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Posts from the ‘Cloud Computing’ Category

Key Takeaways From Gartner’s Market Guide For Configure, Price and Quote (CPQ) Application Suites, 2016

  • NYC SkylineGartner estimates the CPQ application suites market was $570M in 2015, attaining 20% year-on-year growth between 2014 and 2015.
  • Cloud-based CPQ revenue was $157M in 2015, attaining 46% year-over-year.
  • Gartner predicts CPQ will continue to be one of the hottest enterprise apps for the foreseeable future, predicting a 20% annual growth rate through 2020 with the majority being from cloud-based solutions. Legacy on-premise vendors including SAP’s Variant Configurator (VC) are going to face increasingly strong headwinds in the market as a result.
  • SaaS and Cloud solutions are driving the majority of CPQ market growth today, fueling greater innovation in the market.
  • The CPQ market continues to grow as companies replace legacy on-premise CPQ apps and outdated ERP quoting and ordering apps with cloud-based CPQ solutions.

These and many other insights are from the recently published Gartner Market Guide for Configure, Price and Quote Application Suites (PDF, client access required) by Mark David Lewis and Guneet Bharaj on October 27th of this year. CPQ selling strategies are part of the broader Quote-To-Cash (QTC) business process that encompasses, quotes, contracts, order management and billing. CPQ market leaders also are offering solutions that support the creation of quotes and capturing of orders across multiple channels of customer interaction (such as direct sales, contact center, resellers and self-service). Cloud- and SaaS-based CPQ systems scale faster across multiple channels and often have higher adoption rates than their legacy on-premise counterparts due to more intuitive app designs and better integration with Cloud-based Customer Relationship Management (CRM), Sales Force Automation (SFA) and incentives systems.

What makes the Market Guide so noteworthy is that it is the first research piece on CPQ published by a major analyst firm in several years.

Key takeaways from the study include the following:

  • Microsoft Azure and the Salesforce platform are benefiting the most from the intense competition in the CPQ market today. Microsoft Azure is emerging as the enterprise leader from a platform perspective, evidenced by the points made in my previous post, Seven Ways Microsoft Redefined Azure For The Enterprise And Emerged A Leader. Being able to scale globally and provide greater control over security and openly address Total Cost of Ownership (TCO) concerns of enterprises are a few of the many factors driving Azure’s adoption.  Salesforce has gone in a different direction in the CPQ market, choosing to acquire SteelBrick earlier this year. Salesforce in effect became a competitor with its partners in the CPQ market by doing this. According to Gartner, SteelBrick is a good solution for high-tech assemble to order (ATO) and software companies.  Last month Salesforce founder and CEO Marc Benioff was interviewed at the Intel Capital Global Summit, and the video is available here.  At 11 min., 20 seconds, he says that “Steelbrick is not for all customers, so Apttus still has a tremendous opportunity.” Earlier this year Apttus announced their entire QTC suite is now available on Microsoft Dynamics, showing just how critical it is for CPQ engineering teams to move fast from a platform strategy perspective to keep their companies growing.
  • Omnichannel and digital commerce is a high-growth area of CPQ as companies seek to improve buying experiences across all customer-facing channels. For many companies, their omnichannel selling strategies and initiatives are proliferating, driven by how quickly customers are changing the channels they buy through. Leading CPQ and QTC suites are now offering digital commerce and omnichannel apps integrated into their main app platforms. They are having initial success in B2B selling scenarios where self-service configuration is needed.  Gartner mentions Apttus, Oracle CPQ Cloud, and SAP as having the most robust digital commerce offerings today.
  • CPQ vendors are attempting to reinvent themselves by innovating faster and more broadly than before. Relying on machine learning to recommend the optimal incentives, pricing, and terms to close more deals and increase up-sell and cross-sell revenues through guided selling apps is a fascinating area of innovation today. Apttus’ Intelligent Quote-to-Cash Agent Max, Salesforce’s Einstein and others exemplify this area of development. Rapid advances and improvements in visualization, 3D modeling and Configuration Lifecycle Management (CLM) from Configit also illustrate how quickly innovation is changing the landscape. Gartner also mentions intelligent negotiation guidance, mobile configuration support, estimated compensation, verticalization, and deeper integration with back-end fulfillment systems as being additional areas where innovation is redefining the competitive landscape.
  • Improving promotion, incentive and rebate performance across a multitier selling network based on machine learning algorithms is redefining the QTC competitive landscape. Eighteen CPQ vendors are profiled in the market guide, many of them selling into industries that rely on complex multitier distribution, selling and support networks for the majority of their revenue. It’s clear many are moving in the direction of using machine learning to improve the effectiveness of promotions, incentives, and rebates across all selling channels. Being able to provide the best possible incentive to a distributor, dealer or 3rd party sales person defines which manufacturer wins the deal. Look to see more emphasis in this area in 2017 as CPQ vendors work to provide companies with the chance to steer more deals their way in channels they don’t directly control.
  • The CPQ landscape will continue to consolidate as the race for new customers accelerates, driven by the need companies have for improving QTC performance. Gartner mentions how there have been major acquisitions over the last four years including Big Machines being acquired by Oracle, Salesforce acquiring SteelBrick, Configure One acquired by AutoDesk, and Cameleon Software was acquired by Pros. There are many other CPQ vendors privately for sale right now, with all of them looking to find an acquirer or company to merge with who can best complement their core technologies. Look to see the pace of acquisitions accelerate in the next year.
  • I’m looking to see which CPQ vendors further distance themselves from competitors with modern and intuitive user experience design (UX). CPQ, while a necessary foundation piece for B2B use cases is evolving into the broader Quote-to-Cash umbrella. To attain its full market potential, I believe that CPQ vendors must excel at UX across all products and app experiences. I am looking forward to seeing which vendors will invest in modern and intuitive UX to drive this change in the market and deliver great experiences to customers as a result.
  • From the enosiX blog, Key Takeaways From Gartner’s Market Guide For Configure, Price and Quote (CPQ) Application Suites, 2016

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

 

Roundup Of Analytics, Big Data & BI Forecasts And Market Estimates, 2016

  • World map technologyBig Data & business analytics software worldwide revenues will grow from nearly $122B in 2015 to more than $187B in 2019, an increase of more than 50% over the five-year forecast period.
  • The market for prescriptive analytics software is estimated to grow from approximately $415M in 2014 to $1.1B in 2019, attaining a 22% CAGR.
  • By 2020, predictive and prescriptive analytics will attract 40% of enterprises’ net new investment in business intelligence and analytics.

Making enterprises more customer-centric, sharpening focus on key initiatives that lead to entering new markets and creating new business models, and improving operational performance are three dominant factors driving analytics, Big Data, and business intelligence (BI) investments today. Unleashing the insights hidden in unstructured data is providing enterprises with the potential to compete and improve in areas they had limited visibility into before. Examples of these areas include the complexity of B2B selling and service relationships,  healthcare services, and maintenance, repair, and overhaul (MRO) of complex machinery.

Presented below are a roundup of recent analytics and big data forecasts and market estimates:

  • The global big data market will grow from $18.3B in 2014 to $92.2B by 2026, representing a compound annual growth rate of 14.4 percent. Wikibon predicts significant growth in all four sub-segments of big data software through 2026. Data management (14% CAGR), core technologies such as Hadoop, Spark and streaming analytics (24% CAGR), databases (18% CAGR) and big data applications, analytics and tools (23% CAGR) are the four fastest growing sub-segments according to Wikibon. Source: Wikibon forecasts Big Data market to hit $92.2B by 2026.

Wikibon big data forecast 2016

  • In 2015, the Global Analytics and Business Intelligence applications market grew 4% to approach nearly $11.6B in license, maintenance and subscription revenues with SAP maintaining market leadership. SAP led the marketing with 10% market share and $1.2B in Analytics and Business Intelligence (BI) product revenues, riding on a 23% jump in license, maintenance, and subscription revenues. SAS Institute was No. 2 achieving 9% share; IBM was the third at 8%, and Oracle and Microsoft were fourth and fifth place with 7% and 5%, respectively. Source: Apps Run The World: Top 10 Analytics and BI Software Vendors and Market Forecast 2015-2020.

analytics market shares

IDC FutureScape

  • The Total Data market is expected to nearly double in size, growing from $69.6B in revenue in 2015 to $132.3B in 2020. The specific market segments included in 451 Research’s analysis are operational databases, analytic databases, reporting and analytics, data management, performance management, event/stream processing, distributed data grid/cache, Hadoop, and search-based data platforms and analytics. Source: Total Data market expected to reach $132bn by 2020; 451 Research, June 14, 2016.

Worldwide total revenue by segment

overall adoption of big data

  • Improving customer relationships (55%) and making the business more data-focused (53%) are the top two business goals or objectives driving investments in data-driven initiatives today. 78% of enterprises agree that collection and analysis of Big Data have the potential to change fundamentally the way they do business over the next 1 to 3 years. Source: IDG Enterprise 2016 Data & Analytics Research, July 5, 2016.

Data Helps Customer Focused Organizations

  • Venture capital (VC) investment in Big Data accelerated quickly at the beginning of the year with DataDog ($94M), BloomReach ($56M), Qubole ($30M), PlaceIQ ($25M) and others receiving funding. Big Data startups received $6.64B in venture capital investment in 2015, 11% of total tech VC.  M&A activity has remained moderate (FirstMark noted 35 acquisitions since their latest landscape was published last year). Source: Matt Turck’s blog post, Is Big Data Still a Thing? (The 2016 Big Data Landscape).

big data landscape

  • IDC forecasts global spending on cognitive systems will reach nearly $31.3 billion in 2019 with a five-year compound annual growth rate (CAGR) of 55%. More than 40% of all cognitive systems spending throughout the forecast will go to software, which includes both cognitive applications (i.e., text and rich media analytics, tagging, searching, machine learning, categorization, clustering, hypothesis generation, question answering, visualization, filtering, alerting, and navigation). Also included in the forecasts are cognitive software platforms, which enable the development of intelligent, advisory, and cognitively enabled solutions.  Source:  Worldwide Spending on Cognitive Systems Forecast to Soar to More Than $31 Billion in 2019, According to a New IDC Spending Guide.
  • Big Data Analytics & Hadoop Market accounted for $8.48B in 2015 and is expected to reach $99.31B by 2022 growing at a CAGR of 42.1% from 2015 to 2022. The rise of big data analytics and rapid growth in consumer data capture and taxonomy techniques are a few of the many factors fueling market growth. Source: Stratistics Market Research Consulting (PDF, opt-in, payment reqd).

Additional sources of market information: 

Analytics Trends 2016 The Next Evolution, Deloitte.

Big data analytics, Ericsson White Paper Uen 288 23-3211 Rev B | October 2015

Big Data and the Intelligence Economy in Canada Big Data: Big Opportunities to Create Business Value, EMC.

The Forrester Wave™: Big Data Hadoop Distributions, Q1 2016

The Forrester Wave™: Big Data Hadoop Cloud Solutions, Q2 2016

The Forrester Wave™: Big Data Text Analytics Platforms, Q2 2016

The Forrester Wave™: Big Data Streaming Analytics, Q1 2016

The Forrester Wave™: Customer Analytics Solutions, Q1 2016

From Big Data to Better Decisions: The ultimate guide to business intelligence today (Domo)

Gartner Hype Cycle for Business Intelligence and Analytics, 2015

IBM: Extracting business value from the 4 V’s of big data

IDC Worldwide Big Data Technology and Services 2012 – 2015 Forecast

Opportunities in Telecom Sector: Arising from Big Data. Deloitte, November 2015

Who will win as Finance doubles down on analytics?

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.

Internet Of Things Will Replace Mobile Phones As Most Connected Device In 2018

  • abstract, background, banner, telecoms, communication, innovation, concept, design, icon, internet of things, internet, computer, innovate, innovative, ball, circle, sphere, circular, social, data, access, wireless, connection, pattern, global, world map, networking, hexagon, circuit, electric, electronics, microchip, power, gradient, blue, vector, illustration, logo,Internet of Things (IoT) sensors and devices are expected to exceed mobile phones as the largest category of connected devices in 2018, growing at a 23% compound annual growth rate (CAGR) from 2015 to 2021.
  • By 2021 there will be 9B mobile subscriptions, 7.7B mobile broadband subscriptions, and 6.3B smartphone subscriptions.
  • Worldwide smartphone subscriptions will grow at a 10.6% CAGR from 2015 to 2012 with Asia/Pacific (APAC) gaining 1.7B new subscribers alone.

These and other insights are from the 2016 Ericcson Mobility Report (PDF, no opt-in). Ericcson has provided a summary of the findings and a series of interactive graphics here. Ericcson created the subscription and traffic forecast baseline this analysis is based on using historical data from a variety of internal and external sources. Ericcson also validated trending analysis through the use of their planning models. Future development is estimated based on macroeconomic trends, user trends (researched by Ericsson ConsumerLab), market maturity, technology development expectations and documents such as industry analyst reports, on a national or regional level, together with internal assumptions and analysis.In addition, Ericsson regularly performs traffic measurements in over 100 live networks in all major regions of the world. For additional details on the methodology, please see page 30 of the study.

Key takeaways from the 2016 Ericcson Mobility Report include the following:

  • Internet of Things (IoT) sensors and devices are expected to exceed mobile phones as the largest category of connected devices in 2018, growing at a 23% compound annual growth rate (CAGR) from 2015 to 2021. Ericcson predicts there will be a total of approximately 28B connected devices worldwide by 2021, with nearly 16B related to IoT. The following graphic compares cellular IoT, non-cellular IoT, PC/laptop/tablet, mobile phones, and fixed phones connected devices growth from 2015 to 2021.

Internet of Things Forecast

  • 400 million IoT devices with cellular subscriptions were active at the end of 2015, and Cellular IoT is expected to have the highest growth among the different categories of connected devices, reaching 1.5B connections in 2021. Ericcson cites the growth factors of 3GPP standardization of cellular IoT technologies and cellular connections benefitting from enhancements in provisioning, device management, service enablement and security. The forecast for IoT connected devices: cellular and non-cellular (billions) is shown

IoT Connected Devices

  • Global mobile broadband subscriptions will reach 7.7B by 2021, accounting for 85% of all subscriptions. Ericcson is predicting there will be 9B mobile subscriptions, 7.7B mobile broadband subscriptions, and 6.3B smartphone subscriptions by 2021 as well. The following graphic compares mobile subscriptions, mobile broadband, mobile subscribers, fixed broadband subscriptions, and mobile CPs, tablets and mobile routers’ subscription growth.

mobile subscription growth

  • Worldwide smartphone subscriptions will grow at a 10.6% compound annual growth rate (CAGR) from 2015 to 2012. Ericcson predicts that the Asia/Pacific (APAC) region will gain 1.7B new subscribers. The Middle East and Africa will have smartphone subscription rates will increase more than 200% between 2015–2021. The following graphic compares growth by global region.

smartphone subscriptions

  • Mobile subscriptions are growing around 3% year-over-year globally and reached 7.4B in Q1 2016. India is the fastest growing market regarding net additions during the quarter (+21 million), followed by Myanmar (+5 million), Indonesia, (+5 million), the US (+3 million) and Pakistan (+3 million). The following graphic compares mobile subscription growth by global region for Q1, 2016.

Mobile subscriptions Q1

  • 90% of subscriptions in Western Europe and 95% in North America will be for LTE/5G by 2021. The Middle East and Africa will see a dramatic shift from 2G to a market where almost 80% of subscriptions will be for 3G/4G. The following graphic compares mobile subscriptions by region and technology.

Mobile technology by region

  • Mobile video traffic is forecast to grow by around 55% annually through 2021, accounting for nearly 67% of all mobile data traffic. Social networking traffic is predicted to attain a 41% CAGR from 2015 to 2021. The following graphic compared the growth of mobile traffic by application category and projected mobile traffic by application category per month.

mobile video traffic

  • Ericcson also provided mobile subscription, traffic per device, mobile traffic growth forecast, and monthly data traffic per smartphone. The summary table is shown below:

summary table

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.

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