aligned to line-of-business strategies and goals.  The final step is automation, which is the transformation of IT into a foundation for business strategies and future growth.

The following Cisco presentation has several interesting insights into how they are working with their clients to transition from data centers to private clouds.  Results customers are achieving are provided throughout the slide deck, which provide a glimpse into the cost, time, and strategy savings from moving to private cloud architecture.

Cisco treads a fine line between showing a private cloud architecture that is entirely proprietary (like Oracle) and educating the market on how they see private clouds evolving.  They do this by showing how commitment their product strategies are to open integration standards and how critical they see aligning to business strategies first.  The net result is a useful 38-page presentation that is worth checking out, to see how they view the progression of data centers to private clouds occurring in the years to come.

Note: I’m not working for Cisco and they did not pay me to write this.

Flickr attribution: http://www.flickr.com/photos/zengame/265839487/

Oct 16

Network Service Providers as Cloud Providers – New Report From Cisco on Cloud Computing Landscape

[tweetmeme source=@LouisColumbus only_single=false]

In August, 2010 Cisco completed a study that included interviews with 80 enterprise IT decision makers (CIOs, CTOs, and infrastructure VPs) from 43 enterprises and public-sector organizations across industries throughout the US, Europe and India.  In addition, Cisco completed one-one-one interviews with 20 subject-matter experts.

The primary focus of the study was on the adoption of the public cloud for enterprise applications.  The report  Network Service Providers as Cloud Providers Survey Shows Cloud Provision Is a Bright Option can be downloaded here.

Key Take-Aways:

Cisco forecasts that the global market for Cloud Computing Service Revenue will be $43.8B by 2013, with SaaS contributing $29.5B, or 6 7%. Workload migration will also be the greatest in that segment as well.  The study provides additional insight into the IaaS and PaaS key success factors and the implications network service providers. (Click on image to expand it for ease of reading).

The study found that in the Business Processing segment, the greatest near-term opportunity is in SaaS-based ERP, which according to this study is predicted to reach a 13% adoption rate by 2013. This is consistent with International Data Corporation estimates of SaaS-based ERP adoption in comparable time periods.  ERP’s growth on the SaaS platform continues to be constrained by lack of Master Data Management (MDM) functionality, lack of a pervasive mobile APIs on the several SaaS ERP systems launched, and concerns over security of costing. ordering, production, and quality management data. (Click on image to expand it for ease of reading).

Mar 24

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Ada Lovelace Day and a short video from Padmasree Warrior of Cisco on Cloud Services

Celebrating women’s accomplishments and thought leadership in science and technology, Ada Lovelace Day needs to permeate the cultures of the world. Only when that happens will the coming generations of women have a chance to make the most of their potential in these areas.

Padmasree Warrior of Cisco is a case in point of why this day and the thought behind it are important, especially for young women who are gifted in math and science, seeking role models.

Hidden Brilliance That Needs To See the Light of Day

In the graduate courses I’ve taught the most surprising aspect of any class are the women of exceptional brilliance that tend to hide their intelligence in science and math, only to show exceptional command of complex concepts on tests. These women, many from Asian, Middle Eastern and Eastern European cultures, would never engage in a fiery debate over the ethics of the Internet censorship in China or the best approach to defining an ERP system for a given case study. Yet when they put pen to paper as part of our case studies their work is perfect. Flawless. Excellent. The ones who attended British schools in Hong Kong analyze and write at a level that is well beyond their peers. They have so much talent yet such a reluctance to make the most of it. These are the women who need to hear about Ada Lovelace.

Padmasree Warrior, Senior VP and CTO of Cisco Systems Speaking on Cloud Services

In the following video clip Padmasree Warrior explains the fundamentals of Cisco’s Unified Service Delivery, a key component of their foundation for Cloud Services. At 5 minutes it’s worth watching and listening to.

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Feb 25

Understanding the Differences between Private and Public Cloud Computing

Included is an assessment of the integration requirements by Cloud type. At just over 3 minutes it’s an excellent summary of the differences between Cloud Computing platforms and provides a useful context to understand these two concepts.

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