In my current pre-research for eventual dissertation work, I explore the inability of companies to capitalize on analytics capabilities due to a lack of a data-centric culture, and seek to identify a number of key measures for implementing such. This is admittedly an interdisciplinary endeavor. Büschgens, Bausch, & Balkin (2013) focus on the broader organizational culture phenomenon, but their theoretical approach and meta-analysis are relevant. The same principles that foster a successful organizational culture may also be useful for implementing different subcultures or niche cultures that are a part of that broader successful culture.
The authors introduce two important theoretical constructs: Measurement of Behavior and Output (Ouchi, 1979) and the Competing Values Framework (Quinn and Rohrbaugh, 1983; Quinn and Spreitzer, 1991). Ouchi’s model, for our purposes, begins with a low ability to measure outputs. Thus, the organizational process is classified on the knowledge of the transformation process. For implementing a data-centric culture, our hope is that stakeholders are closely engaged, but that is not always within control. Even in a worst-case scenario (or, clan control), it is possible to “[align] the individual’s objectives with those of the organization” (Büschgens, Bausch, & Balkin, 2013, p. 766).
The Competing Values Framework is a useful tool for quantifying the specific means and ends each part of an organization most closely identifies with. This is of particular importance when a data-centric culture spans over multiple internal entities. Finance might be more Hierarchal in their approach, but IT may be more Rational. Appealing to why the data-centric culture is important will require different foci for each department based on their plot on the Competing Values Framework. Such is the focus of the meta-analysis. The authors investigate the relationship between innovation and the four major cultural traits, and outline their findings. Of particular interest are (a) those findings on the relationship and (b) the fact that “organizations that create radical innovations do not exhibit different organizational cultures than those that are rather oriented at incremental innovations” (Büschgens, Bausch, & Balkin, 2013, p. 775). This is encouraging, as organizations may sometimes feel overwhelmed or pushed by the need to make great strides in change when in fact the current climate would not support such radical change, and such a speed is accessible and relevant to all the major cultural types.
Those of us in IT would be wise to don a management consulting hat once in a while, seeking to understand our customers and what why drives their daily productivity.
Büschgens, T., Bausch, A., & Balkin, D. B. (2013). Organizational culture and innovation: A meta-analytic review. Journal of Product Innovation Management, 30(4), 763–781. doi: 10.1111/jpim.12021.
Ouchi, W. G. (1979). A conceptual framework for the design of organizational control mechanisms. Management Science, 25(9), 833–48.
Quinn, R. E., & Rohrbaugh, J. (1983). A spatial model of effectiveness criteria: Towards a competing values approach to organizational analysis. Management Science, 29(3), 363–77.
Quinn, R. E., & Spreitzer, G. M. (1991). The psychometrics of the competing values culture instrument and an analysis of the impact of organizational culture on quality of life. Research in Organizational Change and Development, 5, 15–42.