Posts tagged ‘SaaS ERP’

Mar 30

10 Ways Machine Learning Is Revolutionizing Manufacturing In 2018

Improving semiconductor manufacturing yields up to 30%, reducing scrap rates, and optimizing fab operations is achievable with machine learning.
Reducing supply chain forecasting errors by 50% and lost sales by 65% with better product availability is achievable with machine learning.
Automating quality testing using machine learning is increasing defect detection rates up to 90%.

Bottom line: Machine learning algorithms, applications, and platforms are helping manufacturers find new business models, fine-tune product quality, and optimize manufacturing operations to the shop floor level.

Manufacturers care most about finding new ways to grow, excel at product quality while still being able to take on short lead-time production runs from customers. New business models often bring the paradox of new product lines that strain existing ERP, CRM and PLM systems by the need always to improve time-to-customer performance. New products are proliferating in manufacturing today, and delivery windows are tightening. Manufacturers are turning to machine learning to improve the end-to-end performance of their operations and find a performance-based solution to this paradox.

The ten ways machine learning is revolutionizing manufacturing in 2018 include the following:

Improving semiconductor manufacturing yields up to 30%, reducing scrap rates, and optimizing fab operations are is achievable with machine learning. Attaining up to a 30% reduction in yield detraction in semiconductor manufacturing, reducing scrap rates based on machine learning-based root-cause analysis and reducing testing costs using AI optimization are the top three areas where machine learning will improve semiconductor manufacturing. McKinsey also found that AI-enhanced predictive maintenance of industrial equipment will generate a 10% reduction in annual maintenance costs, up to a 20% downtime reduction and 25% reduction in inspection costs. Source: Smartening up with Artificial Intelligence (AI) – What’s in it for Germany and its Industrial Sector? (52 pp., PDF, no opt-in) McKinsey & Company.

Asset Management, Supply Chain Management, and Inventory Management are the hottest areas of artificial intelligence, machine learning and IoT adoption in manufacturing today. The World Economic Forum (WEF) and A.T. Kearney’s recent study of the future of production find that manufacturers are evaluating how combining emerging technologies including IoT, AI, and machine learning can improve asset tracking accuracy, supply chain visibility, and inventory optimization. Source: Technology and Innovation for the Future of Production: Accelerating Value Creation (38 pp., PDF, no opt-in) World Economic Forum with A.T. Kearney.

Manufacturer’s adoption of machine learning and analytics to improve predictive maintenance is predicted to increase 38% in the next five years according to PwC. Analytics and MI-driven process and quality optimization are predicted to grow 35% and process visualization and automation, 34%. PwC sees the integration of analytics, APIs and big data contributing to a 31% growth rate for connected factories in the next five years. Source: Digital Factories 2020: Shaping the future of manufacturing (48 pp., PDF, no opt-in) PriceWaterhouseCoopers

McKinsey predicts machine learning will reduce supply chain forecasting errors by 50% and reduce lost sales by 65% with better product availability. Supply chains are the lifeblood of any manufacturing business. Machine learning is predicted to reduce costs related to transport and warehousing and supply chain administration by 5 to 10% and 25 to 40%, respectively. Due to machine learning, overall inventory reductions of 20 to 50% are possible. Source: Smartening up with Artificial Intelligence (AI) – What’s in it for Germany and its Industrial Sector? (52 pp., PDF, no opt-in) McKinsey & Company.

Improving demand forecast accuracy to reduce energy costs and negative price variances using machine learning uncovers price elasticity and price sensitivity as well. Honeywell is integrating AI and machine-learning algorithms into procurement, strategic sourcing and cost management. Source: Honeywell Connected Plant: Analytics and Beyond. (23 pp., PDF, no opt-in) 2017 Honeywell User’s Group.

Automating inventory optimization using machine learning has improved service levels by 16% while simultaneously increasing inventory turns by 25%. AI and machine learning constraint-based algorithms and modeling are making it possible scale inventory optimization across all distribution locations, taking into account external, independent variables that affect demand and time-to-customer delivery performance. Source: Transform the manufacturing supply chain with Multi-Echelon inventory optimization, Microsoft, March 1, 2018.

Combining real-time monitoring and machine learning is optimizing shop floor operations, providing insights into machine-level loads and production schedule performance. Knowing in real-time how each machine’s load level impacts overall production schedule performance leads to better decisions managing each production run. Optimizing the best possible set of machines for a given production run is now possible using machine learning algorithms. Source: Factories of the Future: How Symbiotic Production Systems, Real-Time Production Monitoring, Edge Analytics and AI Are Making Factories Intelligent and Agile, (43 pp., PDF, no opt-in) Youichi Nonaka, Senior Chief Researcher, Hitachi R&D Group and Sudhanshu Gaur Director, Global Center for Social Innovation Hitachi America R&D

Improving the accuracy of detecting costs of performance degradation across multiple manufacturing scenarios reduces costs by 50% or more. Using real-time monitoring technologies to create accurate data sets that capture pricing, inventory velocity, and related variables gives machine learning apps what they need to determine cost behaviors across multiple manufacturing scenarios. Source: Leveraging AI for Industrial IoT (27 pp., PDF, no opt-in) Chetan Gupta, Ph.D. Chief Data Scientist, Big Data Lab, Hitachi America Ltd. Date: Sept. 19th, 2017

A manufacturer was able to achieve a 35% reduction in test and calibration time via accurate prediction of calibration and test results using machine learning. The project’s goal was to reduce test and calibration time in the production of mobile hydraulic pumps. The methodology focused on using a series of machine learning models that would predict test outcomes and learn over time. The process workflow below was able to isolate the bottlenecks, streamlining test and calibration time in the process. Source: The Value Of Data Science Standards In Manufacturing Analytics (13 pp., PDF, no opt-in) Soundar Srinivasan, Bosch Data Mining Solutions And Services

Improving yield rates, preventative maintenance accuracy and workloads by the asset is now possible by combining machine learning and Overall Equipment Effectiveness (OEE). OEE is a pervasively used metric in manufacturing as it combines availability, performance, and quality, defining production effectiveness. Combined with other metrics, it’s possible to find the factors that impact manufacturing performance the most and least. Integrating OEE and other datasets in machine learning models that learn quickly through iteration are one of the fastest growing areas of manufacturing intelligence and analytics today. Source: TIBCO Manufacturing Solutions, TIBCO Community, January 30, 2018

Additional reading:

Artificial Intelligence (AI) Delivering Breakthroughs in Industrial IoT (26 pp., PDF, no opt-in) Hitachi

Artificial Intelligence and Robotics and Their Impact on the Workplace (120 pp., PDF, no opt-in) IBA Global Employment Institute

Artificial Intelligence: The Next Digital Frontier? (80 pp., PDF, no opt-in) McKinsey and Company

Big Data Analytics for Smart Manufacturing: Case Studies in Semiconductor Manufacturing (20 pp., PDF, no opt-in), Applied Materials, Applied Global Services

Connected Factory and Digital Manufacturing: A Competitive Advantage, Shantanu Rai, HCL Technologies (36 pp., PDF, no opt-in)

Demystifying AI, Machine Learning, and Deep Learning, DZone, AI Zone

Digital Factories 2020: Shaping the future of manufacturing (48 pp., PDF, no opt-in) PriceWaterhouseCoopers

Emerging trends in global advanced manufacturing: Challenges, Opportunities, And Policy Responses (76 pp., PDF, no opt-in) University of Cambridge

Factories of the Future: How Symbiotic Production Systems, Real-Time Production Monitoring, Edge Analytics and AI Are Making Factories Intelligent and Agile, (43 pp., PDF, no opt-in) Youichi Nonaka, Senior Chief Researcher, Hitachi R&D Group and Sudhanshu Gaur Director, Global Center for Social Innovation Hitachi America R&D

Get started with the Connected factory preconfigured solution, Microsoft Azure

Honeywell Connected Plant: Analytics and Beyond. (23 pp., PDF, no opt-in) 2017 Honeywell User’s Group.

Impact of the Fourth Industrial Revolution on Supply Chains (22 pp., PDF, no opt-in) World Economic Forum

Leveraging AI for Industrial IoT (27 pp., PDF, no opt-in) Chetan Gupta, Ph.D. Chief Data Scientist, Big Data Lab, Hitachi America Ltd. Date: Sept. 19th, 2017

Machine Learning & Artificial Intelligence Presentation (14 pp., PDF, no opt-in) Erik Hjerpe Volvo Car Group

Machine Learning Techniques in Manufacturing Applications & Caveats, (44 pp., PDF, no opt-in), Thomas Hill, Ph.D. | Exec. Director Analytics, Dell

Machine learning: the power and promise of computers that learn by example (128 pp., PDF, no opt-in) Royal Society UK

Predictive maintenance and the smart factory (8 pp., PDF, no opt-in) Deloitte

Priore, P., Gómez, A., Pino, R., & Rosillo, R. (2014). Dynamic scheduling of manufacturing systems using machine learning: An updated review. Ai Edam, 28(1), 83-97.

Smartening up with Artificial Intelligence (AI) – What’s in it for Germany and its Industrial Sector? (52 pp., PDF, no opt-in) McKinsey & Company

Technology and Innovation for the Future of Production: Accelerating Value Creation (38 pp., PDF, no opt-in) World Economic Forum with A.T. Kearney

The Future of Manufacturing; Making things in a changing world (52 pp., PDF, no opt-in) Deloitte University Press

The transformative potential of AI in the manufacturing industry, Microsoft, by Sanjay Ravi, Managing Director, Worldwide Discrete Manufacturing, Microsoft, September 25, 2017

The Value Of Data Science Standards In Manufacturing Analytics (13 pp., PDF, no opt-in) Soundar Srinivasan, Bosch Data Mining Solutions And Services

TIBCO Manufacturing Solutions, TIBCO Community, January 30, 2018

Transform the manufacturing supply chain with Multi-Echelon inventory optimization, Microsoft, March 1, 2018.

Turning AI into concrete value: the successful implementers’ toolkit (28 pp., PDF, no opt-in) Capgemini Consulting

Wuest, T., Weimer, D., Irgens, C., & Thoben, K. D. (2016). Machine learning in manufacturing: advantages, challenges, and applications. Production & Manufacturing Research, 4(1), 23-45.

Jan 13

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By 2020 83% Of Enterprise Workloads Will Be In The Cloud

Digitally transforming enterprises (63%) is the leading factor driving greater public cloud engagement or adoption today.
66% of IT professionals say security is their most significant concern in adopting an enterprise cloud computing strategy.
50% of IT professionals believe artificial intelligence and machine learning are playing a role in cloud computing adoption today, growing to 67% by 2020.
Artificial Intelligence (AI) and Machine Learning will be the leading catalyst driving greater cloud computing adoption by 2020.

These insights and findings are from LogicMonitor’s Cloud Vision 2020: The Future of the Cloud Study (PDF, free, opt-in, 9 pp.). The survey is based on interviews with approximately 300 influencers LogicMonitor interviewed in November 2017. Respondents include Amazon Web Services AWS re:Invent 2017 attendees, industry analysts, media, consultants and vendor strategists. The study’s primary goal is to explore the landscape for cloud services in 2020. While the study’s findings are not statistically significant, they do provide a fascinating glimpse into current and future enterprise cloud computing strategies.

Key takeaways include the following:

83% Of Enterprise Workloads Will Be In The Cloud By 2020. LogicMonitor’s survey is predicting that 41% of enterprise workloads will be run on public cloud platforms (Amazon AWS, Google Cloud Platform, IBM Cloud, Microsoft Azure and others) by 2020. An additional 20% are predicted to be private-cloud-based followed by another 22% running on hybrid cloud platforms by 2020. On-premise workloads are predicted to shrink from 37% today to 27% of all workloads by 2020.

Digitally transforming enterprises (63%) is the leading factor driving greater public cloud engagement or adoption followed by the pursuit of IT agility (62%). LogicMonitor’s survey found that the many challenges enterprises face in digitally transforming their business models are the leading contributing factor to cloud computing adoption. Attaining IT agility (62%), excelling at DevOps (58%), mobility (55%), Artificial Intelligence (AI) and Machine Learning (50%) and the Internet of Things (IoT) adoption (45%) are the top six factors driving cloud adoption today. Artifical Intelligence (AI) and Machine Learning are predicted to be the leading factors driving greater cloud computing adoption by 2020.

66% of IT professionals say security is their greatest concern in adopting an enterprise cloud computing strategy. Cloud platform and service providers will go on a buying spree in 2018 to strengthen and harden their platforms in this area. Verizon (NYSE:VZ) acquiring Niddel this week is just the beginning. Niddel’s Magnet software is a machine learning-based threat-hunting system that will be integrated into Verizon’s enterprise-class cloud services and systems. Additional concerns include attaining governance and compliance goals on cloud-based platforms (60%), overcoming the challenges of having staff that lacks cloud experience (58%), Privacy (57%) and vendor lock-in (47%).

Just 27% of respondents predict that by 2022, 95% of all workloads will run in the cloud. One in five respondents believes it will take ten years to reach that level of workload migration. 13% of respondents don’t see this level of workload shift ever occurring. Based on conversations with CIOs and CEOs in manufacturing and financial services industries there will be a mix of workloads between on-premise and cloud for the foreseeable future. C-level executives evaluate shifting workloads based on each systems’ contribution to new business models, cost, and revenue goals in addition to accelerating time-to-market.

Microsoft Azure and Google Cloud Platform are predicted to gain market share versus Amazon AWS in the next three years, with AWS staying the clear market leader. The study found 42% of respondents are predicting Microsoft Azure will gain more market share by 2020. Google Cloud Platform is predicted to also gain ground according to 35% of the respondent base. AWS is predicted to extend its market dominance with 52% market share by 2020.

Dec 22

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Five Key Take-Aways From North Bridge’s Future Of Cloud Computing Survey, 2015

SaaS is the most pervasive cloud technology used today with a presence in 77.3% of all organizations, an increase of 9% since 2014.
IT is moving significant processing to the cloud with 85.9% of web content management, 82.7% of communications, 80% of app development and 78.9% of disaster recovery now cloud-based.
Seeking simple and clear relationships, over 50% of enterprises opt for online purchasing or direct to provider purchasing of cloud services. Online buying is projected to increase over the next two years up to 56%.
Vendor leadership/consolidation continues to take hold with 75% of enterprises using fewer than ten

These and many other insights are from North Bridge Growth Equity and Venture Partners’ Future of Cloud Computing Survey published on December 15^th. North Bridge and Wikibon collaborated on the study, interviewing 952 companies across 38 different nations, with 65% being from the vendor community and 35% of enterprises evaluating and using cloud technologies in their operations The slide deck is accessible on SlideShare here:

Key takeaways from the study include the following:

Wikibon forecasts the SaaS is worth $53B market today and will grow at an 18% Compound Annual Growth Rate (CAGR) from 2014 to 2026. By 2026, the SaaS market will be worth $298.4B according to the Wikibon forecast. The fastest growing cloud technology segment is Platform-as-a-Service (PaaS), which is valued at $2.3B today, growing at a CAGR of 38% from 2014 to 2026. Infrastructure-as-a-Service (IaaS) has a market value of $25B and is growing at a 19% CAGR in the forecast period. Please see the graphic from the report below and a table from Wikibon’s excellent study, Public Cloud Market Forecast 2015-2026 by Ralph Finos published in August.

Cloud-based applications are becoming more engrained in core business processes across enterprises. The study found that enterprises are migrating significant processing, systems of engagement and systems of insight to the cloud beyond adoption levels of the past. 81.3% of sales and marketing, 79.9% of business analytics, 79.1% of customer service and 73.5% of HR & Payroll activities have transitioned to the cloud. The impact on HR is particularly noteworthy as in 2011; it was the third least likely sector to be disrupted by cloud computing.

78% of enterprises expect their SaaS investments to deliver a positive Return on Investment (ROI) in less than three months. 58% of those enterprises who have invested in Platform-as-a-Service (PaaS) expect a positive ROI in less than three months.

Top inhibitors to cloud adoption are security (45.2%), regulatory/compliance (36%), privacy (28.7%), lock-in (25.8%) and complexity (23.1%). Concerns regarding interoperability and reliability have fallen off significantly since 2011 (15.7% and 9.9% respectively in 2015).

Total private financing for cloud and SaaS startup has increased 4X over the last five years. North Bridge and Wikibon found that average deal size rose 1.8X in the same period. The following graphic provides an overview of cloud and SaaS finance trends from 2010 to present.

Oct 24

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The Hottest Cloud-based Marketing Startups of 2015

Apttus, Booker, Lattice Engines, Segment and Tubular Labs are the five hottest cloud-based marketing startups of 2015.
13 of the hottest 34 cloud-based marketing startups are from the Bay Area, followed by Los Angeles with 3, and Bangalore and New York, both with 2.
14 are in Pre Series A, 7 in A-Stage, 5 in B-Stage and 3 in C-Stage funding rounds.

These and other insights are from a quick analysis completed today using Mattermark Pro, in response to reader requests for more research on marketing startups.

Mattermark uses a combination of artificial intelligence and data quality analysis to provide insights into over 1 million private companies, over 470,000 with employee data, and over 100,000 funding events. In the interest of full disclosure I’m not today and have never done any consulting work of any kind with Mattermark.

Finding The Hottest Cloud-based Marketing Startups

To find the hottest cloud-based marketing startups, an initial query requesting startups competing in the cloud computing and marketing industries was completed. Next, advanced query tools in Mattermark Pro were used to filter out all startups that had exited as indicated by their stage status in Mattermark’s data. This filtered out startups who had been acquired, completed an IPO or had exited through other means. The table below is the result of an analysis completed today with Mattermark data. You can download the table here in Microsoft Excel format.

The Mattermark Growth Score shown in the table below and downloadable Excel file is a measure of how quickly a company is gaining traction at a given point in time. It incorporates the Mindshare Score (web traffic, social traction) as well as business growth metrics (e.g. employee count over time, funding). The underlying assumption is that companies who see growth across these signals are shipping product and talking to customers, and are more likely to continue to grow as a result. This score is not meant to provide guidance on which startup to invest in. Rather it’s a measure of momentum across the metrics and KPIs that Mattermark measures.

Oct 16

Gartner Top 10 Strategic Technology Trends For 2016

Gartner announced their top 10 strategic technology trends for 2016 at the Gartner Symposium/ITxpo held October 4 – 8^th in Orlando. David Cearley, Vice President and Gartner Fellow, presented the company’s Top Ten Strategic Technology Trends for 2016. You can find the video here.

Key take-aways from his presentation and the trends announced are provided below:

Enterprise 3D-printing shipments will attain a 64.1% Compound Annual Growth Rate (CAGR) through 2019. David Cearley mentioned during his keynote that jet engines are being 3D printed today. He gave the example to illustrate that 3D printing will continue to gain adoption in more demanding manufacturing environments including aerospace, automotive, energy, medical devices and military-based markets and industries.

Emergence of an entirely new class of business models based on smart machine technologies, advanced analytics and big data. Combining machine learning, continued adoption of Internet of Things (IoT) sensors and supporting data models, and advanced intelligence to interpret and act on the data, Gartner’s predictions set the stage of an entirely new class of business models. Manufacturing-as-a-Service and paying only for the production time used in a factory are within reach for more companies than before based on these predictions.

The device mesh will expand to include IoT-based devices that scale well beyond the enterprise. Gartner is predicting that in the next three years traditional computing and communication devices, including desktop and mobile devices will increasingly be augmented by wearable devices, home electronics including appliances with sensors, transportation-based sensors and data collection devices, and environmental devices all capable of capturing data in real-time.

A digital mesh will continue to proliferate, aligning apps and devices to individuals’ specific roles and tasks. Gartner sees this digital mesh as an expanding series of devices, services, platforms, informational networks and individuals that integrate together and provide contextual intelligence and enabling greater collaboration. The proliferation of the digital mesh will lead to more ambient, contextually intelligent and intuitive app design over time Gartner predicts.

The next twelve months will also see the proliferation of algorithm-based businesses enabling automated background tasks including smart machines. Gartner’s technology trends for 2016 set a solid foundation for the growth of globally-based smart factories and production centers. Acumatica, Plex Systems and other Cloud ERP providers are ideally positioned for this trend, having proven their ability to provide manufacturing intelligence from the shop floor to the top floor. In addition to cloud platforms, these algorithm-based businesses will need to support unstructured data analysis including latent semantic indexing (LSI), data taxonomy and classification algorithms to ensure data fidelity and scalability, and more robust analytics and predictive modeling systems.

Combining algorithms, analytics, data architectures and smart machines have the potential to revolutionize manufacturing quickly. General Electric’s Predix platform, IBM’s IoT Foundation and several other cloud-based IoT platforms are already making progress on transforming the vision of algorithm-based smart machine production strategies into a reality for manufacturers globally.

Gartner sees a new IT reality taking shape. Adaptive security, advanced systems, Internet of Things (IoT), mesh app & service architectures are the catalysts of the new nature of IT that Gartner is predicting.

A graphic illustrating the top 10 strategic trends is show below:

Sources:

Gartner Identifies the Top 10 Strategic Technology Trends for 2016. Press Release Announcement, October 6, 2015.

Video replay of the keynote: The Top 10 Strategic Technology Trends for 2016

Sep 26

Cloud Computing Dominates Deloitte’s 2015 Global Venture Capital Confidence Survey

Cloud computing is the strongest technology investment sector for the third year in a row.
Biopharmaceuticals and robotics are the two sectors that have gained the greatest venture capital confidence from 2014 to 2015.
U.S. technology hubs (Silicon Valley/San Francisco, New York, Boston, Los Angeles & Chicago), Israel and Canada dominate while confidence continues to fall in Brazil and other emerging markets.

These and other insights are from Deloitte’s 2015 Global Venture Capital Confidence Survey. You can download a copy here (PDF, no opt-in, 70 pp.). Deloitte has also produced and made available infographics of the key findings here (PDF, no opt-in, 4 pp.). Deloitte & Touche LLP and the National Venture Capital Association (NVCA) collaborated on the eleventh annual survey, which was conducted in May & June of this year. The study assesses investor confidence in the global venture capital environment, market factors shaping industries and investments on specific geographies and industry sectors. Please see page 4 of the study for a description of the methodology.

Key take-aways include the following:

Global venture capital investors are most confident in cloud computing (4.18). Investors were asked to rate their confidence level in each sector. Confidence levels were measured on a scale of 1 to 5, with 5 representing the most confidence. Basis points indicate year-over-year changes. Mobile (4.05), Internet of Things (3.95) and enterprise software (3.82) are the top four sectors venture capitalists are the most confident in today. Biopharmaceuticals are experiencing the greatest increase in venture capital confidence today. Please the the graphic below for additional details.

The United States (4.17), Israel (3.90) and Canada (3.60) dominate venture capital investors’ confidence while emerging markets including Brazil continues to fall. U.S. technology hubs including Silicon Valley/San Francisco, New York, Boston, Los Angeles and Chicago continue to retain and reinforce global venture capital investor confidence. The following graphic illustrates global venture capital investor’s confidence by nation.

Silicon Valley/San Francisco (4.28), New York (3.86) and Boston (3.77) are the top three U.S. metros global venture capital investors have the greatest confidence in. Los Angeles (3.43) and Chicago (3.22) are the fourth and fifth most trusted U.S. metros that venture capitalists have confidence in. $15.2B was invested by global venture capital investors in Silicon Valley/San Francisco according to the Deloitte study. The following graphic compares venture capitalist confidence levels and venture capital investment dollars received in 2015 through Q2.

Immigration reform (61%) and patent demand reform (36%) are the top two initiatives U.S.-based venture capitalists want addressed by policy leaders. For non-U.S. venture capitalists, tax incentives/credits (50%), infrastructure and job creation (both 41%) are the top two initiatives they would like to see public policy leaders take on in their home country.

top two

Cloud computing continues across all sectors as the area global venture capital investors have the greatest confidence in. Confidence in biopharmaceuticals grew the fastest of any sector measured by the survey between 2014 and 2015, and this is the first year Deloitte is tracking investor confidence in the Internet of Things (IoT). A sector comparison is provided below.

May 12

2013 ERP Market Share Update: SAP Solidifies Market Leadership

SAP Headquarters, Building 1 Source: Wikipedia

During 2012 the Enterprise Resource Planning (ERP) market experienced sluggish growth of just 2.2%, yet Software-as-a-Service (SaaS), financial management and Human Capital Management (HCM) applications showed potential for breakout growth.

Through the challenging times of the previous year however, SAP still retained worldwide market share leadership. These and other insights were recently published in the recent report, Market Share Analysis: ERP Software Worldwide, 2012 authored by Chris Pang, Yanna Dharmasthira, Chad Eschinger, Koji Motoyoshi and Kenneth F. Brant.

Key Take-Aways

Overall market growth of just 2.2% and the top ten vendors owning 64% of the worldwide ERP market is leading Gartner to predict further consolidation of the industry.
SAP had just over $6B in total ERP software revenue in 2012, leading the worldwide market with 24.6% market share. Oracle had $3.12B and Sage, $1.5B in software revenues for 2012. Oracle’s market share was 12.8%, and Sage, 6.3%. The following graphic shows worldwide ERP market share for 2012.

Infor achieved 49.5% revenue growth in 2012, increasing their 2011 sales from $1B in 2011 to $1.5B in 2012. Their market share increased from 4.2% in 2011 to 6.2% in 2012.
Microsoft achieved 4.2% revenue growth in 2012, increasing revenue from $1B in 2011 to $1.1B in 2012. The majority of these sales are for the Microsoft Dynamics AX ERP system.
The fastest growing ERP vendors in 2012 include Workday, Cornerstone OnDemand, WorkForce Software, Ventyx and NetSuite.
Workday grew 114.7% in 2012, increasing revenue from $88.6M in 2011 to $190.3M in 2012.
Cornerstone OnDemand grew 61.5% in 2012, increasing revenue from $58.4M in 2011 to $94.3 in 2012.
WorkForce Software grew 39.8% in 2012, increasing revenue from $11.8M in 2011 to $16.5M in 2012.
NetSuite grew 34% in 2012, increasing revenue from $139.7M in 2011 to $187.1M in 2012.
SaaS-based ERP revenues are projected to grow from 12% worldwide in 2013 to 17% in 2017. The following graphic from the report Gartner’s Market Trends: SaaS’s Varied Levels of Cannibalization to On-Premises Applications published: 29 October 2012 shows this progression. You can find a research roundup at the previous post SaaS Adoption Accelerates, Goes Global in the Enterprise, which provides additional insights into which factors are driving SaaS adoption.

Bottom line: SAP’s continued market dominance depends on how well the company orchestrates it core ERP strategy with the following areas: BusinessObjects 4.0, its highly regarded analytics suite; social application adoption (StreamWorks and SuccessFactors Jam); the many Cloud-based initiatives they have including SuccessFactors and BusinessbyDesign; mobility platform wins; and major wins with their SAP Sybase DBMS and HANA architectures.

Mar 1

How Cloud Computing Is Redefining the M&A Landscape

In 2013, expect to see the pace of mergers and acquisitions for cloud computing, mobile and analytics technologies accelerate as software vendors look to fill gaps in their product and service strategies. This and other key insights of how cloud computing is reshaping the merger and acquisition landscape can be found in the latest Price Waterhouse Coopers (PwC) report published today.

The US Technology M&A insights: Analysis and Trends in US Technology M&A Activity 2013 provides an excellent overview of merger, acquisitions, private equity, divestures, cross-border transactions across the five key industry sectors. The report, free for download, covers the Internet, IT Services, hardware and networking, software, and semiconductor sectors.

Enterprise Software Players: In Search of Sticky Revenue and Higher Margins

The major catalysts driving cloud deals forward in 2013 are enterprise software companies’ need to redefine their business models and find sources of sticky revenue that can replace for many of them, dwindling maintenance revenue streams. Knowing that the annuity model of cloud computing works best with multiyear payments required at the beginning of a customer engagement, enterprise software companies are looking to strengthen this area of their product portfolios. Third, the faster cloud acquisitions can be integrated into their legacy systems, the more upsell can be achieved with their large installed bases of customers. The greatest challenge many of them face however is selling entirely new cloud applications to entirely new customers they’ve never sold to before. The potential of these entirely new markets however is going to be a valuation multiplier in 2013 and beyond.

Here are the key take-aways from PwC’s report:

Software and Internet deals represented 57% of transactions closed in 2012, a figure that PwC has seen steadily grow over the last two years. Cumulative value for software and Internet deals represented 53% of total 2012 deal value, an increase from 51% in 2011. Software deals represented over a third of 2012 technology deals, generating 35% of deal volume and 36% of deal value for the year A comparison of both years and technology sectors are shown in the following graphic:

PwC takes a cautionary, conservative tone in this report showing how overall IT spending growth finished the year at an anemic 1.2% while technology deal volumes and values dropped by just under 20% from the prior year.
The report cites Gartner and Forrester’s optimistic IT spending forecasts for IT growth predicting a recovery in 2013 followed by accelerating growth in 2014 according to Forrester.
PwC is seeing SaaS, mobile devices, analytics and Big Data as the drivers of current and future M&A growth and a fundamental shift in deal volumes to software and Internet deals based on these technologies. The report says the most promising areas of M&A activity in 2013 are mobile application development start-ups who have the intellectual property it would take years for enterprise software companies to create on their own.
Analytics will move from being a differentiator to the cost of doing business, a key point made in the PwC analysis. PwC claims that analytics M&A will accelerate across all enterprise software vendors as they seek to fill gaps in their product and service strategies, and position themselves for growth in specific areas of the emerging industries using Big Data.
PwC reports that monthly deal volumes for software remained relatively even throughout 2012, hovering at 8-9 transactions per month and averaging just over 20 per quarter. The average deal value of $433M for 2012 was slightly lower than 2011 levels of $438M but an increase in the number of deals in excess of $500M helped to keep average deal values high. The report also shows how 2012 saw 18 deals (21% of volume) in excess of $500M closed, the majority of which closed in the latter half of the year. Fourteen deals greater than $1B closed in 2012, an increase of 8 deals (133%) over 2011. The following is a graphic comparing software sector deals by volume and value:

Bottom line: The land grab is on for intellectual property in the fields of mobile application development, analytics and cloud computing as enterprise software vendors look to fill gaps in their product and service strategies.

Feb 19

Gartner Predicts Infrastructure Services Will Accelerate Cloud Computing Growth

As public cloud computing gains greater adoption across enterprises, there’s an increased level of spending occurring on infrastructure-related services including Infrastructure-as-a-Service(IaaS). Enterprises are prioritizing how to get cloud platforms integrated with legacy systems to make use of the years of data they have accumulated. From legacy Enterprise Resource Planning (ERP) to Customer Relationship Management (CRM) systems, integrating legacy systems of record to cloud-based platforms will accelerate through 2016. I’ve seen this in conversations with resellers and enterprise customers, and this trend is also reflected in Gartner’s latest report on public cloud computing adoption, Forecast Overview: Public Cloud Services, Worldwide, 2011-2016, 4Q12 Update Published: 8 February 2013. Below are the key take-aways from the report:

Global spending on public cloud services is expected to grow 18.6% in 2012 to $110.3B, achieving a CAGR of 17.7% from 2011 through 2016. The total market is expected to grow from $76.9B in 2010 to $210B in 2016. The following is an analysis of the public cloud services market size and annual growth rates:

Gartner predicts that Infrastructure-as-a-Service (IaaS) will achieve a compound annual growth rate (CAGR) of 41.3% through 2016, the fastest growing area of public cloud computing the research firm tracks. The following graphic provides insights into relative market size by each public cloud services market segment:

Platform-as-a-Service (PaaS) will achieve a 27.7% CAGR through 2016, with Cloud Management and Security Services attaining 26.7% in the same forecast period. Software-as-a-Service’s CAGR through 2016 is projected to be 19.5%. The following graphic illustrates the differences in CAGR in the forecast period of 2011 – 2016:

Gartner is projecting the SaaS market will grow at a steady CAGR of 19.5% through 2016, having increased the forecast slightly (.4%) since its latest published report. Global SaaS spending is projected to grow from $13.5B in 2011 to $32.8B in 2016.

CRM will continue to be the largest global market within SaaS, forecast to grow beyond $5B in 2012 to $9B in 2016, achieving a 16.3% CAGR through 2016. The highest growth segments of the SaaS market continue to be office suites (49.1%), followed by digital content creation (34.0%). The following graphic rank orders CAGRs across all public cloud services segments from the forecast period:

59% of all new spending on cloud computing services originates from North American enterprises, a trend projected to accelerate through 2016. Western Europe is projected to be 24% of all spending. A graphic comparing total spending by geography and corresponding growth rates is provided below:

The following tables provide insights into each category of public cloud computing spending throughout the forecast period. Please click on the tables to expand them for easier reading.

Source: Forecast Overview: Public Cloud Services, Worldwide, 2011-2016, 4Q12 Update Published: 8 February 2013.

Jan 24

Plex Systems’ CEO Jason Blessing on the Future of ERP and Software-as-a-Service (SaaS)

Last week Plex Systems, a leading provider of SaaS-based Enterprise Resource Planning (ERP) systems announced enterprise software veteran Jason Blessing has joined their company as CEO. He is responsible for the strategic direction and growth of the company, and has a proven track record in many facets of enterprise software, from new application development to professional services. His extensive experience includes previous executive positions at Oracle, Taleo, PeopleSoft and Price Waterhouse. You can find his LinkedIn profile here.

Plex Systems’ success delivering ERP entirely on the SaaS platform to manufacturers have many industry analysts, experts and pundits saying their unique business model is prescient of the future of enterprise software. Originally designed for an automotive parts manufacturer, Plex Online is being adopted by aerospace and defense, food and beverage, high tech and electronics, industrial machinery, and precision metal manufacturers. You can find an overview of Plex Systems here.

I recently had a chance to speak with Jason and get his views on the future of ERP, SaaS in manufacturing and the enterprise, and what he sees as the greatest challenges and opportunities for Plex Systems.

Here’s a transcript of my interview with Jason Blessing, the new CEO of Plex Systems:

What are the three biggest challenges you see to Plex Systems’ growth over the long-term and how will you and the management team address them?

Our greatest challenge is awareness of who Plex Systems is and the value we are delivering to our manufacturing customers today. We’re already putting together programs that will highlight the very meaningful customer base we have and what they are able to accomplish using Plex Online. Second, we’re going to continue making significant product investments. Our owners are growth-minded and we’re looking to create a beachheads in additional areas to compliment our heritage in auto manufacturing. Third, we’re going to expand our sales and marketing investments to provide better coverage domestically and in Europe and Asia. We’re also on a mission to lead the resurgence of manufacturing in America by giving small and mid-sized companies the systems they need to be formidable global competitors.

SaaS-based applications have proved themselves in the enterprise. How and why are manufacturers adopting SaaS-based ERP systems today? How is this going to change in the future?

Credit has to go to Taleo and Salesforce for proving SaaS can succeed at the departmental level in the enterprise. We’re finding that the combination of financials and Manufacturing Execution Systems (MES) delivered in the cloud is very well-suited for small and medium manufacturers. These manufacturers often don’t have a large Information Technologies (IT) staff and want to offload these systems so they can stay focused on their core business. In this sense we free up these smaller manufacturers to get back to work running their businesses without having to hassle with large, complex and costly ERP deployments.

Will SaaS-based ERP systems cannibalize monolithic ERP systems or coexist and compliment them? Or are you seeing a mix of both cannibalization and coexistence? For Plex Systems, what’s the best direction?

We do see customer that adopt parts of our solution, quality for example, to test the cloud model before going wall to wall Plex. Another approach we see is customers who have global operations bring foreign factories online quicker than they had in the past as a result of SaaS. The end result will be the cannibalization of monolithic ERP systems by those that are SaaS-based.

One of the implicit factors in this area of cannibalization is the typical release cadence of a SaaS provider. Most large cloud providers have, on average, 3 releases a year. Here at Plex Systems we’re on a continuous release cadence. When a customer asks for a feature enhancement or entirely new set of functions, we strive to be very responsive with our release cycles and deliver what is needed.

Plex Systems has done well in several key manufacturing industries including automotive, A&D, electronics, food and beverage, and medical devices. Do you see Plex Systems moving into additional industries, and if so, which ones? Pharmaceutical and biotech for example.

We’re going to be fairly disciplined in our approach within the verticals we’re already selling into. We’re seeing increasing interest in moving core shop floor applications to the cloud for example, and we’re going to expand out our coverage in our core vertical markets as a result.

With the majority of sales in the United States, does Plex Systems have plans for Europe and Asia? What’s your perspective of those markets for SaaS-based ERP system sales?

We’re growing at an approximately compound annual growth rate of 30%+ per year, the majority of that growth coming from North America today. We’re also seeing strong interest from EMEA, South America and Asia. What’s driving our foreign market demand is the need manufacturers have for quickly getting production centers up and running on financials, MES and Supply Chain Management Systems (SCM). We also run our own data centers and have hot standby and back facilities supporting our worldwide customer base.

Two-tier ERP delivers significant business value and is growing in adoption. How will Plex Systems capitalize on this trend and what are the implications for the application development priorities?

We’re delivering two-tier ERP implementations today and one of the largest heavy equipment manufacturers in the world uses Plex Online to run their shop floor operations at several manufacturing centers. Their main ERP system is an SAP R/3 instance, and we integrate to that and help this manufacturer be more efficient at the individual plant and shop floor level.

Last year Plex Systems announced IntelliPlex, SmartPlex, in addition to several other significant new services and partnerships. Of these, IntelliPlex has the potential to deliver analytics and business intelligence to manufacturers who may have never had these metrics available before. How do you see analytics in manufacturing improving this year, and how will this augment Plex Online’s analytics strategy going forward?

Much of our success as a provider of SaaS-based ERP systems is due to the breadth of applications that span from the shop floor to the top floor. We’re seeing analytics resonate really well with the people who write us the checks, the top floor executives and their teams responsible for the getting the highest performance from manufacturing operations. We’re going to augment our analytics this year, supporting mobile devices. We’ve also been doing data mining of production data across the worldwide Plex Systems customer base and see the potential to create an index of manufacturing performance. We’re going to look at how this data will be able to help our customers predict economic conditions in their specific manufacturing industries.

There are a myriad of studies out on the impact of mobile technologies on manufacturing. Last year, Plex Systems introduced SmartPlex Mobile, which gives ERP users access to data on iOS and Android devices. Can you discuss the challenges of mobile adoption in manufacturing and how Plex Systems will address them?

Often mobile technologies installed and used on the factory floor are proprietary to the systems and workflows for that specific factory. They are fine-tuned to the specific workflows on the factory floor, and the proprietary nature of their electronics only work with the systems they are designed for and Plex Online supports many of these devices. Material handling, RFID and other logistics projects are based on these kinds of technologies.

We’ve also found that senior management teams want to get as close to real-time data as possible on each phase of manufacturing operations. SmartPlex Mobile is designed to give senior management teams visibility into operations on Android and iOS devices, and continues to gain interest from existing and new customers alike.

Many manufacturers are dealing with “brain drain” or the retiring and churn of their long-time manufacturing, process control, and quality management professionals. How do you see Plex Systems helping these manufacturers to retain that tacit knowledge in their organizations over their long-term?

We talk quite often about this with our prospects, customers and internally in our development meetings. Prospects are especially interested in how to solve this problem as tribal knowledge is often the most difficult to capture and re-use. It’s common to find manufacturers with a myriad of Microsoft Access databases, legacy systems and data locked on spreadsheets. Our architecture is based on a Master Data Management (MDM) model with gives manufacturers a single source or version of the truth. Using our experience implementing these systems in small and medium-sized manufacturers, we’ve found methods and techniques for managing corporate-wide data effectively.

Visualization in manufacturing including the extensive use of 2D and 3D CAD drawings is also accelerating. What are your thoughts on the future of visualization in manufacturing, and more specifically, which key process areas do you see Plex Systems addressing with its visualization strategy?

This area is critically important for the shop floor as it can drive higher levels of production quality quickly. We’re going to continue to invest in this area, and our Actify partnership gives us a strong foundation to build on in this area. The partnership with Actify allows us to embed engineering drawings directly in Plex, allowing shop floor workers to look up specifications on the fly to ensure high levels of quality. The drawings are highly valuable because they are contextualized in Plex (e.g., tied to the product in question) and don’t require any expensive CAD equipment or training to view.

Plex Systems has also built a strong foundation of partners including system integrators and resellers. Do you anticipate Plex Systems will increasingly rely on resellers or stay with primarily a direct sales strategy?

It’s very important to high fidelity relationships with customers when you’re selling SaaS-based enterprise software so the direct model is important to us. That said, partners are also very important to us because of the value they can bring to customers and the added reach they can provide us. So, we’ve been successful in creating a partner program, which has a rigorous certification process that ensures those we partner with have strong domain expertise to serve our shared customers. Partners can quickly become a force multiplier for us, and we’re working towards that goal by keeping direct sales in balance.

Disclaimer: This interview was done independent of Plex Systems. I have not and have never been a paid consultant of the company. I approached them to do this interview based on insights gained from WordPress analytics showing readers’ interest in ERP, SaaS and enterprise software.