The Scanning Process

This chapter provides a comprehensive overview of the process of environmental scanning. It goes in depth by describing different methods used in environmental scanning.

Ways of seeing

Taxonomies

economics
finance : globalization : poverty : regulations : sustainability : trade environment
agriculture : animals : climate : construction & building materials : environmentalism : food & drink : nature : raw materials : restoration : water

healthcare
disabilities : disease : epidemics : genetics : management : medical research : nutrition : pharmaceuticals : treatment : wellness

industries
arts : biotechnology : clean technology : communications : energy : financial services : life sciences manufacturing & materials : media : mining (new) : retail : transport : travel

lifestyles
consumption : design & engineering : education : families : fashion : homes : leisure : values organization
anticipation : change : competition : culture : innovation : metrics : processes : risk : sales & marketing : strategy : workforce : workplace

politics
government : ideologies : international : military : protest : rights : security

society
community: crime & justice : demographics : gender: generations : networks technology
computing : electronics : intelligence : internet : nanotechnology : realizations : robotics : science : singularity & transhumanism : space

Figure 29. Taxonomy


Using a taxonomy (a knowledge classification system) such as STEEP (Social, Technology, Economy, Environment, Politics) or PESTLE (Politics, Economics, Social, Technological, Legal, Environment) provides you with a starting point for your scanning. If, for example, your scanning anchor is around technology and learning, you will need to search out hits related to different aspects of the issue – delivery, communication, networking, etc. 

Figure 29 shows a typical, but comprehensive, taxonomy. Your scanning is likely to be limited to maybe 1015 topics from this list or others that are specific to your organization. 

Using various ways to classify your data through structured, centrally managed, and classified topics (taxonomy) or by unstructured, distributed, unclassified topics (folksonomy) helps identify the valuable information and to filter out considerable noise. 

 

Figure 30. An unstructured folksonomy displayed in a Wordle tag cloud