- 73% of midmarket companies say the complexity of their stored data requires big data analytics apps and tools to better gain insights from.
- 54% of midmarket companies’ security budgets are invested in security plans versus reacting to threats.
These and many other insights are from Dell’s second annual Global Technology Adoption Index (GTAI 2015) released last week in collaboration with TNS Research. The Global Technology Adoption Index surveyed IT and business decision makers of mid-market organizations across 11 countries, interviewing 2,900 IT and business decision makers representing businesses with 100 to 4,999 employees.
The purpose of the index is to understand how business users perceive, plan for and utilize four key technologies: cloud, mobility, security and big data. Dell released the first wave of its results this week and will be publishing several additional chapters throughout 2016. You can download Chapter 1 of the study here (PDF, no opt-in, 18 pp.).
Key take-aways from the study include the following:
- Orchestrating big data, cloud and mobility strategies leads to 53% greater growth than peers not adopting these technologies. Midmarket organizations adopting big data alone have the potential to grow 50% more than comparable organizations. Effective use of Bring Your Own Device (BYOD) mobility strategies has the potential to increase growth by 53% over laggards or late adopters..
- 73% of North American organizations believe the volume and complexity of their data requires big data analytics apps and tools. This is up from 54% in 2014, indicating midmarket organizations are concentrating on how to get more value from the massive data stores many have accumulated. This same group of organizations believe they are getting more value out of big data this year (69%) compared to last year (64%). Top outcomes of using big data include better targeting of marketing efforts (41%), optimization of ad spending (37%), and optimization of social media marketing (37%).
- 54% of an organization’s security budget is invested in security plans versus reacting to threats. Dell & TNS Research discovered that midmarket organizations both in North America and Western Europe are relying on security to enable new devices or drive competitive advantage. In North America, taking a more strategic approach to security has increased from 25% in 2014 to 35% today. In Western Europe, the percentage of companies taking a more strategic view of security has increased from 26% in 2014 to 30% this year.
- IT infrastructure costs to support big data initiatives (29%) and costs related to securing the data (28%) are the two greatest barriers to big data adoption. For cloud adoption, costs and security are the two biggest barriers in midmarket organizations as is shown in the graphic below.
- Cloud use by midmarket companies in France increased 12% in the last twelve months, leading all nations in the survey. Of the 11 countries surveyed, France had the greatest increase in cloud adoption within midmarket companies. French businesses increased their adoption of cloud applications and platforms from 70% in 2014 to 82% in 2015.
Sources: Dell Study Reveals Companies Investing in Cloud, Mobility, Security and Big Data Are Growing More Than 50 Percent Faster Than Laggards. October 13, 2015
Gartner announced their top 10 strategic technology trends for 2016 at the Gartner Symposium/ITxpo held October 4 – 8th 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:
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
These and other insights are from recent cloud computing forecasts and market estimates published by research and advisory consultancies including International Data Corporation (IDC), Forrester, Gartner, Ovum, Wikibon and others.
While the methodologies differ significantly, the findings from a recent Economist Intelligence Unit study provide the galvanizing thread across this diverse set of data. The Economist found that the most mature enterprises are now turning to cloud strategies as a strategic platform for growing customer demand and expanding sales channels. The study found low-maturity or lagging cloud adopters focus on costs more than growth.
Key take-aways from the round-up are provided below:
- 57% of IT architects and tech professionals are running apps on the Amazon Web Services (AWS) platform today. Rightscale’s 2015 State of the Cloud Report found that AWS adoption is over 4X greater than Microsoft Azure IaaS and 5X that of Rackspace Public Cloud. Rightscale found that AWS, Microsoft Azure IaaS, Azure PaaS, Rackspace Public Cloud and VMWare vCloud Air are the top five public cloud platforms used in enterprises today. Source: RightScale 2015 State Of The Cloud Report
- Goldman Sachs is forecasting the cloud infrastructure and platform market will grow at a 19.62% CAGR from 2015 to 2018, reaching $43B by 2018. Their recent market analysis also forecasts that the global market for cloud infrastructure and platforms will grow from $21B this year to $43B by the end of the forecast period. Source: How Big Can The Amazon Web Services Business Grow In The Future?
- 46% of surveyed firms in the European Union (EU) are using advanced cloud services relating to financial and accounting software applications, customer relationship management or to the use of computing power to run business applications. In 2014, almost twice as many firms used public cloud servers (12%) versus private cloud servers (7%). The following graphic illustrates the degree of dependence on cloud computing, by economic activity, EU-28, 2014. Source: Eurostat Statistics Explained. Cloud computing – statistics on the use by enterprises.
- 64% of Small & Medium Businesses (SMBs) are already using cloud-based apps, with average adoption being 3 apps. 78% of businesses indicate that they are considering purchasing new solutions in the next 2-3 years creating the potential to move the average number of applications used to 7, with 88% consuming at least one service. Source: The small business revolution: trends in SMB cloud adoption.
- Worldwide spending on enterprise application software will grow 7.5% to reach $149.9B in 2015, increasing to more than $201B in 2019 with accelerating cloud adoption driving new software sales. Gartner’s analysis of enterprise software spending shows that alternative consumption models to traditional on-premises licenses are accounting for more than 50% of new software implementations; these include SaaS, hosted license, on-premises subscriptions and open source. Gartner also predicts that by 2020, about a quarter of organizations in emerging regions will run their core CRM systems in the cloud, up from around 10 percent in 2012. Source: Gartner Says Modernization and Digital Transformation Projects Are Behind Growth in Enterprise Application Software Market.
- 2015 Top Markets Report Cloud Computing A Market Assessment Tool for U.S. Exporters U.S. Department of Commerce | International Trade Administration | Industry & Analysis (I&A) July 2015
- Cloud Computing: Principles and Paradigms. (PDF, free, no opt-in, 674 pp.)
- Forrester Research – Adoption Profile: Hosted Private Cloud, North America And Europe, Q3 2014
- Global Cloud IT Infrastructure Market Rose 25 Percent in Q1: IDC
- 451 Research & Microsoft Hosting and Cloud Study 2015 – Beyond Infrastructure: Cloud 2.0 Signifies New Opportunities for Cloud Service Providers Survey Results. (free, no opt-in, 66 pp.)
- IDC Report, Worldwide Cloud Systems Management Software Market Shares, 2014: Year of Hybrid Cloud (free, no opt-in).
- Montclare SaaS 250
- Oracle Industry Analyst Relations Reports
- 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.
- 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.
Bottom line: Big data is providing supplier networks with greater data accuracy, clarity, and insights, leading to more contextual intelligence shared across supply chains.
Forward-thinking manufacturers are orchestrating 80% or more of their supplier network activity outside their four walls, using big data and cloud-based technologies to get beyond the constraints of legacy Enterprise Resource Planning (ERP) and Supply Chain Management (SCM) systems. For manufacturers whose business models are based on rapid product lifecycles and speed, legacy ERP systems are a bottleneck. Designed for delivering order, shipment and transactional data, these systems aren’t capable of scaling to meet the challenges supply chains face today.
Choosing to compete on accuracy, speed and quality forces supplier networks to get to a level of contextual intelligence not possible with legacy ERP and SCM systems. While many companies today haven’t yet adopted big data into their supply chain operations, these ten factors taken together will be the catalyst that get many moving on their journey.
The ten ways big data is revolutionizing supply chain management include:
- Enabling more complex supplier networks that focus on knowledge sharing and collaboration as the value-add over just completing transactions. Big data is revolutionizing how supplier networks form, grow, proliferate into new markets and mature over time. Transactions aren’t the only goal, creating knowledge-sharing networks is, based on the insights gained from big data analytics. The following graphic from Business Ecosystems Come Of Age (Deloitte University Press) (free, no opt-in) illustrates the progression of supply chains from networks or webs, where knowledge sharing becomes a priority.
- Big data and advanced analytics are being integrated into optimization tools, demand forecasting, integrated business planning and supplier collaboration & risk analytics at a quickening pace. These are the top four supply chain capabilities that Delotte found are currently in use form their recent study, Supply Chain Talent of the Future Findings from the 3rd Annual Supply Chain Survey (free, no opt-in). Control tower analytics and visualization are also on the roadmaps of supply chain teams currently running big data pilots.
- 64% of supply chain executives consider big data analytics a disruptive and important technology, setting the foundation for long-term change management in their organizations. SCM World’s latest Chief Supply Chain Officer Report provides a prioritization of the most disruptive technologies for supply chains as defined by the organizations’ members. The following graphic from the report provides insights into how senior supply chain executives are prioritizing big data analytics over other technologies.
- Using geoanalytics based on big data to merge and optimize delivery networks. The Boston Consulting Group provides insights into how big data is being put to use in supply chain management in the article Making Big Data Work: Supply Chain Management (free, opt-in). One of the examples provided is how the merger of two delivery networks was orchestrated and optimized using geoanalytics. The following graphic is from the article. Combining geoanalytics and big data sets could drastically reduce cable TV tech wait times and driving up service accuracy, fixing one of the most well-known service challenges of companies in that business.
- Greater contextual intelligence of how supply chain tactics, strategies and operations are influencing financial objectives. Supply chain visibility often refers to being able to see multiple supplier layers deep into a supply network. It’s been my experience that being able to track financial outcomes of supply chain decisions back to financial objectives is attainable, and with big data app integration to financial systems, very effective in industries with rapid inventory turns. Source: Turn Big Data Into Big Visibility.
- Traceability and recalls are by nature data-intensive, making big data’s contribution potentially significant. Big data has the potential to provide improved traceability performance and reduce the thousands of hours lost just trying to access, integrate and manage product databases that provide data on where products are in the field needing to be recalled or retrofitted.
- Increasing supplier quality from supplier audit to inbound inspection and final assembly with big data. IBM has developed a quality early-warning system that detects and then defines a prioritization framework that isolates quality problem faster than more traditional methods, including Statistical Process Control (SPC). The early-warning system is deployed upstream of suppliers and extends out to products in the field.
- 69% of enterprises expect to make moderate-to-heavy cloud investments over the next three years as they migrate core business functions to the cloud.
- 44% of enterprises are relying on cloud computing to launch new business models today, predicting this will increase to 55% in three years.
- 32% are using cloud computing to streamline their supply chains today. Senior executives predict this figure will increase to 56% in three years, a 24% increase.
- 59% say they use cloud-based applications and platforms to better manage and analyze data today, reflecting the increasing importance of analytics and big data enterprise-wide.
These and other insights are from a recent Oxford Economics and SAP study of cloud computing adoption, The Cloud Grows Up. You can find the study here (no opt-in). In late 2014, Oxford Economics and SAP collaborated on a survey of 200 senior business and IT executives globally regarding the adoption and use of cloud technology. Oxford Economics’ analysts compared the latest survey with one completed in 2012 looking for leading indicators of cloud adoption in enterprises. They found many C- and VP-level executives are taking a more pragmatic, realistic view of what cloud technologies can contribute. Enterprises are moving beyond the hype of cloud computing, putting in the hard work of launching new business models while driving top-line revenue growth.
Oxford Economics has made two interactive infographics available from the study here. The first details cloud adoption, and the second, on how enterprises see cloud computing changing their business models over the next three years. As cloud platforms and applications become a scalable, secure and for the most part reliable, once-elusive enterprise goals and new business models become attainable.
Key take-aways from the study include the following:
- Top–line growth (58%), collaboration among employees (58%), and supply chain (56%) are the three areas enterprises expect cloud computing to impact most in three years. The greatest gains will be in the areas of supply chain (a 24% jump), collaboration among employees (20%) and increased agility and responsiveness to customers (17%). The following graphic compares where enterprises are seeing cloud computing’s impact today and a prediction of each areas’ impact in three years.
- Developing new products & services (61%), new lines of business (51%) and entering new markets (40%) are three key areas cloud computing is transforming enterprises. With a 35% increase, developing new products and services is the most dominant strategy enterprises are relying on to grow their businesses. See the comparison below for further details.
- 58% of enterprises predict their use of cloud computing will increase top-line revenue growth in three years. 67% see the cloud changing skill sets and transforming the role of HR. The following graphic illustrates the first of two interactive infographics Oxford Economics and SAP are providing with the report. You can access the infographic here.
- 74% of enterprises say innovation and R&D is somewhat or mostly cloud-based. 61% say they will have developed new products and services in three years as a result of adopting cloud technologies. The following graphic illustrates the second of two interactive infographics Oxford Economics and SAP are providing with the report. You can access the infographic here.
- Enterprise cloud security strategies are maturing rapidly. From 2012 to 2014, strategies for ensuring the security of API and interfaces increased 24%, from 20% to 44%. Additional concerns that increased include virus attacks (up 19%), and identity theft (up 16%). The following figure compares the top concerns enterprises have in the area of cloud security.
- 31% of respondents say the cloud computing has had a transformative impact on their business. 48%, nearly half, state that cloud computing has had a moderate impact on business performance. The majority believe cloud computing will have a significant impact on top-line revenue growth in three years.
- 67% of enterprises say that marketing, purchasing, and supply chain are somewhat and mostly cloud-based as of today. Cloud-based adoption has reached an inflection point in enterprises, with functional areas having the largest percentage of workloads running on cloud-based apps. Enterprise senior executives see the potential to improve innovation, R&D, and time-to-market via greater collaboration using cloud technologies.
- Enterprises are only realizing 35% of the total potential value of their cloud deployments according to a recent Bain & Company study.
- Companies that moved development to IaaS and PaaS clouds from Amazon Web Services (AWS) reduced downtime by 72% and improved application availability by 3.9 hours per user per year.
These and other key take-aways are from the recent Bain & Company study, Tapping Cloud’s Full Potential. The full report PDF is available for download here (free, no opt-in). The following graphic from the report illustrates the currently realized value of cloud deployments in enterprises today according to Bain & Company.
The researchers found several critical drivers of cloud value with one of the most important being the strengthening and clarifying of a product and service focus. The following graphic illustrates the critical drivers of cloud value.
Cloud Service Providers Give Manufacturers The Ability To Stay Competitive
Cloud-first strategies designed to accelerate and strengthen shifts in emerging business models is paying off according to Bain’s research results.
Manufacturers choosing to pursue a cloud-first strategy are focusing on evolving their business models, processes, systems and performance quickly to stay in step with customers’ needs. For many manufacturers, their customers’ pace is faster than internal IT organizations can anticipate and react to. CSPs are helping to close that gap.
Here are five ways CSPs are making manufacturers more competitive:
- Bringing industry expertise to the shop floor level. The best CSPs serving manufacturers today have management teams that have decades of combined manufacturing experience in specific industries. The CEO of a specialty tools manufacturer remarked that his company’s cloud strategy was more focused on accelerating plant floor performance first. Working with a CSP that had expertise in their industry, this manufacturer was able to gain greater supply chain visibility and improve forecast accuracy, all with cloud-based apps.
- Solving legacy and 3rd party system integration problems so that cloud-based ERP, CRM, supply chain management (SCM) systems can scale quickly. When a rust-belt based manufacturer of heating, ventilation and air conditioning (HVAC) systems had the opportunity to grow their business by expanding into build-to-order customized products, their CSP partner made it possible to integrate an entirely new product configurator and cloud-based ERP system module to manage quote-to-cash. Today, 30% of corporate-wide profits are from build-to-order selling strategies.
- Knowledge-sharing supplier networks are becoming more attainable for manufacturers thanks to cloud technologies and CSPs. All manufacturers have strategic plans that include greater integration of their supplier networks, with many seeking to create knowledge-sharing networks. One of the best studies of how to create a knowledge-sharing network is from Dr. Jeffrey Dyer and Dr. Kentaro Nobeoka based on their intensive work with Toyota. Their study, Creating And Managing A High Performance Knowledge-Sharing Network: The Toyota Case is a great read. The following graphic from the study illustrates the evolution of a knowledge-sharing network. Manufacturers are relying on cloud platforms and CSPs to enable shifts in network structures and nurture change management to create self-sustaining systems.
- Two-tier ERP adoption in manufacturing is growing as CSPs master cloud ERP systems. CSPs are moving beyond providing basic services, specializing in cloud ERP, CRM, SCM, pricing, services and legacy system integration to keep pace with manufacturers’ demands. In one high tech manufacturer, their CSP partner orchestrated the procuring and launch of their cloud-based two-tier ERP system integrated to an SAP instance in their headquarters. Today they operate production centers in Asia, North America and Australia, all coordinated through the main SAP instance in the U.S. headquarters.
- Making Service Level Agreements (SLAs) more relevant to manufacturing business models. Instead of just getting SLAs for uptime, security and system stability, manufacturers are getting advanced manufacturing intelligence dashboards that provide visibility to the plant or production center level.
Bottom Line: Manufacturers are increasingly relying on CSPs’ cloud, industry and integration expertise to support the transition many are making to new business models and get greater than 35% of the value from their cloud investments.
Additional resources on Cloud ERP systems:
according to MoneyTree Report, a collaborative research initiative between PricewaterhouseCoopers and the National Venture Capital Association. A graphic from the latest available data shows how software investments were 39% of all investments in Q4, 2014.
To determine which enterprise software startups have gained the greatest amount of funding since they were founded, Mattermark was used to rank order all enterprise start-ups. Mattermark uses a combination of artificial intelligence and data quality analysis to provide insights into over 1M companies, over 470K with employee data, and over 100,000 funding events.
Mattermark uses their Growth Score is the default ranking for all companies tracked in their service. 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.
Using their free trial, I completed the following analysis of cloud-based enterprise software startups. I’m not a consultant to Mattermark and never have been. As many Forbes readers find software investment data fascinating, I contacted Mattermark and asked for a free trial, which they graciously provided. You can download the list in Microsoft Excel format here.
A Goldman Sachs study published earlier this year projects that spending on cloud computing infrastructure and platforms will grow at a 30% CAGR from 2013 through 2018 compared with 5% growth for the overall enterprise IT.
Centaur Partners and other firms mentioned in this roundup are seeing more enterprise-size deals for cloud computing infrastructure and applications. While each of these consultancies and research firms have varying forecasts for the next few years, all agree that cloud computing adoption is accelerating in enterprises on a global scale.
Key take-aways from the roundup are provided below:
- By 2018, 59% of the total cloud workloads will be Software-as-a-Service (SaaS) workloads, up from 41% in 2013. Cisco is predicting that by 2018, 28% of the total cloud workloads will be Infrastructure-as-a-Service (IaaS) workloads down from 44% in 2013. 13% of the total cloud workloads will be Platform-as-a-Service (PaaS) workloads in 2018, down from 15% in 2013. The following graphic provides a comparative analysis of IaaS, PaaS and SaaS forecasts from 2013 to 2018. Source: Cisco Global Cloud Index: Forecast and Methodology, 2013–2018. (PDF, free, no opt-in).
- Centaur Partners’ analysis of SaaS & cloud-based business application services revenue forecasts the market growing from $13.5B in 2011 to $32.8B in 2016, attaining a 19.5% CAGR. Centaur provides a useful overview of current market conditions including M&A activity in their latest market overview published this month, Introduction to Centaur Partners: SaaS Market Overview, (PDF, free, no opt-in).
- Global SaaS software revenues are forecasted to reach $106B in 2016, increasing 21% over projected 2015 spending levels. Spending on integration, storage management, and database management systems are projected to experience the greatest growth in 2015. These and other key insights are from Forrester’s SaaS software subscription revenue by category show below. Source: Enterprise software spend to reach $620 billion in 2015: Forrester.
- $78.43B in SaaS revenue will be generated in 2015, increasing to $132.57 in 2020, attaining a compound annual growth rate (CAGR) of 9.14%. The following graphic and table provides an overview of Forrester’s Global Public Cloud Computing market size analysis and forecast for the years 2011 to 2020. Source: Institut Sage.
- IDC predicts that by 2016, there will be an 11% shift of IT budget away from traditional in-house IT delivery, toward various versions of cloud computing as a new delivery model. By 2017, 35% of new applications will use cloud-enabled, continuous delivery and enabled by faster DevOps life cycles to streamline rollout of new features and business innovation. Source: 2015-2017 Forecast: Cloud Computing to Skyrocket, Rule IT Delivery.
- By 2018, IDC forecasts that public cloud spending will more than double to $127.5 billion. This forecast is broken down as follows: $82.7 billion in SaaS spending, $24.6 billion for IaaS and $20.3 billion in PaaS expenditures. Source: Forecasts Call For Cloud Burst Through 2018.
- By 2016 over 80% of enterprises globally will using IaaS, with investments in private cloud computing showing the greater growth. Ovum forecasts that by 2016, 75% of EMEA-based enterprises will be using IaaS. These and other insights are from the presentation, The Role of Cloud in IT Modernisation: The DevOps Challenge (free PDF, no opt in). The graphic below provides an analysis of cloud computing adoption in EMEA and globally.
- By 2018, more than 60% of enterprises will have at least half of their infrastructure on cloud-based platforms. These and other are insights are from the keynote Cloud Business Summit presentation Digital Business, Rethinking Fundamentals by Bill McNee, Founder and CEO, Saugatuck Technology. Source: Digital Business, Rethinking Fundamentals.
McKinsey & Company recently published How Big Data Can Improve Manufacturing which provides insightful analysis of how big data and advanced analytics can streamline biopharmaceutical, chemical and discrete manufacturing.
The article highlights how manufacturers in process-based industries are using advanced analytics to increase yields and reduce costs. Manufacturers have an abundance of operational and shop floor data that is being used for tracking today. The McKinsey article shows through several examples how big data and advanced analytics applications and platforms can deliver operational insights as well.
The following graphic from the article illustrates how big data and advanced analytics are streamlining manufacturing value chains by finding the core determinants of process performance, and then taking action to continually improve them:
Big Data’s Impact on Manufacturing Is Growing
In addition to the examples provided in the McKinsey article, there are ten ways big data is revolutionizing manufacturing:
- Increasing the accuracy, quality and yield of biopharmaceutical production. It is common in biopharmaceutical production flows to monitor more than 200 variables to ensure the purity of the ingredients as well as the substances being made stay in compliance. One of the many factors that makes biopharmaceutical production so challenging is that yields can vary from 50 to 100% for no immediately discernible reason. Using advanced analytics, a manufacturer was able to track the nine parameters that most explained yield variation. Based on this insight they were able to increase the vaccine’s yield by 50%, worth between $5M to $10M in yearly savings for the single vaccine alone.
- Accelerating the integration of IT, manufacturing and operational systems making the vision of Industrie 4.0 a reality. Industrie 4.0 is a German government initiative that promotes automation of the manufacturing industry with the goal of developing Smart Factories. Big data is already being used for optimizing production schedules based on supplier, customer, machine availability and cost constraints. Manufacturing value chains in highly regulated industries that rely on German suppliers and manufacturers are making rapid strides with Industrie 4.0 today. As this initiative serves as a catalyst to galvanize diverse multifunctional departments together, big data and advanced analytics will become critical to its success.
- Better forecasts of product demand and production (46%), understanding plant performance across multiple metrics (45%) and providing service and support to customers faster (39%) are the top three areas big data can improve manufacturing performance. These findings are from a recent survey LNS Research and MESA International completed to see where big data is delivering the greatest manufacturing performance improvements today. You can find the original blog post here.
- Integrating advanced analytics across the Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) framework to fuel continuous improvement. Getting greater insights into how each phase of a DMAIC-driven improvement program is working, and how the efforts made impact all other areas of manufacturing performance is nascent today. This area shows great potential to make production workflows more customer-driven than ever before.
- Greater visibility into supplier quality levels, and greater accuracy in predicting supplier performance over time. Using big data and advanced analytics, manufacturers are able to view product quality and delivery accuracy in real-time, making trade-offs on which suppliers receive the most time-sensitive orders. Managing to quality metrics becomes the priority over measuring delivery schedule performance alone.
- Measuring compliance and traceability to the machine level becomes possible. Using sensors on all machinery in a production center provides operations managers with immediate visibility into how each is operating. Having advanced analytics can also show quality, performance and training variances by each machine and its operators. This is invaluable in streamlining workflows in a production center, and is becoming increasingly commonplace.
- Selling only the most profitable customized or build-to-order configurations of products that impact production the least. For many complex manufacturers, customized or build-to-order products deliver higher-than-average gross margins yet also costs exponentially more if production processes aren’t well planned. Using advanced analytics, manufacturers are discovering which of the myriad of build-to-order configurations they can sell with the most minimal impact to existing production schedules to the machine scheduling, staffing and shop floor level.
- Breaking quality management and compliance systems out of their silos and making them a corporate priority. It’s time for more manufacturers to take a more strategic view of quality and quit being satisfied with standalone, siloed quality management and compliance systems. The McKinsey article and articles listed at the end of this post provide many examples of how big data and analytics are providing insights into which parameters matter most to quality management and compliance. The majority of these parameters are corporate-wide, not just limited to quality management or compliance departments alone.
- Quantify how daily production impacts financial performance with visibility to the machine level. Big data and advanced analytics are delivering the missing link that can unify daily production activity to the financial performance of a manufacturer. Being able to know to the machine level if the factory floor is running efficiently, production planners and senior management know how best to scale operations. By unifying daily production to financial metrics, manufacturers have a greater chance of profitably scaling their operations.
- Service becomes strategic and a contributor to customers’ goals by monitoring products and proactively providing preventative maintenance recommendations. Manufacturers are starting to look at the more complex products they produce as needing an operating system to manage the sensors onboard. These sensors report back activity and can send alerts for preventative maintenance. Big data and analytics will make the level of recommendations contextual for the first time so customers can get greater value. General Electric is doing this today with its jet engines and drilling platforms for example.
Additional sources of information on Big Data in Manufacturing:
- Attitudes on How Big Data will Affect Manufacturing Performance. Posted by Greg Goodwin on Thu, Mar 06, 2014. LNS Research. http://blog.lnsresearch.com/blog/bid/194972/Attitudes-on-How-Big-Data-will-Affect-Manufacturing-Performance-DATA From Value to Vision: Reimagining the Possible with Data Analytics, David Kiron, Renee Boucher Ferguson and Pamela Kirk Prentice, MIT Sloan Management Review, March 2013. http://sloanreview.mit.edu/reports/analytics-innovation/introduction/
- Merck Optimizes Manufacturing With Big Data Analytics, Information Week, Doug Henschen. April 2, 2014. http://www.informationweek.com/strategic-cio/executive-insights-and-innovation/merck-optimizes-manufacturing-with-big-data-analytics/d/d-id/1127901
- Takeaways from the MIT/Accenture Big Data in Manufacturing Conference. Posted by Greg Goodwin on Wed, Nov 27, 2013. http://blog.lnsresearch.com/blog/bid/190482/Takeaways-from-the-MIT-Accenture-Big-Data-in-Manufacturing-Conference
- The Internet of Things and the future of manufacturing. McKinsey and Company. Executives at Robert Bosch and McKinsey experts discuss the technology-driven changes that promise to trigger a new industrial revolution. June 2013 | by Markus Löffler and Andreas Tschiesner. http://www.mckinsey.com/insights/business_technology/the_internet_of_things_and_the_future_of_manufacturing
- The Rise of Industrial Big Data: Leveraging large time-series data sets to drive innovation, competitiveness and growth — capitalizing on the big data opportunity, GE Intelligent Platforms White Paper, April 2012. http://www.ge-ip.com/library/detail/13170
- When Big Data Meets Manufacturing. Stephen Chick, Serguei Netessine, INSEAD Professors of Technology and Operations Management and Arnd Huchzermeier, Chaired Professor of Production Management at WHU-Otto Beisheim School of Management | April 16, 2014. http://knowledge.insead.edu/operations-management/when-big-data-meets-manufacturing-3297