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Posts tagged ‘CRM’

Salesforce Now Has Over 19% Of The CRM Market

 

  • Salesforce dominated the worldwide CRM market with a 19.5% market share in 2018, over double its nearest rival, SAP, at 8.3% share.
  • Worldwide spending on customer experience and relationship management (CRM) software grew 15.6% to reach $48.2B in 2018.
  • 72.9% of CRM spending was on software as a service (SaaS) in 2018, which is expected to grow to 75% of total CRM software spending in 2019.
  • Worldwide enterprise application software revenue totaled more than $193.6B in 2018, a 12.5% increase from 2017 revenue of $172.1B. CRM made up nearly 25% of the entire enterprise software revenue market.

CRM remains the largest and fastest growing enterprise software category today according to the latest market sizing, and market share research Gartner published this weekGartner defines CRM as providing the functionality to companies across the four segments of customer service and support, digital commerce, marketing, and sales. All four subsegments of the CRM market grew by more than 13.7%, with marketing emerging as the fastest growing segment, increasing by 18.8% and representing more than 25% of the entire CRM market. Customer service and support retain its No. 1 position, contributing 35.7% of CRM market revenue, attaining $17.1B in revenues in 2018.

Key insights include the following:

  • With 19.5% market share, Salesforce has over 2X the CRM sales SAP has and over 3X of Oracle. Salesforce continues to dominate CRM globally, increasing its market share from 18.3% in 2017 to 19.5% in 2018. Adobe is the only other vendor to grow its market share in 2018. Microsoft and SAP successfully held onto to market share while Oracle lost share.

  • Adobe and Salesforce grew faster than the overall market, increasing CRM revenues 21.7% and 23.2% respectively. Adobe’s CRM sales jumped from $2B in 2017 to $2.4B in 2018. Salesforce CRM revenues increased from $7.6B in 2017 to $9.4B in 2018, growing the fastest of all competitors in this market. SAP grew 15.5% between 2017 and 2018, just below the overall market growth of 15.6%. Microsoft (15%) and Oracle (7.1%) grew slower than the market. The following graphic compares growth rates between 2017 and 2018.

  • Adobe dominates the marketing subsegment of CRM with 19% market share in 2018. Salesforce has 11.7% of the marketing subsegment, followed by IBM (5.7%), SAP (4%), Oracle (3.6%) and HubSpot (3.4%). Gartner estimates the marketing subsegment was a $12.2B market in 2018, increasing from $10.3B in 2017, achieving 18.8% growth in just a year.
  • Eastern and Western Europe were the fastest growing regions at 19.7% and 17.5% respectively. North America and Western Europe were the largest two regions with North America growing at 15.2% to reach $28.1B in revenue.

Sources:

Gartner Says Worldwide Customer Experience and Relationship Management Software Market Grew 15.6% in 2018

Market Share: Customer Experience and Relationship Management, Worldwide, 2018 (client access required)

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CPQ Needs To Scale And Support Smarter, More Connected Products

  • For smart, connected product strategies to succeed they require a product lifecycle view of configurations, best attained by integrating PLM, CAD, CRM, and ERP systems.
  • Capgemini estimates that the size of the connected products market will be $519B to $685B by 2020.
  • In 2018, $985B will be spent on IoT-enabled smart consumer devices, soaring to $1.49B in 2020, attaining a 23.1% compound annual growth rate (CAGR) according to Statista.
  • Industrial manufacturers will spend on average $121M a year on smart, connected products according to Statista.

Succeeding with a smart, connected product strategy is requiring manufacturers to accelerate their IoT & software development expertise faster than they expected. By 2020, 50% of manufacturers will generate the majority of their revenues from smart, connected products according to Capgemini’s recent study. Manufacturers see 2019 as the breakout year for smart, connected products and the new revenue opportunities they provide.

Industrial Internet of Things (IIoT) platforms has the potential of providing a single, unified data model across an entire manufacturing operation, giving manufacturers a single unified view of product configurations across their lifecycles. Producing smart, connected products at scale also requires a system capable of presenting a unified view of configurations in the linguistics each department can understand. Engineering, production, marketing, sales, and service all need a unique view of product configurations to keep producing new products. Leaders in this field include Configit and their Configuration Lifecycle Management approach to CPQ and product configuration.

Please see McKinsey’s article IIoT platforms: The technology stack as a value driver in industrial equipment and machinery which explores how the Industrial Internet of things (IIoT) is redefining industrial equipment and machinery manufacturing. The following graphic from the McKinsey explains why smart, connected product strategies are accelerating across all industries. Please click on the graphic to expand it for easier reading.

CPQ Needs To Scale Further To Sell Smart, Connected Products

Smart, connected products are redefining the principles of product design, manufacturing, sales, marketing, and service. CPQ systems need to grow beyond their current limitations by capitalizing on these new principles while scaling to support new business models that are services and subscription-based.

The following are the key areas where CPQ systems are innovating today, making progress towards enabling the custom configuration of smart, connected products:

  • For smart, connected product strategies to succeed they require a product lifecycle view of configurations, best attained by integrating PLM, CAD, CRM, and ERP systems. Smart, connected product strategies require real-time integration between front-end and back-end systems to optimize production performance. And they also require advanced visualization that provides prospects with an accurate, 3D-rendered view that can be accurately translated to a Bill of Materials (BOM) and into production. The following graphic is based on conversations with Configit customers, illustrating how they are combining PLM, CAD, CRM and ERP systems to support smart, connected products related to automotive manufacturing. Please click on the graphic to expand it for easier reading.

  • CPQ and product configuration systems need to reflect the products they’re specifying are part of a broader ecosystem, not stand-alone. The essence of smart, connected products is their contributions to broader, more complex networks and ecosystems. CPQ systems need to flex and support much greater system interoperability of products than they do today. Additional design principles include designing in connected service options, evergreen or long-term focus on the product-as-a-platform and designed in support for entirely new pricing models.
  • Smart, connected products need CPQ systems to reduce physical complexity while scaling device intelligence through cross-sells, up-sells and upgrades. Minimizing the physical options to allow for greater scale and support for device intelligence-based ones are needed in CPQ systems today. For many CPQ providers, that’s going to require different data models and taxonomies of product definitions. Smart, connected products will be modified after purchase as well, evolving to customers’ unique requirements.
  • After-sales service for smart, connected products will redefine pricing and profit models for the better in 2019, and CPQ needs to keep up to make it happen. Giving products the ability to send back their usage rates and patterns, reliability and performance data along with their current condition opens up lucrative pricing and services models. CPQ applications need to be able to provide quotes for remote diagnostics, price breaks on subscriptions for sharing data, product-as-a-service and subscription-based options for additional services. Many CPQ systems will need to be updated to support entirely new services-driven business models manufacturers are quickly adopting today.

Which CRM Applications Matter Most In 2018

 

According to recent research by Gartner,

  • Marketing analytics continues to be hot for marketing leaders, who now see it as a key business requirement and a source of competitive differentiation
  • Artificial intelligence (AI) and predictive technologies are of high interest across all four CRM functional areas, and mobile remains in the top 10 in marketing, sales and customer service.
  • It’s in customer service where AI is receiving the highest investments in real use cases rather than proofs of concept (POCs) and experimentation.
  • Sales and customer service are the functional areas where machine learning and deep neural network (DNN) technology is advancing rapidly.

These and many other fascinating insights are from Gartner’s What’s Hot in CRM Applications in 2018 by Ed Thompson, Adam Sarner, Tad Travis, Guneet Bharaj, Sandy Shen and Olive Huang, published on August 14, 2018. Gartner clients can access the study here  (10 pp., PDF, client access reqd.).

Gartner continually tracks and analyzes the areas their clients have the most interest in and relies on that data to complete their yearly analysis of CRM’s hottest areas. Inquiry topics initiated by clients are an excellent leading indicator of relative interest and potential demand for specific technology solutions. Gartner organizes CRM technologies into the four category areas of Marketing, Sales, Customer Service, and Digital Commerce.

The following graphic from the report illustrates the top CRM applications priorities in Marketing, Sales, Customer Service, and Digital Commerce.

Key insights from the study include the following:

  • Marketing analytics continues to be hot for marketing leaders, who now see it as a key business requirement and a source of competitive differentiation. In my opinion and based on discussions with CMOs, interest in marketing analytics is soaring as they are all looking to quantify their team’s contribution to lead generation, pipeline growth, and revenue. I see analytics- and data-driven clarity as the new normal. I believe that knowing how to quantify marketing contributions and performance requires CMOs and their teams to stay on top of the latest marketing, mobile marketing, and predictive customer analytics apps and technologies constantly. The metrics marketers choose today define who they will be tomorrow and in the future.
  • Artificial intelligence (AI) and predictive technologies are of high interest across all four CRM functional areas, and mobile remains in the top 10 in marketing, sales and customer service. It’s been my experience that AI and machine learning are revolutionizing selling by guiding sales cycles, optimizing pricing and enabling CPQ to define and deliver smart, connected products. I’m also seeing CMOs and their teams gain value from Salesforce Einstein and comparable intelligent agents that exemplify the future of AI-enabled selling. CMOs are saying that Einstein can scale across every phase of customer relationships. Based on my previous consulting in CPQ and pricing, it’s good to see decades-old core technologies underlying Price Optimization and Management are getting a much-needed refresh with state-of-the-art AI and machine learning algorithms, which is one of the factors driving their popularity today. Using Salesforce Einstein and comparable AI-powered apps I see sales teams get real-time guidance on the most profitable products to sell, the optimal price to charge, and which deal terms have the highest probability of closing deals. And across manufacturers on a global scale sales teams are now taking a strategic view of Configure, Price, Quote (CPQ) as encompassing integration to ERP, CRM, PLM, CAD and price optimization systems. I’ve seen global manufacturers take a strategic view of integration and grow far faster than competitors. In my opinion, CPQ is one of the core technologies forward-thinking manufacturers are relying on to launch their next generation of smart, connected products.
  • It’s in customer service where AI is receiving the highest investments in real use cases rather than proofs of concept (POCs) and experimentation. It’s fascinating to visit with CMOs and see the pilots and full production implementations of AI being used to streamline customer service. One CMO remarked how effective AI is at providing greater contextual intelligence and suggested recommendations to customers based on their previous buying and services histories. It’s interesting to watch how CMOs are attempting to integrate AI and its associated technologies including ChatBots to their contribution to Net Promoter Scores (NPS). Every senior management team running a marketing organization today has strong opinions on NPS. They all agree that greater insights gained from predictive analytics and AI will help to clarify the true value of NPS as it relates to Customer Lifetime Value (CLV) and other key metrics of customer profitability.
  • Sales and customer service are the functional areas where machine learning and deep neural network (DNN) technology is advancing rapidly.  It’s my observation that machine learning’s potential to revolutionize sales is still nascent with many high-growth use cases completely unexplored. In speaking with the Vice President of Sales for a medical products manufacturer recently, she said her biggest challenge is hiring sales representatives who will have longer than a 19-month tenure with the company, which is their average today.  Imagine, she said, knowing the ideal attributes and strengths of their top performers and using machine learning and AI to find the best possible new sales hires. She and I discussed the spectrum of companies taking on this challenge, with Eightfold being one of the leaders in applying AI and machine learning to talent management challenges.

Source: Gartner by Ed Thompson, Adam Sarner, Tad Travis, Guneet Bharaj,  Sandy Shen and Olive Huang, published on August 14, 2018.

Top 10 Ways Integration Will Transform Manufacturing In 2017

SAP and CRM Integration critical to manfuacturing innovation

Integrating ERP, CRM, and legacy systems lead to greater manufacturing innovation, setting the foundation to move beyond business models that don’t stay in step with customers’ fast-changing needs. Bringing contextual intelligence into manufacturing that centers on customers’ unique, fast-changing requirements is a must-have to keep growing sales profitably. By integrating ERP, CRM, SCM, pricing and legacy systems together, manufacturers can provide customers what they want most, and that’s accurate, fast responses to their questions and perfect orders delivered.

Integration Powers Manufacturing Innovation

Enabling a faster pace of innovation in manufacturing starts by using systems and process integration as a growth catalyst to profitably grow.There is a myriad of ways integration will transform manufacturing in 2017, and the top 10 ways are presented below:

  1. Real-time visibility across selling, pricing, product, manufacturing and service improves the speed of customer response and makes planning easier. By integrating legacy SAP ERP systems with CRM, pricing, product catalog, Manufacturing Execution Systems (MES) and service, telling customers in real-time the status of their orders is possible. Having real-time data on manufacturing operations provides planners with the visibility they need to optimize production schedules, including fine-tuning Material Requirements Planning (MRP). By orchestrating these areas of manufacturing more efficiently, customer satisfaction increases, the potential of upselling and cross-sell improves and less order fulfillment errors turn into higher profits.
  1. Making analytics the fuel manufacturing needs to move faster, attaining time-to-market goals and exceeding customer expectations. One of the quickest ways manufacturers are going to use integration to fuel greater growth in 2017 is by using analytics to measure operations from the customer’s perspective first. From quality management to order fulfillment and meeting delivery dates, every manufacturer has the baseline data they need to begin a customer-driven analytics strategy today. Integration is the catalyst that is making this happen. Making quality a company-wide focus begins with real-time integration of quality management and broader IT systems. enosiX has taken a unique approach to real-time integration, streamlining quality inspections and inventory control for beverage equipment manufacturer Bunn.
  1. Improving new product success rates by integrating CRM, pricing, product catalog, service, and Product Lifecycle Management (PLM) systems are enabling manufacturers to create new product lines that drive new business models. For consumer electronics and high-tech products manufacturers serving B2C (business to consumer) and Business to Business (B2B), speed and time-to-market are a core part of their business models. Capitalizing on the speed of customers’ changing requirements is more important to stay ins type with than competitors, however. To do this, manufacturers capturing feedback from service and PLM systems and then putting it into context using CRM systems can innovate faster than competitors who track each other instead of customers.
  1. Configure-Price-Quote (CPQ) will continue to be one of the most effective strategies manufacturers can use for accelerating sales in 2017, made possible by the real-time integration between ERP, CRM, pricing and manufacturing systems. Winning new customers and closing deals often comes down to being faster than competitors at delivering accurate, complete quotes and proposals. By integrating CRM, ERP, and pricing systems manufacturers can trim days and in some cases weeks and months off of how long it takes to produce a quote or proposal. CPQ will continue to accelerate in 2017, gaining momentum as more manufacturers move beyond their manually-based methods of quoting and opt for more integrated approaches to excelling at this vital selling activity.
  1. Industry 4.0’s many advantages including creating smart factories are dependent on the real-time integration of traditional IT and manufacturing systems increasing production speed and quality. Engraining greater contextual intelligence into every phase of manufacturing increases shop-floor visibility. It also makes planning more efficient and customer-driven. The key to revitalizing existing production centers and getting them started on the journey to becoming smart factories depends on the real-time integration of IT and manufacturing systems.
  1. Personalizing pricing strategies by customer persona and segment using real-time integration between CRM, pricing, accounting and finance systems to optimize profitability. Manufacturers doing this today also have propensity models that define which customers are most and least likely to accept up-sell and cross-sell offers. For many manufacturers, this level of pricing precision is possible today with greater systems integration. By having pricing strategies defined by persona and segment, measuring just how much speed and time-to-market matters to each is possible by measuring sales rates of new products and services.
  1. IT system security companywide improves with tighter real-time integration as long-standing legacy systems are updated to enable greater connectivity with newer systems. When manufacturers choose to pursue a more focused, urgent strategy fo systems integration to improve manufacturing performance, system security often improves companywide. It’s because longstanding legacy systems, often the most vulnerable to unauthorized use, get re-evaluated at the operating system and integration levels. The result is company-wide IT security improves when real-time integration is attained. For manufacturers where 70% or more of their materials and costs are from outside their owned production centers, this is more important in 2017 than ever before.
  1. Sensor data generated from the Internet of Things (IoT) combined with advanced analytics is transforming manufacturing today and will accelerate in 2017. Manufacturers with globally-based operations are piloting and using IoT strategies in daily operations today. A few are working with semiconductor manufacturers to design in their specific requirements at the chip level. Having real-time integration in place between ERP, CRM, pricing and services systems provides the scalable, secure foundation to build advanced analytics and IoT platforms that can scale over the long-term.
  1. Market leaders in manufacturing are designing in real-time integration to their connected products, enabling new sources of revenue. General Electric’s approach to monitoring jet engines in flight and providing real-time data to aircraft manufacturers including Boeing and airlines globally is an example of how integration is enabling entirely new business models. A global aerospace manufacturer who requested anonymity is working with integrated circuit developers Broadcom, Intel, and Qualcomm to create chipsets that can provide sensor-based data on an entire jet’s health in real-time anywhere in the world, anytime.
  1. Greater visibility and speed are coming to supply chains, enabling manufacturers the ability to take an accepted quote and turn it into build instructions in real-time. Automating the steps of taking a quote and turning it into a bill of materials, scheduling the best possible work teams, and orchestrating parts and materials all is becoming automated from quote approval. From a customer’s perspective, all they see is the approved quote and activity starting immediately to provide the products they ordered. By having this level fo real-time supply chain integration, speed becomes the new normal and customer expectations are met and often exceeded.

Five Strategies For Improving Customer Relationships Using Salesforce Integration

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

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

Five Strategies For Improving Customer Relationships Using Salesforce Integration

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

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

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

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

10 Ways Machine Learning Is Revolutionizing Manufacturing

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

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

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

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

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

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

factory and demand analytics

Source:  GE Global Research Stifel 2015 Industrials Conference

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

Azure IOT Services

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

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

OEE Graphic

Source: Using Big Data for Machine Learning Analytics in Manufacturing

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

Salesforce AI Acquisitions

Salesforce revenue sources

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

Additional reading:

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

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

Focus Group: Big Data Analytics for Smart Manufacturing Systems

GE Predix: The Industrial Internet Platform

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

Machine Learning: What It Is And Why It Matters

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

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

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

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

University of Washington CSE 446 – Machine Learning – Winter 2014

Sources:

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

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

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

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

Gartner Top 10 Strategic Technology Trends For 2016

2016 Gartner technology trends graphicGartner 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 2016You 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:

top ten technology trends 2016

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

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

  • globeCloud 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.

cloud growth

  • 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.

globe

  • 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.

US Metro

  •  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.

sector investing

2015 Roundup Of Analytics, Big Data & Business Intelligence Forecasts And Market Estimates

  • NYC SkylineSalesforce (NYSE:CRM) estimates adding analytics and Business Intelligence (BI) applications will increase their Total Addressable Market (TAM) by $13B in FY2014.
  • 89% of business leaders believe Big Data will revolutionize business operations in the same way the Internet did.
  • 83% have pursued Big Data projects in order to seize a competitive edge.

Despite the varying methodologies used in the studies mentioned in this roundup, many share a common set of conclusions. The high priority in gaining greater insights into customers and their unmet needs, more precise information on how to best manage and simplify sales cycles, and how to streamline service are common themes.

The most successful Big Data uses cases revolve around enterprises’ need to get beyond the constraints that hold them back from being more attentive and responsive to customers.

Presented below is a roundup of recent forecasts and estimates:

  • Wikibon projects the Big Data market will top $84B in 2026, attaining a 17% Compound Annual Growth Rate (CAGR) for the forecast period 2011 to 2026. The Big Data market reached $27.36B in 2014, up from $19.6B in 2013. These and other insights are from Wikibon’s excellent research of Big Data market adoption and growth. The graphic below provides an overview of their Big Data Market Forecast.  Source: Executive Summary: Big Data Vendor Revenue and Market Forecast, 2011-2026.

Wikibon big data forecast

  • IBM and SAS are the leaders of the Big Data predictive analytics market according to the latest Forrester Wave™: Big Data Predictive Analytics Solutions, Q2 2015. The latest Forrester Wave is based on an analysis of 13 different big data predictive analytics providers including Alpine Data Labs, Alteryx, Angoss Software, Dell, FICO, IBM, KNIME.com, Microsoft, Oracle, Predixion Software, RapidMiner, SAP, and SAS. Forrester specifically called out Microsoft Azure Learning is an impressive new entrant that shows the potential for Microsoft to be a significant player in this market. Gregory Piatetsky (@KDNuggets) has done an excellent analysis of the Forrester Wave Big Data Predictive Analytics Solutions Q2 2015 report here. Source: Courtesy of Predixion Software: The Forrester Wave™: Big Data Predictive Analytics Solutions, Q2 2015 (free, no opt-in).

Forrester Wave Big Data Predictive Analytics

  • IBM, KNIME, RapidMiner and SAS are leading the advanced analytics platform market according to Gartner’s latest Magic Quadrant. Gartner’s latest Magic Quadrant for advanced analytics evaluated 16 leading providers of advanced analytics platforms that are used to building solutions from scratch. The following vendors were included in Gartner’s analysis: Alpine Data Labs, Alteryx, Angoss, Dell, FICO, IBM, KNIME, Microsoft, Predixion, Prognoz, RapidMiner, Revolution Analytics, Salford Systems, SAP, SAS and Tibco Software, Gregory Piatetsky (@KDNuggets) provides excellent insights into shifts in Magic Quadrant for Advanced Platform rankings here.  Source: Courtesy of RapidMinerMagic Quadrant for Advanced Analytics Platforms Published: 19 February 2015 Analyst(s): Gareth Herschel, Alexander Linden, Lisa Kart (reprint; free, no opt-in).

Magic Quadrant for Advanced Analytics Platforms

  • Salesforce estimates adding analytics and Business Intelligence (BI) applications will increase their Total Addressable Market (TAM) by $13B in FY2014. Adding new apps in analytics is projected to increase their TAM to $82B for calendar year (CY) 2018, fueling an 11% CAGR in their total addressable market from CY 2013 to 2018. Source: Building on Fifteen Years of Customer Success Salesforce Analyst Day 2014 Presentation (free, no opt in).

Salesforce Graphic

  • 89% of business leaders believe big data will revolutionize business operations in the same way the Internet did. 85% believe that big data will dramatically change the way they do business. 79% agree that ‘companies that do not embrace Big Data will lose their competitive position and may even face extinction.’ 83% have pursued big data projects in order to seize a competitive edge. The top three areas where big data will make an impact in their operations include: impacting customer relationships (37%); redefining product development (26%); and changing the way operations is organized (15%).The following graphic compares the top six areas where big data is projected to have the greatest impact in organizations over the next five years. Source: Accenture, Big Success with Big Data: Executive Summary (free, no opt in).

Big Data Big Success Graphic

Frost & Sullivan Graphic

 

global text market graphic

 

  • Customer analytics (48%), operational analytics (21%), and fraud & compliance (21%) are the top three use cases for Big Data. Datameer’s analysis of the market also found that the global Hadoop market will grow from $1.5B in 2012 to $50.2B in 2020, and financial services, technology and telecommunications are the leading industries using big data solutions today. Source: Big Data: A Competitive Weapon for the Enterprise.

Big Data Use Cases in Business

  • 37% of Asia Pacific manufacturers are using Big Data and analytics technologies to improve production quality management. IDC found manufacturers in this region are relying on these technologies to reduce costs, increase productivity, and attract new customers. Source: Big Data and Analytics Core to Nex-Gen Manufacturing.

big data in manufacturing

  • Supply chain visibility (56%), geo-location and mapping data (47%) and product traceability data (42%) are the top three potential areas of Big Data opportunity for supply chain management. Transport management, supply chain planning, & network modeling and optimization are the three most popular applications of Big Data in supply chain initiatives. Source: Supply Chain Report, February 2015.

Big data use in supply chains

  • Finding correlations across multiple disparate data sources (48%), predicting customer behavior (46%) and predicting product or services sales (40%) are the three factors driving interest in Big Data analytics. These and other fascinating findings from InformationWeek’s 2015 Analytics & BI Survey provide a glimpse into how enterprises are selecting analytics applications and platforms. Source: Information Week 2015 Analytics & BI Survey.

factors driving interest in big data analysis

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

Why Salesforce Is Winning The Cloud Platform War

300px-Salesforce_Logo_2009The future of any enterprise software vendor is being decided today in their developer community.

Alex William’s insightful thoughts on Salesforce Is A Platform Company. Period. underscores how rapidly Salesforce is maturing as a cloud platform.  And the best measure of that progress can be seen in their developer community.

(To be clear, Salesforce and the other companies mentioned in this post are not clients and never have been.  I track this area out of personal interest.)

DevZone force.com

The last four years I’ve made a point at every Salesforce Dreamforce event to spend the majority of my time in the developer area.  Watching mini hacks going on in the DevZone, mini workshops, the Salesforce Platform and Developer keynotes over the last few years has been a great learning experience.  An added plus: developers are often skeptical and want to see new enhancements help streamline their code, extend its functionality, and push the limits of the Force.com platform. This healthy skepticism has led to needed improvements in the Force.com platform, including a change to governor limits on Application Programmer Interface (APIs) performance and many other enhancements.  Despite the criticisms of Force.com being proprietary due to Apex and SOQL, the crowds at developer forums continue to grow every year.

I’ve started to look at the developer area as the crucible or foundry for future apps.  While the Cloud Expo shows how vibrant the partner ecosystem is, the developer area is where tomorrow’s apps are being coded today. The Force.com Workbook, an excellent reference for Force.com developers, was just released October 1 and DeveloperForce shows how far the developer support is matured in Salesforce.  In addition a new Force.com REST API Developer’s Guide is out just last month.

The Journey From Application To Platform

In visiting the developer area of Dreamforce over the last four years I’ve seen indications that Salesforce is successfully transforming itself into a cloud platform business:

  • Significant jump in the quantity and quality of developer attendees from 2010 to 2012.  The depth of questions, sophistication of code samples, calls for more flexibility with governor limits, and better mobile support typified these years.
  • Steady improvement to visual design tools, application development environment and support for jQuery, Sencha and Apache Cordova.
  • The steady maturation of Salesforce Touch as a mobile development platform and launch of Salesforce Platform Mobile Services Launched in 2011, this platform continues to mature, driven by developer’s requirements that reflect their customers’ needs for mobility support.  HTML 5 is supported and the apps I’ve seen written on it are fast, accurate and ideal for customer service.  ServiceMax has created exceptional mobile apps including their comprehensive ServiceMax for iPad app on the Force.com platform.
  • 2012: Rise of the Mobile Enterprise Developer.  Salesforce’s enterprise customers in 2009 weren’t nearly as active as they were last year with questions on legacy systems integration and how to create web services capable of integrating customer data.  2011 was a breakout year in mobile app development with 2012 showing strong momentum on mobile web services development.  I expect this year’s Dreamforce developer community to reflect the rapidly growing interest in mobile as well.

How Enterprise Applications Make The Salesforce Platform Work For Them

In speaking with Salesforce developers over the years one of my favorite questions continues to be “what is the real payoff of having a native Force.com application in your company?”  Initially I thought this was marketing spin from enterprise software vendors attempting to use features as benefits, however after a closer look it is clear that the platform has significant advantages, especially for any solution requiring global deployments or large numbers of users.  Here is what I found out:

  • The investments Salesforce.com has made in their cloud infrastructure over several years (and continue to make) has resulted in a platform that developers  are leveraging to rapidly deliver enterprise applications that deliver world-class performance, reliability, and security.
  • Of the many native Force.com applications that extend Salesforce beyond CRM, it’s been my experience the most challenging are Configure-Price-Quote (CPQ) and contract management.  Creating a single system of record across these two areas is challenging even outside of Force.com, which is why many companies in this space have two entirely different product strategies.  Apttus is the exception as they have successfully created a unified product strategy on Force.com alone.  I recently had the chance to speak with Neehar Giri, President and Chief Solutions Architect.  “Apttus’ strategic decision to deliver our enterprise-class applications natively on the Salesforce platform has allowed us to focus on our customer needs, meeting and exceeding their expectations in both functionality and speed of innovation,” said Neehar Giri, president and chief solutions architect, Apttus.  “We’ve seen the platform evolve rapidly in its capabilities and global scalability.  Apttus’ customers have and continue to benefit from the true multi- tenancy, world class security, reliability and performance of the Salesforce Platform.”
  • Salesforce.com’s multi-tenant architecture allows for optimization of computing resources resulting in savings and significant gains in efficiency for global enterprises even over applications deployed on private clouds.
  • Native Force.com applications share the same security model as Salesforce apps.  Financialforce.com chose to develop their accounting, ordering and billing, professional services automation and service resource planning entirely on the Force.com architecture due to shared master data, multi- tenancy, world class security, reliability and performance.  This shared architecture also benefits enterprise consumers of native applications by providing best-in-class uptime.
  • Native Force.com applications are contributing to greater return on investment (ROI). IT often does not need to manage data integration or sync issues, upgrades to even large numbers of users are easily deployed, and users can remain in a familiar interface.   These benefits support faster and easier deployment as well as rapid user adoption both of which are critical to success and a high ROI for any solution. Enterprise developers have often mentioned the familiar interface and ease of deployment have led to higher rates of adoption than any other approach to delivering new application functionality.
  • Advanced APIs to support integration of legacy applications not on the Force.com platform.
  • Proven ability of Salesforce.com to support global deployments.  The company has expanded its global support centers.  Salesforce.com also publishes real-time statistics on system status: http://trust.salesforce.com/trust/.
  • A continuing acceleration of new capabilities resulting from increasing numbers of developers driving the advancement of the platform through their collective input, suggestions and requirements.
  • Ability to design applications that respond with greater customer insight and intelligence across mobile devices.  ServiceMax has an impressive series of mobile applications that do this today.  I had a chance to speak with David Yarnold, their CEO about his vision for the company.  He wants to give ServiceMax’s customers the ability to deliver flawless field service where every interaction is perfect.  By building on the Force.com architecture he explained how each service customers’ contextual intelligence can be seen in real-time by everyone involved in serving customers.  Clearly ServiceMax is capitalizing on the mobile development platform area of Force.com as well.

Bottom Line: Enabling developers to attain greater revenue growth, while creating an extensive mobile app development platform is further proof Salesforce has turned the corner from being an application company to a platform provider.

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