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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

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