Outperforming experts using simple models: improving planning information by cutting the complexity by Abigail Hird

Predicting the future is tough. This is especially true in New Product Development planning as uncertainty is inherent in innovation and design. After all, it wouldn’t be new if it weren’t innovative. Even the most intensively-deliberated, resource-consuming and best-laid planning efforts regularly result in huge overruns. Can we plan projects when what we are trying to achieve is complex and uncertain?

At Strathclyde we have developed a new approach that can totally revolutionise how we deal with this long-standing issue. It allows us to accurately predict resource and schedule requirements at the outset so decisions can be made with good quality, reliable information.

Once developed our models allow forecasts to be generated almost instantly by those with decision making power – removing the need to consult and rely upon local, and often biased, domain experts.  Transparent and consistent forecasts eliminate political agendas and personal biases.


The revolutionary aspect of our approach is the fact that no data is required to develop these models. Traditional modelling methods require data describing hundreds, thousands or even tens of thousands of relevant legacy projects.

If a business is in a fast-moving sector, developing innovative products, or subjected to long lead times the quantity and quality of data required to develop predictive models will not usually be available. This means that despite significant shortcomings estimation-based forecasts are the only alternative.


It is likely that the simple models are able to outperform experts because usually experts have no formalised structure for considering what exactly impacts resource demand or schedule. With so many factors possibly having an impact, it is easy for an expert to over-weight insignificant factors and overcompensate for interactions between factors.

In reality, the 80:20 principle applies. A small number of factors have a significant effect on the schedule and resource requirements and with insight into the weightings that these factors carry we can develop a simple yet robust model.


In the real world through KTP of course! We are working with Alexander Dennis, the UK’s leading bus and coach manufacturer, employing around 2,000 people at facilities in the UK, continental Asia and North America to improve resource demand forecasting on New Product Development projects.


As someone at the beginning of my career, having recently gained a doctorate in Systems Engineering, KTP was highlighted to me as an exciting means of validating my new method through use in practice. The KTP project has allowed the method to be tested and further developed in practice.  It also means I can have a real strategic impact on UK business.


Abigail Hird
Research Associate,
Department of Design, Manufacture and Engineering Management,
University of Strathclyde

Post Rating


There are currently no comments, be the first to post one.

Post Comment

Name (required)

Email (required)


Enter the code shown above: