Коллектив авторов - Рефлексивные процессы и управление. Сборник материалов XI Международного симпозиума 16-17 октября 2017 г., Москва

The backdraft of implementing BDA is, that it cannot imply all of the knowledge on complex issues, especially if the data quality or the number of cases recorded is not sufficient to provide reliable models. Therefore Big Data stored knowledge should be focussed on supporting processes, related to relatively simple instances, with multiple repetitions.

3.4 The mechanisms to manage the representation of the complexity are redefined. The main goal of an organisation is to coordinate individual capabilities to achieve itsindividually defined goals. The knowledge of an organisation is a complex combination of structured rules and shared tacit knowledge on multiple levels, gained from previous experiences – gained through previous activities or acquired from the environment.

Figure 3. Learning by observation

BDA tools use a different approach than Business intelligence. Instead of reducing variety and focusing solely on financial business outcomes, they provide the option to understand, predict or even propose activities on the detailed data, provided by the organisation.

3.5 The inter and trans team learning and experience sharing is redefined.

Figure 4. Sharing experience across teams

The experiences of multiple teams in similar situations can be successfully identified, understood, and learned upon with the help of BDA. For example, the effects of using multiple communication marketing campaigns in multiple markets can be compared.

There is though a limitation of using BDA to support learning between the teams. It works well in a highly repetitive processes, where data on similar situations are easily obtainable, as for instance sales, or mass production. If there are not enough similar cases, or if the data variety to explain a cases is too high, BDA cannot adequately provide insight.

3.6 BDA support the interhierarchical learning processes and reduce the number of the hierarchical recursion levels.

Figure 5. Understanding the drivers

The BDA is used by the higher levels in two ways: First, by elaborating the feedbacks of the lower structural recursion levels, it can fine-tune the activities, guiding to the desired results. Secondly, it can use BDA to better understand the needs, processes and relations at lower levels to propose solutions that provide value added for all the subjects, affected by the organizations. The higher capacity to manage variety also reduces the need for hierarchy and allows structural recursion. In some cases, the automated guiding systems can entirely eliminate the need for intermediaries between the consumer and provider on a global scale.

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Abstract. As a way of conceptualizing and of pursuing epistemological practices, such as learning, designing and researching, cybernetics should enjoy a front row position within academic settings today. However, being aligned orthogonally to – and occasionally challenging – the utilitarianism, revenue models, reward-orientation, and control structures of many academic and research organizations, cybernetics as an academic discipline is in serious crisis. In many parts of the world, it no longer enjoys the levels of funding support, student numbers, academic workforce and opportunities to offer study programs it enjoyed a few decades ago. While many cybernetic ideas and theories have been absorbed by other fields, where they are pursued in specialist engineering approaches, the study of cybernetics as a generalist philosophy has all but disappeared from formal curricula in many parts of the world. Furthermore, in many parts of the word the more generalist subject of cybernetics and its more specialist sister subject of computing have drifted apart, resulting in a disciplinary as well as philosophical fragmentation of the field.