Rationale Thoughts now superseded by timvangelder.com

I have recently produced a combination blog/personal website, http://www.timvangelder.com

The blog on that site supersedes Rationale Thoughts.  All the content from Rationale Thoughts has been moved across.

There will be no more entries here, but the blog will remain available for a while.

Subscribers to this blog may wish to move their subscription to timvangelder.com

What is hypothesis mapping?

1. Hypothesis mapping (HM) is diagramming the thinking involved in hypothesis investigation. Roughly speaking, in HM we draw “box and arrows” diagrams linking our main question (e.g., “Who killed JFK?”) with hypotheses, items of evidence, supporting arguments, etc..  See graphic below.
2. Hypothesis investigation (HI) is determining which hypothesis is “most true” (or most likely to be true) in a given situation.  It includes generating adequate hypothesis sets, hypothesis evaluation (assessing relative plausibility of hypotheses given the evidence), and hypothesis testing (determining what evidence to obtain in order to conduct proper evaluation).
3. HM is an aid to diagnostic judgment.  In a simple tripartite classification of judgments, diagnostic judgment is addressing the question “What is going on?” (or “What will be going on?”)  Diagnostic processes attempt to ascertain “how things are” based on available or obtainable evidence.   (More questions which help convey what diagnostic judgement is for: What is happening? What is the problem?  What is the cause? What are they thinking? What is their strategy?)
4. HM makes the thinking involved in HI visual, and is thus able to exploit the massive processing power of our visual systems.
5. HM imposes structure on the thinking involved in HI, by requiring that information be classified and positioned on the map.
6. HM, when done properly, imposes discipline on the HI process.  There are rules or guidelines to be followed; there is expertise to be acquired.  HM can be done badly or it can be done well.  Doing it well requires understanding and observing the rules.
7. Hypothesis mapping, when done competently, promises a number of advantages relative to typical, ad hoc or informal approaches to HI.  Most importantly, it promises to improve one’s “hit rate” in HI, i.e. help you be more right more often in the conclusions you draw about what is going on.  It also aids in making the HI process more efficient and rigorous, sharing the thinking behind HI within a team, and making conclusions more defensible and accountable.
8. HM is a general purpose method.  It can be used in just about any domain – medicine, engineering, science, business, etc. etc.
9. However HM is particularly relevant to intelligence analysis.  HM should be seen as a new addition to the intelligence analyst’s toolkit.
10. As such, HM is an alternative to the well-known Analysis of Competing Hypotheses (ACH) method.  Of course somebody might want to use both methods, HM for some problems and ACH for others, or as two different frameworks for approaching the same problem.
11. HM and ACH have complementary strengths and weaknesses.  Fundamentally, HM is based on hierarchical structure, while ACH is based on matrix or table structure.  Both share the insight that bringing rigor to thinking about hypotheses requires conforming that thinking to explicit external (”outside the mind”) structures.  Any given type of structure will have certain advantages, but also certain costs.  The expert practitioner will be able to use the most appropriate tool for the task, with awareness and depth understanding of the strengths and weaknesses of the tool.
12. Arguably, some of the advantages of HM over ACH – particularly its more intuitive character, and more attractive visualisation – will lead to HM displacing ACH as the default tool for HI in intelligence.
13. HM, when done in a sophisticated fashion, involves the detailed articulation and assessment of arguments, and so draws on argument mapping.  In particular, HM cannot be done with full rigor without proper appreciation of the role of co-premises in argument structures.
14. The best way to do HM is to use software designed to support HM activities.  bCisive 2 is currently the leading software for HM (as well as decision mapping and argument mapping).
15. Austhink Consulting, which has been pioneering hypothesis mapping, provides training, facilitation and consulting services in HM.

Bouquets appreciated

I’ve been engaged (with a great team) in building argument mapping software for over a decade now.  Its been an uphill battle most of the way.  The acid test of success is sales, but there are other measures, such as positive, insightful feedback from users who “get it,” i.e. understand what we’ve done.  Such as the feedback which arrived today:

“I could go on at length about how much I like Rationale.  Where to start.  Where it end.  First of all a big sincere thanks to the designers – developers.  Your product is superlative.  It functions flawlessly, doesn’t crash, no small accomplishment.  The conceptual method of Rationale diagramming is really great.  It is easy and fun to use.  If more readers were aware of the methodology gently introduced in Rationale’s tutorials, they would reach more intelligent conclusions and be more demanding of writers.  I am just starting the final exercise sets in Rationale.  They appear to have a pretty good dose of philosophy, a fair stretch made easy by your excellent tutorials. Rationale is a truly different, truly useful product.”

Future trend: hypothesis mapping displacing ACH

Slides from a presentation at an intelligence & security seminar in Canberra last week.

Thanks to Brett Peppler for getting me the gig.

The three kinds of judgement

[originally posted to BlogCisive]

To a first approximation, all deliberative judgements (i.e., those that turn on to-some-degree careful consideration of the relevant arguments) can be usefully sorted into three kinds.

These are the three Ds of judgement.

1. Decision

Decision is a matter of choosing from among options, particularly where those options are possible actions.  The question here is “What should I (we) do?”

2. Diagnosis

Diagnostic judgements concern what is going on.   The question is “What is happening?” or “What’s the situation?”  The term diagnosis has medical connotations, but here I’m widening its use to include various kinds of investigation, hypothesis testing,  and problem-solving.  All diagnostic judgements involve hypotheses (conjectures) as to what is actually happening.  A good example of diagnostic judgement in this sense is the assessment in intelligence analysis.

3. Deliberation

Deliberation is trying to determine the truth of some proposition by considering the arguments for or against it.  The question is “Is it true?”

Austhink has two products – Rationale, and bCisive.  Rationale, the argument mapping tool, supports deliberation.  bCisive, the business decision mapping tool, has been positioned as supporting decision.  We haven’t had a tool for diagnosis, and have tended to recommend that people wanting to make diagnostic judgements use some variant of the “Analysis of Competing Hypotheses” (ACH) method.

However, just as argument mapping supports deliberation, and business decision mapping supports decision, so “hypothesis mapping,” an alternative to ACH, supports diagnosis.  Further, hypothesis mapping is quite easily handled in bCisive as it stands. 

Austhink is currently working on a “Pro” version of bCisive which will include crucial features needed for supporting both deliberation and diagnosis. 

This means that one tool will help users map the thinking behind all three major kinds of deliberative judgement. 

The tool should be available in a few months.

Mapping Out the Options

[Draft of a piece written for an IT weekly magazine]

“In the affair of so much importance to you, wherein you ask my advice, I cannot for want of sufficient premises, advise you what to determine, but if you please I will tell you how.”

So began some of the best advice on decision making ever given. 

It was 1772, and the great Benjamin Franklin was advising his scientific colleague Joseph Priestley. But his advice is just as relevant today, when critical business and IT decisions must be made under conditions of great uncertainty and time pressure.  

Recently, his insights have been incorporated into software packages which can improve and accelerate organisational decisions, including IT decisions. 

His counsel, briefly, was take a sheet of paper, divide it into two columns, and write down all the advantages of a certain path of action in one column, and disadvantages in the other.  Then, by “cancelling out” items in one column with items in the other, assess which column is the more weighty.

Simple but powerful, Franklin’s “Moral Algebra” has given great service over the decades.  Research has shown that such methods reliably produce better decisions than ordinary unstructured deliberation.  Even Charles Darwin deployed the method, using it in deciding whether to get married.  Balancing considerations such as “terrible waste of time” on one hand with “object to be beloved and played with” on the other, he drew the clear conclusion that marrying was the right option, resulting in a long and happy union and thirteen children.

A method good enough for Franklin and Darwin is not to be dismissed lightly.  But we must also acknowledge that, in its classic form, it can’t do justice to many business decisions.

Most obviously, the Moral Algebra frames the problem as whether to undertake a particular action. But most decisions are not yes/no or go/no-go; rather, they involve choosing from a range of possible actions.  For example in a hiring situation, the decision problem is likely to be not whether to hire Jones but rather which of Jones, Jiminez or Jagonski to hire.  Moreover, the options may form a kind of hierarchy; at one level the decision is whether to hire an accountant or a tax lawyer; at the next level, if an accountant is to be hired, which one?

Another problem is that the method focuses on only one part of the decision problem, which is how to do the overall “weighing up” of the various considerations.  But in business decisions, much of the work goes into determining the validity or strength of those considerations in the first place.  A claimed advantage of hiring a tax lawyer is that she can manage certain difficult issues to do with complex tax structures.  But is this really true? Perhaps the issues are too complex for any one lawyer, and external advice would have to be obtained anyway. 

Recognizing that we need something more than a simple pro/con approach, many textbooks, professors and consultants will prescribe moving to some technical, usually quantitative methodology such as multi-attribute utility theory or decision analysis.  These certainly have their uses, but the reality is that most decision makers do not use these technical methods for the bulk of their decisions, even if they were taught how to use them in business school.  And those decision makers are not just being lazy; often these sorts of complex analytical tools just don’t get a grip on the distinctive texture of business decisions.  Real problems often can’t be reduced to numbers, algorithms and decision rules. 

There is an alternative, one that works better for a wide range of decisions, whether in IT, strategy, or even in one’s personal life. Rather than discarding Franklin’s method, we can extend and adapt it to handle more of the complexities of business decision making.

Business Decision Mapping is such an extension.  It preserves Franklin’s essential insight, that deciding usually involves weighing up of diverse, usually qualitative considerations.  But it elaborates his method to handle multiple options and lower-level arguments and evidence.  But it keeps the complexity under control by laying all this out in a special kind of diagram – a decision map.

Here, briefly, are the most basic steps in decision mapping. (1) First frame the decision problem using an open question.  Not “Should we hire Jones?” but rather “Who should we hire?” – or even better, “What should we do about our tax accounting needs?”

Put the question in a box, preferably with a Question icon so its status is always immediately apparent. 

(2) Canvass the major actions you might take in response to the problem.  Write these down in boxes, connected by arrows to the question.

For each action, write down the most salient pros and cons.  Draw arrows to the relevant option boxes.  (3) Consider the major arguments bearing on the pros and cons.  Add them to the map.  (4) Consider the detailed pieces of evidence supporting the major arguments.  Add them also.

(5) When this has been done as exhaustively and rigorously as circumstances allow, evaluate the evidence, arguments, and the pros and cons.  (6) Choose the most strongly supported options. In making these assessments, you might use Franklin’s “cancelling out” approach. 

Compared with standard informal deliberation (e.g., arguing around the boardroom table), business decision mapping takes some extra effort but offers many advantages. 

First, it improves the clarity and rigour of thinking behind the decision.  With the thinking laid out in front of us, we can more easily survey the full range of considerations and take proper account of them. 

Second, it improves collaboration.  A decision map is an easier way to communicate a complex structure of options, argument and evidence.  With better sharing, team time is spent more productively. 

Third, the decision mapping process automatically results in a concrete record of the thinking behind the decision.  This is useful if – as often happens – the decision needs to be revisited at some later point in time.  It also helps the decision makers be accountable.  Once a decision is made, things might still turn out badly for other reasons; but at least the decision maker can easily show that the decision was well-grounded at the time.

Business decision mapping can be done on paper, whiteboard, or computer screen, using markers or generic software packages.   However, like most things, it can be done better and faster with dedicated tools.   In recent years, dedicated decision mapping software has emerged, making creating, modifying and sharing of decision maps relatively simple and fast.   Decision mapping, supported by such software, deserves a place as a standard part of the toolkit of IT analysts and executives.

Decision at the center

Chandler is an attempt to re-invent the “personal information manager” (think: Outlook).  Dreaming in Code is a fascinating book about the Chandler journey.

The Chandler developers had to think long and hard about the nature of knowledge work.  On their website, on a page called Chandler Project Vision, they describe their Target Users:

They work closely with every member of their team, acting as a communication hub. They know how to ask the right questions to gather input and feedback. They identify problem areas, figure out when meetings need to happen, who needs to be there, what needs to be discussed, and then they facilitate the discussion to define concrete next actions and ultimately drive their team towards informed decisions. They take on the responsibility of defining realistic goals for their team and getting everyone pointed in the same direction to reach those goals.

On this description, Chandler’s target users are very closely related to the target users of bCisive, i.e. “business decision makers.”

Alongside the description of their target users, the page has a graphic:

This graphic of course is a direct play on the 19th century phrenological diagram:

The Chandler graphic both pays homage to, and satirizes, those early attempts to relate mental function to cerebral locations.

As with the phrenological diagrams, the Chandler graphic’s assignment of functions to locations is almost completely fanciful.  However there is one thing that is worth saving in it, albeit in a metaphorical interpretation – the locating of Decide! in the center, almost like the hub around which all other higher mental functions revolve.  (Note also that it is the only activity which gets an exclamation mark!)

Something similar is true of decision in knowledge work – it is the pivotal task.  Every other type of task can be seen as leading up to a decision, or following on from the making of a decision.

This central place is reflected in the structure of organisations – generally speaking, the higher one is in an organisation, the more one’s job is about making important decisions.

[Cross-posted to BlogCisive]

Tools for Thinking – Management Consulting

Draft magazine piece.  Comments welcome.

In the late 1950s, a young engineer by the name of Douglas Engelbart made a decision that was to have a immense effect on all of our lives. Engelbart realised that the massive challenges faced by humanity, such as hunger or nuclear war, would place unprecedented demands on our thinking capacities – indeed, they may be so complex that our finite human brains may be unable to find solutions. With youthful idealism, he wondered how he could fix this problem.

As an engineer, his natural inclination was to build something – in this case, something that could expand our innate thinking capacities, much as a shovel or an excavator can greatly extend our digging capacities. In short, his mission in life became building tools which augment human intelligence. Over the following decades, he and his co-workers developed the key aspects of the personal computer, including innovations such as the mouse, hyper-linking and videoconferencing. Via Apple and Microsoft, these innovations rapidly became a standard part of every office worker’s equipment.

These days it seems hard to imagine how a management consultant could function without spreadsheets, presentation software, email, and so forth, all incorporating the basic functionality developed by Engelbart. These tools obviously help speed up various activities, thereby helping us get more done. An email or an instant message is immensely faster than “snail mail,” so turnaround is quicker and results can be delivered earlier.

However a focus on speed and convenience obscures the most profound change here. A consultant with a spreadsheet can perform analyses that would have been practically impossible fifty years ago. The spreadsheet magnifies the consultant’s effective thinking capacities. The sum of consultant plus spreadsheet is more intelligent than the consultant – or spreadsheet – alone. This is Engelbart’s dream become reality.

Yet, as profound as the changes to date have been, they are probably only the beginning. There is still plenty of scope for human intelligence, in its diverse manifestations, to be further augmented.

This is of great significance for management consulting, since consulting is, more than any other profession or industry, a matter of applied intelligence.

It is a curious fact that the computer aids or “cognitive prosthetics” used by management consultants are for the most part the same as those used by other knowledge workers. Excel and PowerPoint are found on most office computers, not just those of consultants.

To be sure, management consultants have some distinctive conceptual tools; the McKinsey 7S framework, the BCG matrix, and the Minto Pyramid Principle are well known examples. Yet as useful as these may be, they are not realised in hardware in the way a spreadsheet is and so can’t share the cognitive workload in the same way. Bluntly, they don’t “do” anything. We are now, however, starting to see new thinking tools which dovetail well with consulting work, and which may be adopted earlier in the consulting domain than in most others.

One characteristic intellectual skill of the management consultant is hierarchical structuring. Whether it is building logic trees, issue diagrams, pyramid structures, or any other type of “tree,” hierarchical structuring can bring rigour and depth to thinking, and experienced consultants develop facility with this technique. While hierarchical structuring can to some extent be done in the head, when things get complex it helps to lay them out visually – hence the familiar tree structures on whiteboards, with sticky notes, or on-screen using presentation or drawing tools.

But these aids, while handy, have their limitations. Most importantly, diagrams created by these manual methods are not easily modified. Organising information hierarchically is a process. A good hierarchical analysis typically evolves through a number of drafts; observing one attempt suggests a better way it might be done. The more quickly you can reshape the structure, the more quickly your thinking advances. But with whiteboards, sticky notes and generic drawing tools, this reshaping can be slow and frustrating; thinking is interrupted, and thinking has lost “flow.”

New tools designed specifically for hierarchical structuring largely remove these speedbumps. When you can build and modify a visual tree structure almost as fast as you can think, the visual representation becomes like an extension of your own cognitive equipment – a “mind’s eye” that just happens to be outside the head. A consultant using such a tool produces a logic tree better and faster than a similar consultant working on a whiteboard. The net result is that the former consultant is, for practical purposes, smarter.

Another area where new thinking tools can augment consultants’ high-level thinking is in argument construction. Very often a consultant’s primary task is to provide recommendations backed by compelling arguments. Those arguments consist of information organised in evidential or logical relationships. As with hierarchical structures, when it helps to lay arguments out in diagrams when they become complicated.

Back in 1962, in a landmark report, Engelbart described a system in which a user could, on a screen, organise propositions into complex argument structures. To have envisaged such a system well before computers even had monitors, let alone contemporary graphical user interfaces, was a remarkable achievement. Fast forward to this decade, and research teams at universities and software companies around the world are exploring argument visualisation and developing new software applications for this unique task. Just as spreadsheets support calculation, new commercial-grade “argument mapping” applications are supporting argumentation.

In a consulting context, argument mapping applications can be used to construct, refine, evaluate and present the thinking behind a recommendation. The visual display reduces the cognitive load involved in maintaining a complex argument structure in one’s head alone — freeing up mental resources for the more interesting and valuable thinking tasks involved in improving or critiquing an argument.

You can see for easily yourself how powerful this effect can be. Play a game of tic-tac-toe with a friend or colleague. No problem. But then play again, this time without using pen & paper or anything similar. Each player should hold the state of the board in her mind and call out her move in turn. Played the normal way, the game is trivial. Played without visual aids, it is far more laborious and error prone.

Remarkably, consultants usually carry out one of their most central tasks – the development of clear, compelling arguments – either without a “board” at all (i.e., in their heads), or by making do with generic tools such as word processors and presentation software. It is a bit like a carpenter trying to work without a saw.

The main reason for this is that until recently the “saw” for argument construction had not been developed. Going forward, however, we will see consultants increasingly using argument visualisation to augment their inbuilt reasoning abilities. A particular benefit of argument mapping is that, once an argument has been laid out diagrammatically, simple, almost mechanical checks can uncover hidden assumptions which might be critical weaknesses in the case. Extensive research at the University of Melbourne and elsewhere has shown that practise based on argument mapping can dramatically accelerate critical thinking skill gains in university students. This suggests another role for these new thinking tools.

A major challenge for consulting firms is helping new recruits come to “think like a consultant.” There are many aspects to this, but cultivating the two skills already discussed – hierarchical structuring and argument construction – is at the heart of it. Introducing suitably-designed software tools into training can speed up the process whereby new consultants develop understanding and mastery of these skills. The intuitive visual format promotes comprehension, the interactivity supports “hands on” practice, and inbuilt assistance helps provide guidance.

Finally, using these tools can help consultants collaborate on solving tough thinking problems. Traditionally, each consultant on a team holds in her head her own “take” on the evolving state of the group’s thinking about an issue. The trouble is that each take may be somewhat different, leading to confusion, error and wasted time. A better way is to have the thinking shared in a visual display, on a screen or projected onto a wall, with every contribution immediately and transparently incorporated into the common understanding. Such software can make this happen.

Management consulting has long had a reputation for snapping up the best and the brightest. The raw human intelligence of these young minds is greatly magnified as they come to master consulting’s “tools of the trade”. Despite the kind of inertial and conservative tendencies found in any profession, this toolkit does evolve over time. The latest additions are increasingly aiding consultants in some of the most distinctive of their intellectual tasks.

Everyweek decisions

In a nutshell: describes the distinctive character of decisions managers or executives must make on a weekly basis.

It is a curious fact about the English language that the second most common word (”of”) occurs about half as often as the most common word (”the”); the third most common word occurs 1/3 as often as the most common word; and this pattern holds pretty well for the first 1000 words or more.

This pattern, known as Zipf’s Law, or more generally a power law distribution, occurs for a suprisingly diverse range of phenomena, from cities (the bigger they get, the fewer there are of that size) to earthquakes to price variations.

I don’t know of any any measurements to verify this, but it seems plausible that such a pattern would hold for business decisions as well. These decisions can be rated in terms of their level of significance, ranging from the trivial or everyday (Where should we go for lunch? Use “Yours sincerely” or “Cheers”?) to the truly momentous (Should we pay bribes to Saddam Hussein to sell more wheat?). In a given period, the typical manager or executive would make a great many everyday decisions, very few momentous ones, and a generous handful of “mid-sized” decisions.

Making everyday decisions would generally take only moments or at most minutes; momentous decisions might take months or years. Somewhere in between are decisions that the typical decision maker would make regularly but not everyday; she might make a few a week, and each would be thought about over a period of days or weeks. We might call these “everyweek” decisions (as opposed to everyday decisions).

Examples might be:

• Who should we hire for this job? (Should we fire Jones?)
• Should we revamp the current website, commission a new one – or what?
• Should we pay for a booth at the XX tradeshow?
• What legal structure should our US subsidiary have?

Everyweek decision problems tend to have the following properties:

• They involve considering a number of options, and “weighing up” the considerations bearing on these options.
• The weighing-up is done intuitively, i.e., without using any strict rule or calculation.
• Each option has various pros and cons.
• The pros and cons are heterogeneous, i.e., very different in nature.
• The pros and cons are generally qualitative; it is impracticable or even nonsensical to put numbers on them.
• The pros and cons may need to be backed up by evidence.
• Indeed, the pros and cons are often disputable; we may need to consider the arguments for or against them, and the debate may get quite complex.
• Generally not all the options, or pros and cons, are immediately apparent; it will take effort to “uncover” or generate them.
• Everyweek decision problems are made under time pressure.
• The time pressure rules out doing lots of research or investigation; we have to “make do” what what knowledge or beliefs we have already, or can access quickly and easily
• Everyweek decisions are collaborative, i.e., there are multiple people involved in thinking through the decision.
• These people may be remote, i.e. far away and in a different time zone
• The decision maker is “accountable” for the decision.
• In particular, the decision maker may have to justify the decision, i.e., explain the thinking behind it

It seems that the great majority of the non-trivial decisions the typical business decision maker has to make are “everyweek” in scale and nature.

I’m hoping, in subsequent posts, to discuss a number of issues related to everyweek decisions, such as:

1. How everyweek decisions are generally made;
2. What problems or “pain points” there are in everyweek decision making;
3. The lack of good tools to support everyweek decision making
4. The direction we (Austhink) are taking in addressing these issues.

Asbestos and Extinctions

Over the Xmas break various family members were engaging in an interesting conversation whose starting point was the way many people are excessively, indeed sometimes hysterically concerned about the dangers of asbestos fibres from nearby demolitions or renovations.

The background theme was how poorly people understand risks, especially small risks, and how they misplace their anxieties about risks.

I suggested that the emotional energy people put into obsessing about floating asbestos fibres would be better invested doing something about much larger dangers such as, say… global warming.

To put things in a bit of perspective, consider:

“This end-Permian extinction is beginning to look a whole lot like the world we live in right now,” Payne said. The end-Permian extinction (mentioned in an example in the previous post on this blog) was a catastrophe 250M years ago when the great majority of land and marine species were eliminated.

Payne is “assistant professor of geological and environmental sciences at Stanford University… a paleobiologist who joined the Stanford faculty in 2005, studies the Permian-Triassic extinction and the following 4 million years of instability in the global carbon cycle.”

Payne says: “The good news, if there is good news, is that we have not yet released as much carbon into the atmosphere as would be hypothesized for the end-Permian extinction. Whether or not we get there depends largely on future policy decisions and what happens over the next couple of centuries.”

See The Day the Seas Died: What Can the Greatest of All Extinction Events Teach Us About Climate Change?