The Observatory for Weak Signals

Comment

Comment by John England on April 15, 2010 at 1:54am

As I previous commented, I believe there are two basic types of blogger:

1. Those who say “That is interesting or I do not agree with that” followed by “But I wonder if there is a useful idea there or can I build on that thought?” You never know there may be, dare I say, a hint of a “Weak Signal” in there somewhere.
2. Those who love to rain on everyone’s parade and prove they are intellectual giants. Comments frequently focus on semantics. Positive contribution is rare.

Well Richard I guess congratulations are in order ... 0 out of 10 in category 1 and 10 out of ten for category 2. I have carefully read your comments here and in your own blog and I cannot find a single useful suggestion that might help micro-brain business people such as I get some practical use out of the fascinating theory.

I issue you a challenge: Please come up with at least one practical approach, which answers Holger’s original question: “What's your suggestion for a strategy which helps to filter out the weak from the strong signals?”

Note to Holger: If I have this wrong and you want this s be a purely academic discussion (and that is fine if you do) please let me know and I will stop taking up your valuable blog space. By the way, I think your implementation of this blog in having a “city” where various buildings house different topics is brilliant!

Comment by Richard Veryard on April 13, 2010 at 4:31pm

In a further comment, John England tries to explain the example between the expected and the unexpected using an example based on controlling the power grid. He regards a variation in TV transmission times as "expected", and regards an outage in a power source as "unexpected". However, I presume that both of these classes of event are anticipated by the designers of the control dashboard, and fully covered by the training received by the managing engineer, so they can hardly be regarded as weak signals.

In fact the outage of a power source is clearly an example of a strong signal, which Holger Nauheimer describes thus. "Strong signals about things going the wrong way are easy to notice in an organization - or even to measure by numbers. Strong signals will show up anyway and everybody will be concerned about them. When we notice strong signals we know that something needs to be done." In comparison, the variation in TV transmission times might once have been disregarded by power engineers, because it doesn't seem relevant until we make the connection between TV viewing and kettles (and for that matter toilets), so it might formerly have been a weak signal. However, the monitoring of TV transmission times is now embedded in standard working practices for the control of various networks including power grid and water, so it is no longer a weak signal relative to current knowledge and practices.

If that is the kind of thing that Mr England means by "expecting the unexpected", then it doesn't entail anything more than "being prepared for known problems to occur at any time". And that is not going to be much help in detecting genuinely weak signals. However, Mr England defines "weak signals" as merely "variations from the norm" and recommends "systems to constantly monitor specific bodies of knowledge", which suggests that he is talking about something rather different from the rest of us, and certainly different from the notion of weak signal introduced by Ansoff in the mid 1970s.

At some point in the future, simultaneous mass viewing of TV programmes may dwindle into relative insignificance, and network engineers will be looking for alternative (as yet unformulated) predictors of spikes in demand, or early warning of impending component failure. This is where genuine weak signals may come into this example - to indicate that it is time to switch to a different management and control system.

Meanwhile, for most people including Oscar Wilde, the phrase "expect the unexpected" has a paradoxical air, so it sounds more like a Zen koan than a simple usable guideline. As for "approaching every situation with an open mind and leaving your baggage at the door" - this is something we might all want to achieve, we might even imagine we are good at it, while noting how often other people fail to do this. Simply telling people to be open-minded is useless, because everyone already imagines himself or herself to be pretty open-minded already. The point is to construct a social process (this is part of what I call organizational intelligence) that allows preconceptions and expectations to be exposed and challenged, and allows weak signals to be detected and reasoned about.

We may not all have the kind of software that is used by the FBI and Homeland security (which Mr England describes as a "luxury"), but there are many organizations that are a lot better than these at detecting and dealing with weak signals, so there is no need to regard the processing of weak signals as outside the capabilities of any organization.

Comment by John England on April 11, 2010 at 10:44am

I was watching a fascinating documentary a couple of evenings ago called, I think, “Great Britain from Above”. This involved looking at the UK by satellite, aircraft and visual schematics. Items examined were traffic flow, GPS tracks for aircraft, power consumption, sewage flow ... in fact all the flows that keeps the UK alive. However, the one that caught my attention was the control of the national power grid as it seemed to illustrate well the Mindsystems rule 4 of “Look for and expect the unexpected” As I have explained before we take a “Occam’s Razor” approach (The simplest solution is likely to be the most workable) to personal and business effectiveness. And while I realize that the Occam rule is perhaps reviled by the academic as it makes life too simple, I do think it deserves consideration and hence the further examination of rule 4. So to the power grid!

The managing engineer sits before a huge schematic of the total UK power distribution grid with the ability to control any part of it. This system is an example of attempting to describe the “expected” in detail such that it should be possible to detect and cope with the “unexpected” when it occurs. The example shown was an event unique to the UK, which is the rolling of the final credits at the end of the daily episode of the soap, “Eastenders”. Unfortunately, programmes can finish both before and after the published time so we find the Controller sitting watching TV for the exact moment the credits start to roll. So why is this important? Well as the credits roll well over a million people get up and switch on their electric kettles to make a cup of English tea! The result is a huge power spike as each kettle consumes at least 1.5KW. The engineer immediately moved a Scottish hydroelectric plant from 50% to 100% and connected a supplementary feed from France. Then the unexpected as the French link began to shut its self down due to its own overload problems. The engineer now looked at the “expected” (the detailed, real time schematic) to determine how he could deal with this unexpected event. I suggest this is a great practical example of the simplistic statement “look for and expect the unexpected”

How can we apply these principles to personal and business efficiency and productivity by identifying variations from the norm, or “Weak Signals”? The Mindsystems approach is based on the concept that all functions in business can be represented by clearly defined systems that can be described by documented procedures. In fact, this is very similar to the principles of Continuous Improvement. The steps are:

1. Define important procedures using a simple graphical approach such and an indented tree**
2. Identify and define specific control/measurement points thought the procedures
3. Set up regular routines to monitor the results
4. Look for changes, exceptions and anomalies on a regular basis

NOTE: For this to work you must also introduce a systems/procedure which calls for regular examination and updating of the other procedures

**(If anyone wants detail information on developing procedures and indented trees please contact me directly at jce@mindsystems.com.au)

The reasoning behind this approach is that we are trying to create a systems which aids the world’s best noise filter, the human brain, to remove background noise and reveal small changes or “weak signals”. This method has the added benefit of generally improving quality and efficiency while helping to identify new and emerging trends.
It is possible to set up similar systems to constantly monitor specific bodies of knowledge.

This approach may well lack academic rigor, but it actually works!

Comment by John England on April 5, 2010 at 5:33am

How to filter weak signals from strong signals?
Well I would suggest the start point is to approach life with a neutral mindset. This comes from an approach we (Mindsystems) developed which we have tagged “Method Neutral”. Let me explain: I have personally known Tony Buzan, the father of mind mapping, for over 25 years and was instrumental in producing the first English language help files (for what is now Mindjet’s MindManager) when the first translation from the German version occurred and we are now one of the large MindManager distributors. I mention this to establish that I a mind mapping supporter. Now while mapping is superb for brain dumps, brainstorming, or harvesting small group intelligence at the start of a project, it can, unfortunately, can become much less useful as the maps grow larger and larger. This is because with large maps you tend to spend more time on the interface (i.e. mapping) than you do focussing on the information contained in the map. Indeed some individuals (and companies of course) make a living by trying to proclaim that mapping is the business panacea, which is simply not practically true. As a result of years of experience in the visual information field we developed the “Method Neutral” approach to software development.
MN is defined as “Multiple forms of information handling in a flexible workspace”. This means that the information should be represented in a neutral fashion with the option to display it in a range of ways. To put it another way, the focus should be on the information not the interface. How many times have you seen a software system that forces a company to adapt their processes to match the software? I suggest this is not sensible. We soon realised that the MN approach not only applied to software design but also to personal and business development.
One of the basic rules of this approach can be simply stated as “Approach every situation with an open mind and leave your baggage at the door” (baggage refers to prejudice and preconceived ideas). This brings me to Mr Veryard’s blog in which he states: “As for expecting the unexpected, this is of course perfect nonsense, as Oscar Wilde knew perfectly well” referring to Mindsystems rule 4 which says “Look for and expect the unexpected”. My first reaction was poor old Oscar ... yet again he is being used to add pseudo intellectual credibility to a random statement. However let’s consider this more closely. There are a limited number of ways in which people respond to blogs:
• They can look at the information and say “I wonder how I could use that information/statement?”
• They can see it as an opportunity to prove they are intellectual giants by exercising the academic equivalent of Political Correctness.
For example, I could look at the title of Richard Veryard’s blog, which is entitled “Demand Change” and draw the following conclusions:
• Great idea! This says to me that we should always be pushing ourselves to improve
• Sitting on a street corner with a cup in front of you, demanding change from passersby does not seem like the basis for a productive life.
Of course, the second statement might be faintly amusing, but it is not very helpful is it? So let’s go back to the rule “Look for and expect the unexpected”. I am interested in taking a pragmatic approach to business and personal development to the point when I often feel it useful to take academic or theoretical approaches and translate them into simple English so that it may be easily used by more ordinary folk such as myself and the typical businessperson. I tried to do this with the work of Coffman and others. Therefore, while my approach may not satisfy the academic I do believe it offers some usable guidelines for daily use and team development. After all not all of us have the luxury having access to software used by the FBI and Homeland security which can (so we are told) totally filter background noise and link weak signals into significant patterns. In the mean time I suggest that the human mind, given the right mental approach and basic guidelines, can still be a very effective filter.
“Approach every situation with an open mind and leave your baggage at the door” or to put it another way “Look for and expect the unexpected”
It also helps if you have a good neutral information-handling product such as Mindsystems Amode ... but then again I am clearly biased!

Comment by Loretta Donovan on April 3, 2010 at 1:44pm

Weak signals, as described by Bryan Coffman, was inherent in the "transition management" approach of MG Taylor where I was an associate in the late 90s. While quantitative data analysis may help you to define their source, there is a real time source available to managers. Weak signals are also found in the organizational narrative - meaning the stories of the employees, customers, suppliers and managers themselves. In using Appreciative Inquiry, I ask those stakeholders to recall the unusual successes and circumstances they are experiencing. When the collection of elements are mapped, they coalesce from individual weak signals into more coherent patterns indicating what may be on the horizon.

Comment by Steve Banhegyi on April 3, 2010 at 11:51am

Another area of interest for weak signal detection is Process Psychology - listening to the Liminal people in the organisation..

We run SETI @homesoftware on our server here and they use algorithms to sort through masses of data to see 'if there is anything out there' and I wonder what algorithms might wish to write if one were to detect weak signals in an organisation? This could be problematic because much of the data in an organisation is analog and multi-source and so it has to be integrated with digital information. The questions are: What to measure, how to measure it and how does it have any bearing on what we are interested in?

Comment by Holger Nauheimer on April 3, 2010 at 10:29am

Richard Veryard opened an interesting discussion about the Theory of Weak Signals on his blog Demanding Change. It is basically about how weak signals can actually be detected in an organization.

Here is a couple of interesting background texts:

Filters in the Strategy Formulation Process (by Leena Ilmola and Anna Kotsalo-Mustonen

Weak Signal® Research by Bryan S. Coffman

Weak Signal Analysis by Dale Coffman

What's your suggestion for a strategy which helps to filter out the weak from the strong signals?