Why we need Donald Trump in Australia

Trump is the kind of President Australia needs

That headline was an example of ‘click bait.

It has little or nothing to do with the actual topic under discussion, but it something the writer knows will get clicks. (In this case, absolutely nothing.)

After you have clicked on the click bait, you are bound to be annoyed. But, I don’t care because your eyeballs have been captured.

Do you know how Facebook et al measures ‘engagement’ with its advertising product?

The technical term is ‘more than zero’. That is anything more than zero pixels, for more than zero milliseconds. That counts as a view.

And advertisers are charged for those views.

Back in bricks-and-mortar land, we have the same thing.

A really cool ‘brand’. Or a stunning fit-out. Funky music. Posters in the window that make grand lifestyle promises.

The problem starts when people ‘click’ and enter the store - and everything sucks from that point in. No service. Poor assortment. Meaningless pricing. Dodgy product quality. The stuff that really matters is missing and the customer leaves with a sour taste in the mouth.

It is in instances like these that good marketing works against you. You will catch the customer once, maybe twice. But unless you can fulfill the promises with an authentic offer that actually matches the brand, it will become increasingly harder and harder to capture the customer.

Even if you change and fix all of that; it is a matter of twice bitten, once shy.

One of the retail businesses that I admire most in Australia is Lowes Menswear. They have survived and prospered for more than a century - and at the core of that success is perfect congruence between brand promise and execution. They have resisted ‘image drift’ and just kept on executing those fundamentals straight out of the Retail 101 handbook.

In technology we talk about a WYSIWYG program. In the ‘real’ world, What You See Is What You Get should also apply because that is how you earn (and keep) consumer trust.

And trust is the currency of any successful business.

Check out our new initiative: WWW.YEARONE.SOLUTIONS

The BOT revolution for retail

No way I will talk to a machine, or is there?

At least that is what I told Siri.

And she just laughed.

Because she knows stuff.


Reason 1: Look at the numbers.

Reason No 2: The Big 3 are playing in this space and that should tell you something. 

●     Facebook: Messenger & WhatsApp

●     Amazon: Alexa

●     Google: Allo

That is not to mention applications like Slack and dozens of others who have their own bot-solution. I was personally confused with Facebook’s strategy to buy WhatsApp for such an exorbitant price, particularly when they already own Messenger. As bots have gained in popularity, it is beginning to make more sense.

Reason No 3: The learning curve with Chatbots is flat (few barriers).

You don’t even need an App for that, because there are services like Magic that does not even require an App Platform, and whilstOperator is an App, it is completely agnostic about what you want and simply gets onwith the job of getting it. Like a global concierge that you just ask and it happens. (US and China only, more countries to follow.)

The buzz words are chatbots and conversational commerce, and it is worth thinking about the trends to understand if and why they are important.


Chatbots are applications that respond intelligently to user input. It is a simple process to install the application on your own website, your own app or run within an existing messaging platform.

The chatbot maker can choose to build conversations that are programmatic and structured. That is, you build a conversation tree that reflects conversational options. As you can imagine it is difficult to anticipate every possible variation, it is important to build a sensible fall back option.

Or you can choose to use Natural Language Programming (NLP). It is vastly more complicated and you will need a developer for this. This can also evolve into the real AI (Artificial Intelligence) or ML (Machine Learning). These bots get smarter over time. Think how SIRI gets to recognise different accents of the same words.

Chatbots have many uses - from dating to gambling to news, but in the retail environment two broad types of activities; SALES and SERVICE. We are looking at Chatbots as a means of delivering Micro Learning. Imagine the CEO could ‘talk’ to all staff across a country-wide network of stores, get feedback and pass on tips and focus for the day – all with no ongoing cost after setup?

From a retail perspective, it is called ‘conversational commerce’ because a series of SMS-like conversations easily (and very securely) can terminate in a ONE-CLICK purchase. (No doubt Facebook will want to clip this particular ticket in some way in the future, so bear that in mind.)

The other application is to create stock response for your FAQs on your FB page or on your website. (The ChatBot can be installed in your website with an easy copy & paste). Customers can ask questions, the bot reads and responds accordingly. No human intervention - and that is the big cost saving.

One of the more sophisticated examples of such a BOT is one called KIT. It is now owned by Shopify, and it is deployed to ‘take instructions’ from Shopify store owners and then ‘creates’ social media campaigns (like Facebook Ads) - all automated. It costs the store owner $10 per month, and you don’t have to think too hard about creating and scheduling Facebook Ads.


No 1:

Everybody has Facebook/Messenger etc - it’s ubiquitous, so you as the retailer/business entity don’t have to persuade the user/consumer to download yet another app.

No 2:

You get more data from the user (via the associated platform like Facebook) than you would have ordinarily from a one-way medium like email. This enables better targeting and more relevance of your communications.

No 3:

High open rates and engagements.

No 4:

Inexpensive to run (no data charges or costs like SMS etc), although right now most of the early Gold Rush providers will persuade businesses to fork out hundreds of thousands when it should be thousands or maybe tens of thousands to set up bots.

No 5:

Most importantly, Chatbots enable two-way conversation and are immediate and therefore more relevant (than an email newsletter peddling week-old news.)


No 1:

They are really easy to build. You can YouTube it, pay $20 on Udemy or simply DIY because the technology enables you to get basic BOT simply by dragging and dropping elements on a screen.

I can’t do any coding, not even HTML, and I built a bot in a weekend. (Try it out at our Facebook page.) In my explanation that follows I will refer Facebook and Messenger as an example because they are commonly used, but most applies to all messaging apps.

Because it is so easy, expect bot-pollution to occur rapidly. Because of the pollution, consumers will be swamped and it will lose its efficacy very quickly; particularly for the inefficient or irrelevant bots.

Just like email marketing is crumbling under the onslaught of spam and waste, so too will chatbots.  Email click-through rates are now commonly around 2%. Messages can be over 80%. (When was the last time you ignored a message on Messenger or WhatsApp or even SMS?)

But it is even easier to block a bot than it is to unsubscribe.

No 2:

With email marketing, at least you owned an asset - an email address with permission to use it. That meant you could go to any email platform, depending on your needs. I am sure everybody has now left Aweber, and are exploring MailChimp and Active Campaign and the like.

With message bots, you have access to a much richer data sets since you receive profile-related info from Facebook. But you can’t leave the platform (Facebook/Messenger), so you never own that data.

You are also dependent on the platform to make the rules, and what is free today will not be free tomorrow if it has any value.


No 1:

Planning the actual Bot. Having now built a few myself, I cannot stress the importance of planning enough. It is tempting and easy to just start building with a vague idea.

No 2:

Adopting a Chatbot strategy. It is very important that you take an eco-system approach. You should think about ALL the bots that you might want to run, and then decide which platforms you will be using, and how you will be using them.

CRITICALLY - you must create a digital asset library and keep a record of the bots and the assets (images, links etc.) that they use. You will have to make changes in the future, and if that means you have to practically re-write the bot, you will spend all the money you thought you were going to save. And part of the eco-system will be a digital product roadmap that will (a) keep you on course and (b) help to manage system when people churn and when the technology changes.


As with any new technology, there will be different types of people to be on the lookout for:

●     The Zealots who believe this is the latest must-have.

●     The Cowboys who will be rushing in with a bravado that is not backed by knowledge and experience.

●     The Hustlers who will be out to make a buck as quickly as possible while there is a premium to be paid for people (who claim to have) the right experience.

●     The Gurus who will be proclaiming words of wisdom from the highest blog mountain.

Right now, there are very few people who know everything. You will find UX experience in marketing agencies, you will find the technical nous typically amongst the technical development community. And you will find the sales-and service experience in the retail community.

Few have all of these requirements in sufficient quantities to be able to guarantee that all efforts will be succeed.



At the bottom of this page there are two videos that explains the notion of ‘fractured value’. That provides the background to why it is so critical for survival and growth to be able pivot, adapt and innovate.


●     Some of the brands doing interesting stuff with bots.

●     A directory of bots that will prompt you to think widely about the applications

●     A slightly different, non-commercial use of Bots we developed


Drag-and Drop Design Platforms

●     MotionAI

●     ManyChat

●     Chatfuel

●     API.ai (A bit more complex for NLP)


Storyboarding and Planning Tools

●     Twinery

●     yEd

●     LucidChart or Draw.io (Apps that integrate with Google Drive, and is connected directly)

●     List of 17 Free Drawing Software applications


Long-timers who may recall some previous writing here on Inside Retailing, may remember that it has been a bit of a Mantra that the required response to the Next Big Thing is NOT to merely jump on the bandwagon.
We suggest you jump on the bandwagon(s) because that is how you build and retain the capability to adapt and change.

In fact, the key to success is not whether you are backing the right technology horse, it is your whether you have the capacity and ability to turn on a dime - to mix some metaphors for you.

You become agile by being agile.

I asked SIRI, and she agrees with me.

Dennis Price: Founder at Ganador: Retail Advisory with a focus on the customer.

When your plane doesn't want to fly

During WWII, 12,000 heavy bombers were shot down and two out three Allied bomber crews were lost for each plane destroyed.

Ultimately over 100,000 Allied bomber crewmen were killed over Europe.

Losing your best, most expensive resources (people and machines) is never a good strategy, so the problem was quite urgent.

The planes needed more or better armour.

The Air force gathered some data on the problem.

IImage from How Not To Be Wrong by Jordan Ellenberg

IImage from How Not To Be Wrong by Jordan Ellenberg

They saw an opportunity for efficiency by achieving the same protection with less armour.

If you concentrate the armour on the places with the greatest need (most holes per square foot), the planes would be safer and lighter and therefore quicker.

A man named Abraham Wald, a mathematician, oversaw the project. He started by creating a simple diagram—the outline of a plane—and he marked bullet holes corresponding to where each returning bomber had been shot showing the most common areas of damage to the plane. The wings, nose, and tail were found to be the spots that needed more armor, but the challenge was that armour was (is) heavy and made the planes even more vulnerable by slowing them down.




But Wald flipped conventional logic with some impressive statistical research. If he was alive today, he’d probably be calling this Big Data.

His insight?

The Air Force didn’t need to reinforce the spots that had bullet holes. They needed to reinforce the spots that didn’t have bullet holes.

Can you see the logic of his conclusion?

The planes that had been shot in these bullet-free zones never made it home to be accounted for.

A plane shot through the wing featured on his diagram. A plane shot through the cockpit (the white area on the diagram) didn’t feature on the diagram because the plane was burning in field somewhere in enemy territory.

[Aside: A question for consultant peers: How long would the report have been giving what is essentially one line of advice?]

Some lessons:

Forest and trees and all that.

But there is more.

The people flying the planes are not always in the best position to see the answer.
A small diagram is as useful as big data.
Don’t underestimate the power of a visual representation of the problem.
There is no substitute for smart people.

Flip your thinking, it may just be all that is needed.

The source of the solution may not be the most obvious person.

The problem is not always obvious until it is obvious. Then it is obvious, of course; because well, it is obvious.

Do you have planes that don’t fly?

Sometimes business obsesses about getting more planes in the air, or worrying about getting the planes to fly faster and more efficiently.

The real problem is that it shouldn’t even be be planes. Or it may not be about getting there faster, but more about where are you flying to.

Asking the right question is really half the battle won.

Are you a leaders who is afraid of the dark?



On May 24, 1924 a Massachusetts newspaper printed an instance with a Boston setting. A police officer saw a man on his hands and knees “groping about” around midnight and asked him about his unusual behavior: 1

“I lost a $2 bill down on Atlantic avenue,” said the man.

“What’s that?” asked the puzzled officer. “You lost a $2 bill on Atlantic avenue? Then why are you hunting around here in Copley square?”

“Because,” said the man as he turned away and continued his hunt on his hands and knees, “the light’s better up here.”

Abraham H. Maslow referenced the joke by applying it to his own profession. In “Motivation and Personality”, he wrote:

Ultimately this must remind us of the famous drunk who looked for his wallet, not where he had lost it, but under the street lamp, “because the light is better there,” or of the doctor who gave all his patients fits because that was the only sickness he knew how to cure.

It applies to us even today, since this seems to be a human problem that all leaders struggle with. In fact, it even has a name: the streetlight effect. (Or as it is fondly know, the ‘drunkard’s search’).

This observational bias is so pervasive, we may even twist it into positives:

‘Play to your strengths’.

The problem is that your strengths may not be what the company needs or the problem requires.

‘Fish where the fish are’.

The problem is that everybody fishes where the fish are - the ‘red ocean’ scenario.

The starting point for a successful leader and manager must normally be to ask what the desired (right/best) outcome is; then create solutions and strategies that matches that.

It may seem an archaic notion, but leadership requires bravery. Leadership requires you to step outside your comfort zone. Not to focus on the low-hanging fruit, but to pick the fruit that actually needs to be picked.

Go from the easy, to the whatever is required, even if it is hard.

Go from the light to the dark, if that is where the problem is.

Don’t be afraid.

When you have a rat on board

Image: http://www.pestworld.org/

Image: http://www.pestworld.org/

A story is told about a British pilot who was terrified when he looked down, to discover a rat chewing on the fuel line.

He was going to have to land his plane as soon as possible but he was calculated that he did not have sufficient time to do so before irreparable damage was done to the aircraft.

What he did next was counter-intuitive and non-obvious.

Instead of attempting the landing, he flew the plane even higher. The decrease in oxygen was enough to kill the rat.

When you are faced with dire circumstances, you  could simply hope for the best.

You could waggle your wings and try to shake things off.

You could bet against the odds and attempt to land safely.

Or you could double-down. Go harder, go higher.

Guy Kawasaki says Silicon Valley’s successes are more a matter of people throwing things at a wall and painting a target around what sticks.

That is true for most successes. But that is not a story of luck or synchronicity, it is a story of people failing at a hundred things, persisting.

When things look grim, they double down and go harder. Instead of landing, they fly higher. Of course, many, many, many sink without trace.

But the ones that make it, are characterised by persistence that eventually finds that a solution.

Persistence required bravery.

How brave are we?

The New Marketing

Which is a little bit ironic, because when you look at it closely, it is actually very old.

So old, that I have called it ARTISANAL MARKETING

What does that look like?

I created this graphic in 2012. Not bad, hey?

I am just putting the finishing touches to a presentation for a conference. And I address something that is variously called 'dark value' or 'fractured value'. It is used to explain the successes that companies like Uber and Netflix has experienced in recent times.

I have created a little video to accompany the talk, because this concept couldn't be addressed properly in the time allocated. I will post that later.

How to innovate by learning from the customer

There are essentially two ways to look at innovation:

1: Play, search and discover something. Test to see if it is useful for the market.

2. Learn from the customer, and adapt your offer in a constant, incremental cycle.

We are a fan of approach no 2. There are merits in both, but we feel No 2 is:

  • More sustaiable
  • Can be 'baked in' to the way you do busines
  • Has immediate benefits.

So we came up with the 10 rules of constant innovation.

NOTE: The image is only somewhat original - it has been adapted from somethign I have seen somewhere, but now long forgotten. Happy to correct attribution if it is claimed.

A framework for thinking about problems - Part 5


If you followed this framework, you would identify OR eliminate different types of problems. In the example used earlier with the machinery breaking down, you would apply it as follows:
Your sound asset management strategies may have kept (ageing) equipment in good nick = potential problem eliminated.

Your people may be very skilled at planned preventative maintenance = potential problem eliminated.

You may have sufficient staff, and they are appropriately organised (right people, covering all the shifts, doing all the right work)
And so on...

Following the framework, you may eventually discover that you don’t have the system in place to monitor the performance (say heat loads) to warn you when something needs replacing or fixing or whether the usages should be changed. 

The problem may well (simply) be the age of the machinery, but unless you have explored ALL the elements (strategy, systems, skills etc) of the problem, you can’t identify the real issue and you can’t solve the problem.

It is invaluable to have a tool/framework to think about and to help solve problems. Besides the obvious productivity benefits of solving the right problems quickly and efficiently, it has a very positive impact on the culture of the business as a good, methodical approach to solving problems based on logic. There are no ‘blame games’ to play, and no one needs to worry about defending the indefensible.

And it may just expose the people (which everybody knows) who have been gaming the system for years, and that is not a bad thing either - a rather positive unintended consequence.
Takeaways for the real world
I don’t expect anyone would ever whip out the little diagram in the middle of the next meeting and use it as a cheat sheet to solve a problem. (I don’t, so not sure you should.)

But what you can attempt to remember is:
Be critical in your considerations to understand whether a ‘problem’ being presented is actually merely a symptom.
Think carefully about whether the nature of that problem is a resource-type, a context-type or an opportunity type of problem. 
Dig deeper into the nature of the problem: Ask yourself what type of resource, what type of opportunity etc.(It will be a bonus if you can remember the 4Ms, PESTLE and Product:Market fit.)
The root cause is likely to be one of the 6S’s. (If you forget what they are, just Google Peters & Waterman, In Search of Excellence.)
Figure out how to address the root cause.

Back to the Clever Engineer
Remember our opening story where the engineer solved the production line issue with a simple fan?

I disagree with the premise of the story.

Sure the engineer came up with a ‘smart’ resolution. However, the problem as I see it, is that they still have a problem (possibly many, including semi-daft CEO) not the least of which being that they still have a production line that does not fill every tube. Whether the Band Aid cost $20 for a fan or $8m for fancy scales, it is STILL a band-aid.

I tried to explain in this article how, by having a clear typology of problems, one can successfully and comprehensively diagnose the issues in such a way that the remedy is self-evident. 

NOTE: This is the final part (5) in the series. Visit our blog and find the rest of the series which will be published on consecutive days. 

Alternatively you can download the whitepaper in a single PDF. 

A framework for thinking about problems - Part 4

Problems vs Symptoms

This is a mistake many people make, and they make it all the time, so let’s revisit the example above.

Equipment constantly breaking may have been identified as the problem. A typical response to this ‘problem’ would be to replace the equipment; only to find that pretty soon the new equipment keeps breaking down.With only a little thought, once should realise that breaking equipment is not the problem, but rather a symptom, and that we need an actual cause. 

This is where this typology comes into its own.

Using this framework will:
Help you frame the real problem (not the symptom)
Help you approach the solution from a holistic perspective
Help organise the response in a way that ensures you have effective alignment bakes into your solution

Example 1

Let’s say the business has identified that the source (or area) it has a problem in, is MACHINE -  i.e. technology/ Infrastructure to conduct business. This can be refined with more detail. You may identify the issues for instance as specifically being a particular piece of IT infrastructure, or even more specifically the Intranet or you can have an issue with ageing plant & equipment in the factory.

(Note: The 7th element, shared values or culture, being the result of the interplay of the other 6 elements, is usually symptomatic of a problem rather than the actual problem.)

Considering your technology/ machine problem above - and let’s assume it is Plant & Equipment in your factory. I will only ask one leading question per element for the sake of example. In the real world, you will ask many more.

You have six avenues to explore the problem, and example questions are:

  • Is your STRATEGY in terms of asset management effective?
  • Is the organisation and all its resources organised (STRUCTURED) in such a way that the management of these assets are appropriate?
  • Are the SYSTEMS in place to monitor the uses of the plant?
  • Do we have the right people (STAFF) in place manage the equipment?
  • Do they have the right SKILLS to do their jobs?
  • Are we effectively leading them (STYLE) with the right levels of motivation and empowerment to achieve the results.

When you start digging into the problems from these six perspectives, you may find that one issue is the dominant one. For instance, you just don’t have the right monitoring systems, and that is why the machines always break down. The staff, their skills the leadership etc. may all be in good shape, and you can then focus on fixing the problem.

And even if you can’t identify a simple problem, you will get greater clarity on the nature and the dynamics of complex problems.

Example 2

Let’s say an organisation has poor sales.

That is NOT a problem, it is a symptom. To identify the problem, you may want to use this framework to identify/eliminate possible problems.

You will first identify the CATEGORY of problem (resource problem, opportunity problem or context problem.) Each of these categories of problem have common elements to how they are solved. 

Each category of problem can be further subdivided into sub-categories. Your resources problem could be related to capital or could be related to technology etc. (The further categorisation again facilitates better understanding and greater specificity, and allows you to see complex problems as mentioned earlier.)

You do this through your forensic questioning:
Is this a problem because of my <Insert category here>.

With due consideration, you will identify those categories and subcategories that impact your sales figures.

Assume you have identified the primary problem as relating to your product-market fit, and specifically that it relates to the ‘market’. 

As above, you do this through your forensic questioning:
Is this a problem because of my <Insert element here>.

This is to assess whether it relates to your strategy in selection (designing your business model), a poor organisational structure (no one is accountable) or whether it is lack of skills in segmenting the markets incorrectly etc.

Once you have identified that it is (e.g.) because your marketing team is insufficiently skilled in applying market segmentation tools, you know the problem to fix. (And you can stop flogging your sales reps and you can stop handing out sales incentives.)

NOTE: This is part 3 in the series. Visit our blog and find the rest of the series which will be published on consecutive days. 

Alternatively you can download the whitepaper in a single PDF. 

A frameworks for thinking about problems - Part 3

Basic Premise 

You can only solve a problem if you identify the right problem.

The above will make more sense once I describe it and you have studied the accompanying graphic. 

There are three CATEGORIES of problems, each of which can be subdivided into a subset of problems. After that you can continue to subdivide a problem to an ever-increasingly granular level. Each of those subsequent layers of ‘problem’ you encounter, can be further classified as TYPES of problems, which then provides the insight to SOLVE the problem.

In order to figure out what types of business problems there are, we first need to have a definition of what a business actually is. At the very highest/moist generic level, a business can be defined as:

A collection of resources that are applied to an opportunity in a particular environment. 

That definition reveals the starting point for identifying what can go wrong, and provides the major categories of problems. Once you have identified the major category of problem (sources), you run the problem across the 6 S’s on the Y-axis of the framework. In this way you have 6 potential nodes for every ‘problem’. 


Economics 101 tells us that there are four types of resources: Human resources (man) as well as the (raw) materials, the technology (machine) and finally capital. Or: man - machine - materials - money. The 4 Ms.

It makes sense that things can go wrong on any of those fronts and that they would generally be different problems. 

Problems at this level is typically easier to identify, except when the problem is the ‘man’ - or the humans in the system. Resources can have many different problems relating to quality, performance, complexity, availability, cost and so forth.

In the case of ‘human resources’, we have additionally have a subjectivity issue. The people are not only a resource for the system, they are the resources that build the system and create and/or solve most other problems in the system. Consequently, ‘people’ is a big part of every problem and every solution.


This category of problem relates to the Business Model. That is, your product/offer is a response to a market opportunity. In startup terms, we talk product-market fit. Without that you cannot have a viable business.

I mentioned that problems can be made even more granular. I have refrained from including that in the graphic, but if you choose to, it will result in an ever-increasing cascade. Allow me to explain how problems with your product can be further refined to be made more specific.

‘Product’ problems could relate to things like Quality, Design or Price. ‘Market’ problems could relate to Access or Communication. And that can refined even further. For instance, ‘access’ could relate to timing, or to channels. Communication can be refined to identify whether it is about awareness or frequency or content.

When looking at these product:market fit problems, we would rely on the elements of excellence to identify whether the problem is primarily related to our strategy or skills or our organisation or whatever other element that may be applicable. (A more detailed example follows below.)


These problems are harder to solve since they are driven by EXTERNAL factors. Examples are when a dictator chooses to nationalise an industry or your exchange rate collapses or (more likely) when a competitor disrupts the industry. The only thing that you could have done proactively about these types of problems was to plan for the risk/likelihood of it happening.

We are all familiar with the P.E.S.T.L.E. variables that we encounter when conducting strategic planning; and when it comes to the perspective of being ‘business problem’, the only real problem is that the business failed to anticipate the problem. 

In order to reduce visual clutter, the matrix does not graphically extend to each variable. Each variable is uncontrollable (external is by definition uncontrollable), so the problem is quite simple to identify and is the same basic problem, even if ‘fixing’ it or preventing it a lot easier said than done.

NOTE: This is part 3 in the series. Visit our blog and find the rest of the series which will be published on consecutive days. 

Alternatively you can download the whitepaper in a single PDF. 

A framework for thinking about problems - Part 2

Theory vs Practice

As I outline this approach, you may perceive that it somewhat ‘theoretical’, academic even. That may have something to do with how I write, rather than what I am actually writing. I get that a lot. 

“It sounds complicated.” “It sounds very smart, but…” Some people tell me outright they have “no idea what I am talking about” when I go off on something. So a short note in self-defense:

People have the wrong view about what constitutes academic/theoretical; especially when it comes to the social sciences like management/business. Academics and researchers who study business and write books about it are NOT the thought leaders. They are NOT the pioneers who formulate new ways of doing things.

Academics and Researchers LAG the practitioners. The so-called thought-leaders of Marketing are now writing about Uber and Netflix and how particular strategies explain their successes. And how other businesses should follow the framework or the recipe or the mode.

The fact is, the entrepreneurs and the leaders at these organisations had figured out how to do things (trial and error OR by design, that does not matter) and they are the real thought leaders. Researchers merely describe what is already happening. (It is called RE-search.)

The Academic or Researcher is simply looking at things with a broader lens, seeing other patterns and gaining other insights and helping to connect dots to put things in a framework that allows others to see in a few minutes or hours what has taken a long time to discover, clarify and document.

I am not an academic or a researcher, but I see the patterns and connect the dots. I know the actual frameworks or models are no reality, but they are representations of reality.  By using the frameworks to systematically look at the knowledge it seeks to convey, they become tools that practitioners can use to manage more effectively.

Management THEORY is merely the description of existing PRACTICES. It is unhelpful to dismiss ‘theory’ as something that is disconnected with day-to-day management.
The System of Excellence Framework
The six variables (6 S’s) on the Y-axis of the matrix is the framework identified by Peters and Waterman in the mid 80s. Whilst they used the 7S’s to explain ‘excellence’, I think it simply explains the organisation. I have come to see the 6 S’s as the DNA of the organisation. The 7th S is ‘Shared Values’ or Culture, which is the dynamic interaction of the six core elements. 

For example, if you have a ‘money’ issue (i.e. insufficient cash) you would want to identify the specific element (one of the 6 S’s) that will help identify and articulate the nature of the problem. Does it relate to the strategic management of funds (making the wrong hedging decisions) or is it because the system does not tell us in good time we will run short of funds or whatever. BY cross-referencing the origin (source) with the element, you will be able to accurately label the problem. (At which stage you will apply root cause analysis to identify primary and secondary causes.)

Don’t worry, it will become clearer as I explain.

Complex vs Simple Problems

The nature of the beast is such that all problems and all elements are somewhat inter-connected, so invariably one problem is linked to another via cause or effect. This creates complex problems. When a problem is isolated and relatively independent, it would be a simple problem.

In this article problems are treated as ‘simple’ problems, for the sake of easy identification, recognising that many are actually part of a complex problem. In the real world of problems and opportunities, you will find that several of the ‘nodes’ in the diagram above will cluster together and will need to be unravelled.

In fact, all problems are complex problems, but treating them as simple problems is pragmatic because one has to start somewhere.


NOTE: This is part 2 in the series. Visit our blog and find the rest of the series which will be published on consecutive days. 

Alternatively you can download the whitepaper in a single PDF. 

A framework for thinking about problems - Part 1

A story about problems

Have you heard the story about the clever engineer?

A toothpaste factory had a problem: Due to the way the production line was set up, sometimes empty boxes were shipped without the tube inside. People with experience in designing production lines will tell you how difficult it is to have everything happen with timings so precise that every single unit coming off of it is perfect 100% of the time. Small variations in the environment (which cannot be controlled in a cost-effective fashion) mean quality assurance checks must be smartly distributed across the production line so that customers all the way down to the supermarket won’t get frustrated and purchase another product instead. 

Understanding how important that was, the CEO of the toothpaste factory gathered the top people in the company together. Since their own engineering department was already stretched too thin, they decided to hire an external engineering company to solve their empty boxes problem. 

The project followed the usual process: budget and project sponsor allocated, RFP (request for proposal), third-parties selected, and six months (and $8 million) later a fantastic solution was delivered — on time, on budget, high quality and everyone in the project had a great time. The problem was solved by using high-tech precision scales that would sound a bell and flash lights whenever a toothpaste box would weigh less than it should. The line would stop, and someone had to walk over and yank the defective box off the line, then press another button to re-start the line. 

A short time later, the CEO decided to have a look at the ROI (return on investment) of the project: amazing results! No empty boxes ever shipped out of the factory after the scales were put in place. There were very few customer complaints, and they were gaining market share. “That was some money well spent!” he said, before looking closely at the other statistics in the report.  

The number of defects picked up by the scales was 0 after three weeks of production use. How could that be? It should have been picking up at least a dozen a day, so maybe there was something wrong with the report. He filed a bug against it, and after some investigation, the engineers indicated the statistics were indeed correct. The scales were NOT picking up any defects, because all boxes that got to that point in the conveyor belt were good. 

Perplexed, the CEO traveled down to the factory and walked up to the part of the line where the precision scales were installed. A few feet before the scale, a $20 desk fan was blowing any empty boxes off the belt and into a bin. Puzzled, the CEO turned to one of the workers who stated, “Oh, that…One of the guys put it there ’cause he was tired of walking over every time the bell rang!”

The moral of this story is in the final line, where the author asks:

$8 million vs $20    Hmmm! Money well spent?

Is this the right outcome?

I will answer this at the end of the series.

I am going to try to explain in this article how, by having a clear typology of problems, one can successfully and comprehensively diagnose the issues in such a way that the remedy is self-evident. If we can achieve that, I am sure you will agree that it will be a worthwhile tool.

NOTE: This is part 1 in the series. Visit our blog and find the rest of the series which will be published on consecutive days. 

Alternatively you can download the whitepaper (PDF) here

Click on the image and find the PDF cover as above

Click on the image and find the PDF cover as above

Most really dangerous lies are at least partially true, and so is this one

I was told that the time to get out a hot stock in the market is when the cabbies starting offering that stock as an investment tip. No offense to cabbies intended but you know what I mean.

One of the popular topics on the blogosphere is Neuroscience. We introduced the principle of Neuroscience into our training programs in 2009, before the ‘cabbies’ started talking about it. There are valuable insights that can make a real difference to the learnings. (Given my formal, academic credentials, I feel justified in claiming some ability to know and understand the applicability of the research, and the shortcomings - unlike most pundits who read Cialdini and not much else.)

Then it became a bandwagon.

In 2013, I wrote a post Neuroscience is not everything it's cracked up to be. And in the same year, another one where I continued the theme, trying to debunk some myths. I pointed out for instance that the adherence to those ‘neuroscientific’ findings amounted to little more than pseudoscience.

For instance, most people would believe most (if not all) of these.

  • The “left-brain” is rational, the “right-brain” is creative
  • Dopamine is a pleasure chemical
  • Low serotonin causes depression
  • Video games, TV violence, porn or any other social spectre of the moment “rewires the brain”.
  • We have no control over our brain but we can control our mind.

I don’t want to get in an argument, with you, but it turns out that: NONE of those are true.

Raymond Tallis (scientist and philosopher) describes society’s current fetish as a ‘neuromania’ and worse, the ‘Darwininization of our understanding of humanity.’ we have all seen the brain pictures with the yellow and red blotches that are supposed to be so insightful. But consider the reality for a moment: neuronal activity lasts milliseconds. Blood flow, which is what the brain scans actually measure, lags between 2 and 10 seconds. Tallis also points out that event the simplest experiments have such low reproducibility that all conclusions initially drawn could be voided.

Science has a long history of constantly disproving itself. In fact, I find it peculiar how people can so much faith in science, when virtually everything that we take as scientific gospel today is the opposite of what we believed only a few years ago, and will be different yet again in a few years. (I think people confuse the relationship between science and technology, but that is another post.)

That is why I believe the current state of Neuroscience will be viewed as much contempt as we view Phrenology today.

Let’s take one such a popular topic: CONFIRMATION BIAS. Here is a recent article from a relatively reputable site. But it makes the same claims about confirmation bias, which are only partially true.

Most really dangerous lies are at least partially true.

The article describes confirmation bias as follows: It (confirmation bias) arises because people search for information that confirms their view of the world and ignore what doesn’t fit.

This is partially true.

But the full story is a bit more complicated.

Your initial ‘perception’ is formed for a reason. An incident, a lesson an insight triggered the belief. That is filtered through an existing personality and worldview. And, yes, out pops a ‘belief’ of how the world works. (Menstruation is affected by the full moon.)

Confirmation bias is then a description of what happens next. Basically, people see (and hear) and come to believe what they do because some initial ‘bias’ is strengthened and reinforced over time.

Confirmation bias is actually not a bias at all. Pragmatically it can be described as functioning like a sifter - you only see/hear that which reinforces the existing belief. Much like a sieve only lets through grains of a certain size.

Confirmation bias is necessary for your survival. The original belief emerged and got established because it was a heuristic that helped to explain the world. If you let everything through your sieve, you will be swamped by a tonne of grain.

Confirmation bias is not fixed. Much like if that sifter did not allow ANY grains through, you would starve. The fact is, once it outlives its usefulness or actually threatens your survival, you will adapt and change your beliefs. People figure these things out.

Confirmation bias is a normal function. Just like a plane needs to sight some guiding lights on the airstrip, humans need to sight these confirmation markers to keep us confident that we are on the right path.

Confirmation bias is moderated with experience. The frequency of the reinforcement determines the strength of the ‘bias’. The more frequent it is experienced, the stronger the bias. The stronger the bias, the more likely that it actually confirms with the truth (or actual reality.)

So, in fact:

  • A strong confirmation bias is actually more likely to be a true reflection of your experience than something ‘bad’ that should be avoided.
  • The danger lies in having ‘weak’ confirmation bias, and then making decisions that are very important based on that bias. That does not happen often enough to threaten our survival, or we would not function that way.
  • If you tried to consciously adjust for confirmation bias on almost every belief that you have (and there are thousands that affect your everyday life) you will actually probably develop mental health issues.


So confirmation bias is not really a problem that must be managed.

And listening to the ‘gurus’ will actually quite literally send you mad.