Big Data Modelling of the Knowledge Economy

A computer-generated 3D model is used to illustrate the advantages of in silico techniques in virtual reality. The model is derived from theoretical data available for SMEs in service industries and for example enables a business owner (or consultant) to identify where the particular organization is on this three-dimensional landscape and draw quantitative conclusions about fruitful future directions for the organization, as well as how high the benefits will be and what costs will be due along the journey.Clearly this landscape map is of immense value for academics and practitioners alike, and is available “ready-to-go” in a generic and easily-applicable form. This Masterclass will go further and show participants the use of software tools to construct a contour landscape that is specific for their own client organization.We will create the basic 3-dimensional fold in Maple and discuss the implications for SME growth and development. We will then move to Markov Chain Monte Carlo modelling, which - put simply - is throwing virtual balls down the basic fold to show how the fold can be used and manipulated to model and predict outcomes of “Knowledge Engineering”. In particular we will model; adding multi-skilled innovators, adding network input from the external environment, looking at the cost of controlling management by showing how much bad information gatekeeping at departmental manager level actually costs and investigating the value-adding effect of intellectual capital.If time allows, participants will be presented with a small case study and – together with the class leader – will work through a simple solution thus illustrating the ease and applicability of the model in a practical and hands-on fashion