Is "solid" a discontinued model?
Whether now or later, the next economic downturn is bound to come, even for mechanical engineering. And even in this cycle of consolidation, there will be companies that cope with it better than others. What can companies do right now to prepare for the crisis?
Insight in brief
- Whether now or later, the next economic downturn is bound to come.
- There will be companies that cope with it better than others.
- What can companies do right now to prepare for the crisis?
On the surface, everything stays the same: it's all about maximising profit. There are still only two options here, namely higher sales revenues and/or lower spending. Both routes have one thing in common: data will play an increasingly important role, and may well even become a critical success factor. Thus, for both of the options mentioned, the path to a "Data Driven Organisation" should not simply be 'watched': on the contrary, it should become part of the corporate strategy. But this also means that it is precisely the “solid” companies that are struggling here.
As preparation for a crisis, we recommend a comprehensive approach that takes both aspects into account. On the one hand, new business models that generate innovative products and services. On the other, the issue of operational excellence: optimise processes by means of digitalisation and agilisation, thus saving costs and often also time to the end customer when implementing the order.
In this article I concentrate on the first aspect: increasing revenues through new and innovative products and services that are geared to the needs of the market. In view of the pressure to innovate, especially in sectors such as mechanical and plant engineering, this topic is already high on the agenda for many companies. And not without good reason. After all, even in a crisis these needs will not disappear all that quickly.
New technologies and methods open the door to innovative products
In view of the high degree of maturity of many products, the decisive question is, "How can companies still be truly innovative when further efficiency increases for customers are only an innovation on the data sheet, but the processes on the customer side do not really advance?" It is particularly the "solid", established companies, which are regarded as technological leaders in their industry, that often have to go down new routes in product innovation and approach new products more as a startup would. Often it is the examination of new technologies such as Mixed/Virtual Reality, but also of methods such as Data Science, which is a starting point for the development of new, innovative products.
Methods such as Lean Canvas help to broaden the often very domain- and technology-centric perspective of these companies with an in-depth consideration of the customer perspective and profitability. Experience has shown that just the interdisciplinary view, from customer service to R&D, produces strong "Aha!" effects. Insights into product usage gained through IoT solutions and integrated data analytics can also provide valuable input. The goal should be to produce a well-founded proof of concept as quickly and simply as possible and with it obtain feedback from target customers/personas. Based on this, the product definition and the business case must be detailed so that, with a view to the customer experience, the relevant user stories are described in terms of requirements that can be developed. With a healthy mix of, for example, Scrum and RUP (Rational Unified Process) methodologies, this is followed by agile software- and/or hardware-development for the industrialisation of the new product.
Friction between expectations and agile methods
Innovation in products or in services – in the end, it's all about developing business cases and then putting them into operation. The resulting solution can then be industrialised. Sounds easy, doesn't it? Experience shows that even just the established Stage Gate or product development process in companies ensures that the friction between expectations/promises in the higher-level process and the agile development process leads to project heat.
But this development process can also generate far more sustainable added value: far-sighted companies use it to create a data platform for networking their products/solutions, so laying the foundation for consistent and flexible data collection. This completes the circle of customer-centred development and data generation, both from the company's own core processes and from the end customers via the products. It is precisely these end-customer needs, often captured in data for the first time, that help to sustain innovation.
Agilisation of the organisation as the biggest challenge
Only when Engineering 4.0 (the provision and use of all data) and Science 4.0 (the use of AI to automatically extract knowledge from data) converge will the necessary step towards data-driven innovation and ultimately a "data-driven organisation" really work. This requires new approaches, however, not to mention know-how and technologies that are often beyond the core competence of the companies. To tackle this problem, it is not a weakness to occasionally fall back on external know-how while building up one's own know-how in parallel: rather, it helps to orchestrate the innovation triangle of business, technology and customer focus in a timely manner and in this way create the basis for further innovative products, services and business models.
Experience has shown that the greatest challenge here is the agilisation of the organisation – including those functions beyond the R&D area. When evaluating new technologies, companies must consider the whole process, and not “get hung up” on individual, department-centric features. It should be clear to everyone that the latter would quickly bring us to "that's the way we've always done it" and anxieties about rationalisation. And please do not underestimate the cultural change. In comparison, digitalisation – including the technical interface integration – is actually "easy to handle". The implementation should be carried out step by step with this big picture in mind.
Gerald Brose is Director Business Development at the Zühlke Group. An Economics graduate, he is responsible for business development in Germany for the industrial sector with a focus on plant and mechanical engineering. Before joining Zühlke, he worked as a consultant and key account manager in IT outsourcing. In addition to the overarching theme of digitalisation, Gerald is currently focused on IP ownership in product innovation, monetisation of data science use cases, and customer experience.
Rolf Höpli is Director and Partner at the Zühlke Group. As a Machine Engineering and Computer Science graduate, he is responsible for business development in Switzerland for the industrial MEM sector. In addition to the overarching theme of digitalization, Rolf is currently focused on the transformation of the customer experience, interdisciplinary product innovation and monetization of data science use cases. Rolf is a speaker and lecturer, he passes on his experience on the topic of digitization at universities of applied sciences (ffhs and BFH) and at MEM congresses.