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Posts tagged ‘Cloud Computing’

Analytics, Data Storage Will Lead Cloud Adoption In 2017

  • cioU.S.-based organizations are budgeting $1.77M for cloud spending in 2017 compared to $1.30M for non-U.S. based organizations.
  • 10% of enterprises with over 1,000 employees are projecting they will spend $10M or more on cloud computing apps and platforms throughout this year.
  • Organizations are using multiple cloud models to meet their business’s needs, including private (62%), public (60%), and hybrid (26%).
  • By 2018 the typical IT department will have the minority of their apps and platforms (40%) residing in on-premise systems.

These and many other insights are from IDG’s Enterprise Cloud Computing Survey, 2016. You can find the 2016 Cloud Computing Executive Summary here and a presentation of the results here.  The study’s methodology is based on interviews with respondents who are reporting they are involved with cloud planning and management across their organizations. The sampling frame includes audiences across six IDG Enterprise brands (CIO, Computerworld, CSO, InfoWorld, ITworld and Network World) representing IT and security decision-makers across eight industries. The survey was fielded online with the objective of understanding organizational adoption, use-cases, and solution needs for cloud computing. A total of 925 respondents were interviewed to complete the study.

Key takeaways include the following:

  • The cloud is the new normal for enterprise apps, with 70% of all organizations having at least one app in the cloud today. 75% of enterprises with greater than 1,000 employees have at least one app or platform running in the cloud today, leading all categories of adoption measured in the survey. 90% of all organizations today either have apps running in the cloud are planning to use cloud apps in the next 12 months, or within 1 to 3 years. The cloud has won the enterprise and will continue to see the variety and breadth of apps adopted accelerating in 2017 and beyond.

use-of-cloud-technology-continuously-expanding

 

  • Business/data analytics and data storage/data management (both 43%) are projected to lead cloud adoption in 2017 and beyond. 22% of organizations surveyed are predicting that business/data analytics will be the leading cloud application area they will migrate to in the next twelve months. 21% are predicting data storage/data management apps are a high priority area for their organizations’ cloud migration plans in 2017.

data-storage-and-analytics-moving-to-the-cloud

 

  • 28% of organizations’ total IT budgets is dedicated to cloud computing next year. Of that, 45% is allocated to SaaS, 30% to IaaS and 19% to PaaS. The average investment organizations will make in cloud computing next year is $1.62M, with enterprises over 1,000 employees projected to spend $3.03M. The average investment in cloud computing remains constant in organizations with $1.62M invested in 2014, $1.56M in 2015 and $1.62M in 2016. 10% of enterprises with over 1,000 employees are projecting they will spend $10M or more on cloud computing apps and platforms throughout this year.

cloud-budget

 

  • CIOs, IT architects and IT networking/management control cloud spending in the enterprise. In contrast, CEOs, CIOs, and CFOs are driving small and medium business (SMB) cloud spending this year. The following graphic compares how influential the following groups and individuals are in the cloud computing purchase process.

cloud-investment

 

  • Just 46% of organizations are using Application Programmer Interfaces (APIs) to integrate with databases, messaging systems, portals or storage components. 40% are using them for creating connections to the application layer of their cloud and the underlying IT infrastructures. The following graphic provides insights into how APIs are being used and which teams see the most value in them.

apis

 

  • In 18 months the majority of organizations’ IT infrastructures will be entirely cloud-based. IDG found that in 18 months nearly one-third (28%) of all organizations interviewed will be relying on private clouds as part of their IT infrastructure. Just over a fifth (22%) will have public cloud as part of their IT infrastructure, and 10% will be using hybrid By 2018 the typical IT department will have the minority of their apps and platforms (40%) residing in on-premise systems.

it-shifts-to-the-cloud

 

  • Concerns about where data is stored (43%), cloud security (41%) and vendor lock-in (21%) are the top three challenges organizations face when adopting public cloud technologies. Private and hybrid cloud adoption in organizations is also facing the challenges of cloud security and vendor lock-in. Private and hybrid cloud adoption are being slowed by a lack of the right skill sets to manage and gain the maximum value from cloud investments.

challenges

Five Strategies For Improving Customer Relationships Using Salesforce Integration

Bottom line: Defining salesforce integration strategies from the customers’ perspective that streamline every aspect of their relationship with your company drives greater revenue, earns trust and creates upsell and cross-sell opportunities in the future.

In the most competitive selling situations the company that has exceptional insights into what matters most to prospects and customers win the most deals. It’s not enough to just have a CRM system that is hard-wired into the core customer-facing processes of a business. To win more sales cycles companies are getting the most from every system they have available. From SAP Enterprise Resource Planning (ERP) systems to legacy pricing, operations, services, pricing, and CRM systems, companies winning more deals today can use Salesforce integration as a catalyst for driving more revenue.

Five Strategies For Improving Customer Relationships Using Salesforce Integration

  1. Making the Configure-Price-Quote (CPQ) process more efficient for customers and prospects by integrating ERP data into every quote. Today speed is a feature every system must have to stay competitive. Being able to create quotes that include the date the proposed configuration will ship and coordinate with services and programs delivery while providing order status from ERP systems is winning deals today. The tighter the ERP system integration, the better the quote accuracy in a CPQ system and the higher the chance of winning a sale. The following table shows the many benefits of having a well-integrated CPQ process.

business-impact-of-an-integrated-cpq-process

  1. Creating an omni-channel experience for customers needs to start with ERP, legacy, 3rd party and Salesforce integration that sets the foundation to exceed customer experiences daily. Providing a unified experience across every channel is challenging yet attainable, with market leaders using a series of integration strategies to provide this level of insight so customers’ expectations are exceeded in every single interaction. Only by integrating CRM systems including Salesforce with SAP ERP systems can any company hope to deliver a consistent, excellent series of experiences across all channels, all the time.
  1. Set up sales teams for exceptional performance with tightly integrated mobile apps that accelerate sales cycles. By using mobile apps that integrate SAP ERP systems, Salesforce CRM, and legacy systems into simplified, highly efficient workflows, sales teams can close more deals without having to come back to their offices.  Senior management teams can get more done using mobile apps that are an extension of their SAP ERP systems as well. Mobile apps are revolutionizing productivity thanks to SAP and Salesforce integration.
  1. Attaining high product quality levels that exceed customer expectations by providing every manufacturing department real-time visibility into quality inspections and inventory control. By integrating inbound inspection, inventory control, and quality management data across manufacturing, Bunn can deliver products that exceed customer expectations. Bunn’s product quality inspectors can perform and record results right at the machines being tested. The warehouse management system can scan and record inventory counts in real time to SAP. Maintaining high levels of product quality are what make Bunn’s beverage equipment machines a market standard globally today.
  1. Making new product launches more successful by having a tightly integrated approach to selling, producing and servicing new products that are in step with customers’ changing needs. From apparel to high-tech and financial services, customers are rapidly redefining which channels they choose to purchase through, how they choose to customize products, and which services they prefer to bundle in.  Integrating Salesforce, e-commerce and ERP systems into a single, unified workflow that is designed to provide customers exactly what they need is essential for enabling new product launches to succeed. With an integrated system across Salesforce, ERP, distribution and pricing systems, new product launches can scale globally quicker and still allow for personalization to customers’ unique preferences.  Salesforce integration is essential for successful new product introductions as the entire launch process gains speed, scale, and simplicity as a result.

Originally published on the enosiX blog, Five Strategies For Improving Customer Relationships Using Salesforce Integration. 

Google Getting More Aggressive In The Cloud

  • google-cloud-platformDeutsche Bank estimates Google Cloud Platform (GCP) has a $750M revenue run-rate estimate today.
  • The combined revenues of AWS, Microsoft Azure, and GCP are still less than $15B for a market penetration of just 1%-2% of the Total Available Market (TAM).
  • During the 2Q16 call, Google called out Cloud as the primary driver of the re-accelerating growth for Licensing and Other revenue, the first time the business has been called out in pole position.
  • Recent Orbitera and Apigee acquisitions underscore Google’s new focus and aggressiveness to grow GCP. Google has spent $1B+ on Cloud M&A over the past 12 months.
  • Deutsche Bank predicts GCP is preparing a series of new product announcements in September to strengthen their customer-facing roadmap further.

These and other insights are from Deutsche Bank Markets Research study, Google Getting More Aggressive In The Cloud, (client access) published 8 September 2016 by Ross Sandler Karl Keirstead, Deepak Mathivanan, Aki Aggarwal and Taylor McGinnis. Deutsche Bank found that Google is investing heavier in the cloud, making a financial commitment with over $1B in acquisitions in the past year including the recent Apigee deal. The study is based on interviews Deutsche Bank contacted with channel partners, prospects, partners, and customers. Despite the renewed focus on growth, Deutsche Bank predicts that GCP would continue to trail AWS and Microsoft Azure for the foreseeable future.

Key takeaways of the Deutsche Bank Markets Research survey include the following:

  • Deutsche Bank defines the Total Available Market (TAM) enterprise IT spend in nine categories that together account for over a $1T TAM. Deutsche Bank defines the Enterprise IT spending market by combining storage, network equipment, infrastructure software, IT outsourcing and support, data management software, BI/analytics, application software and consulting Deutsche Bank sees AWS make significant progress across a wide spectrum of their taxonomy categories.

IT Infrastructure TAM

  • GCP new product launches are concentrating on machine learning, data analytics and security, including data encryption and identity and access management. Google’s aggressiveness regarding the cloud is most visible from their new service announcements shown in the table below.  Recent announcements include SQL Server Images, where customers can now natively spin up Microsoft database instances on GCP, akin to AWS RDS for SQL Server. GCP also announced a second generation version of Cloud SQL, its cloud-hosted alternative to MySQL and AWS Aurora. While all of these announcements provide GCP with greater potential to compete against AWS and Microsoft Azure, Google’s two larger competitors have formidable momentum in enterprises.

new service announcements

  • Aggressive build-out of global infrastructure locations continues. Google announced during their 4Q15 earnings call they would build 12 new regions in 2016 and 2017. Of the 12 new planned GCP regions, the US Western region in Oregon opened in July 2016, and Google has said that the new Tokyo region will be available later this year, leaving ten more regions to be added in 2017.

infrastructure

  • Google continues to believe in the importance of machine learning and artificial intelligence. Deutsche Bank interviews with GCP customers confirmed interest in using machine learning and artificial intelligence on the Cloud. Customers also perceive GCP is well ahead of AWS and Azure in this regard.
  • Google is quickly hiring enterprise sales reps in an attempt to close the sales gap between themselves and AWS & Microsoft Azure. Deutsche Bank found that Google has been “hiring very aggressively” to scale its enterprise sales rep capacity and also retrofitting existing sales reps from elsewhere in Google into GCP.
  • GCP is gaining share rapidly within the startup community. Deutsche Bank spoke with customers who estimated that 25% startups are using GCP today (with 75% on AWS), while another estimated the ratio to be 20%/80%. While both agreed that a couple of years ago only 10% of startups were using GCP (with 90% using AWS). During the GCP NEXT Asia-Pacific keynote earlier this month Google disclosed that Snapchat “is one of our largest customers,” making up to 2 million queries per second and consuming more Google bandwidth than any other organization except for YouTube.
  • Recent Orbitera and Apigee acquisitions underscore Google’s new focus and aggressiveness to grow GCP. Last month Google acquired Orbitera, a small cloud commerce platform. Orbitera simplifies the buying and selling of cloud-based software by providing vendors with packaging and provisioning, billing, and marketplace solutions on AWS and Azure. Earlier this month Google acquired Apigee for $625M, which is 5.2x Apigee’s FY17e revenues of $120M. Apigee is expected to grow by 30%-35% in The company focuses on larger enterprises (Walgreens, Nike, Target, AT&T) and despite an ongoing mix shift to the cloud or SaaS model, it still has a legacy on-premise license/maintenance business.
  • Google is very focused on building relationships with all systems integration (SI) firms but that building out a GCP channel is proving to be challenging. Deutsche Bank believes that Microsoft is also finding it tough to build out it’s Azure channel, in part because many traditional partners and resellers struggle with how they can monetize Azure, given its different price points and the lower services attach rate

6M Developers Are Creating Big Data And Advanced Analytics Apps Today

  • analytics-development2M developers are working on IoT applications, increasing 34% since the last year.
  • Over 50% of the developers working on IoT applications are writing software that utilizes sensors in some capacity.
  • 4M enterprise developers play decision-making roles when it comes to selecting organizational IT development resources. Another 5.2 million hold decision-making authority for selecting IT deployment resources.
  • 4M developers (26% of all developers globally) are using the cloud as a development environment today
  • The APAC region leads the world with approximately 7.4M developers today, followed by EMEA with 7.2M, North America with 4.4M and Latin American with 1.9M.

These and many other fascinating insights are from the Evans Data Corporation Global Developer Population and Demographic Study 2016 (PDF, client access) published earlier this week. The methodology Evans Data has created to produce this report is the most comprehensive developed for aggregating, analyzing and predicting developer populations globally. The study combines Evans Data’s proprietary global developer population modeling with the current results of their semi-annual global developer survey.

Key takeaways from the study include the following:

  • 6M developers (29% of all developers globally) are involved in a Big Data and Advanced Analytics project today. An additional 25% of developers, or 5.3M, are going to begin Big Data and Advanced Analytics projects within the next six 13% or 2.6M of all developers globally are going to start Big Data and Advanced Analytics projects within the next 7 to 12 months.  The following graphic provides an overview of the involvement of 21M developers in Big Data and Advanced Analytics projects today. Please click on the image to expand for easier viewing.

involvement in big data analytics

  • 4M developers (26% of all developers globally) are using the cloud as a development environment today. Developers creating new apps in the cloud had increased 375% since Evans began measuring developer participation in mobile development in 2009 when just slightly more than 1.2M developers were using the cloud as their development platform. 4.5M developers (21% of all global developers) plan on beginning app development on cloud platforms in the next six months, and 3.9M (18% of all global developers) plan on starting development on the cloud in 7 – 12 months. Please click on the image to expand for easier viewing.

plans for cloud development

  • 8M developers in APAC (24% of all developers in the region) are currently developing on cloud platforms. 29% of APAC developers are planning to start cloud-based development in six months, and 20% in 7 – 12 months. The following graphic compares the number of developers currently using the cloud as a development environment today and the number who plan to in the future. Please click on the image to expand for easier viewing.

plans for cloud development by region

  • 34% of all Commercial Independent Software Vendors (ISVs) globally today (1.8M developers) are using the cloud as a development environment. An additional 1.4M are planning to begin cloud development in the next six months.  28% of developers globally creating apps in the cloud are from custom system integrators (SI) and value-added resellers (VARs).  23% or approximately 1.2M are from enterprises.  The following graphic compares the percent of developers by developer segment who are currently creating new apps in cloud environments. Please click on the image to expand for easier viewing.

Plans for cloud development by developer segment

  • 30% of developers (6.2M developers globally) are currently developing software for connected devices or the Internet of Things today, with an additional 26% planning to begin projects in 6 months. Evans Data found that this increased 34% over the last year. Also, 2.1M developers plan to begin development in this area within the next 7 to 12 months. The following graphic compares the number of developers globally by stage of development for creating software for connected devices or the Internet of Things. Please click on the image to expand for easier viewing.

Plans for Internet of Things Development

  • 41% of global developers creating connected device and IoT software today are from 27% are from North America, 24% are from EMEA and 7% from Latin America.  There are 6,072,048 developers currently working on connected device and IoT software today globally.  The following graphic provides an overview of the distribution of developers creating connected device and IoT software by region today. Please click on the image to expand for easier viewing.

Development for Connected Devices By Region

  • 34% of developers actively creating software for connected devices or the Internet of Things work for custom System Integrators (SI) and VARs today. ISVs are the next largest segment of developers working on IoT projects (30%) followed by enterprises (21%). The following graphic provides an overview of the global base of developers creating software for connected devices and IoT. Evans Data found there are 6.1M developers currently creating apps and solutions in this area alone. Please click on the image to expand for easier viewing.

Development for connected devices by developer segment 2

Seven Ways Microsoft Redefined Azure For The Enterprise And Emerged A Leader

  • cloud startupsAs of Q2, 2016 Microsoft Azure has achieved 100% year-over-year revenue growth and now has the 2nd largest market share of the Cloud Infrastructure Services market according to Synergy Research.
  • Microsoft’s FY16 Q4 earnings show that Azure attained 102% revenue growth in the latest fiscal year and computing usage more than doubling year-over-year.
  • 451 Research predicts critical enterprise workload categories including data, analytics, and business applications will more than double from 7% to 16% for data workloads and 4% to 9% for business applications.
  • Cloud-first workload deployments in enterprises are becoming more common with 38% of respondents to a recent 451Research survey stating their enterprises are prioritizing cloud over on-premise.

451 Research’s latest study of cloud computing adoption in the enterprise, The Voice of the Enterprise: Cloud Transformation – Workloads and Key Projects provides insights into how enterprises are changing their adoption of public, private and hybrid cloud for specific workloads and applications. The research was conducted in May and June 2016 with more than 1,200 IT professionals worldwide. The study illustrates how quickly enterprises are adopting cloud-first deployment strategies to accelerate time-to-market of new apps while reducing IT costs and launch new business models that are by nature cloud-intensive. Add to this the need all enterprises have to forecast and track cloud usage, costs and virtual machine (VM) usage and value, and it becomes clear why Amazon Web Services (AWS) and Microsoft Azure are now leaders in the enterprise. The following graphic from Synergy Research Group’s latest study of the Cloud Infrastructure Services provides a comparison of AWS, Microsoft Azure, IBM, Google, and others.

Cloud Infrastructure Services

Seven Ways Microsoft Is Redefining Azure For The Enterprise

Being able to innovate faster by building, deploying and managing applications globally on a single cloud platform is what many enterprises are after today. And with over 100 potential apps on their cloud roadmaps, development teams are evaluating cloud platforms based on their potential contributions to new app development and business models first.

AWS and Microsoft Azure haven proven their ability to support new app development and deployment and are the two most-evaluated cloud platforms with dev teams I’ve talked with today. Of the two, Microsoft Azure is gaining momentum in the enterprise.

Here are the seven ways Microsoft is making this happen:

  • Re-orienting Microsoft Azure Cloud Services strategies so enterprise accounts can be collaborators in new app creation. Only Microsoft is coming at selling Cloud Services in the enterprise from the standpoint of how they can help do what senior management teams at their customers want most, which is make their app roadmap a reality. AWS is excellent at ISV and developer support, setting a standard in this area.
  • Giving enterprises the option of using existing relational SQL databases, noSQL data stores, and analytics services when building new cloud apps. All four dominant cloud platforms (AWS, Azure, Google, and IBM) support architectures, frameworks, tools and programming languages that enable varying levels of compatibility with databases, data stores, and analytics. Enterprises that have a significant amount of their legacy app inventory in .NET are choosing Azure for cloud app development. Microsoft’s support for Node.js, PHP, Python and other development languages is at parity with other cloud platforms. Why Microsoft Azure is winning in this area is the designed-in support for legacy Microsoft architectures that enterprises standardized their IT infrastructure on years before. Microsoft is selling a migration strategy here and is providing the APIs, web services, and programming tools to enable enterprises to deliver cloud app roadmaps faster as a result. Like AWS, Microsoft also has created a global development community that is developing and launching apps specifically aimed at enterprise cloud migration.  Due to all of these factors, both AWS and Microsoft are often considered more open cloud platforms by enterprises than others. In contrast, Salesforce platforms are becoming viewed as proprietary, charging premium prices at renewal time. An example of this strategy is the extra 20% Salesforce charges for Lightning experience at renewal time according to Gartner in their recent report, Salesforce Lightning Sales Cloud and Service Cloud Unilaterally Replaced Older Editions; Negotiate Now to Avoid Price Increases and Shelfware Published 31 May 2016, written by analysts Jo Liversidge, Adnan Zijadic.
  • Simplifying cloud usage monitoring, consolidated views of cloud fees and costs including cost predictions and working with enterprises to create greater cloud standardization and automation. AWS’ extensive partner community has solutions that address each of these areas, and AWS’ roadmap reflects this is a core focus of current and future development. The AWS platform has standardization and automation as design objectives for the platform. Enterprises evaluating Azure are running pilots to test the Azure Usage API, which allows subscribing services to pull usage data. This API supports reporting to the hourly level, resource metadata information, and supports Showback and Chargeback models. Azure deployments in production and pilots I’ve seen are using the API to build web services and dashboards to measure and predict usage and costs.
  • Openly addressing Total Cost of Ownership (TCO) concerns and providing APIs and Web services to avoid vendor lock-in. The question of data independence and TCO dominates sustainability and expansion of all cloud decisions. From the CIOs, CFOs and design teams I’ve spoken with, Microsoft and Amazon are providing enterprises assistance in defining long-term cost models and are willing to pass along the savings from economies of scale achieved on their platforms. Microsoft Azure is also accelerating in the enterprise due to the pervasive adoption of the many cloud-based subscriptions of Office365, which enables enterprises to begin moving their workloads to the cloud.
  • Having customer, channel, and services all on a single, unified global platform to gain greater insights into customers and deliver new apps faster. Without exception, every enterprise I’ve spoken with regarding their cloud platform strategy has multichannel and omnichannel apps on their roadmap. Streamlining and simplifying the customer experience and providing them with real-time responsiveness drive the use cases of the new apps under development today. Salesforce has been successful using their platform to replace legacy CRM systems and build the largest community of CRM and sell-side partners globally today.
  • Enabling enterprise cloud platforms and apps to globally scale. Nearly every enterprise looking at cloud initiatives today needs a global strategy and scale. From a leading telecom provider based in Russia looking to scale throughout Asia to financial services firms in London looking to address Brexit issues, each of these firms’ cloud apps roadmaps is based on global scalability and regional requirements. Microsoft has 108 data centers globally, and AWS operates 35 Availability Zones within 13 geographic Regions around the world, with 9 more Availability Zones and 4 more Regions coming online throughout the next year. To expand globally, Salesforce chose AWS as their preferred cloud infrastructure provider. Salesforce is not putting their IOT and earlier Heroku apps on Amazon. Salesforces’ decision to standardize on AWS for global expansion and Microsoft’s globally distributed data centers show that these two platforms have achieved global scale.
  • Enterprises are demanding more control over their security infrastructure, network, data protection, identity and access control strategies, and are looking for cloud platforms that provide that flexibility. Designing, deploying and maintaining enterprise cloud security models is one of the most challenging aspects of standardizing on a cloud platform. AWS, Azure, Google and IBM all are prioritizing research and development (R&D) spending in this area. Of the enterprises I’ve spoken with, there is an urgent need for being able to securely connect virtual machines (VMs) within a cloud instance to on-premise data centers. AWS, Azure, Google, and IBM can all protect VMs and their network traffic from on-premise to cloud locations. AWS and Azure are competitive to the other two cloud platforms in this area and have enterprises running millions of VMs concurrently in this configuration and often use that as a proof point to new customers evaluating their platforms.

Bottom line: Amazon AWS and Microsoft Azure are the first cloud platforms proving they can scale globally to support enterprises’ vision of world-class cloud app portfolio development.

Sources:

451 Research: The Voice of the Enterprise: Cloud Transformation – Workloads and Key Projects

Gartner Magic Quadrant for Cloud Infrastructure as a Service, Worldwide 2016 Reprint

Microsoft Earnings Release FY16 Q4 – Azure revenue grows 102% year-over-year

Synergy Research Group’s latest study of the Cloud Infrastructure Services

 

5 Ways Brexit Is Accelerating AWS And Public Cloud Adoption

  • London sykline duskDeutsche Bank estimates AWS derives about 15% of its total revenue mix or has attained a $1.5B revenue run rate in Europe.
  • AWS is now approximately 6x the size of Microsoft Azure globally according to Deutsche Bank.

These and other insights are from the research note published earlier this month by Deutsche Bank Markets Research titled AWS/Cloud Adoption in Europe and the Brexit Impact written by Karl Keirstead, Alex Tout, Ross Sandler, Taylor McGinnis and Jobin Mathew.  The research note is based on discussions the research team had with 20 Amazon Web Services (AWS) customers and partners at the recent AWS user conference held in London earlier this month, combined with their accumulated research on public cloud adoption globally.

These are the five ways Brexit will accelerate AWS and public cloud adoption:

  • The proliferation of European-based data centers is bringing public cloud stability to regions experiencing political instability. AWS currently has active regions in Dublin and Frankfurt, with the former often being used by AWS’ European customers due to the broader base of services offered there. An AWS Region is a physical geographic location where there is a cluster of data centers. Each region is made up of isolated locations known as availability zones. AWS is adding a third European Union (EU) region in the UK with a go-live date of late 2016 or early 2017. Microsoft has 2 of its 26 global regions in Europe, with two more planned in the UK.  Google’s Cloud Platform (GCP) has just one region active in Europe. The following Data Center Map provides an overview of data centers AWS, Microsoft Azure and GCP have in Europe today and planned for the future.

Data Center Map

  • Brexit is making data sovereignty king. European-based enterprises have long been cautious about using cloud platforms to store their many forms of data. Brexit is accelerating the needs European enterprises have for greater control over their data, especially those based in the UK.  Amazon’s planned third EU region based in London scheduled to go live in late 2016 or early 2017 is well-timed to capitalize on this trend.
  • Up-front costs of utilizing AWS are much lower and increasingly trusted relative to more expensive on-premise  IT platforms. Brexit is having the immediate effect of slowing down sales cycles for managed hosting, enterprise-wide hardware and software maintenance agreements. The research team found that the uncertainty of just how significant the economic impact Brexit will have on the European economies is making companies tighten capital expense (CAPEX) budgets and trim expensive maintenance agreements.  UK enterprises are reverting to OPEX spending that is already budgeted.
  • CEOs are pushing CIOs to get out of high-cost hardware and on-premise software agreements to better predict operating costs faster thanks to Brexit. The continual pressure on CIOs to reduce the high hardware and software maintenance costs is accelerating thanks to Brexit. Because no one can quantify with precision just how Brexit will impact European economies, CEOs, and senior management teams want to minimize downside risk now. Because of this, the cloud is becoming a more viable option according to Deutsche Bank. One reseller said that public cloud computing platforms are a great answer to a recession, and their clients see Brexit as a catalyst to move more workloads to the cloud.
  • Brexit will impact AWS Enterprise Discount Program (EDP) revenues, forcing a greater focus on incentives for low-end and mid-tier services. Deutsche Bank Markets Research team reports that AWS has this special program in place for its very largest customers. Under an EDP, AWS will give price discounts to large customers that commit to a full year (or more) and pay upfront, in many cases with minimum volume increases. One AWS partner told Deutsche Bank that they’re aware of one EDP payment of $25 million. In the event of a recession in Europe, it’s possible that such payments could be at risk. These market dynamics will drive AWS to promote further low- and mid-tier services to attract new business to balance out these larger deals.

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.

Internet of Things, Machine Learning & Robotics Are High Priorities For Developers In 2016

  • 200213603-00156.4% of developers are building robotics apps today.
  • 45% of developers say that Internet of Things (IoT) development is critical to their overall digital strategy.
  • 27.4% of all developers are building apps in the cloud today.
  • 24.7% are using machine learning for development projects.

These and many other insights are from the Evans Data Corporation Global Development Survey, Volume 1 (PDF, client access) published earlier this month. The methodology was based on interviews with developers actively creating new applications with the latest technologies. The Evans Data Corporation (EDC), International Panel of Developers, were sent invitations to participate and complete the survey online. 1,441 developers completed the survey globally. Please see page 17 of the study for additional details on the methodology.

Key takeaways from the study include the following:

  • Big Data analytics developers are spending the majority of their time creating Internet of Things (IoT).  The second-most popular Big Data analytics applications are in professional, scientific and technical services (10%), telecommunications (10%), and manufacturing (non-computer related) (9.6%). The following graphic provides an overview of where Big Data analytics developers are investing their time building new applications.

Best Describes App

  • Robotics (56.4%), Arts, Entertainment and Recreation (56.3%), and Automotive (52.9%) are the three most popular industries data mining app developers are focusing on today. Additional high priority industries include telecommunications (48.3%), Internet of Things (47.1%) and manufacturing (46.7%). A graphic from the study is shown below for reference.

Data Mining adoption

  • Nearly one-third (27.4%) of all app developers globally are planning to build new apps on the cloud. 66.9% expect to have a new cloud app within 12 months. Overall, 81.3% of all developers surveyed are building cloud apps today. The following graphic compares developers’ predicted timeframes for cloud app development over the next two years.

Plans for Apps In the Clouds

  • Better security (51.9%), more reliability (42%) and better user experience (41%) are the top three areas that motivate developers to move to new cloud platforms. Additional considerations include a better breadth of services (39.4%), networking and data center speed (37.8%), better pricing options (37.5%), better licensing structures (34.6%) and completeness of vision (30.9%). The following graphic compares the key factors that most motivate developers to switch cloud platforms.

key factors

  • 45% of developers say that Internet of Things (IoT) development is very important to their overall digital strategy. 7% say that IoT is somewhat important to their digital strategy. The study also found that 29.5% of all developers are creating Internet of Things (IoT) apps today. The following graphic illustrates the relative level of importance of IoT to developers’ digital strategies.

importance of IoT strategy

  • 41% say that cognitive computing and artificial intelligence (AI) are very important to their digital strategies. In speaking with senior executives at services firms, the opportunity to provide artificial intelligence-based services using a subscription model is gaining momentum, with many beginning to fund development projects to accomplish this on a global scale.

AI Importance

  • Most frequently created machine learning apps include those for the Internet of Things (11.4%), Professional, Scientific and Technical Services (10%), and Manufacturing (9.4%) industries.  Additional industries include telecommunications (8.3%), utilities/energy (8.1%), robotics (7.2%) and finance or insurance (6.8%). The following graphic breaks out the industries where machine learning app development is happening today.

Machine learning industries final

  • The majority of developers (84.2%) say that analytics is important for enabling their organizations to operate today. Of that group, 45.7% say that analytics are very important for their organizations to attain their goals.

2015 Gartner CRM Market Share Update

  • Worldwide customer relationship management (CRM) software totaled $26.3B in 2015, up 12.3% from $23.4B in 2014.
  • SaaS revenue grew 27% yr-over-yr, more than double overall CRM market growth in 2015.
  • Asia/Pacific grew the fastest of all regions globally, increasing 9% 2015, closely followed by greater China with 18.4% growth.

These and many other insights into the current state of the global CRM market are from Gartner’s Market Share Analysis: Customer Relationship Management Software, Worldwide, 2015 (PDF, client access) published earlier this month.  The top five CRM vendors accounted for 45% of the total market in 2015. Salesforce dominated in 2015, with a 21.1% annual growth rate and absolute growth of over $902M in CRM revenue, more than the next ten providers combined. Gartner found that Salesforce leads in revenue in the sales and customer service and support (CSS) segments of CRM, and is now third in revenue in the marketing segment. Gartner doesn’t address how analytics are fundamentally redefining CRM today, which is an area nearly every C-level and revenue team leader I’ve spoken with this year is prioritizing for investment. The following graphic and table compare 2015 worldwide CRM market shares.

CRM Market Share 2015

table 1

Adobe, Microsoft, and Salesforce Are Growing Faster Than The Market

Adobe grew the fastest between 2014 and 2015, increasing worldwide sales 26.9%. Salesforce continues to grow well above the worldwide CRM market average, increasing sales 21.1%. Microsoft increased sales 20% in the last year.  The worldwide CRM market grew 12.3% between 2014 and 2015.

Spending by vendor 2015

 Analytics, Machine Learning, and Artifical Intelligence Are The Future Of CRM

Advanced analytics, machine learning and artificial intelligence (AI) will revolutionize CRM in the next three years. Look to the five market leaders in 2015 to invest heavily in these areas with the goal of building patent portfolios and increasing the amount of intellectual property they own. Cloud-based analytics platforms offer the scale, speed of deployment, agility, and ability to rapidly prototype analytics workflows that support the next generation of CRM workflows. My recent post on SelectHub, Selecting The Best Cloud Analytics Platform: Trends To Watch In 2016, provides insights into how companies with investments in CRM systems are making decisions on cloud platforms today. Based on insights gained from discussions with senior management teams, I’ve put together an Intelligent Cloud Maturity Model that underscores why scalability of a cloud-based analytics platform is a must-have for any company.
cloud-maturity-model

Sources:  Gartner Says Customer Relationship Management Software Market Grew 12.3 Percent

The Era Of The Intelligent Cloud Has Arrived

intelligent cloudBottom line: Enterprises are impatient to translate their investments in cloud apps and the insight they provide into business outcomes and solid results today.

The following insights are based on a series of discussions with C-level executives and revenue team leaders across several industries regarding their need for an Intelligent Cloud:

  • In the enterprise, the cloud versus on-premise war is over, and the cloud has won. Nearly all are embracing a hybrid cloud strategy to break down the barriers that held them back from accomplishing more.
  • None of the C-level executives I’ve spoken with recently are satisfied with just measuring cloud adoption. All are saying the want to measure business outcomes and gain greater insights into how they can better manage revenue and sales cycles.
  • Gaining access to every available legacy and 3rd party system using hybrid cloud strategies is the new normal. Having data that provides enterprise-wide visibility gives enterprises greater control over every aspect of their selling and revenue management processes. And when that’s accomplished, the insights gained from the Intelligent Cloud can quickly be turned into results.

Welcome to the Era of the Intelligent Cloud

The more enterprises seek out insights to drive greater business outcomes, the more it becomes evident the era of the Intelligent Cloud has arrived. C-level execs are looking to scale beyond descriptive analytics that defines past performance patterns.  What many are after is an entirely new level of insights that are prescriptive and cognitive. Getting greater insight that leads to more favorable business outcomes is what the Intelligent Cloud is all about. The following Intelligent Cloud Maturity Model summarizes the maturity levels of enterprises attempting to gain greater insights and drive more profitable business outcomes.

maturity model

 

Why The Intelligent Cloud Now?  

Line-of-business leaders across all industries want more from their cloud apps than they are getting today. They want the ability to gain greater insights with prescriptive and cognitive analytics. They’re also asking for new apps that give them the flexibility of changing selling behaviors quickly.  In short, everyone wants to get to the orchestration layer of the maturity model, and many are stuck staring into a figurative rearview mirror, using just descriptive data to plan future strategies.  The future of enterprise cloud computing is all about being able to deliver prescriptive and cognitive intelligence.
Consider the following takeaways:

 

Who Is Delivering The Intelligent Cloud Today?

Just how far advanced the era of the Intelligent Cloud is became apparent during the Microsoft Build Developer Conference last week in San Francisco.  A fascinating area discussed was Microsoft Cognitive Services and their implications on the Cortana Intelligence Suite. Microsoft is offering a test drive of Cognitive Services here. Combining Cognitive Services and the Cortana Intelligence Suite, Microsoft has created a framework for delivering the Intelligent Cloud. The graphic below shows the Cortana Analytics Suite.
Cortana suite

 

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