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Posts from the ‘enosix’ Category

McKinsey’s 2016 Analytics Study Defines The Future Of Machine Learning

  • U.S. retailer supply chain operations who have adopted data and analytics have seen up to a 19% increase in operating margin over the last five years.
  • Design-to-value, supply chain management and after-sales support are three areas where analytics are making a financial contribution in manufacturing.
  • 40% of all the potential value associated with the Internet of Things requires interoperability between IoT systems.

These and many other insights are from the McKinsey Global Institute’s study The Age of Analytics: Competing In A Data-Driven World published in collaboration with McKinsey Analytics this month. You can get a copy of the Executive Summary here (28 pp., free, no opt-in, PDF) and the full report (136 pp., free, no opt-in, PDF) here. Five years ago the McKinsey Global Institute (MGI) released Big Data: The Next Frontier For Innovation, Competition, and Productivity (156 pp., free no opt-in, PDF), and in the years since McKinsey sees data science adoption and value accelerate, specifically in the areas of machine learning and deep learning. The study underscores how critical integration is for gaining greater value from data and analytics.

Key takeaways from the study include the following:McKinsey Analytics

  • Location-based services and U.S. retail are showing the greatest progress capturing value from data and analytics. Location-based services are capturing up to 60% of data and analytics value today predicted by McKinsey in their 2011 report. McKinsey predicts there are growing opportunities for businesses to use geospatial data to track assets, teams, and customers across dispersed locations to generate new insights and improve efficiency. U.S. Retail is capturing up to 40%, and Manufacturing, 30%.  The following graphic compares the potential impact as predicted in McKinsey’s 2011 study with the value captured by segment today, including a definition of major barriers to adoption.

uneven-progress

  • Machine learning’s greatest potential across industries includes improving forecasting and predictive analytics. McKinsey analyzed the 120 use cases their research found as most significant in machine learning and then weighted them based on respondents’ mention of each. The result is a heat map of machine learning’s greatest potential impact across industries and use case types.  Please see the report for detailed scorecards of each industry’s use case ranked by impact and data richness.

machine-learning-impact

  • Machine learning’s potential to deliver real-time optimization across industries is just starting to evolve and will quickly accelerate in the next three years. McKinsey analyzed the data richness associated with each of the 300 machine learning use cases, defining this attribute as a combination of data volume and variety. Please see page 105 of the study for a thorough explanation of McKinsey’s definition of data volume and variety used in the context of this study The result of evaluating machine learning’s data richness by industry is shown in the following heat map:

rich-data-is-an-enabler

  • Enabling autonomous vehicles and personalizing advertising are two of the highest opportunity use cases for machine learning today. Additional use cases with high potential include optimizing pricing, routing, and scheduling based on real-time data in travel and logistics; predicting personalized health outcomes, and optimizing merchandising strategy in retail. McKinsey identified 120 potential use cases of machine learning in 12 industries and surveyed more than 600 industry experts on their potential impact. They found an extraordinary breadth of potential applications for machine learning.  Each of the use cases was identified as being one of the top three in an industry by at least one expert in that industry. McKinsey plotted the top 120 use cases below, with the y-axis shows the volume of available data (encompassing its breadth and frequency), while the x-axis shows the potential impact, based on surveys of more than 600 industry experts. The size of the bubble reflects the diversity of the available data sources.

machine-learning

  • Designing an appropriate organizational structure to support data and analytics activities (45%), Ensuring senior management involvement (42%), and designing effective data architecture and technology infrastructure (36%) are the three most significant challenges to attaining data and analytics objectives. McKinsey found that the barriers break into the three categories: strategy, leadership, and talent; organizational structure and processes; and technology infrastructure. Approximately half of executives across geographies and industries reported greater difficulty recruiting analytical talent than any other kind of talent. 40% say retention is also an issue.

barriers-to-analytics-and-machine-learning-adoption

  • U.S. retailer supply chain operations who have adopted data and analytics have seen up to a 19% increase in operating margin over the last five years. Using data and analytics to improve merchandising including pricing, assortment, and placement optimization is leading to an additional 16% in operating margin improvement. The following table illustrates data and analytics’ contribution to U.S. retail operations by area.

us-retail-data-sheet

  • Design-to-value, supply chain management and after-sales support are three areas where analytics are making a financial contribution in manufacturing. McKinsey estimates that analytics have increased manufacturer’s gross margins by as much as 40% when used in design-to-value workflows and projects. Up to 15% of after-sales costs have been reduced through the use of analytics that includes product sensor data analysis for after-sales service. There are several interesting companies to watch in this area, with two of the most innovative being Sight Machine and enosiX, with the latter enabling real-time integration between SAP and Salesforce systems. The following graphic illustrates the estimated impact of analytics on manufacturing financial performance by area.

manufacturing

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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.

Integration Will Accelerate Internet Of Things, Industrial Analytics Growth In 2017 

  • internet of thingsEnabling real-time integration across on-premise and cloud platforms often involves integrating SAP, Salesforce, third-party and legacy systems. 2017 will be a break-out year for real-time integration between SAP, Salesforce, and third party systems in support of Internet of Things and Industrial Analytics.
  • McKinsey Global Institute predicts that the Internet of Things (IoT) will generate up to $11T in value to the global economy by 2025.
  • Predictive and prescriptive maintenance of machines (79%), customer/marketing related analytics (77%) and analysis of product usage in the field (76%) are the top three applications of Industrial Analytics in the next 1 to 3 years.

Real-Time Integration Is the Cornerstone Of Industrial Analytics

Industrial Analytics (IA) describes the collection, analysis and usage of data generated in industrial operations and throughout the entire product lifecycle, applicable to any company that is manufacturing and selling physical products. It involves traditional methods of data capture and statistical modeling. Enabling legacy, third-party and Salesforce, SAP integration is one of the most foundational technologies that Industrial Analytics relies on today and will in the future. Real-time integration is essential for enabling connectivity between Internet of Things (IoT) devices, in addition to enabling improved methods for analyzing and interpreting data. One of the most innovative companies in this area is enosiX, a leading global provider of Salesforce and SAP integration applications and solutions.  They’re an interesting startup to watch and have successfully deployed their integration solutions at Bunn, Techtronic Industries, YETI Coolers and other leading companies globally.

A study has recently been published that highlights just how foundational integration will be to Industrial Analytics and IoT. You can download the Industrial Analytics Report 2016/17 report here (58 pp., PDF, free, opt-in). This study was initiated and governed by the Digital Analytics Association e.V. Germany (DAAG), which runs a professional working group on the topic of Industrial Analytics. Research firm IoT Analytics GmbH was selected to conduct the study. Interviews with 151 analytics professionals and decision-makers in industrial companies were completed as part of the study. Hewlett-Packard Enterprise, data science service companies Comma Soft and Kiana Systems sponsored the research. All research and analysis related steps required for the study including interviewing respondents, data gathering, data analysis and interpretation, were conducted by IoT Analytics GmbH. Please see page 52 of the study for the methodology.

Key Takeaways:

  • With real-time integration, organizations will be able to Increase revenue (33.1%), increase customer satisfaction (22.1%) and increase product quality (11%) using Industrial Analytics. The majority of industrial organizations see Industrial Analytics as a catalyst for future revenue growth, not primarily as a means of cost reduction. Upgrading existing products, changing the business model of existing products, and creating new business models are three typical approaches companies are taking to generate revenue from Industrial Analytics. Integration is the fuel that will drive Industrial Analytics in 2017 and beyond.

Internet of Things

  • For many manufacturers, the more pervasive their real-time SAP integration is, the more effective their IoT and Industrial Analytics strategies will be. Manufacturers adopting this approach to integration and enabling Industrial Analytics through their operations will be able to attain predictive and prescriptive maintenance of their product machines (79%). This area of preventative maintenance is the most important application of Industrial Analytics in the next 1 – 3 years. Customer/marketing-related analytics (77%) and analysis of product usage in the field (76%) are the second- and third-most important. The following graphic provides an overview of the 13 most important applications of Industrial Analytics.

Internet of Things

  • 68% of decision-makers have a company-wide data analytics strategy, 46% have a dedicated organizational unit and only 30% have completed actual projects, further underscoring the enabling role of integration in their analytics and IoT strategies. The study found that out of the remaining 70% of industrial organizations, the majority of firms have ongoing projects in the prototyping phase.

Internet of things

  • Business Intelligence (BI) tools, Predictive Analytics tools and Advanced Analytics Platforms will be pivotal to enabling industrial data analysis in the next five years. Business Intelligence Tools such as SAP Business Objects will increase in importance to industrial manufacturing leaders from 39% to 77% in the next five years. Predictive Analytics tools such as HPE Haven Predictive Analytics will increase from 32% to 69%. The role of spreadsheets used for industrial data analytics is expected to decline (i.e., 27% think it is important in 5 years vs. 54% today).

Internet of Things

  • The Industrial Analytics technology stack is designed to scale based on the integration of legacy systems, industrial automation apps and systems, MES and SCADA systems integration combined with sensor-based data. IoT Analytics GmbH defines the technology stack based on four components inclouding data sources, necessary infrastructure, analytics tools, and applications. The following graphic illustrates the technology stack and underscores how essential integration is to the vision of Industrial Analytics being realized.

Internet of Things

  • Industrial Internet of Things (IIoT) and Industry 4.0 will rely on real-time integration to enable an era of shop-floor smart sensors that can make autonomous decisions and trade-offs regarding manufacturing execution. IoT Analytics GmbH predicts this will lead to smart processes and smart products that communicate within production environments and learn from their decisions, improving performance over time. The study suggests that Manufacturing Execution System (MES) agents will be vertically integrated into higher level enterprise planning and product change management processes so that these organizations can synchronously orchestrate the flow of data, rather than go through each layer individually.

Internet of Things

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

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

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

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

Key takeaways from the study include the following:

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

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. 

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