“We shall court a similar fate if we develop cleverness without wisdom”
Like many in the consultancy industry, I am sometimes employed to create improvements in Programme Management within high-tech engineering industries. These projects are both exciting and daunting. Exciting because I am involved in an ambitious undertaking which is both important and challenging. It is daunting because it can often be a forlorn hope to deliver such improvements in an environment of mind-boggling complexity and decades of mechanistic behaviour, among both the leadership and the workforce. I am struck by the clash between the spirits of the Industrial and Information Ages, both of which inform and contest the “way we do things here”. We are living in the disputed borderlands between these two great empires. Our behaviour is conditioned by the obsolescent Industrial Age, even as we try to embrace the new digital era. There is often no way of living with both philosophies; they are mutually exclusive. The early Industrialists embraced efficiency and this is now encoded in the deep culture of engineering firms. The Information Age, conversely, creates disruptive opportunities for messy, noisy but agile communication. Programme Management is embroiled in a battle for its soul between the forces of efficiency and agility. You cannot have your cake and eat it. In this article I will describe the battle between these opposing forces, although I cannot offer a simple solution, in fact I hope that readers will realise the chimeric nature of simple solutions.
Approaches to complexity
Planning in a complex environment relies on capturing large data sets prior to starting any new venture. These data are complex and often incomplete. They may only partially reflect the real situation. Prior to the start of a new activity the data are mapped to a semi-rigid collection of processes which forms the Programme or Project Management Plan, or equivalent. The Programme, the processes, the IT platforms and the human beings operating them form a cybernetic system. This is a network of machines and human beings communicating through various modalities, which I will call the system for the purposes of this article. The system may be called something more specific in your work place.
Due to the incompleteness of the data it is very likely that the Programme will be disrupted from the start as new issues emerge throughout the activity. As such Programmes are invariably change programmes, and the system is always in the midst of change control. I call this planned de-stabilisation as it immediately throws the human component into an effort to return to the original Programme. As such the system is rarely, if ever, in a so-called stable state. Considerable effort has to be expended to wrestle the Programme to a position where it can deliver on time and to standard. The ability of people to achieve the ‘impossible’ is always surprising but operating in an environment of constant flux requires stamina and creativity.
The system is, in fact, a Complex Adaptive System (CAS). The complexity of the system arises from the number and variability of the embedded tasks and modes of operation. Human beings communicate with high-context social and behavioural information. Computers communicate with low-context digital information. Computer communication is efficient but not agile whereas human communication is agile but not efficient. The system is adaptive largely because of the computational power within the system, to present data, and the fluidity of human decision making. However, most CAS operate in bureaucratic and hierarchical structures following mechanistic Industrial Age processes. As such, they are rarely agile (which is not a criticism) but always adaptive, as the name suggests.
The system works on a large number of levels from planning to execution, which is of special interest to students of complexity. It is well known that interaction between levels can lead to the emergence of chaotic effects which have unpredictable outcomes. This means that the end-state of an activity is unknowable even if we do know the starting-state. In fact, the starting-state is not normally completely known due to the data gaps already described.
Today we work within two decision making structures (or some combination of the two):
- Industrial Age hierarchies (high efficiency)
- Information Age networks (high agility)
Our environment is undergoing a change from the very efficient industrial practices designed to control scarce information and allocate it to specialist divisions (often called stove-pipes). With the advent of the Information Age, data are no longer scarce which allows networked communication and decision making at all levels of the network. This is more agile but at the expense of efficiency; due to the move away from control. Complex adaptive systems can be agile but often exist within industries that are still mechanistic in nature. The complexity of tasks in the industrial sector is a strong incentive to retain a high level of control, it’s hard to imagine a chaotic swarm approach to production scheduling. The Programme is expressly designed to remove uncertainty and yet chaotic effects are highly likely due to interaction of variations within the system.
Conclusion I cannot offer a solution to the dichotomy of Industrial and Information Age practices. I would be highly suspicious of anyone who claims to. Arguably, the military has the best understanding of volatile, uncertain, complex and uncertain (VUCA) scenarios1 and the need to balance agility with control. This stems from the increasingly asymmetric warfare which conventional military organisations face post 9/11. After a baptism of fire, military leaders are now more comfortable in the fog of war than ever before. The same cannot always be said for commercial organisations, many of which revert to mechanistic practices. It is unlikely that such businesses will survive in the Information Age.
- VUCA was developed by the US Army War College from around 2002
Does your business need help overcoming the two paradoxes?
Systematic business analysis