- The business value-add of blockchain will grow to slightly more than $176B by 2025, then exceed $3.1T by 2030 according to Gartner.
- Typical product recalls cost $8M, and many could be averted with improved track-and-traceability enabled by blockchain.
- Combining blockchain and IoT will revolutionize product safety, track-and-traceability, warranty management, Maintenance, Repair & Overhaul (MRO), and lead to new usage-based business models for smart, connected products.
- By 2023, 30% of manufacturing companies with more than $5B in revenue will have implemented Industry 4.0 pilot projects using blockchain, up from less than 5% today according to Gartner.
Blockchain’s greatest potential to deliver business value is in manufacturing. Increasing visibility across every area of manufacturing starting with suppliers, strategic sourcing, procurement, and supplier quality to shop floor operations including machine-level monitoring and service, blockchain can enable entirely new manufacturing business models. Supply chains are the foundation of every manufacturing business, capable of making use of blockchain’s distributed ledger structure and block-based approach to aggregating value-exchange transactions to improve supply chain efficiency first. By improving supplier order accuracy, product quality, and track-and-traceability, manufacturers will be able to meet delivery dates, improve product quality and sell more.
Capgemini Research Institute’s recent study, Does blockchain hold the key to a new age of supply chain transparency and trust? provide valuable insights into how blockchain can improve supply chains and manufacturing. A copy of the study is available here (PDF, 32 pp., no opt-in). Capgemini surveyed 731 organizations globally regarding their existing and planned blockchain initiatives. Initial interviews yielded 447 organizations who are currently experimenting with or implementing blockchain. Please see pages 25 & 26 of the study for additional details regarding the methodology.
Key takeaways of the study include the following:
- Typical product recalls cost $8M, and many could be averted with improved track-and-traceability enabled by blockchain. Capgemini found that there was 456 food recalls alone in the U.S. last year, costing nearly $3.5B. Blockchain’s general ledger structure provides a real-time audit trail for all transactions secured against modifications making it ideal for audit and compliance-intensive industries.
- Gaining greater cost savings (89%), enhancing traceability (81%) and enhancing transparency (79%) are the top three drivers behind manufacturer’s blockchain investments today. Additional drivers include increasing revenues (57%), reducing risks (50%), creating new business opportunities (44%) and being more customer-centric (38%). The following graphic from the study illustrates the manufacturer’s priorities for blockchain. Capgemini finds that improving track-and-traceability is a primary driver across all manufacturers, consistent with the broader trend of manufacturers adopting software applications that improve this function today. That’s also understandable given how additional regulatory compliance requirements are coming in 2019 and those manufacturers competing in highly regulated industries including aerospace & defense, medical devices, and pharma are exploring how blockchain can give them a competitive edge now
- Digital marketplaces, tracking critical supply chain parameters, tracking components quality, preventing counterfeit products, and tracking asset maintenance are the five areas Capgemini predicts blockchain will see the greatest adoption. Based on interviews with industry experts and startups, Capgemini found 24 blockchain use cases which are compared by level of adoption and complexity in the graphic below. The use cases reflect how managing supplier contracts is already emerging as one of the most popular blockchain use cases for manufacturing organizations today and will accelerate as compliance becomes even more important in 2019.
- Manufacturers have the most at-scale deployments of blockchain today, leading all industries included in the study. Blockchain adoption is still nascent across all industries included in the study, with 6% of manufacturers having at-scale implementations today. Customer products manufacturers lead in pilots, with 15% actively [purusing blockchain in limited scope today. And retailers trail all industries with 91% having only proofs of concept.
- Combining IoT and blockchain at the shipping container level in supply chains increases authenticity, transparency, compliance to product and contractual requirements while reducing counterfeiting. In highly regulated industries including Aerospace & Defense (A&D), Consumer Packaged Goods (CPG), medical devices, and pharma, combining IoT and blockchain provides real-time data on the shipping container conditions, tamper-proof storage, each shipment’s locational history and if there have been changes in temperature and product condition. Capgemini sees use cases where a change in a shipment’s temperature as measured by a sensor change sends alerts regarding contractual compliance of perishable meats and produce, averting the potential of bad product quality and rejected shipments once they reach their destination.
- Capgemini found that 13% of manufacturers are Pacesetters and are either implementing blockchain at scale or have pilots in at least one site. Over 60% of Pacesetters believe that blockchain is already transforming the way they collaborate with their partners. Encouraged by these results, Pacesetters are set to increase their blockchain investment by 30% in the next three years. They lead early stage experimenters and all implementers on three core dimensions of organizational readiness. These include end-to-end visibility across functions, detailed and defined supportive processes, and availability of the right talent to succeed.
- Lack of a clear ROI, immature technology and regulatory challenges are the top three hurdles Pacesetter-class manufacturers face in getting blockchain initiatives accepted and into production. All implementations face these three challenges in addition to having to overcome the lack of complementary IT systems at the partner organizations. The following graphic compares the hurdles all manufacturers face in getting blockchain projects implemented by the level of manufacturers adoption success (Pacesetter, early-stage experimenters, all implementers).
Capitalizing on new digital business models and the growth opportunities they provide are forcing companies to re-evaluate ERP’s role. Made inflexible by years of customization, legacy ERP systems aren’t delivering what digital business models need today to scale and grow.
Legacy ERP systems were purpose-built to excel at production consistency first at the expense of flexibility and responsiveness to customers’ changing requirements. By taking a business case-based approach to integrating Artificial Intelligence (AI) and machine learning into their platforms, Cloud ERP providers can fill the gap legacy ERP systems can’t.
Closing Legacy ERP Gaps With Greater Intelligence And Insight
Companies need to be able to respond quickly to unexpected, unfamiliar and unforeseen dilemmas with smart decisions fast for new digital business models to succeed. That’s not possible today with legacy ERP systems. Legacy IT technology stacks and the ERP systems they are built on aren’t designed to deliver the data needed most.
That’s all changing fast. A clear, compelling business model and successful execution of its related strategies are what all successful Cloud ERP implementations share. Cloud ERP platforms and apps provide organizations the flexibility they need to prioritize growth plans over IT constraints. And many have taken an Application Programming Interface (API) approach to integrate with legacy ERP systems to gain the incremental data these systems provide. In today’s era of Cloud ERP, rip-and-replace isn’t as commonplace as reorganizing entire IT architectures for greater speed, scale, and customer transparency using cloud-first platforms.
New business models thrive when an ERP system is constantly learning. That’s one of the greatest gaps between what Cloud ERP platforms’ potential and where their legacy counterparts are today. Cloud platforms provide greater integration options and more flexibility to customize applications and improve usability which is one of the biggest drawbacks of legacy ERP systems. Designed to deliver results by providing AI- and machine learning insights, Cloud ERP platforms, and apps can rejuvenate ERP systems and their contributions to business growth.
The following are the 10 ways to improve Cloud ERP with AI and machine learning, bridging the information gap with legacy ERP systems:
- Cloud ERP platforms need to create and strengthen a self-learning knowledge system that orchestrates AI and machine learning from the shop floor to the top floor and across supplier networks. Having a cloud-based infrastructure that integrates core ERP Web Services, apps, and real-time monitoring to deliver a steady stream of data to AI and machine learning algorithms accelerates how quickly the entire system learns. The Cloud ERP platform integration roadmap needs to include APIs and Web Services to connect with the many suppliers and buyer systems outside the walls of a manufacturer while integrating with legacy ERP systems to aggregate and analyze the decades of data they have generated.
- Virtual agents have the potential to redefine many areas of manufacturing operations, from pick-by-voice systems to advanced diagnostics. Apple’s Siri, Amazon’s Alexa, Google Voice, and Microsoft Cortana have the potential to be modified to streamline operations tasks and processes, bringing contextual guidance and direction to complex tasks. An example of one task virtual agents are being used for today is guiding production workers to select from the correct product bin as required by the Bill of Materials. Machinery manufacturers are piloting voice agents that can provide detailed work instructions that streamline configure-to-order and engineer-to-order production. Amazon has successfully partnered with automotive manufacturers and has the most design wins as of today. They could easily replicate this success with machinery manufacturers.
- Design in the Internet of Things (IoT) support at the data structure level to realize quick wins as data collection pilots go live and scale. Cloud ERP platforms have the potential to capitalize on the massive data stream IoT devices are generating today by designing in support at the data structure level first. Providing IoT-based data to AI and machine learning apps continually will bridge the intelligence gap many companies face today as they pursue new business models. Capgemini has provided an analysis of IoT use cases shown below, highlighting how production asset maintenance and asset tracking are quick wins waiting to happen. Cloud ERP platforms can accelerate them by designing in IoT support.
- AI and machine learning can provide insights into how Overall Equipment Effectiveness (OEE) can be improved that aren’t apparent today. Manufacturers will welcome the opportunity to have greater insights into how they can stabilize then normalize OEE performance across their shop floors. When a Cloud ERP platform serves as an always-learning knowledge system, real-time monitoring data from machinery and production assets provide much-needed insights into areas for improvement and what’s going well on the shop floor.
- Designing machine learning algorithms into track-and-traceability to predict which lots from which suppliers are most likely to be of the highest or lowest quality. Machine learning algorithms excel at finding patterns in diverse data sets by continually applying constraint-based algorithms. Suppliers vary widely in their quality and delivery schedule performance levels. Using machine learning, it’s possible to create a track-and-trace application that could indicate which lot from which supplier is the riskiest and those that are of exceptional quality as well.
- Cloud ERP providers need to pay attention to how they can help close the configuration gap that exists between PLM, CAD, ERP and CRM systems by using AI and machine learning. The most successful product configuration strategies rely on a single, lifecycle-based view of product configurations. They’re able to alleviate the conflicts between how engineering designs a product with CAD and PLM, how sales & marketing sell it with CRM, and how manufacturing builds it with an ERP system. AI and machine learning can enable configuration lifecycle management and avert lost time and sales, streamlining CPQ and product configuration strategies in the process.
- Improving demand forecasting accuracy and enabling better collaboration with suppliers based on insights from machine learning-based predictive models is attainable with higher quality data. By creating a self-learning knowledge system, Cloud ERP providers can vastly improve data latency rates that lead to higher forecast accuracy. Factoring in sales, marketing, and promotional programs further fine-tunes forecast accuracy.
- Reducing equipment breakdowns and increasing asset utilization by analyzing machine-level data to determine when a given part needs to be replaced. It’s possible to capture a steady stream of data on each machine’s health level using sensors equipped with an IP address. Cloud ERP providers have a great opportunity to capture machine-level data and use machine learning techniques to find patterns in production performance by using a production floor’s entire data set. This is especially important in process industries where machinery breakdowns lead to lost sales. Oil refineries are using machine learning models comprise more than 1,000 variables related to material input, output and process perimeters including weather conditions to estimate equipment failures.
- Implementing self-learning algorithms that use production incident reports to predict production problems on assembly lines needs to happen in Cloud ERP platforms. A local aircraft manufacturer is doing this today by using predictive modeling and machine learning to compare past incident reports. With legacy ERP systems these problems would have gone undetected and turned into production slowdowns or worse, the line having to stop.
- Improving product quality by having machine learning algorithms aggregate, analyze and continually learn from supplier inspection, quality control, Return Material Authorization (RMA) and product failure data. Cloud ERP platforms are in a unique position of being able to scale across the entire lifecycle of a product and capture quality data from the supplier to the customer. With legacy ERP systems manufacturers most often rely on an analysis of scrap materials by type or caused followed by RMAs. It’s time to get to the truth about why products fail, and machine learning can deliver the insights to get there.
- Legacy Services ERP providers excel at meeting professional & consulting services information needs yet often lack the flexibility and speed to support entirely new services business models.
- Configure-Price-Quote (CPQ) is quickly emerging as a must-have feature in Services-based Cloud ERP suites.
From globally-based telecommunications providers to small & medium businesses (SMBs) launching new subscription-based services, the intensity to innovate has never been stronger. Legacy Services ERP and Cloud ERP vendors are responding differently to the urgent needs their prospects and customers have with new apps and suites that can help launch new business models and ventures.
Services-based Cloud ERP providers are reacting by accelerating improvements to Professional Services Automation (PSA), Financials, and questioning if their existing Human Capital Management (HCM) suite can scale now and in the future. Vertical industry specialization is a must-have in many services businesses as well. Factoring all these customer expectations and requirements along with real-time responsiveness into a roadmap deliverable in 12 months or less is daunting. Making good on the promises of ambitious roadmaps that includes biannual release cycles is how born-in-the-Cloud ERP providers will gain new customers including winning many away from legacy ERP providers who can’t react as fast.
The following key takeaways are based on ongoing discussions with global telecommunications providers, hosters and business & professional services providers actively evaluating Cloud ERP suites:
- Roadmaps that reflect a biyearly release cadence complete with user experience upgrades are the new normal for Cloud ERP providers. Capitalizing on the strengths of the Salesforce platform makes this much easier to accomplish than attempting to create entirely new releases every six months based on unique code lines. FinancialForce, Kenandy and Sage have built their Cloud ERP suites on the Salesforce platform specifically for this reason. Of the three, only FinancialForce has provided detailed product roadmaps that specifically call out support for evolving services business models, multiple user interface (UI) refreshes and new features based on customer needs. FinancialForce is also one of the only Cloud ERP providers to publish their Application Programming Interfaces (APIs) already to support their current and next generation user interfaces.
- Cloud ERP leaders are collaborators in the creation of new APIs with their cloud platform provider with a focus on analytics, integration and real-time application response. Overcoming the challenges of continually improving platform-based applications and suites need to start with strong collaboration around API development. FinancialForce’s decision to hire Tod Nielsen, former Executive Vice President, Platform at Salesforce as their CEO in January of this year reflects how important platform integration and an API-first integration strategy is to compete in the Cloud ERP marketplace today. Look for FinancialForce to have a break-out year in the areas of platform and partner integration.
- Analytics designed into the platform so customers can create real-time dashboards and support the services opportunity-to-revenue lifecycle. Real-time data is the fuel that gets new service business models off the ground. When a new release of a Cloud ERP app is designed, it has to include real-time Application Programming Interface (API) links to its cloud platform so customers can scale their analytics and reporting to succeed. What’s most important about this from a product standpoint is designing in the scale to flex and support an entire opportunity-to-revenue lifecycle.
- Having customer & partner councils involved in key phases of development including roadmap reviews, User Acceptance Testing (UAT) and API beta testing are becoming common. There’s a noticeable difference in Cloud ERP apps and suites that have gone through UAT and API beta testing outside of engineering. Customers find areas where speed and responsiveness can be improved and steps saved in getting workflows done. Beta testing APIs with partners and customers forces them to mature faster and scale further than if they had been tested in isolation, away from the market. FinancialForce in services and IQMS in manufacturing are two ERP providers who are excelling in this area today and their apps and suites show it.
- New features added to the roadmap are prioritized by revenue potential for customers first with billing, subscriptions, and pricing being the most urgent. Building Cloud ERP apps and suites on a platform free up development time to solve challenging, complex customer problems. Billing, subscriptions, and pricing are the frameworks many services businesses are relying on to start new business models and fine-tune existing ones. Cloud ERP vendors who prioritize these have a clear view of what matters most to prospects and customers.
- Live and build apps by the mantra “own the process, own the market”. Configure-Price-Quote (CPQ) and Quote-to-Cash (QTC) are two selling processes services and manufacturing companies rely on for revenue daily and struggle with. Born-in-the-cloud CPQ and QTC competitors on the Salesforce platform have the fastest moving roadmaps and release cadences of any across the platform’s broad ecosystem. The most innovative Services-focused Cloud ERP providers look to own opportunity-to-revenue with the same depth and expertise as the CPQ and QTC competitors do.
Configure-Price-Quote (CPQ) continues to be one of the hottest enterprise apps today, fueled by the relentless need all companies have to increase sales while delivering customized orders profitably and accurately. Here are a few of the many results CPQ strategies are delivering today:
- Companies relying on CPQ are growing profit margins at a 57% greater rate year-over-year compared to non-adopters.
- 89% improvement in turning Special Pricing Requests (SPRs) into sales by automating them using a cloud-based CPQ system.
- 67% reduction in reworked orders at a leading specialty vehicle manufacturer due to quotes reflecting exactly what customers wanted to buy.
- 23% improvement in upsell and cross-sell revenue by having the CPQ system intelligently recommend the optimal product or service that has the highest probability of purchase and best possible gross margin.
- CPQ strategies excel when they are designed to reach challenging selling, pricing, revenue and operational performance goals versus automating existing selling workflows.
Another factor fueling CPQs’ rapid growth is how quickly results of a pilot can be measured and used for launching a successful company-wide launch. Pilots often concentrate on quote creation time, quoting accuracy, sales cycle reduction, automating Special Pricing Requests (SPRs), up-sells and cross-sells, perfect order performance, margin improvements and best of all, winning new customers. These are the baseline metrics many companies use to measure their CPQ performance. Throughout 2017 these metrics across industries are accelerating. There is a revolution going on in selling today.
5 Ways CPQ Is Revolutionizing Selling Today
Cloud- and SaaS-based CPQ solutions are quicker to implement, easier to customize to customers’ requirements, and available 24/7 on any Internet-enabled device, anytime. Many are designed to integrate into Salesforce, further accelerating adoption seamlessly. The following five factors are the primary catalysts revolutionizing selling today:
- Designing in excellent user experiences (UX) is the new normal for CPQ apps – CPQ vendors are competing with the quality of user experiences they deliver in 2017, moving beyond packing every feature possible into app releases. This is having a corresponding impact on adoption, increasing the number of sales representatives and entire teams who can get up and running fast with a new CPQ app. The net result is reduced sales cycles, growing pipelines, and more sales reps actively using CPQ apps to increase their selling effectiveness.
- Integrating with legacy CRM, ERP and pricing systems in real-time are using service-oriented frameworks gives sales teams what they need to close deals faster – Legacy CPQ systems in the past often had very precise field mappings to 3rd party legacy CRM, ERP and pricing systems. They were brittle and would break very easily, slowing down sales cycles and making sales reps resort to manually-based approaches from decades before. In 2017 there are service-oriented frameworks that make brittle, easily broken mappings thankfully an integration practice in the past. With a loosely coupled service framework, real-time integration between CRM and ERP systems can be quickly be implemented and sales teams can get out and close more deals. Leaders in the area include enosiX, who are enabling their customers’ sales forces to enter sales orders into SAP directly from Salesforce, saving valuable selling time and increasing order accuracy.
- Competing for deals using Artificial Intelligence (AI), machine learning and Intelligent Agents are force multipliers driving greater sales – Salesforce’s Einstein is an example of the latest generation of AI applications that are enabling sales reps and teams to gain insights that weren’t available before. Combining customer data with these advanced predictive data analytics technologies yields insights into how selling strategies for different accounts can customize to specific prospect needs. Selling strategies are more effective and focused when AI, machine learning, and Intelligent Agents are designed in to guide quoting, pricing and product configuration in real-time.
- CPQ apps optimized for mobile devices are enabling sales reps to drastically reduce quote creation times, sales cycles and increase sales win rates – For many companies whose sales teams are in the field calling on accounts the majority of the time, mobile-based CPQ apps are how they get the majority of their work done. Salesforce’s Force.com is one of the leading platforms CPQ software companies are relying on to create mobile apps, further capitalizing on the already-established levels of familiarity sales teams have with the Salesforce platform.
- The vision many companies have of synchronizing multichannel and omnichannel selling as part of their CPQ strategies is now attainable – One of the greatest challenges of expanding sales channels is ensuring a consistently high-quality customer experience across each. With on-premise CPQ, CRM and ERP selling systems, this is very challenging as there are often multiple database systems supporting each. This is a breakout year for omnichannel selling as cloud-based CPQ systems and the platforms they are built on can securely scale across all selling channels a company chooses to launch. Being able to track which CPQ deals emanated from which marketing program, and which channels are the most effective in closing sales is now possible.
There are many reasons why IT integration projects fail. From the lack of senior management support to imprecise, inaccurate goals, IT integration projects fail more often than they have to. Based on consulting I’ve done with system integrators, distribution providers, financial services firms, logistics providers and manufacturers, five core lessons emerge. One of the most innovative companies taking on these challenges is enosiX, whose customer wins at Yeti Coolers, Vera Bradley, BUNN and others provide a glimpse into the future of real-time integration.
- Middleware forces IT integration projects to focus only on moving data instead of improving business processes.
- Not having a clear idea of the goals the integration needs to attain in the first place.
- Sacrificing application response times, data accuracy and user experience in never-ending middleware projects.
Five Lessons Learned From IT Integration Failures
The following lessons learned are based on my experiences and work with IT departments, Vice Presidents of Infrastructure, Enterprise Systems, Cloud Platforms, CIOs, and CFOs. The lessons learned from them are helping current and future IT integration projects increase the odds of success.
- Selecting middleware or an integration platform not capable of offline, mobile use with the ability to synchronize in real-time once connected. The fastest growing areas of Customer Relationship Management (CRM) are being fueled by the real-time availability of data on mobile devices. In Configure-Price-Quote (CPQ) and Quote-to-Cash (QTC) workflows, tethered and untethered use cases dominate. To be competitive, any company relying on these two strategies to sell must have an integration framework capable of delivering data in real-time that enables quick app response times, higher performance, and a better user experience. IT integration projects that don’t take this requirement into account nearly always fail.
- Selecting an integration solution that requires time-consuming, expensive training and has a steep learning curve. When a given middleware, integration technology or framework is too difficult for IT to learn and use, projects fail fast. The middleware landscape is littered with companies whose marketing is covering up products that have non-existent to mediocre documentation and learning materials. One of the primary factors behind Salesforce’s exceptional growth is their commitment to making the user experience on their platform immediately scalable to each application developed and launched on it. Within 30 minutes, sales teams are often up and running with new apps, successfully selling as a result. Integration frameworks that don’t force system users to change how they work are the new gold standard and are driving the market forward.
- Using middleware for business process logic integration when it is designed for data only. Attempting to use middleware for business process logic workflows can get complex and costly fast. It’s one of the main reasons IT integration projects don’t deliver results. In reality, the most valuable aspects of any integration project are the business processes and supporting logic that is automated, streamlined and tailored to a businesses’ unique needs, revolutionizing it in the process. This point of failure happens when IT architects push middleware beyond its limits and attempt to do what more streamlined integration frameworks are designed to accomplish. Business process logic is core to the future of any IT integration project. It is surprising that more organizations don’t look for integration frameworks that have this capability designed into the core architecture.
- Failing to consider how data transfers can be minimized or eliminated in the planning and deployment of an integration project. The more customer-centric a project, the more the variety and depth of data transfers required for the integration to be complete. Data transfers grow exponentially and can challenge the scale of a middleware platform quickly. The most successful IT integration projects aren’t data transfer-intensive, they are business strategy driven. One of the most effective best practices of integration is not having to move the data at all. Using an SOA-based framework as a means to enable data consumption without having to perform lengthy ETL processes is the future of integration. By definition, middleware relies on a series of tightly-coupled integration points designed to move data asynchronously. In contrast, SOA-based frameworks are designed to enable real-time synchronous communication through the use of loosely-coupled connections that can flex in response to business process requirements.
- Failure to plan and anticipate how a change in one cloud platform or enterprise application including those running on Salesforce’s Force.com, a SAP R/3 system and other platforms impact the entire company’s IT stability. The VP of Infrastructure for a globally-based gaming and hospitality chain told me he and his team often are given the challenging task of bringing up new casino and hotel operations offices globally in two weeks. He sends in an advance team to determine how best to integrate with any legacy on-premise systems. The team also works to integrate any unique Salesforce apps that need to be included into the main Salesforce instance at the tab level, and to determine how best to integrate into the SAP R/3 procurement system. System security is the highest priority during the integration pilot and go-live work. The company has standardized on a series of network adapters and connectors that are designed to shield all traffic across the network. He told me that just one API change in the IT stack supporting their SAP R/3 integration would cause all adapters to quit working, report an error condition and force debugging to the line level. They learned this during a go-live with a Reno property. Today all changes to middleware are run in a pilot mode in a sandbox first, and the company is looking to get away from middleware entirely as a result.
From the enosiX blog post, Why IT Integration Projects Fail.
- 93% of global product leaders say that predictive maintenance combined with real-time equipment monitoring enabled by integration is a must-have for factory planning today.
- 75% of global product leaders plan to implement factory of the future initiatives and programs in the next five years or less, starting with Industry 4.0
- 67% of automotive executives expect that new technologies enabled by real-time integration will enable their teams to reach and exceed lean management and continuous improvement goals starting this year and accelerating through 2030.
Boston Consulting Group’s recent article, The Factory of the Future provides insights into a recent global survey the consulting firm conducted of more than 750 manufacturing product leaders from leading companies in three industrial sectors: automotive (which includes suppliers and original equipment manufacturers, or OEMs), engineered products, and process industries. The survey’s objective is to define the vision for the factory of the future in 2030. Determining long-term benefits and the roadmap to implementation are also goals of the study Boston Consulting Group (BCG) and its research partner, the Laboratory for Machine Tools and Production Engineering at RWTH Aachen University, achieved. The Factory of the Future is a vision for how manufacturers should enhance production by making improvements in three dimensions: plant structure, plant digitization, and plant processes.
5 Ways Integration Fuels The Factory Of The Future’s Growth
Real-time integration based on intelligent objects that connect diverse enterprise systems including SAP, Salesforce and others is the foundation that manufacturing companies must adopt to excel in their Factory of the Future efforts. These real-time objects illustrate the future of Application Programmer Interfaces (API). APIs that will fuel and drive the Factory of the Future will enrich each real-time integration points across manufacturing networks. Intelligent Objects pervasively used today are the precursors to the most valuable APIs that will enable Factories of the Future tomorrow. With APIs continually improving and gaining the capability to provide insight and intelligence, the essential role of real-time integration in all factories of the future becomes clear.
The following are the five ways integration is enabling the Factory of the Future today:
- Real-time integration enables the value chains supporting the Factories of the Future to continually accelerate, excel and improve with additional insight that drives future growth strategies. Bringing greater intelligence into each integration point across the value chains supporting the Factories of the Future leads to new technologies delivering greater lean management benefits. Real-time integration will deliver strong benefits in the areas of lean management, predictive maintenance, modular line setups, and the orchestration and collaboration of smart robots.
- The Implementation Roadmap for the Factory of the Future shows how critical real-time integration is to the Factory of the Future’s vision being attained. Multidirectional layouts, modular line setups, sustainable production, the orchestration of smart and collaborative robotics and attainment of big data and analytics plans all are dependent on real-time integration. The following graphic from the study illustrates just how central integration is to the optimizing of plant structure and plant digitization.
- By integrating large-scale enterprise systems including those from SAP, Salesforce and others with legacy, 3rd party and homegrown systems, every area of production quality will improve. The most urgent need global manufacturers have is finding new ways to improve product, process and service quality without raising costs. Improving the quality of these three dimensions makes any manufacturer more trusted and successful in selling next-generation products. By aggregating data using real-time integration so that Big Data and advanced analytics can be used to find new patterns, some of the world’s most well-known manufacturers are excelling on product quality. To produce cylinder heads at its plant in Untertürkheim, Germany, Mercedes-Benz uses predictive analytics to examine more than 600 parameters that influence quality. Mercedes-Benz is an early adopter of using Big Data and advanced analytics to improve quality management and bring high precision to engineering. Bosch has implemented software that analyzes data about its production of fuel injectors in real time. The software monitors process adherence and recognizes trends. It automatically transmits information about deviations to operators, allowing them to improve the process accordingly.
- Real-time integration across and within manufacturing systems enables multi-directional layouts of production workflows. The Audi R8 manufacturing facility in Heilbronn, Germany, does not have a fixed conveyor so the teams there has greater multidirectional flexibility in building customized vehicles. Real-time integration across the Audi factory floor is essential to provide R8 production teams with the specifics of how they can best collaborate and deliver the highest quality vehicles in the shortest amount of time. Real-time integration is enabling driverless transport systems, guided by a laser scanner and radio frequency identification technology in the floor, which moves the car bodies through the assembly process. These systems enable assembly layout changes quickly with no impact on existing production. Enabling real-time integration often involves extensive field mapping between different systems, which is a lengthy and error-prone process. Integration technology provider enosiX has developed a unique, real-time integration technology that obsoletes the need for field mapping and supports bi-directional data updates.
- Enabling the Factory of the Future’s production operations to flex in response to rapidly changing customer requirements is entirely dependent on real-time, reliable integration of production and customer-facing systems. The implications of the study on the future of manufacturing underscore just how critical it is for manufacturers to be agile enough to create entirely new business models while gaining insight and intelligence into how they can continually improve lean manufacturing. When real-time integration unifies a value chain for any manufacturer, their speed, scale and ability to simplify the complex processes required to serve customers turns into a formidable competitive advantage.
- 35% of companies adopting Industry 4.0 predict revenue gains over 20% in the next five years.
- Data analytics and digital trust are the foundations of Industry 4.0.
- Cost-sensitive industries including semiconductors, electronics, and oil and gas are the most focused on adopting Industry 4.0, with 80% of companies in these industries saying it is one of their top priorities.
The recent article by Boston Consulting Group (BCG), Sprinting To Value In Industry 4.0, provides insights into how real-time integration between enterprise systems is an essential catalyst for Industry 4.0 growth. Industry 4.0 focuses on the end-to-end digitization of all physical assets and integration into digital ecosystems with value chain partners encompassing a broad spectrum of technologies. BCG surveyed 380 US-based manufacturing executives and managers at companies representing a wide range of sizes in various industries to complete the study.
Industry 4.0 Is At An Inflection Point Today
Having attained initial results from Industry 4.0 initiatives, many manufacturers are moving forward with the advanced analytics and Big Data-related projects that are based on real-time integration between CRM, ERP, 3rd party and legacy systems. A recent Price Waterhouse Coopers (PwC) study of Industry 4.0 adoption, Industry 4.0: Building The Digital Enterprise (PDF, no opt-in, 36 pp.) found that 72% of manufacturing enterprises predict their use of data analytics will substantially improve customer relationships and customer intelligence along the product life cycle. Real-time integration enables manufacturers to more effectively serve their customers, communicate with suppliers, and manage distribution channels. Of the many innovative start-ups taking on the complex challenges of integrating cloud and on-premise systems to streamline revenue-generating business processes, enosiX shows potential to bridge legacy ERP and cloud-based CRM systems quickly and deliver results.
There are many more potential benefits to adopting Industry 4.0 for those enterprises who choose to create and continually strengthen real-time integration links across the global operations. Recent research completed by Boston Consulting Group and PwC highlight several of them below:
- Manufacturers expect to gain the greatest value from Industry 4.0 by reducing manufacturing costs (47%), improving product quality (43%) and attaining operations agility (42%). 89% of all manufacturers see an opportunity to use Industry 4.0 to improve manufacturing productivity. Reducing supply chain costs (37%), enabling product innovation (33%) and attaining faster time-to-market (31%) are the next level of benefits manufacturers expect to attain. The following graphic provides an analysis of where manufacturers see Industry 4.0 having the greatest impact on their organizations.
- Manufacturers are gaining the greatest value from Industry 4.0 by creating pilot projects that create flexible, agile real-time platforms supporting new business models with real-time integration. Industry 4.0’s focus on enabling end-to-end digitization of all physical assets and integration into digital ecosystems relies on real-time integration to succeed. For manufacturers in cost-sensitive industries, the urgency of translating the vision of digital transformation into results is key to their future growth. The more competitively intense an industry, the more essential real-time integration
- Investing in greater digitization and support for enterprise-wide integration is predicted to increase 118% by 2020 in support of Industry 4.0. 33% of manufacturers surveyed report they have a high level of digitization today, projected to increase to 72% by 2020. The leading areas of these investments include vertical value chain integration (72%), product development and engineering (71%), and customer access including sales channels and marketing (68%).
- New product development and optimizing existing products and services are the greatest areas of growth potential for analytics and Big Data using Industry 4.0 technologies and integration strategies through 2020. Industry 4.0 is revolutionizing the use of analytics and manufacturing intelligence, setting the foundation for greater optimization of overall business and control, better manufacturing, and operations planning, greater optimization of logistics and more efficient maintenance of production assets and machinery. By better orchestrating these strategic areas, manufacturers are going to be able to attain levels of accuracy and responsiveness to customers not achievable before.
- Globally, manufacturing enterprises expect to gain an additional 2.9% in digital revenues per year through 2020, with digitizing their existing product portfolios (47%) leading all other strategies, further underscoring the need for real-time integration. Introducing an entirely new digital product portfolio is the second most common strategy (44%) followed by creating and offering new digital services to external customers (42%). Just over a third (38%) plan to create and sell big data analytics services to external customers.
The more integrated the systems are supporting any selling strategy, the greater the chances sales will increase. That’s because accuracy, speed, and quality of every quote matter more than ever. Being able to strengthen every customer interaction with insight and intelligence often means the difference between successful upsells, cross-sells and the chance to bid and win new projects. Defining a roadmap to enrich selling strategies using SAP integration is delivering results across a variety of manufacturing and service industries today.
Getting more value out of the customer data locked in legacy SAP systems can improve selling results starting with existing sales cycles. Knowing what each customer purchased, when, at what price, and for which project or location is invaluable in accelerating sales cycles today. There are many ways to improve selling results using SAP integration, and the following are the top three based on conversations with SAP Architects, CIOs and IT Directors working with Sales Operations to improve selling results. These five approaches are generating more leads, closing more deals, leading to better selling decisions and improving sales productivity.
3 Ways SAP Integration Is Improving Selling Results
- Reducing and eliminating significant gaps in the Configure-Price-Quote (CPQ) process by integrating Salesforce and SAP systems improves selling and revenue results quickly. The following two illustrations compare how much time and revenue escape from the selling process. It’s common to see companies lose at least 20% of their orders when they rely on manual approaches to handling quotes, pricing, and configurations. The greater the complexity of the deal is the more potential for lost revenue. The second graphic shows how greater system integration leads to lower costs to complete an order, cycle time reductions, order rework reductions, and lead times for entire orders dropping from 69 to 22 days.
- Having customer order history, pricing, discounts and previously purchased bundles stored in SAP ERP systems integrated into Salesforce will drive better decisions on which customers are most likely to buy upsells, cross-sells and new products when. Instead of having just to rely on current activity with a given customer, sales teams can analyze sales history to find potential purchasing trends and indications of who can sign off on deals in progress. Having real-time access to SAP data within Salesforce gives sales teams the most valuable competitive advantage there is, which is more time to focus on customers and closing deals. enosiX is taking a leadership role in the area of real-time SAP to Salesforce integration, enabling enterprises to sell and operate more effectively.
- Improving Sales Operations and Customer Service productivity by providing customer data in real-time via Salesforce to support teams on a 24/7 basis worldwide. The two departments who rely on customer data more than sales need to have real-time access to customer data on a 24/7 basis from any device at any time, on a global scale. By integrating customer data held today in SAP ERP and related systems to Salesforce, Sales Operations, and Customer Service will have the visibility they’ve never had before. And that will translate into faster response times, higher customer satisfaction and potentially more sales too.
Accenture, Empowering Your Sales Force
Aberdeen Group, Configure-Price-Quote: Best-In-Class Deployments that Speed The Sale
Aberdeen Group, Configure/Price/Quote: Better, Faster Sales Deals Enabled
Aberdeen Group, Sales Enablement Advances In Configure/Price/Quote Solutions
Forbes, What’s Hot In CRM Applications, 2015: Why CPQ Continues To Accelerate
Forbes, Cloud-Based CPQ Continues To Be One Of The Hottest Enterprise Apps Of 2016
Forbes, Five Ways Cloud-Based CPQ Increases Sales Effectiveness And Drives Up CRM Adoption
The Sales Management Association, The Impact of Quoting Automation: Enabling the Sales Force, Optimizing Profits, and Improving Customer Engagement
Gartner announced their top 10 strategic technology trends for 2016 at the Gartner Symposium/ITxpo held October 4 – 8th in Orlando. David Cearley, Vice President and Gartner Fellow, presented the company’s Top Ten Strategic Technology Trends for 2016. You can find the video here.
Key take-aways from his presentation and the trends announced are provided below:
- Enterprise 3D-printing shipments will attain a 64.1% Compound Annual Growth Rate (CAGR) through 2019. David Cearley mentioned during his keynote that jet engines are being 3D printed today. He gave the example to illustrate that 3D printing will continue to gain adoption in more demanding manufacturing environments including aerospace, automotive, energy, medical devices and military-based markets and industries.
- Emergence of an entirely new class of business models based on smart machine technologies, advanced analytics and big data. Combining machine learning, continued adoption of Internet of Things (IoT) sensors and supporting data models, and advanced intelligence to interpret and act on the data, Gartner’s predictions set the stage of an entirely new class of business models. Manufacturing-as-a-Service and paying only for the production time used in a factory are within reach for more companies than before based on these predictions.
- The device mesh will expand to include IoT-based devices that scale well beyond the enterprise. Gartner is predicting that in the next three years traditional computing and communication devices, including desktop and mobile devices will increasingly be augmented by wearable devices, home electronics including appliances with sensors, transportation-based sensors and data collection devices, and environmental devices all capable of capturing data in real-time.
- A digital mesh will continue to proliferate, aligning apps and devices to individuals’ specific roles and tasks. Gartner sees this digital mesh as an expanding series of devices, services, platforms, informational networks and individuals that integrate together and provide contextual intelligence and enabling greater collaboration. The proliferation of the digital mesh will lead to more ambient, contextually intelligent and intuitive app design over time Gartner predicts.
- The next twelve months will also see the proliferation of algorithm-based businesses enabling automated background tasks including smart machines. Gartner’s technology trends for 2016 set a solid foundation for the growth of globally-based smart factories and production centers. Acumatica, Plex Systems and other Cloud ERP providers are ideally positioned for this trend, having proven their ability to provide manufacturing intelligence from the shop floor to the top floor. In addition to cloud platforms, these algorithm-based businesses will need to support unstructured data analysis including latent semantic indexing (LSI), data taxonomy and classification algorithms to ensure data fidelity and scalability, and more robust analytics and predictive modeling systems.
- Combining algorithms, analytics, data architectures and smart machines have the potential to revolutionize manufacturing quickly. General Electric’s Predix platform, IBM’s IoT Foundation and several other cloud-based IoT platforms are already making progress on transforming the vision of algorithm-based smart machine production strategies into a reality for manufacturers globally.
- Gartner sees a new IT reality taking shape. Adaptive security, advanced systems, Internet of Things (IoT), mesh app & service architectures are the catalysts of the new nature of IT that Gartner is predicting.
A graphic illustrating the top 10 strategic trends is show below:
Gartner Identifies the Top 10 Strategic Technology Trends for 2016. Press Release Announcement, October 6, 2015.
Video replay of the keynote: The Top 10 Strategic Technology Trends for 2016
Alan Kay’s saying that the best way to predict the future is to create it resonates through the best cloud computing and enterprise software predictions for 2014. Constraints that held start-ups back from delivering sophisticated new apps and services are disappearing fast. The dynamics of one of my favorite books, The Innovator’s Dilemma by Clayton Christensen, are in full force across the cloud and enterprise landscape.
There are many predictions being generated right now and instead of writing yet another set, I’m providing a listing of those that are the most interesting and thought-provoking. They are listed below:
- 10 Cloud Computing Predictions for 2014 – In-depth analysis of ten predictions including how more companies will realize they are really in the software business, private cloud computing having a moment of truth and continued adoption of cloud brokerages. This set of predictions is an interesting read and provides useful insight. I’d just add that as application developers go, so goes an industry, a point Bernard Golden refers to in this post.
- Analytics Eats the World in 2014 – George Mathew of Alteryx is one of the most driven people I’ve ever met about analytics programming and development. He’s very focused on breaking down constraints that hold analysts back from getting more value from their data. His predictions provide insight into how business analysts’ roles are changing based on rapid advances in analytics app development, model development and use.
- Changing Cloud Scapes in 2014 – Jeff Kaplan, Managing Director of THINKstrategies provides ten insightful predictions regarding the continued adoption of cloud computing platforms in the enterprise. His fourth prediction, “Although horizontal cloud solutions will continue to experience significant growth, vertical market solutions aimed at specific industries will grow even more rapidly” is starting to emerge today. The recent success of Veeva Systems supports his prediction and points to next year seeing more vertical market solutions being successfully launched.
- Cloud computing experts forecast the market climate in 2014 – Excellent summary of seven cloud computer experts’ predictions for 2014 including Mark Eisenberg, Roger Jennings, Paul Korzeniowski, David S. Linthicum, Tom Nolle, Dan Sullivan and Mark Szynaka. Highlights include IDC analysts predicting the “Over the 2013 to 2017 forecast period, public IT cloud services will have a compound annual growth rate [CAGR] of 23.5%, five times that of the IT industry as a whole,” and PaaS will lead IaaS and SaaS with a CAGR of 29.7%. What’s useful about these set of predictions is the breadth of expertise reflected in market statistics, market and technology projections and insights shared.
- My One Big Fat Cloud Computing Prediction for 2014 – I have been following the industry analysis, writing and research of Joe McKendrick for years based on the excellent insight he provides. Joe predicts that cloud computing is set to become mainstream computing, period. He cites Cisco’s research showing the majority of data center will be cloud-based and shares his perspective of the market. Joe has an innate sense of how enterprises adopt and use technology and this post reflects that expertise.
- SaaS predictions for 2014 – Chris Kanaracus is predicting that multitenancy will fade away as a major concern in SaaS, geographic depth of coverage will accelerate with cloud vendors announcing new data center openings around the world, and more vertical market adoption of SaaS. He also prefaces his predictions with the Gartner forecast for SaaS (software as a service) quoting their figures of the total market will toping $22 billion through 2015, up from more than $14 billion in 2012.
- Top Predictions about Software Companies in 2014 – In-depth analysis and predictions of which companies are going to be the most interesting to watch in 2014 and predictions regarding the enterprise software landscape. This post provides a great overview of how industry veterans see enterprise software changing as a result of cloud computing as well.
- Troubling, Challenging 2014 ERP Predictions – Brian Sommer’s predictions are the most thought-provoking and honest of any written so far this year. He writes “for an ERP vendor to sell CX (customer experience) software and then mistreat their own customers so badly is more than ironic (or moronic). It’s a death wish. Yet, it happens.” If there is only one set of predictions you read from this list, be sure to read this set.
- What Should CMOs Do In 2014? IDC’s Top Ten Predictions – Gil Press provides in-depth analysis of IDC’s predictions of how the role of CMO will change in 2014. He’s summarized the key points of the recent webinar including market forecasts from IDC, providing his insight and expertise in this post. IDC is predicting that digital marketing investment will exceed 50% of total program budget by 2016, up from 39% in 2013 and that by the end of 2014, 60% of CMOs will have a formal recruiting process for marketers with data skills.