Research has shown that signals identified during environmental scanning should be stored in separate weak and strong signals databases. While the literature does not specifically recommend separating the signals, the necessity of this approach became evident through case study research, and the comments by foresight experts who focus primarily on weak signals.
In most cases, foresight activities cover signals with a potential impact timeframe of at least five to ten years ahead, and in some cases, organisations look beyond ten years. The signals that an organisation manages to identify and collect are placed into the signals databases (signals collection and storing). There, a signals management team needs to further analyse and process the signals. This includes the addition of descriptions and the defining of characteristics for every signal source, followed by signal classification and analysis, and potentially first reports to senior management and stakeholders. Research shows that trend scanning is the optimal method of collecting weak signals, focusing on desk research by cross functional teams utilising existing knowledge from experts (expert opinions and panels), literature/authors (trend reports and science fiction novels) and universities. One case organisation utilised over 60 data sources and conducted over 20 expert interviews to collect over 400 unique signals from the external and internal environment.
Figure 3: Environmental Scanning, Databases and Signals Analysis (© Marc K Peter / FutureScreening.com™)
For the collection of strong signals or mega trends (such as the aging society, the importance of individualism, health developments, the knowledge driven society, the rise of the digital age etc.), traditional methods such as brainstorming activities and external scanning using PEST and SWOT are regarded as sufficient and are recommended. As discussed previously, these strong signals are excluded for the purpose of signals analysis and processing in the best practice framework, and only later added back to the process in the scenario workshops in order to enrich and test scenarios.
There is evidence that a successful framework for signals collection and analysis requires an institutionalised process to ensure that knowledge amongst team members will be exchanged while retaining flexibility in the system. Generally, research and evidence from practical successes suggest applying the following methods (evident through case study research and foresight experts, supported by the literature) to identify and collect signals:
- General market and trend analysis, via environmental and media/literature scanning;
- Expert interviews and panels (external) and future agent networks (internal);
- Networking with partners and exchange of best practice research with other organisations;
- Observation of consumer behaviour; and
- Innovation laboratories or innovation “spaces” in organisations, utilising creativity methods.
PEST and SWOT are barely more than frameworks used in an attempt to bring structure into the strategic planning process and their use is not advisable for identifying weak signals. Successful organisations use qualitative methods and utilise PEST only to categorise insights. Research shows that companies which consider results solely from traditional planning tools prepare and describe convergent perspectives on the future, which only provides leverage for incremental change; the potential of these traditional analytical frameworks is intrinsically limited by their structured nature.
The need for signals analysis and processing is confirmed and supported by the literature, foresight experts and case study research. The signals processing methodology is described as follows: collected signals are grouped according to categories and their potential projections, redundancies are removed, and then prioritised to narrow down the number of signals. This process is entirely qualitative and is conducted in a workshop environment (with internal future agents, senior managers and external experts attending), mainly based on expertise, judgement and some guess work.
In terms of the research question, the foresight steps of signals collection, analysis and processing support an organisation’s effort to prepare for the future and subsequent flexible decision-making, to generate future strategic projects and nurture an innovation driven culture. It is important to provide a tool set of user friendly, qualitative methodologies which allow the collection, analysis and description of weak signals.
Practice Implications Derived through the Research
Foresight cannot succeed where rigid hierarchical strategy development is enforced: a centralised and authoritarian process will limit the lack of initiative in the organisation and as a result, makes it blind to potential strategic foresight. Qualitative methods and tools are necessary to successfully apply foresight. PEST and SWOT methods only result in “lists” with no meaning for stakeholders and contribute little value to foresight and the strategy development process. It is acknowledged by both case organisations that the main use for these methods is structuring information around strong signals. Traditional, analytical and structured methodologies suffer from a conflict between innovation and bureaucracy and therefore limit the availability of foresight knowledge, prevent the exposition of alternative strategies and actions, and therefore restrict the ability for flexible decision-making later in the process. The methodology approach chosen is largely dependent on senior management’s approach to strategy, culture and innovation.