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Foresight | Innovation OS | Trend & Tech Scouting

Monitoring Trends & Developments: How to Accelerate Weak Signal Detection

Weak signals are difficult to spot and interpret. The sheer volume of signals makes it challenging to monitor areas of interest to your business. Yet, as an innovation leader, you're expected to read the market and respond in a timely and competitive fashion. Automated monitoring that leverages machine learning makes it easier to notice early indicators of phenomenal change, helping you stay ahead of the curve.

Difference between signals and weak signals

Weak signals are fragments of information suggesting significant change could be underway, such as emerging issues that could grow to affect your business. In the 1970s, Igor Andsoff proposed the concept of weak signals as a type of warning: the first indicators of change might seem insignificant but could potentially be very disruptive. As an analogy, think of weak signals in the context of seismic data analysis. An Earth scientist monitors seismic activity for early warning signs of coming earthquakes. This is called a weak signal because it suggests something much larger is coming, but is difficult to detect against the background noise of insignificant movements under the earth's surface.

Now, apply this concept to the field of innovation management and foresight. Weak signal detection involves monitoring a broader area of interest to your business and spotting small indicators of coming earthquakes in the market.

A signal is just a piece of information, such as a news article, a photo, a statement from a public figure. A weak signal is more significant than a signal because a weak signal has an interpretation attached to it. A signal becomes a weak signal once someone says, "This means something; it's a hint of bigger things to come, even if we don't yet understand that change on the horizon." There are millions of signals, but weak signals are rare.

Some weak signals evolve to become macro trends and technologies, then larger megatrends:

Inverted triangle hierarchy of weak signals, macro, trends, and megatrends

Weak signals: First signs of emerging trends. Effect duration is 3-5 years.

Macro trends: Observable change that is moving in a specific direction. Effect duration is 5-10 years.

Megatrends: Major social, economic, political, environmental, or technological changes that will fundamentally affect everything else. Observed over decades, 25-30 years.

What is an example of a weak signal? Well, someone reading Berkshire Hathaway's annual report in 2003 may have noticed Warren Buffet describing derivatives as "financial weapons of mass destruction" that could accentuate systemic problems in a major way. Four years later, derivatives in the mortgage market were a major cause of the 2008 financial crisis. Or, consider the decline in usage of Google Search in developing countries in the mid-2010. This may indicate a move towards an internet that is no longer centered on webpages, as people prefer to source information from people they know on social apps rather than read reputable websites.

Monitoring is time-consuming

Imagine all the sources there are to monitor for weak signal detection. Your business environment comprises external drivers of change, including trends, emerging technologies, startups, competitors, markets, business models, risks, regulations, and customer needs. Environmental scanning typically involves collecting relevant data from news sites, RSS feeds, patents, and publications of science and technology information. The sheer volume of information that entails makes it a huge challenge to monitor weak signals.

We often hear from innovation leaders who say there's just too much signal noise to decipher what the important developments are. They need a tool for environmental scanning that mitigates the noise in order to more quickly identify weak signals and react to them before the competition. These processes can clearly benefit from automation.

How to do weak signal detection

The first step in environmental scanning is determining the topic themes that are relevant to your business. We call these opportunities: areas of interest based on the strategic direction of the company. These themes may be topics based on your unique industry or linked to specific emerging technologies or trends. Don't base this on one person's opinion. Get input from across the organization to gain consensus and buy-in on what opportunities are important. This defines a company’s “Where to play?": the areas in which future growth is possible and even necessary.

The process for weak signal detection differs from monitoring. You set a broad scope for research without narrowing it to a specific trend or technology. For instance, an iron ore company may want to understand where the future of mining is headed. It’s a search for Unknown Unknowns: these are things the company does not know they don’t know. Such a search may for instance highlight a scientific paper on biological microorganisms that release carbon-based minerals from ore without the need for extensive mining. Such a weak signal suggests a possible future in which current mining practices become obsolete, or a huge opportunity for the company to innovate.  In contrast, monitoring has a narrower scope than weak signal detection. The company identifies a particular trend in their industry to monitor. This is therefore a search for known unknowns.

Circle graphic of Known Unknowns and Unknown Unknowns

Before the advent of specialized foresight research tools, environmental scanning typically involved sifting through analyst reports, science research, news media, startup activities, and patent databases. The scouting team would then identify distinct and anomalous fragments of information that suggest potential shifts in the foreseeable future then collate these in a spreadsheet shared within a company.

This process is time-consuming and not a faultless method for foresight. It is not practically about predicting the future but is more realistically focused on the detection of weak signals as indicators of potential change. Jonas Muhrer, Product Manager at ITONICS, describes this problem as follows: "Let’s be honest; weak signal detection isn’t some magical power that lets us foresee the future with unerring accuracy. It’s more like trying to decipher a murky message written on an infinite parchment."

This problem can, however, be made significantly easier with the help of innovation tools that incorporate machine learning.

Save time with automated monitoring

Innovation leaders want to be better informed of opportunities and risks on the horizon to respond to changes in the marketplace. But who has time to monitor the forces impacting their business every day manually? Such repetitive processes are prime candidates for automation via artificial intelligence. ITONICS enables automated monitoring of signals within a defined interest area. You can declare your area of interest in the software by for instance creating a Trend or Strategic Focus Field element. The alerting engine then automatically monitors for rapid developments in this area.

A signal graph spike in ITONICS software

Every time a spike or drop in signals for your area of interest is detected, it is added as a Key Event on the date graph. This alerting engine takes the burden off your team, freeing up valuable time by substituting the requirement to manually check in regularly on areas of interest for sudden developments. It helps ensure that your teams won't miss out on big developments that demand attention.  If there is a significant change in signals within your area of interest, ITONICS sends an email alert to you.

ITONICS sends email alerts to your inbox when there is sudden growth in your area of interest

This means that you can receive automated alerts when the graph for signals relevant to your company, such as sustainable packaging, shows sustained growth in publication interest or application in patents. These alerts, linked to your areas of interest, help you to react promptly to relevant changes, spikes, or drops in signals, facilitating timely actions and decision-making. Machine learning automates the monitoring, but you need a human brain to make sense of the signals and add an interpretation that transforms a signal into a weak signal that hints at a large shift in the future.

The ITONICS vision for augmenting human understanding with machine intelligence lets each component do what it does best. An innovator's ingenuity and strategic thinking are essential to interpret weak signals. But with the machine intelligence in the ITONICS INNOVATION OS, you can say goodbye to manual and resource-heavy tracking.  Automate your monitoring process and get to what matters faster. Experience the benefits of ITONICS today with a free demo.



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