Technologies and methods based on the Internet of Things (IoT) support the planning, implementation and optimisation of manufacturing and communication processes based on real-time data. They also constitute the prerequisites for initiating flexible, agile and decentralised decision-making and organisation processes and automating large parts of logistics and manufacturing. At the same time, effectively deployed Industry 4.0 and IoT technologies are an important driver of new business models, products and services, and thus a core element of digital transformation.
The starting point for a sustainable and viable IoT and Industry 4.0 strategy is a complete and objective view of the potential and implementation hurdles in the company with regard to industrial digitization. In practice, a systematic maturity analysis has proven successful. The method ensures transparency and makes it possible to evaluate the initial situation in a structured manner, collect ideas, and also derive improvement and development approaches. Here, fields of action are prioritised and an initial roadmap is created with concrete implementation measures.
The IoT pyramid is used as a general heuristic. This maps the sequential stages of digitization and serves as a reference frame for both the maturity level observation and the derivation of the individual IoT roadmap. The IoT pyramid also functions as a methodological basis for the IoT scan developed by ROI.
Based on several hundred projects, cross-industrial benchmarks, and comprehensive technology and organisational expertise, ROI has developed a methodical and didactically sound instrument for measuring the IoT maturity of companies.
The IoT scan considers the design fields that can be influenced by the company itself in terms of organisational structure, IT landscape, corporate culture and process resources. The IoT scan concentrates on the skills necessary to take steps in each individual area towards a higher IoT maturity level.
On the one hand, it considers the responsibilities relevant for the transformation – such as controlling, purchasing, development, maintenance, logistics, manufacturing, quality, supply chain, sales or plant planning. On the other hand, the available material resources and capabilities – such as experience, system thinking, interdisciplinary thinking, data based learning, data based decision, data interfaces, and data preprocessing – are examined. The IoT scan is modular and can be optimally adapted to the individual corporate situation by preselecting the relevant variables.
The IoT scan is carried out in three phases
- In the first step, the degree of maturity is determined according to the current Industry 4.0 development stage. A mix of methods is used, including workshops, site inspections and questionnaire evaluations. The evaluations of individual processes are aggregated in such a way that valid statements about the IoT maturity level of both individual areas and the overall company can be quickly provided.
- Building on this, and based on the external and internal best practices and the analysis results of the first phase, the development stages to be achieved within the IoT pyramid are determined. For this purpose, the actual and target capabilities are defined and prioritised together with external experts and those responsible for the relevant business areas.
- In the third phase, an initial roadmap is finally created with fields of action prioritised in terms of benefits and cost/complexity and brought into line with the overall strategy of thecompany. The individual measures are derived from this, thus creating the basis for a step-by-step restructuring of the entrepreneurial skills.
在家具行业，使用数字技术可以多方面受益 —— 虚拟现实、大型数据分析或在线配置，这都有可能开辟新的销售渠道, 吸引新的客户。其挑战是，找到与客户需求、价值流设计相关的、合适的技术组合。针对全球床上用品制造商，瑞欧盈实现了一个 “端到端” 数字化项目，它考虑了所有相关的价值创造点：从客户体验到生产、物流。
有时，即使你做的一切都对，那也不够。例如，一个强大的开发团队与家用电器制造商共同取得了坚实的成功。但是现在，客户想要在他们的“智能家居”中将厨房用具、冰箱和搅拌机与 Alexa 联网，并控制这些家电。瑞欧盈通过“数字原生代”的新观点，建立了一个“I团队”，彻查观察其内部变化过程。
当某汽车零部件供应商想优化其仪表板制造工厂时，面临着两个挑战。首先，整个过程链，连同所有与生产、供应商管理相关的风险因素，必须变得更加透明。另一个挑战是，必须降低报废率，因为处理某敏感材料时，即使一个微小的错误也会导致整个部件的报废。该企业与合作，使用 “数字孪生体” 将整个生产过程逐步地绘制出来。由此产生一个物联网试行项目，它能辨识是否有改进的潜力，以及触发针对供应商生产和价值流管理方面的改进。