We are living in a complex world and due to current changes it is getting more complex every day. Decisions have to be made in real-time and stability can nowadays only be achieved through constant and dynamic change. If we take Ashby’s law of requisite variety (1956) this means that the control system has to become more complex in order to deal with the complexity that has to be controlled. Therefore it seems at hand to reduce the complexity and focus on the essential aspects relevant for an organization. As Beer (1979) states that a lower number of varieties are necessary to maintain the viability of an organization. But is it possible to disregard everything as white noise that is not following linearity and is not normally distributed. By that we can simplify the decisions of an organization but mostly we are establishing a big blind spot for the chaotic environment organization exists. Organizations have to move beyond reductionism (Barabási, 2012) and have to shift (back) towards complexity (Scholz, 2013).
In this paper we propose that support for dealing with complexity can be found in data and information. Today organization, actors and stakeholders generate data every time and everywhere. This is called big data. The concept of big data could become a little helper for an organization. However using big data in raw form is like searching for a needle in a haystack. Still though the data is present and should be used strategically.
Big data can be classified in four dimensions: Volume, variety, velocity and veracity (Schroeck et al. 2012). Volume represents the vast amount of data; variety states the number of different forms of data that can be already organized or is unstructured. Furthermore velocity is dealing with the speed data is collected and data is processed. Veracity is about the inconsistencies within the data. Especially the last dimensions reveals that big data should always be a support and not a substitution. It also means that data on its own is useless and organizations have to plan extensively before implementing any big data application.
Such big data strategies can help to cope with the complexity and filter the data according their relevance. Based on a strategic management it is possible to reduce the complexity according several governing rules. Furthermore there is the potential to develop threshold criteria that allow a dynamic approach of filtering. Changes in the data will be hidden until a defined tipping point occurs and after that point become relevant and hence are flagged by the system. Big data becomes a little helper that allows a rapid assessment of relevant issues concerning the organization and the affiliated actors within the complex system. A process of sense making is possible that allows evolving the big data applications to become more effective and more efficient.
Still though it is furthermore necessary to develop a framework within big data is used. Using big data is an on-going process of balancing the benefits and the risks. Questions according privacy and ethical use have to be tackled. Even though data can be collected everywhere and every time, it is essential that big data stays a little helper and doesn’t emerge towards a big brother. It is critical to state that big data is a tool, but its usage will have a strong influence on the complex system, it could chance the social contract (Peters, 2012) and eventually the working world.
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Beer, S. The Heart of Enterprise, London (Wiley), 1979.
Peters, B., The Age of Big Data, in: http://www.forbes.com/sites/bradpeters/2012/07/12/the-age-of-big-data/, last accessed on 27.08.2013.
Scholz, T. M., Complex Systems in Organizations and Their Influence on Human Resource Management, in: Gilbert T./Kirkilonis, M./Nicolis, G. (eds.), Proceedings of the European Conference on Complex Systems, Heidelberg (Springer), 2013, 745-750.