Transforming and delivering government policy from outline initiatives frequently relies on the skills and intuition of experienced public servants. Policy delivery rarely seems to involve extensive consideration of how the stakeholders of the policies, particularly users and other government departments, will be affected. A good example of this was the UK community charge.
With governments under pressure to meet higher stakeholder expectations, there is an increasing imperative for policies to be developed and implemented in a way that will deliver their objectives and enhance perceptions of 'better government'.
Complex policy interactions are usually not considered
The complexity of the issues involved in many areas of policy implementation frustrate its effective delivery.
With government facing resource constraints when seeking to maintain existing 'services', let alone the imposition of new policies, potential exists for decisions to be taken where there are hidden, negative, or untimely consequences. These can lead to an increase in political exposure and adverse public reaction.
Government needs a method of anticipating policy outcomes, as accurately and holistically as possible, in a risk-free environment. Given this, government could:
- Produce supported policy options in which ministers and civil servants would have confidence to sell and deliver major change.
- Stick with these policies in the face of opposition.
- Effectively manage the implementation timing to strengthen public perceptions of government.
Addressing the issues
One option is conventional modelling techniques and economic models, but these do not capture interactions and feedback loops, the understanding of which is key to the successful implementation of complex policies.
Another approach is dynamic business simulation modelling, which has already been used extensively in high-value businesses to support complex decision-making and market investment decisions in a variety of industries, including financial services, aerospace and transport. For example when applied to the operations of a major card issuer in the financial services sector, the use of dynamic simulation techniques resulted in the development of a co-branding strategy that improved market share by 40% and added $5 billion in profits to member banks.
The technique has also been applied in a limited number of instances to support, develop and implement governments' policies. Examples in the US include:
- Disaster/contingency planning for defence, to help with risk reduction and risk mitigation strategies.
- Business case development for a dam in the Susquehanna river.
- Investigation of the trade-offs between investment and development of the medical practice (paying patients), versus teaching and medical research activities (attracting funding from key organizations), in a large medical centre.
Dynamic business simulation modelling
For governments, a particular advantage of dynamic business simulation modelling is that the process draws upon the perspectives of key stakeholder groups, as well as economic and other contexts, to define the structure, relationships and feedback loops within the policy implementation environment. For example, the ability to look at and understand the impact across and within government departments (to demonstrably support development of joined-up and modernized government) may be an essential facet of being able to deliver new services.
Governments seeking to improve the investment of public money can take advantage of the systems thinking and dynamic modelling, which, as industry has shown, can deliver substantial value in high-risk, high-cost policy initiatives where getting it right is absolutely essential.
The benefits from adopting such an approach can be significant and compelling, including:
- The process of policy definition becomes tractable; through a better understanding of the complexity of the dynamic variables with visual representation in a risk free environment.
- Key inter-relationships can be better defined; by modelling the causal relationships between entities and the relative advantages and disadvantages of policy options, in terms of key performance indicators
This approach is particularly relevant to areas of government that are capital- and asset-intensive, such as rail and road infrastructure.
Framework for understanding policy impacts
An element in helping to understand policy impacts is the partitioning of complexity into a framework of 'planes', which can be used to collectively describe any policy context—environmental, political, institutional and regulatory, economic, business, operational, technical, and the user plane which can interact more readily with all the others. Each plane can be thought of as a jigsaw with many degrees of freedom and interactions between the pieces. Pieces also interact with those on other planes and a significant benefit is the identification of key links between planes and particular measures and requirements, which will help to control their collective behaviour in a manageable and predictable manner.
Systems thinking and impact modelling
Taking this generic framework for classification, it is then necessary to identify key entities within each plane and the interactions that can occur between them.
Whatever the policy context, one of the strengths of the technique is that it can be used as a means of communicating and creating consensus about the key causal relationships within an area of policy deployment within and across government departments and beyond.
Dynamic simulation development
The causal relationships are then developed into mathematical representations (using information from experienced specialists). This process is iterative and may identify additional relationships, or alter the relative strengths of those already represented.
Once the model structure is 'complete', the tool has the power to influence policy development and refinement, offering the opportunity to understand and modify the impacts and implementation timing to produce outcomes that are in keeping with the desired objectives.
Effective programme design and implementation
As the forecasting process develops, and the impact and interactions of the various policy initiatives are identified, assessed and evaluated, the development of implementation options for each policy component and the most favourable sequence and deployment methods begin to emerge.
As a policy moves into live implementation, possibly as part of a pilot programme in the first instance, the dynamic business simulation model continues to provide value. The emerging results can be fed back into the model and used to make modifications, particularly where implementation responses are different from those which were expected. This is particularly valuable where the policy being introduced is a sufficient step change from the status quo and where the original predicted outcomes are based strongly on experts' opinions, rather than hard fact.
A way forward
Key decision-makers will readily see that proven, quantified techniques can provide considerable assistance in understanding and formulating approaches to the implementation of public policies in complex situations. Importantly, where used, they can help minimize the potential for taking an inappropriate approach to capital-intensive initiatives that, if implemented badly, could lead to specific policies being discredited at great cost to the public purse. For many in government, this may appear to be an unconventional approach, but the value of identifying the most effective policy options and implementation strategies is undeniable.
