Daniel Albert, PhD
Daniel Albert is an Assistant Professor of Management with a particular focus on Strategy and Innovation. He received his Ph.D. from the University of St. Gallen in Switzerland and was a (postdoctoral) research scholar at the Wharton School.
Daniel serves on the Editorial Boards of Organization Science, Long Range Planning, and Journal of Organization Design.
His research focuses on how decision makers can design and manage organizational complexity in such ways to foster innovation and enable strategic change. Daniel’s research has investigated questions such as:
- is organizational complexity hindering or helpful for strategic change?
- how does organizational structure influence a firm’s ability to innovate?
- how should firms experiment to find novel product architectures?
- how visionary should firms set their long-term goals; and how can they achieve them?
Daniel uses various methodological approaches to study the phenomenon of complexity and decision making, such as statistical analysis of archival data and computer simulations.
Why complexity can help with strategic renewal
Together with my colleagues, I have reviewed what decades of research have to say about the role of complexity and the ability to strategically change and renew. In a nutshell, there are different types of complexity:
* Structural complexity – the way business activities are clustered, hierarchical, and linked with external players
* Policy complexity – the rules by which interdependent business activities are governed, such as the standardization and their time sensitivity
A common approach of reducing complexity has been to cluster homogenous business activities, decentralize and reduce dependence on external players. However, we argue that such strategy runs the risk of not quickly enough picking up on critical changes in the environment. Instead, a more complex organization, that is one that has integrated business activities, potentially even a hierarchical order among them, and a wide reach of external links can be more sensitive to important changes in the environment.
The ability for such complex organizations to explore and evolve to new strategies is particularly beneficial when interactions are governed by more standardized but less time-sensitive policies.
How power and modularity in organizational structures can hinder reorganization
Large corporations regularly overhaul their organizational structure by recombining different business segments in an attempt to better address changing market needs. The decision how to reorganize existing businesses is crucial because the implementation is often difficult and expensive. While it seems that companies may be ‘free’ to change their structure in any way, looking at 14 years of reorganization decisions in large European universal banks, this study finds that the business and power structure can substantially influence future reorganization decisions.
- Large banks that were more centralized, were more likely to reorganize their divisions
- Within large banks, business divisions that were more powerful, with respect to their representation the bank’s top management team, were less likely to be recombined with other divisions, and more likely to absorb other units.
However, divisions with powerful subunits were found to promote the break-up of their divisions and often sought autonomous division status for themselves.
So how does this inform managerial decision makers? It certainly does not alleviate the decision whether or not to reorganize in the first place. However, it informs how a given structure might ease or hamper reorganization in the future. Constant reorganization is at the heart of strategy development and firm survival. If structural decisions can influence the path of reorganization in the future, recognizing the importance of such choices can have lasting effects on corporations’ long-term strategy.
How to innovate by changing product architectures instead of components
Product innovation lies at the core of many firms’ competitive advantage over close rivals. Therefore, for many organizations improving their innovation process is of high priority. There are at least two prominent ways in which product innovation happens. First, designers search for new product component designs as well as new combinations of product components. This leads to the arguably most discussed and observed innovation type: ‘component Innovation’. Second, designers may alter the way in which existing components are linked, termed ‘architectural innovation’. Research has shown that architectural innovation is more difficult for rivals to spot and copy and has provided many firms with tremendous technological advantages over competitors.
We have investigated how design teams may want to structure their search for new, innovative architectures. In a computer simulation that has widely been used and found useful to model firm innovation processes, we find that architectural search is fundamentally different from component innovation. Incremental experimentation with architectural changes bear greater benefits over time than broader experimentation — a quasi reverse recommendation as for component innovation.
Albert, Daniel, and Siggelkow, Nicolaj, Architectural Search and Innovation. Organization Science (Mar 2021):
Albert, Daniel, Organizational Module Design and Architectural Inertia: Evidence from Structural Recombination of Business Divisions. Organization Science 29 (Sep 2018): 890-911.
Albert, Daniel, Kreutzer, Markus, and Lechner, Christoph, Resolving the paradox of interdependency and strategic renewal in activity systems. Academy of Management Review 40 (Apr 2015): 210-234.
Albert, Daniel, and Ganco, Martin, “Landscape Models of Complex Change.” Oxford Handbook of Organization Change and Innovation, Ed. Van de Ven, A.H. & Pool. M.S.. Oxford, U.K.: Oxford University Press, (2021):
Editorial Board Service
Journal of Organization Design – Member (2020–Present)
Long Range Planning – Member (2020–Present)
Organization Science – Member (2020–Present)
Journal of Organization Design – Member (2019)
Long Range Planning – Member (2019)
PhD - University of St. Gallen Switzerland 2013