Рефлексивные процессы и управление. Сборник материалов XI Международного симпозиума 16-17 октября 2017 г., Москва. Коллектив авторов
The Origins of Power, Prosperity, and Poverty. New York: Random House, 2012.
2. Campbell, Donald T. (1969). "Reforms as Experiments." American Psychologist, 24 (4), pp. 409–429.
3. Conger, D. Stuart. (1974). Social Inventions. Prince Albert, Canada: Saskatchewan Newstart, 1974.
4. Dunn, William N. (1998). The Experimenting Society: Essays in Honor of Donald T. Campbell. Transaction Publishers, 232 pages.
5. Lepskiy, V. (2010), Reflexive and Active Environments of Innovative Development, "Kogito-Center" Publishing House, Moscow (in Russian). http://www.reflexion.ru/Library/Lepsky 2010a.pdf
6. Lepskiy, V. (2015a), Evolution of concepts about control (methodological and philosophical analysis, "Kogito Center" Publishing House, Moscow (in Russian). http://www.reflexion.ru/Library/Lepskiy2015.pdf
7. Lepskiy, V.E. (2015b). "Economic cybernetics of self-developing environments (third-order cybernetics)", Management sciences. No. 4, pp. 22–33 (in Russian). http://www.old.fa.ru/dep/upravnauki/Documents/%D0%A3%D0%9D4 2015. pdf
8. Umpleby, Stuart & Eric Dent. (1999). "The Origins and Purposes of Several Traditions in Systems Theory and Cybernetics."Cybernetics and Systems: An International Journal, 30:79-103.
9. Umpleby, Stuart. (2002). "The Design of Intellectual Movements." Proceedings of the annual meeting of the International Society for the Systems Sciences, Shanghai, China, 2002.
10. Umpleby, Stuart. (2017). "How Science is Changing." Cybernetics and Human Knowing, 24(2), pp. 89–91.
11. Walton, Mary. (1986). The Deming Management Method. New York: Perigee.
Igor Perko(University of Maribor, Slovenia), Raul Espejo(World Organisation of Systems and Cybernetics, UK)
Big data analytics organisational learning
Abstract. Purpose. We will identify the potentials that big data analytics (BDA) have on the of the learning processes of an organisation. We are particularly interested in the speed of these learning processes;on the memorising and sharing of knowledge, on the ability to recognise the environmental feedback information and on the impact to micromanaging internal organisational processes. Design/methodology/approach. To assess the current state, we offer a theoretic background of the organisational learning processes and the BDA related research reports. To analyse the BDA supported organisational learning processes, we invoke the Viable system model (VSM) and especially the Viplan methodology. Based on the results, a universal BDA supported organisation learning model is proposed. Findings – A universal organisational model, focusing on BDA supported learning processes. Originality/value – to elaborate an organisational learning model, encapsulating the BDA toolset. Research limitations – the proposed results rely on published research reports and arenot validated in a real life experiments. Research/Practical/Social/Environment implications – For the researchers the model will provide a new organisational paradigm and articulate multiple research directives. Members of the professional community will better understand the BDA potentials for organisational learning.Because of the universality of the model, it will have the potential to be applied on all organisational levels, ranging from individualsto society and environment.
Keywords: Systems thinking, Cybernetics, Big Data analytics, Learning processes, Viable system model, Viplan methodology
1.1 Problem situation.Current information technology, particularly social media such as Facebook, Goggle, LinkedIn and many more, are hugely increasing data flows and interactions in society and organisations. Algorithms and artificial intelligence or BDA are dealing with the related data, suggesting that they can handle these data flows in the benefit of people‘s decisions and actions. We believe that this perception of increased observational and action capacity needs revision. BDA have a great capacity to deal with data and articulate options but these new capabilities may increase people‘s illusion that they have an improved understanding of their relevant situations and also an increased capacity to deal with them effectively. We want to test and improve these perceptions and argue, in conceptual and methodological terms, that there are dangers in an unrestricted data management driven by sophisticated BDA; what drawbacks are they posing to aspects such as organisational effectiveness, individual autonomy, privacy and fairness.
The organisation helps people to learn and understand the state and dynamics in the environment, as well as state and dynamics within the system. With accessibility to high volumes of data, the personal capacity to understand and react upon the data may be overpowered. Prior to the BDA approach, using the business intelligence, the means of reducing variety was mostly focused on financial results and summarisation was used to provide views on the higher levels in the organisation (Kimball, 2002). Based on this lack of variety, business intelligence had serious problems, especially it lacked understanding of the implications of high-level decisions, and focusedmostly on the financial aspects of the business it measured.
The BDA potentials to disrupt the existing organisations are undisputed. It is though important to use systems thinking to maximise the positive impact and to thoroughly understand the implications it has on the other players in the system. It should support the cooperation and not only provide short-term competitive advantage to system performance.
The foci of our arguments are first, on the relationships of people and organisations with their environmental agents and second, on their multiple interactions, which are responsible for self-organising processes. Today these relationships and interactions are increasingly mediated by BDA and therefore it is necessary to explore:
1) The extent to which BDA is supporting individual and organisational learning through its contribution to increasing effective relationships and interactions. This requires revision of relationships and interaction among actors within an organisation. In this purpose we focus on varied issues of concern in business organisations. Often these organisations support relationships that increase the chances of hierarchical structures and therefore of inhibited learning throughout them;they are driven by fragmentation, inadequate coordination of actions and lack of trust. How can BDA overcome these shortcomings and therefore increase cohesion and the organisation's dynamic performance?
2) The extent to which people in organisations, supported by BDA, can develop effective interactions and relationships with environmental agents. For particular issues of concern we explore both 'operational interactions' with customers and 'problematic interactions' with multiple agents to increase opportunities for innovation and adaptability. We discuss for these issue technologically mediated interactions and relationships that increase individual and organisational competencies and therefore their learning.
1.1.1 Methodology. In this paper we use the Viable System Model (Beer, 1979, 1981, 1985) – VSM- and the VIPLAN Methodology (Espejo, 1993; Espejo & Reyes, 2011); they help us to discuss the braiding of organisational learning (Espejo, Schuhmann, Schwaninger, & Bilello, 1996) and technological processes. We support model and methodology by a systemic epistemology, which highlights holism, in particular the relevance of communications, interactions and complexity. More specifically we adapt the Viplan Methodology (Espejo & Reyes, 2011) to the use of BDA.
The emphasis is in the interactions and relationships of agents at multiple levels, from the global to the local. We use a systemic epistemology that highlights structural determinism in organisations and structural coupling between agents and actors (Maturana & Varela, 1992). Structural determinism highlights the autonomy of organisational systems; it is the closure of their structures that determines which environmental data makes sense within the organisation. Structural coupling highlights the history of communications and interactions between agents and actors leading to the structural congruence between them.
Big data is produced by the huge number of transactions natural to all situations. The problem is their management. Crucially to focus on relational aspects we use Ashby's Law of Requisite Variety (Ashby, 1964)and the ideas of variety operators to balance performance at satisfactory levels. Dealing with data requires considering how they are absorbed by the structures affected by them, as well