WEAK SIGNALS — EARLY WARNINGS OF WHAT IS COMING
(You can read and download the full pdf here)
1. Weak Signals — Research Foundations
Igor Ansoff was one of the first authors to put in the agenda of strategic management the concepts of turbulence and uncertainty in the firm’s environment, defending the use of information of the type of Weak Signals as mechanisms or instruments capable to help anticipating future events.Ansoff used the term “strategic surprises” to define these future events, which can assume the form of threats or opportunities (Ansoff, 1975, 1984).
The concern that Ansoff gave to the level of turbulence and the degree of uncertainty of the firm’s environment was highlighted when, in 1984, the author presented the evolution of business management throughout the twentieth century divided in four major periods (Ansoff, 1984: 14–15, Nikander, 2002: 23):
Management by (after the fact) control of Performance, which was adequate when change was slow;
Management by extrapolation, when change accelerated, but the future could be predicted by extrapolation of the past;
Management by anticipation, when discontinuities began to appear rapidly, but change was still slow enough to allow a timely anticipation and response;
Management through flexible/rapid response, which emerges under conditions in which many significant challenges develop too fast to allow timely anticipation.
Ansoff positioned these management strategies in a timeline evolution relating them to the degree of visibility of the future (which, according to the author, went from a familiar or recognizable environment to contexts marked by novelty or discontinuity) and the level of turbulence (which implies different attitudes or strategic responses). According to Ansoff, the theory of Weak Signals is linked to the time scale of “management by flexible/rapid response” in the form of “Weak Signal issue management”.
Earlier in the 1960s Herman Kahn emphasized the need to think the unthinkable (this is the question to ask when we are searching for “wildcards”) and it was, according to some authors (Bell, 1997a; Wack, 1985a), the first author to define and use the concept of scenarios as a concept to incorporate the uncertainty in the exploration of the future.
By the time Ansoff was criticizing the traditional methods of strategic planning (beginning of the 1970s), Pierre Wack was dramatically changing the strategic planning process in Royal Dutch / Shell, introducing Scenarios as the more appropriate approach to face uncertainty and sudden discontinuities in the company environment (Wack, 1985a, 1985b). In 1985 Wack publishes two articles where he explains how this change was implemented in Royal Dutch / Shell, and in particular the contribution of the Scenario Planning method for the anticipation of the 1973’s oil shock. (Wack, 1985a, 1985b)
Ansoff also uses the example of the oil crisis in the beginning of the 1970s when OPEP increased abruptly the oil price, as an illustration for the inability of traditional strategic planning and monitoring processes to respond to a more turbulent and uncertain environment. “Strategic planning requires the information provided by the environment to be available for use sufficiently early and in an adequately exact form. These requirements caused by sudden changes in the business environment cannot be fulfilled by monitoring trends, as this is based on information accumulated over time. Strategic planning is inevitably late.” (Ansoff, 1984)
According to Nikander (2002: 22), it’s possible to divide the Ansoff’s Theory in two different parts:
The first one is based on the existence of Weak Signals and in the level of information that those incorporate.
The second part analyses the use of Weak Signals in the form of Weak Signals Strategic Issue Management Systems, including activities or procedures of environmental scanning and identification of sources of strategic information (Ansoff uses the term “issue”, which includes both threats and opportunities).
One of the premises of the theory developed by Ansoff relates to the fact that strategic surprises give advanced information of themselves. The author argues that although this information is initially inexact, that is, the signals are vague, fuzzy, and difficult to interpret, they gradually become more distinct and easier to understand.
Although the results are scarce, some authors link Weak Signals or Early Warnings to strategic planning and strategic management. Articles and literature published in business economics suggest that the existence of early warnings is somehow given as guaranteed. The terms used for these warnings are multiple: early warnings, early indicators, symptoms, Weak Signals, soft form of information (Ansoff, 1984, Webb, 1987, Weschke, 1994, Michman, 1989, Mintzberg, 1984, Sharma, Mahajan, 1980, King, 1987, Taylor, 1987, Juran, 1995). An analysis to the content of these different terms shows that the authors are referring to identical or very similar phenomena.
2. Defining Weak Signals
Although the term Weak Signal was used for the first time by Igor Ansoff in 1975, only later he offers a more rigorous and complete definition of the concept (Lesca, Blanco, 2002). In 1982 Ansoff defines Weak Signals as warnings (which can be found inside or outside the company), events or developments that for the fact of being too much incomplete do not allow any type of estimation on their impacts and rigorous answers (Ansoff, 1982).
Some years later he presents the following definition of Weak Signals: “A development about which only partial information is available at the moment when response must be launched (…).” (Ansoff et al., 1990: 490, in Lesca, Blanco, 2002: 3)
In 1997, Bryan Coffman published a couple of non-scientific articles about Weak Signals, relating them to Information Theory, cybernetics, and complexity. He defends the possibility of organizations to develop and implement models that allow them to obtain competitive advantages from the exploration of that type of information. Coffman presents the following definition of Signals in changing environments and organizational dynamics (Coffman, 1997):
“an idea or trend that will affect how we do business, what business we do, and the environment in which we will work;
new and surprising from the signal receiver’s vantage point (although others may already perceive it)
sometimes difficult to track down amid other noise and signals
a threat or opportunity to your organization
often scoffed at by people who “know”
usually has a substantial lag time before it will mature and become mainstream
therefore, represents an opportunity to learn, grow and evolve.” (Coffman, 1997)
Hiltunen (2001: 3), after the identification and analysis of different definitions of Weak Signals presented by several authors, suggests the existence of two distinct ways to define the concept of Weak Signal.
According to Hiltunen, Weak Signals can be understood as anticipative information (early information) on future trends or changes. The Ansoff’s approach fits in this perspective. Ansoff argues that the existence of turbulence in one specific area does not mean that the phenomenon can be identified in its final form. To get to this point it’s necessary to detect and explore gradual responses to Weak Signals, understanding these as anticipative information.
On the other hand, we can define Weak Signals as being the first symptoms of change. According to Hiltunen, the approach of Aberg fits in this perspective. “If a company wants to examine its quality level, it should consider what are the first symptoms or Weak Signals that are raised if the quality level decreases. Another example is an autumn flue. The first symptom could be tiredness. The next thing to come is sore throat and rhinitis and there are no more doubts what caused the tiredness. It was the first symptom or Weak Signal of the flue.” (Hiltunen, 2001: 3)
In a different perspective, in which Weak Signals are integrated more explicitly in processes of Environmental Scanning or Competitive Intelligence, and with a particular attention to actors role and behavior, Porter (1980) defines Early Warning Signals as being any action made by competitors which gives direct and indirect indications about their intentions, motivations, and objectives or about the company’s internal situation (Porter, 1980)
Humbert Lesca highlights the importance of Weak Signals, putting this type of information in the centre of his definition of “Veille Stratégique”. For him, “Veille Stratégique” is the information process through which companies prospectively monitor their environment by gathering Weak Signals in order to create opportunities and reduce the uncertainty (Lesca, 1994).
Lesca and Blanco (2002: 15) present the features that this kind of information that we call “Weak Signal” should have: fragmented; with a weak visibility; with a weak meaning and strong ambiguity (not evident); not (or little) familiar; with an apparent weak utility; d’une faible «saisissabilité», “fugace”; with an apparent weak feasibility.
Having Ansoff’s approach as the foundational support, Humbert Lesca and Sylvie Blanco (Lesca, Blanco, 2002) identify a set of dimensions that must exist as conditions for us to classify a signal as weak (see Table below).
3. Weak Signals Models
According to Ansoff, Weak Signals offer inexact and anticipative indications about events that are plausible to occur in the future and have a strong potential impact on the organization.
In this sense, Weak Signals are vague information that develop and improve in a gradual way through time (Ansoff, 1975). The dynamic and evolutionary nature of Weak Signals is reflected in the gradual increase of their intensity as the signals of the business environment become stronger. Ansoff refers to this evolution of the intensity of the signal strength as an “amplification process” (Ansoff, 1975).
Coffman (1997) represents conceptually this process of amplification of the signal and the benefits that the same can bring through time in a two-dimensional plan built from two dimensions: the force of the signal and the time.
Figure 8: Amplification of the Signal in a Channel with Noise (Coffman, 1997)
Source: Coffman, 1997.
According to Ansoff’s theory, as the signal becomes stronger and an increasing number of information allows a more detailed analysis about the possible situation and options that can be made, less time the organization has to act or react (Ansoff, 1984: 367, Lesca, 2002: 22). As stated by Ansoff “(…) there are two modes in which a firm can respond to the environment: the normal response in which the established planning and implementation systems are used, and the ad hoc crash response which crosses established lines and uses ad hoc task forces to produce a rapid response.” (Ansoff, 1984: 367)
4. The Signal Intensity — Weak versus Strong Signals
According to Ansoff, information that companies receive from the environment can be placed in two opposite extremes regarding its degree of definition and the level of anticipative knowledge they offer. Ansoff called these two extreme stages respectively Strong and Weak Signals (Ansoff, 1984, Lesca, 2002).
The definition presented by Ansoff for “strong signals” is the following:“Issues identified through environmental surveillance will differ in the amount of information they contain. Some issues will be sufficiently visible and concrete to permit the firm to compute their impact and to devise specific plans for response.” (Ansoff, 1984: 22)
The definition he gives to Weak Signal in the same work is the following: “(…) imprecise early indications about impending impactful events … all that is known (of them) is that some Threats and Opportunities will undoubtedly arise, but their shape and nature and source are not yet known.” (Ansoff, 1984: 22)
Ballaz and Lesca (1992) connect Weak Signals to fragmented and “drowned” information in a context of noisy information. In this sense, a Weak Signal is a signal that it is difficult to “hear”, in opposition to a strong signal that will tend to overlap the environment’s noise. Strongly related to the level of intensity of the signals is the question of their credibility. Being the strong signals more easily detected, implying a more rational and less intuitive approach, the degree of credibility regarding their existence and detection is higher, being equally easier to interpret and to generate consensus.
Aberg (1993) argues that the Weak Signals are usually so vague that they are easily missed altogether. In this sense, it is more difficult to believe in their existence and, in opposition to strong signals, the Weak Signals tend to be uncertain and less credible (Nikander, 2002). Aberg (1993) states that the central problem in the identification and use of Weak Signals relates with their detection and acceptance:
Is the detected signal a message, a change in the situation, a symptom of a relevant change, or merely arbitrary changes or scattered information?
How can signals be detected in the earliest possible stage, when they are still weak, so that will be possible to formulate the responses appropriate to the threat? (Åberg, 1993, in Nikander, 2002: 33].
(You can read and download the full pdf here) NOTE: This paper is based on a chapter of the author’s PhD thesis “Scenarios as a tool to give context and sense to Weak Signals in a process of Competitive Intelligence”, Université Jean Moulin III, Lyon, November 2010.