From a series of recent combined events, we can see the clues of the future trend of IIoT. On July 16, General Electric GE and Microsoft announced that they have reached the largest partnership in the history of the two parties to accelerate the implementation of IIoT services for the Industrial Internet of Things. GE will standardize the Predix solution on the Microsoft Azure cloud platform, and deeply integrate the Predix product portfolio with Azure's local cloud functions (including Azure IoT and Azure data and analysis). At the same time, the two parties will also conduct joint sales and marketing activities. Not long ago, on July 9, Alibaba Cloud and Siemens signed a memorandum of cooperation in Berlin, Germany, to jointly promote the development of the Industrial Internet of Things IIoT in China. The two companies plan to launch the MindSphere platform deployed on Alibaba Cloud in 2019. In addition, joint market development and cultivation of the IIoT ecosystem are also included in the cooperation. As the trend of cooperation between major companies has become clearer and deeper, the battle for IIoT platforms in the industrial Internet of Things has gradually escalated into fierce battles between giants. The Matthew effect has intensified, and small and medium-sized IIoT platforms are bound to face panic and impact, but then It will also open a new cycle for the narrow road leader: the brewing and outbreak of industrial SaaS (Software-as-a-Service). Industrial SaaS, in simple terms, is the function that allows industrial enterprises to obtain and use software like services. For many small and medium-sized enterprises, SaaS is the best way to adopt advanced technology. It lowers the "threshold" for enterprises to purchase, build and maintain infrastructure and applications, and only need to pay a certain "subscription" fee to enjoy To the corresponding hardware, software, and maintenance services, this is the most effective business model for network applications. Therefore, in this article you will see: 1. Why is the industrial SaaS super cycle about to start? 2. Where will the first industrial SaaS be deployed? 3. What are the innovation opportunities for industrial SaaS? In addition to the above partnerships, Siemens Mindsphere has previously established cooperation with Aerospace Science and Industry, Amazon AWS, SAP and Microsoft, GE Predix has cooperated with Apple and Huawei, and Tencent Cloud has cooperated with Sany Heavy Industry, Shugen Internet, Foxconn... Although the giants The cooperation between them is not exclusive, but the expansion of the ecological camp through cooperation is deterministic. From the perspective of the development stage, most industrial giants have included the IIoT platform as the main channel of development. From the perspective of the nature of the industry, the industrial Internet of Things platform is a field that emphasizes technology, capital, continuous investment, and long-term returns. With the increasing competition among industry giants, the market share left to small and medium players is bound to decline sharply. According to official data, GE Predix cost 1 billion US dollars to build, and in 2016, GE's investment in digital R&D was as high as 2.1 billion US dollars. Siemens’ R&D investment in the 2018 fiscal year (October 1, 2017 to September 30, 2018) will exceed 5.6 billion euros. Although there is no specific data for Mindsphere, Siemens stated that about 500 million euros will be dedicated to the “company†Research and development in the field of core technology. The domestic IIoT enterprise Root Internet has also announced a cumulative investment of more than 1.5 billion yuan. The accelerated cooperation between giants and the huge investment in the IIoT platform show that this field is no longer suitable for start-ups to survive. Medium-sized IIoT platforms need to be alert to the risk of subsequent investment cut-off. Companies that cannot grit their teeth for continuous investment will gradually widen the gap with the first echelon led by giants. With the competitive situation of the IIoT platform gradually becoming clearer, the best strategy for innovative companies is to join the ecosystem created by giants, leverage their strength, and seize the window period for the rise of industrial SaaS. Although the imagination of industrial SaaS is far less than the size of the IIoT platform, it has the opportunity to obtain higher profit margins. At the same time, if industrial SaaS applications in certain vertical fields can open up various links in the industrial chain, it does not rule out the ultimate horizontal expansion The possibility of a platform of fact. There are two reasons why I judge that industrial SaaS is about to usher in the rising super cycle: ■First, in the process of building the ecosystem of the IIoT platform, the giants will inevitably provide "high premium" support for valuable industrial SaaS applications in order to gather more partners for collaborative development. ■Second, the sales cost of industrial SaaS is generally high. With the help of the giants to build momentum for the IIoT platform, the market activities standing on the shoulders of the giants will effectively share the promotion costs, and may also use the giants’ "halo" to establish their own brand effect . We will analyze the above two points separately. For industrial SaaS application support, here is Siemens Mindsphere and GE Predix as examples. You can learn about Siemens' support for Mindsphere developers through the website siemens.mindsphere.io. In addition to basic technology, interfaces and training support, MindSphere also provides local development sandboxes. Developers can perform a thorough simulation of the MindSphere environment through downloading operations and obtain an intuitive experience of MindSphere. And can share various resources of MindSphere development community (for example, developer portal, seminars, free sample applications and templates, etc.). Siemens also joined Edge2Web to further simplify the difficulty of programming. At the end of 2017, Siemens launched the MindSphere partner program, a globally unified 3-level (platinum, gold and silver) structure, each level has clear business development benefits and requirements. Partners at all levels can get new business development benefits. Gold and platinum-level partners can also obtain business development funds that can be used to promote concept, marketing and technical activities to accelerate business and investment. GE Predix provides developers with an entry point that provides a service resource library, analysis model library, and basic application library, covering more than a hundred basic modules. Predix is ​​open to all developers, striving to create a strong "industrial community". According to GE estimates, by 2020, 20,000 developers will develop application software on the Predix platform every year. With the advent of a large number of new applications, this "industrial community" will activate the world's largest industrial application with more than $225 billion. market. Considering that enterprises in the industrial field are highly dispersed, user demand is wide, and fragmentation is high, the giants are The sales activities and marketing of the IIoT platform are also hands-on and spare no effort. In June 2017, Siemens organized a Mindsphere Day user event. IoT think tanks participated in the joint organization to bring the IIoT vision into reality through digital experience. At the beginning of 2018, Siemens joined hands with 18 partners to establish the "MindSphere World" global user organization, aiming to promote the global development of the MindSphere ecosystem. The first batch of companies to join include Julang Group, Festo, KUKA, Rittal, Sick Corporation, and Mike Weili AG. At the same time, Shanghai Dazhi Technology, Atos Information Technology, Accenture, SEEQ, evosoft and other companies are developing industrial SaaS based on Mindsphere. It is estimated that by the end of the 2018 fiscal year, that is, September 30, 2018, the number of devices interconnected through MindSphere will reach 1.25 million. According to the information disclosed in the 2017 GE Minds + Machines event, more than 33,000 developers and 300 cooperative companies around the world are developing applications based on the Predix platform, including a large number of consulting agencies, integrators and independent software developers, representative Companies such as Infosys, Wipro, Accenture, Capgemini, TATA, etc. Industrial companies such as BP, Exelon, Schindler and Maersk are using the GE Predix platform to improve their operational efficiency. At present, the first batch of industrial SaaS has more than 100 models, which can be inquired through the official websites of Siemens and GE: If various industrial SaaS are classified, they can be divided into asset performance management, production and operation monitoring, operation process monitoring, data visualization, quality management, energy management, field service, business intelligence decision-making, etc. I will not give examples one by one here, but only list the ones that are worthy of attention. MyMachines: This is a cloud machine tool management SaaS, aimed at small and medium-sized machinery manufacturing OEM customers, used to monitor machine tools, improve machine availability and productivity. MyMachines allows machine manufacturers to create digital services and innovative business models, improve the transparency of machine production status, optimize the machine life cycle, perform faster failure analysis and innovative after-sales service. Similar SaaS applications also include Analyze MyDrives, which improves the state transparency of drive systems in the motion control field. ServiceMax: This SaaS provides an on-site service solution. Readers of the [Wu Women's Heart Sutra] are not unfamiliar with ServiceMax. The company was previously acquired by GE for $915 million. Data shows that GE has brought more than 70% of profits through its service maintenance business. ServiceMax can automate operational planning, such as manpower optimization, advanced scheduling and scheduling, parts logistics, inventory and warehouse maintenance, and installed basic services. APM (Asset Performance Management): This SaaS is based on the prototype product of Meridium, which was acquired by GE, and uses data and analysis to reduce unplanned asset downtime, improve reliability and availability, minimize costs, and reduce operational risks. It can be said that APM covers the needs of most industrial assets, including machine and equipment health, reliability management and maintenance optimization. Product Intelligence: This is a killer SaaS application, so let me say a few more words. Currently, the official price of the SaaS service is 50,000 US dollars per year. Product Intelligence can automatically dig out the mechanism from contextualized product performance data. It can be distributed in product life cycle management PLM, enterprise resource planning ERP, manufacturing execution system MES, quality management system QMS, customer relationship management CRM, and other enterprise-level data The source data are combined and integrated into the integrated security data layer for analysis. Based on powerful algorithms, Product Intelligence divides product-related attributes into individual events and connects them together to establish a data context, which can search for tens of billions of events in a few seconds. The technical support behind this industrial SaaS is Omnio, an industrial big data product that has received widespread industry attention, and its patented Discovery algorithms and functions. Finally, we briefly analyze the development direction and innovation opportunities of industrial SaaS, which mainly includes the following three levels: Efficiency-driven: Although there are many types of industrial SaaS that have been online, most of them have similar commonalities, that is, they are driven by data, which reduces the uncertainty in execution and completes operation monitoring and decision-making. People" play an important role in it. The above-mentioned industrial SaaS types such as production and operation monitoring, operation process monitoring, data visualization, quality management, energy management, field service, business intelligence decision-making, etc., no matter which type, most of them are through the collection, refinement and visualization of field data. It enables the operators or decision makers of the enterprise to evaluate and optimize the efficiency of the operation process more objectively and with evidence, improve the product experience, and enhance the decision-making level. Technology-driven: With the deepening of data thinking, the "human" factor may be gradually weakened. Through machine intelligence, field data is refined into information and knowledge, which is fed back to industrial scenes to achieve higher-level intelligent production. Replacing "people" with "things" to make decisions will maximize the value of data. What needs to be emphasized here is that the data analysis algorithms in this kind of industrial SaaS are often more complex, and the analysis results are directly used by machines and production lines, so that they can continue to iterate themselves. At present, relevant industrial SaaS is rare. The Product Intelligence product in this article has made a certain exploration in this regard. Cross-industry collaboration: Industrial SaaS serves industrial enterprises, but you should not just bind yourself to the industrial field. Effective use of the new technological cycle and the new financial cycle to promote the recombination of industrial resources can more easily stimulate innovative business opportunities. In the previous article, I mentioned that we are facing an inflection point in many fields such as technology, economy, finance, and politics, and we are entering a new type of cycle, in which waves are superimposed. The driving forces of new technologies such as artificial intelligence and blockchain have begun to emerge. The environment in which the entire financial industry is located is also undergoing major changes. Financial leasing and supply chain finance are gradually integrating with the industry. Industrial SaaS may as well keep up with changes in the times and seize cross-industry opportunities. At present, GE Predix and Ericsson have provided a blockchain-as-a-service module for developers to use. Unlike the initial approach that only counts investment, the giants have formulated a clear profit plan for the IIoT platform. For example, Siemens has set up a clear MindSphere profit schedule and plans to achieve a balance of MindSphere business in fiscal year 2020. According to a Siemens report, it is expected that MindSphere and industrial SaaS businesses will bring in a total of 1 billion by fiscal year 2022. Euro revenue. Judging from the reality, many industrial SaaS have not gotten rid of the "old road" of traditional software sales. In order to meet the needs of customers, they have done more customized work, which does not conform to the basic route of SaaS productization. In any case, for industrial SaaS, revenue generation is the last word. Because industrial SaaS generally adopts a subscription-based charging model, the customer's repurchase rate has become a key indicator, and valuable products will stand out after a certain period of time. 1. The Matthew effect of the industrial Internet of Things IIoT platform has intensified, and small and medium-sized IIoT platforms are bound to face panning and transformation. 2. Industrial SaaS is about to usher in the rising super cycle. As the first echelon to land, efficiency-driven SaaS products have been launched. 4. There are three main levels of innovation opportunities for industrial SaaS: efficiency-driven, technology-driven, and cross-industry collaboration.
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