Digitization of the value chain as the basis

Not so long ago, only engineers were concerned with "digitalization". In the meantime, the term has made a career for itself and "digitization" can be found everywhere. Due to the multi-layered use of the term, it also has several different meanings. In order to be able to formulate strategies in the context of digitalization, a differentiated view is therefore essential.

Originally called Digitalisation is a purely technical process of converting analogue signals into digital form. into discrete numerical values. These numerical values are electronically transported, stored or processed in binary form - ones and zeros. The compact disc for music was the first widely used digital medium. Before that, most music was recorded, stored and played back in analogue form. The digitization of any sig- nals and measured values (digitization) is now possible and common in all areas and the basic prerequisite for all further forms of "digitization".

Based on this technical possibility of the digital representation of signals the first stage of digitisation: the complete digitisation of all data. As a rule, digital data can be used to automate procedures and processes and make them more cost-effective. A distinction should be made between efficiency gains through simplification in transport and storage and gains through automated processing. The fax or scanned documents were initial examples of simple efficiency gains: storage, access and transport can be accelerated and simplified. Processing, on the other hand, the workflows and processes remain the same. If, on the other hand, the original information is digitized directly, individual work steps can also be automated. The exchange of payment orders and bookings with banks is an example of the exchange and direct processing of data. Only this form of electronic data processing can fully exploit automation. It can be achieved mainly through technical measures and usually requires investment in IT: systems, processes, skills. It forms the basis for the next stage.

If all required and accruing data are digitally available in a process, it can be redesigned. This The second stage is referred to as the digitalisation of value chains. (English: digitalization). The following drivers can be distinguished:

• parallelization of processesUnlike physical dossiers, digital data can be effortlessly used and processed simultaneously at will. From an information point of view, processes can be parallelized at will. Processes can be redesigned from a data perspective.
• Processing of large amounts of data: A business can be scaled to unimaginable dimensions. Thanks to electronic processing in digital value chains, companies like Amazon can serve huge markets that were unimaginable until recently.
• Use of data to influence the value chainIn digitalized value chains, vast amounts of additional data such as customer behavior can be tapped. This data can be processed and used to influence or control value chains. This is often referred to as Big Data or Business Intelligence (BI).

The aspect of Business Intelligence is overestimated
The three drivers are to be understood as the development of competencies. The advantages of the individual competencies vary greatly depending on the industry and company. The aspect of business intelligence is often overestimated, as very few companies in Switzerland have enough data to be able to make statistically relevant statements in the league of "big data". In addition to IT skills, successful digitization of value chains requires skills in corporate development (change) and software development.

With the competence to be able to digitally design value-added chains, the The third stage is the digital transformation of companies. In the process, new types of business models are being designed - business models that would be impossible without digitized value chains. Examples are Airbnb or Uber, which can only be operated effectively and efficiently if they are fully automated. In the process, these "digital" players are completely ploughing up existing industries by means of highly efficient marketplaces. The following digital business models can be identified at the core:

• Marketplaces of all kinds are the oldest, most obvious and most visible digital business models. A large number of suppliers and customers are brought together via a platform. The actual value creation often only consists of the matchmaking, the bringing together of two parties for a transaction. The actual transaction takes place outside the platform. Ebay or Airbnb are typical examples.
• About a deepened vertical integration the marketplaces are being expanded into virtual services. The service provider is decoupled from the end customer. The intermediary carries out parts of the transactions. The digital insurance broker Knip operates such a model in Switzerland. Knip bundles various insurances into overall offers and also implements business processes, such as damage reports. The insured and the insurance company no longer have a direct and explicit exchange.
• Finally follows about Reduction of marginal costs the efficient production in batch size one. Digital value chains, sophisticated logistics and technologies for the efficient production of individual items or very small series, such as additive manufacturing, enable the manufacture of individual products or even production on site at the customer. For example, Adidas plans to use 3D printing to manufacture shoes individually and yet cost-effectively from 2018 onwards.

Quality management for digitization
Throughout the various development stages of the digitization of a company, quality management must develop along with it. Quality management will have to digitalize itself in the sense of a digitalized value chain. And in order to be able to secure the invisible and sometimes complex processes in a digital value chain, quality management must integrate itself even more strongly into the value creation. This requires, among other things, new skills in quality management and especially in quality assurance (for more on this, see Part 4 in the last issue).

For the first stage of the digitization of data, a comprehensive Data Quali management is necessary: Ensuring the correctness, integrity and protection of data against loss, manipulation and unauthorised access. Comprehensive measures must be taken both in the context of the actual technical digitization and for the operational use and maintenance of the data. In order to secure data sustainably and comprehensively, the integration of data quality management into the value chain is indispensable. The correctness of data, for example, must be ensured at the point of entry. The protection of data, for example, must be ensured in every interaction.

For the second stage of the digitalisation of value chains, the Compe skills in software development be indispensable. Without customized software, it will only be possible to digitize value chains to a limited extent. It can also be assumed that software will become an integral part of many services and products. Comprehensive quality management of software is becoming a key discipline for the successful digitization of value chains. Software in this area will be developed using agile methods, so that the ability of quality management of empirical processes will play a decisive role. This will have to be done via the integrated quality management system.

The Finally, the supreme discipline the quality assurance of developing new digital business models for the third stage of the digital transformation. Analogous to software development, quality management will have to be integrated into the strategy process and focus on empirical processes. The quality assurance of soft factors such as culture and leadership as well as Generation Y's demand for meaning and values will contribute to the success of the transformation.

Conclusion
The digitalisation of value chains, the digital transformation of companies and the penetration of technology companies such as Amazon, Google, Facebook, Apple etc. into traditional markets is leading to unpredictable developments in the economy and society, and indeed globally. Planning horizons are shrinking, and the ability to react and adapt is becoming more important. The ability to react to this change is referred to as "agility". Agile companies cultivate an agile culture, use agile methods, processes, frameworks and tools, and build services and products according to agile design patterns and construction principles.

"Often overrated is the business intelligence aspect."

In order to subject a company to a digital transformation, strategy development, corporate development and leadership are indispensable competencies. This is a major challenge, as the understanding of leadership is changing at the same time. Teams are becoming bosses and bosses are becoming coaches. This multi-complex starting situation requires step-by-step action and planning, agile strategies and an appropriate risk culture, so that despite all the dynamics of the working world 4.0 and the market economy, the goals can be achieved successfully and compliantly.

With the claim to be universally valid, the latest version of ISO 9001:2015 in particular not only offers a company-specific lean approach. It represents an ideal, complementary system framework for agile companies. Everything that digitalization entails is likely to influence the previous quality metrics with new ones - whether to strengthen or replace them.

Either way, quality remains a differentiating feature and offers new opportunities and perspectives for quality management and the role of the quality manager. The question today is no longer if, but when. The "when" in turn is driven by the degree of digitalization of individual industries and the maturity of the management system of one's own company.