One of the most frequent excuses I hear from would-be innovators for their inability to shift from their current situation relates to regulation: ‘We can’t possibly change the design, because the regulations don’t allow it’.
The rules of football are very clear. The rules for throw-ins are also very simple:
At the moment of delivering the ball, the thrower:
faces the field of play
has part of each foot either on the touch line or on the ground outside the touch line
holds the ball with both hands
delivers the ball from behind and over his head
delivers the ball from the point where it left the field of play
These are the rules. And they become the limiting factor when a footballer desires to throw the ball further than the opposing players might expect to be possible: we’d love to throw the ball further than anyone else, but the regulations prevent us.
Now one plausible response to this situation might be to appeal to the football regulators asking for a rule change. Another – usually more immediately effective one – is to recognize that we have a contradiction. And then to go and see how others have already done some hard work to solve that contradiction for us.
Here’s how we might map the longer-throw-in-versus-regulation problem onto the Contradiction Matrix:
Interesting to note how the amazingly inventive, fully regulation compliant, throw-in solution in the video offers us such an elegant illustration of Inventive Principles 15 (Dynamics – move from a stationary (feet) to dynamic situation) and 14 (Curvature – switch to a rotating motion).
We often assume that the Contradiction Matrix comes from patents and is to be used for difficult technical problems. But, as we see here, it also comes from studying anyone anywhere that’s determined to break the rules without breaking the Rules.
The twin drives for Operational Excellence and Business-School-inspired ‘Imperative For Action’ have generated enormous ROI for enterprises around the world. But inside every silver lining is a cloud…
…most enterprises are now so ‘Action-Oriented’ they forget to engage their collective brains. 98% of all change initiatives fail. 90% of them failed the day they started.
As with all things, the original concepts tend to get corrupted. Take ‘continuous improvement’, the primary engine behind Operational Excellence since the Japanese-lead Quality revolution of the 70s. One of the main ideas underpinning continuous improvement is the Plan-Do-Study-Act cycle. It is pretty much ubiquitous inside any enterprise these days. As a customer, I’d say that was a good thing.
When the originators of Plan-Do-Study-Act thought about things, they came up with the idea that each of the four activities required about the same level of time and attention. The area of the four boxes, in other words, was designed to illustrate time.
This is the bit that has been corrupted. It’s all well and good for people like George Washington to talk about chopping down trees in eight hours and spending six of those hours sharpening the axe, but in ‘Imperative for Action’ World, those six hours of sharpening can very quickly come to look and feel like waste. And in Operational Excellence Land, waste is very definitely unwelcome. If we can’t tangibly see and feel ‘progress’, then it gets categorised as bad. If my boss comes into my cubicle and sees me drawing something on the CAD system, or, better still, comes into the lab and sees me busy doing stuff, then she goes away happy. If she sees me scratching my chin thinking about stuff, I don’t look busy, and i’m more likely to be rebuked than rewarded for my ‘slacking’: ‘Don’t just stand there, do something’.
I’m sure it’s not the case in your organisation, but if I had to draw an average of the amount of time I see companies or teams Planning, Doing, Studying and Acting, I think the picture I’d find myself drawing is this:
In the Doing box, everything looks fine. We like ‘Doing’. We look busy and we feel busy, and both are psychologically very appealing. Planning, on the other hand, is psychologically very unappealing. When we’re Planning something we don’t look busy and we don’t feel busy either. Planning can very easily begin to look and feel like waste. Even more scary is that when we’re thinking about what we’re supposed to be doing, we might inadvertently find some bad news that causes us to have to go backwards. Even worse still, we might have to go and tell our boss as much. All the time knowing that messengers find themselves shot more often than celebrated. Better to brush bad news under the carpet, and get on to the Doing part of the job.
Then, when we’ve finished Doing something, we’re supposed to step back and Study what we’ve Done. More chin-stroking. More psychological discomfort. Especially since most company’s don’t know what they’re supposed to be Studying at this point.
What very likely does happen during this Study phase, however, is the bad news re-appears from under the rug and it becomes obvious to all that we’ve Done the wrong thing. And so the Act phase of the continuous improvement cycle quickly turns into Firefighting. Which also turns out to be very appealing, psychologically-speaking. The expression ‘firefighters light fires’ exists for a reason. Firefighters get to be the hero when the problem is solved. Hooray.
Except, of course, for the fact thatwe’ve just consumed a vast amount of time and effort conducting nugatory activities. We spent most of our time looking anf feeling busy, but most of that time we were busy being fools. Operationally excellent fools, admittedly, but fools all the same.
That was the real waste.
Sadly, I don’t think any manager inculcated into the ways of Operational Excellence is going to be very compfortable using expressions like, ‘don’t just do something, stand their’ to their workers. It’s just not the way we’re all wired. We’re wired to Do. And more specifically to Do what gets rewarded.
But I think what we can hope for, is that we ask better questions during the Planning and Studying phases of the continuous improvement cycle (i.e. TRIZ), and that we might start to get managers to design systems that reward people for sometimes not doing, and standing there instead.
Marketing: we’re getting feedback from parents that our off-road quad bike toy is dangerous.
Design: Huh?
Marketing: well, not actually dangerous, but potentially dangerous.
Design: Potentially dangerous?
Marketing: Yes. If the child is playing outside, they might think it’s a real off-road quad bike and heaven knows what they might get up to.
Design: In their garden?
Marketing: We have to think about these things.
Design: Sure. But when the things turn out to be stupid, we’re supposed to ignore them.
Marketing: We need to send the message to parents that we actually did think about it.
Design: We advise them that the kid should wear a helmet.
Marketing (shaking head, solemn): apparently they’re also potentially dangerous.
Design: So what do you want us to do?
Marketing: Could we bring it indoors? Make it usable indoors where Mum and Dad can keep their eye on things?
Design: You want an indoor off-road quad bike?
Marketing: Yes, but without the element of danger.
Design: Danger of what? They’re indoors.
Marketing: Falling down stairs. Banging into the walls. Furniture. The home’s a minefield.
Design: How about if we put it on rails?
Marketing (smiling for the first time): Rails! That sounds more like it. Railways are fun. (Pause) They’re still a bit dangerous though, right?
Design: Not if we form the track into a circle.
Marketing: Won’t the kid get dizzy?
Design: We could add a couple of straight bits.
Marketing: Hmm. Yes. Better.
Design: We could add a slightly jiggly bit too.
Marketing: How jiggly?
Design: Well, side to side a bit. Not up and down.
Marketing: Great.
(pause)
Design: Okay. We’re on it.
Marketing: Great. We’ll start working on the name. Something that says ‘off-road fun’ without scaring mum and dad.
Design: Traction control?
Marketing (shaking heads): leave the fun problem to us.
Design: Even though it won’t actually be fun?
Marketing: You’re forgetting the giggle-jiggle.
(long pause)
Design: Maybe, when the kid reaches thirteen, when they’re allowed outside, they’ll work out they can take it off the track? Maybe that’s when the fun part comes in?
(longer pause)
Design: Or maybe it’s when they’re sixteen and learn how to set it on fire?
(even longer pause)
Design: Using the track as kindling.
Learn more about Generation Z and what their Generation Y parents are doing to them in one of our DNA books.
This one’s for the inventors. Or, better yet, the innovators that might actually do something with their ideas for improving the crappy products we are about to rank.
‘Worst product’ surveys are everywhere on the internet. The problem with all of them is they’re very subjective, and too often compiled by an individual with a bee in his – occasionally ‘her’ – bonnet about one crappy product in particular.
We thought it was time to bring some structure to the discussion. What do we really mean by ‘worst’? And how might we objectively compare a bad apple with a worse orange?
It sounded like a job for PanSensic again. Meaningful measurement, we eventually decided, needed to think not just about the overall rubbishness of a product, but also how easy it ought to be to put it right. The idea being that if something was easy to put right, but no-one had, that somehow compounds the insult to the poor consumer.
It felt like time for a 2×2 matrix.
Up the vertical axis we formulated an integrated parameter to quantify product ‘terribleness’. Because our focus was on everyday products, we decided that terribleness needed to combine three different elements. Firstly the amount of negative emotion the product generates from customers. Scraping social media for such negative emotions, however, quickly revealed a problem. Our relationship with bad products is somewhat akin to the Kübler-Ross Grief Cycle: When we first realise we need a product and go out and buy one only to then realise that it doesn’t do what we want it to do very well, we tend to blame ourselves and grind to a halt. Then, when we realise it’s not our fault we get frustrated. This is the stage when good organisations begin to recognize there is an innovation opportunity and do something to make the product better. Less proactive companies, or industries in our case, let the frustration devolve into Anger. They do this, I sometimes think, because they realise that if no-one does anything to fix the problems with the product, the Anger eventually devolves to Confusion and then Apathy. And later still, assuming the poor old consumer still has a need for the function of the product, they learn to Adapt their behaviour to compensate as best they can for the ineptness of the product, and then finally Accept that this is the way the world is. The reason for mentioning this rubbish-product-grief-cycle is that we can’t just use our usual Frustration measure as the prime indicator of terribleness. A really bad product has gone past Frustration for most of its customers and so when we’re looking for social media narrative we also need to be on the lookout for post-Frustration Anger, Apathy, Confusion, Apathy, Adaptation and Acceptance. The further along that sequence things are allow to get, the worse the product.
Or almost. The second factor that needs to be taken into consideration somehow is whether there is a level of taboo associated with the product. Certain things are unlikely to be discussed in a social media context because it’s just not socially acceptable to do so. Picking up how people feel about things they tend not to talk about is inevitably more difficult than something that’s at the front of everyone’s mind, but then again, one of the key start points for the whole PanSensic story was ‘reading between the lines’. So that’s what we’ve built into the calculation.
Thirdly then is the ubiquity of the product. A bad product design that never sells is, according to our algorithm, less terrible than one that everyone has Accepted is rubbish and goes out and purchases anyway.
So much for the vertical axis. Along the horizontal we’ve plotted ‘ease of solution’. The way we’ve calculated this is through a combination of two quantifiable aspects of current product designs. Firstly how much untapped Evolution Potential the product possesses. The more untapped potential it has, the easier it will be to make a trend jump to advance the capability of the solution. Second is how many contradictions would need to be solved in order to improve the design. A product with lots of current unsolved contradictions will need more work to improve than a product that is being held back by a smaller number of contradictions.
Here’s what the plot looks like for all of the candidate rubbish products we’ve been able to identify from our PanSensic analyses:
The way the plot is configured, the ‘real’ worst products are revealed as the ones closest to the top right hand corner of the 2×2 matrix.
They are (drum roll), in reverse rubbishness order…
#5 Leaf-Blower – the ultimate design solution for bored gardeners and street cleaners. Basically a noisy pollution machine designed to temporarily move half a dozen leaves in the opposite direction to the prevailing wind. Only to watch them all blow back to precisely where they started five minutes after the leafblower operative goes off to get more fuel.
#4 Hand-Dryer – when you see Dyson getting involved in a product, you can be pretty certain they’ve spotted a current product that is rubbish. Sometimes they create a solution that is better than the incumbent rubbishness. And then sometimes they find themselves going in the opposite direction. Like the Airblade. All the stupidity of a hot air hand-dryer, but now with added noise and a small lake on the floor. I think in some circles its called a ‘design statement’. A statement that in this case goes something like, ‘we have no fecking clue what we’re doing’.
#3 Sanitary Napkins – the clue is probably in the name, but things get seriously worse when we see the horrendous rate of urinary tract infections this product causes. Not to mention advertising campaigns based on ‘X% better protection’. Who in their right mind bases an advertising campaign on the USP of ‘slightly less rubbish than everyone else’s product’? Oh, wait, I know, the sort of person that launches a Minion napkin ‘innovation’. Did I miss that scene in the movie?
#2 Dental Floss – everyone knows they’re supposed to floss. 80% give up. Two-thirds of the people who persevere make things worse than if they hadn’t bothered in the first place. It’s like someone walking up to you in the street and whispering in your ear, ‘psst, if you buy this really expensive string, I promise you’ll get gum disease’ and you ask him how much to buy enough for the whole family?
And, finally, our winner…
#1 Toilet Brush – let’s see if I can get this right. The toilet is blocked, so I’m supposed to stick a high surface-area brush into the u-bend to try and unblock it. I then take the faecal matter covered brush out again, and move it, all the time praying it doesn’t drip poison onto the toilet seat and bathroom floor, to an odour-releasing, fly-attracting, bacteria-magnet display-receptacle for all my guests to admire. So they can then repeat the process. Did I miss something?
Okay, enough already. Over to you, Kickstarter… even though you’re not even in the Top 20 yet.
MAITRE D: And finally, monsieur, a wafer-thin mint.
Mr. CREOSOTE: Nah.
:
MAITRE D: It’s only wafer thin.
Mr. CREOSOTE: Look. I couldn’t eat another thing. I’m absolutely stuffed. Bugger off.
MAITRE D: Oh, sir, just– just one.
Mr. CREOSOTE: [groaning] All right. Just one.
Rule #1 with my friend Ancient Steve is don’t phone him at home early evening during the week. I’m not sure he knows about this rule, but I think all of his other friends have worked it out too. The rule, so far as I could establish it was an actual rule, started about a year ago. The change happened suddenly, though, and that’s the point of this post. How small changes can create non-linear change. How one last straw comes to break camel’s back.
Phone Ancient Steve up on a Wednesday evening now and, if he bothers to answer the phone at all, what you’ll hear on the other end of the phone is a gruff, curt, borderline offensive ‘what do you want this time?’ kind of hello. The same call a year ago would have been answered by normal Ancient Steve. Still a bit gruff, but gruff in a pleasant enough tone that you knew he wasn’t going to snap your head off.
Somewhere between the two, something happened.
What it turned out happened is that, because Ancient Steve doesn’t believe in things like phones with caller id on them or going ex-directory, when someone calls him, he doesn’t know who it is on the other end of the line until he picks the phone up.
Now the brain is really just a big old prediction engine as far as most of our lives are concerned. All those neurons are there to anticipate what’s going to happen in the next half second. This is a good thing to be able to do from an evolutionary survival perspective. It also means that, when the phone rings, our brain immediately gets busy anticipating who’s going to be on the other end of the line.
Prior to tweleve months agao, when Ancient Steve’s brain was making that prediction, the weight of probability was that the person on the other end of the line was going to be friendly, and so Ancient Steve was able to flood his response system with ‘be-polite’ chemicals and respond accordingly.
Around this time, Ancient Steve was also, it turns out, receiving a growing number of cold-calls from feckless salespeople. Early evenings during the week, the whole world of double-glazing sales personnel around the country gradually came to realise that Ancient Steve might be interested in buying replacement windows. Or a free life insurance assessment. Or a better deal on his utilities.
This was sort of okay until the fatal day when the balance of probabilities shifted past the fifty percent mark. When our brain does its prediction thing and tries to establish whether the incoming call is from a friend or double-glazing vending foe, the calculation is an essentially binary one. If 50.1% of past calls have been a friend, then the prediction that gets made is ‘the caller is friendly, be polite’. Ditto if the percentage is 50.01%. But, come the day that the balance of experience tips the probability the other side of the 50% mark, to 49.99%, then the default prediction becomes ‘the caller is an enemy, be gruff, surly and borderline offensive’. One call from the wrong person, one more piece of straw, tipped Ancient Steve’s behavioural balance.
And then, soon enough, they also affected mine. My prediction engine when I called Ancient Steve used to tell me, ‘here comes good old Ancient Steve’, so that I could pre-fire my own version of ‘be-vaguely-polite’ chemicals. But the moment the balance of probability in my own head about whether Ancient Steve was going to be gruff in a good way or a bad way shifted to the point where it was more likely I was going to hear the Bad version, then that’s the prediction I made.
Again, all it took was one too many calls to Bad Ancient Steve for me to change my whole view of what to expect when I phoned him.
That’s how it works. And until such times as Good Ancient Steve comes on the phone more than Bad Ancient Steve, that will remain my default expectation. Its the same thing with every other prediction calculation we make.
When I’m driving, and I see a car coming towards me flashing its headlights, my default reaction used to be to check that I hadn’t inadvertently left mine on full-beam. Then, when I realized I almost never had my lights on full-beam, my automatic, balance of probability prediction tipped to flashing my lights back at them to demonstrate that, look you idiot, I didn’t leave my full-beam on. Now I’ve lived in rural Devon for a year, the balance of probability has tipped again. When someone driving towards me flashes their lights at me now, the likelihood is there’s a silage-toting farm vehicle around the corner.
Strange that one wafer thin mint too many, as with Mr Creosote, can have such a non-linear results.
And, stranger still, even knowing all of this, is wondering how come after nearly a year of trying I haven’t managed to sell Ancient Steve any double-glazing yet.
One old joke goes that the opposite of ‘innovation’ is ‘innovation consultant’. I can see a fair amount of truth in this assertion. Especially if we qualify the statement as ‘innovation consultant who thinks the problem to be solved is lack of creativity’.
More pragmatically, it seems there is no antonym for the word. A bit like when Nassim Nicholas Taleb struggled to find an opposite for fragile. He ended up with ‘anti-fragile’, but I’m not sure the same prefix does the job in innovation-land. ‘Anti-innovation’ somehow sounds more like a protest than the proactive act of not innovating.
In any event, I’ve always kind of struggled with these kinds of opposite ends of a spectrum question anyway. Mainly because I think, rather than forming the two ends of a straight line, the two ends somehow bend themselves around to form an almost complete circle. The two ends, in other words, become effectively the same thing.
Love and hate for example. It’s a thin line between love and hate, so says the song, the implication being that you can love someone or something so much, you’re a tiny mis-step away from falling off a cliff and hating them or it. Or vice-versa. Which is pretty much the premise of nearly every Hollywood romcom ever made come to think of it: Boy meets girl; boy loses girl; boy gets girl back again.
Put love and hate at two ends of a spectrum, curve the line into a circle and the actual opposite of love becomes the halfway point along the spectrum. The opposite of love, in other words, is indifference.
The other classic two-ends-of-a-spectrum-are-the-same can be seen in left versus right wing politics. Go far enough in either direction and the end result looks pretty much the same as far as citizens are concerned. The political opposite of left or right is thus in reality something along the lines of laissez-faire liberalism.
For a long time, I’ve assumed that love/hate and left/right are the only cases where the two ends of a spectrum are to all intents and purposes identical. Now I’ve come to think the model generalizes to pretty much any kind of supposed spectrum of extremes. If I define any two spectrum extremes as ‘A’ and ‘-A’, and draw circle such that they meet, the other side of the circle – their actual opposite – is the mean, μ, or, if the distribution isn’t skewed, zero.
Can that be true?
Is extreme Fragility the same as extreme Anti-Fragility?
Is extreme Freedom the same as extreme Responsibility?
Is extreme Fight the same as extreme Flight?
Is extremely expensive the same as extremely cheap?
In each case, I think the answer is they are: either the outcome is the same, or, as with love/hate, they are separated by a very thin line forming the edge of a cliff.
Once I accept that A is the same as –A, the real opposite of each pair becomes ‘μ’. It’s zero. It’s apathy. It’s doing what everyone else at the middle of the normal curve is doing.
In which case we might think of ‘Anti-Innovation’ as ‘proactively staying the same, irrespective of what’s happening in the external environment’. And that in turn means the meaningful opposite opposite of Innovation is not ‘Anti-Innovation’ it’s ‘Continuous Improvement’.
Speaking as someone who spends the majority of his life staying in hotels, I’d have to say the novelty of the signs encouraging me to re-use my towels was pretty short-lived. Now, probably ten years since the signs first started appearing in hotel bathrooms around the planet, they’ve come to feel like some kind of dripping-tap torture.
The reason for the torture comes through the knowledge that, despite knowing the signs have never worked, somehow the hotel industry still hasn’t worked out how to dig themselves out of the hole it’s dug for itself.
It’s not as if the reasons for the counter-productive outcomes the signs produce are that difficult to diagnose. We can all read the words, but we also, too, make a swift interpretation of what the hotel management actually means. Something along the lines, ‘our laundry bill is really high, help us to lower it, please, even though we won’t be passing any of that saving along to you. Thanks.’
The signs are a clear signal of an industry that, ironically – given that they’re fundamentally in the ‘people business – doesn’t understand what drives peoples’ behaviour.
What’s really annoying about this is that we know the human behaviour story pretty much boils down to the ABC-M quartet of drivers we so frequently talk about in our workshops. Human Intangibles Rule #1: when you change anything, make sure stakeholders perceive perceptions of their Autonomy, Belonging, Competence and Meaning have all become better than they were before the change.
Look at the ‘save our planet’ towel re-hanging signs through this ABC-M lens and it becomes more than obvious why the signs would never work:
Autonomy – by telling people they have ‘the choice’ while at the same time shaming them into hanging up their towel, the sign speaks from a higher moral ground and thus takes away autonomy.
Belonging – while in theory playing on the idea that we all have a collective responsibility to do something about the environment, the only tribe that wins were I to hang up my towel is the hotel chain and their lowered laundry bill, and that’s a tribe I don’t belong to.
Competence – by telling me something that I’ve already known about for the last decade, the sign implicitly assumes I’m an incompetent idiot.
Meaning – saving the planet is highly meaningful; re-hanging towels is such a trivial part of that story that by attempting to make a connection between the two the enormous contrast in effect exaggerates the meaninglessness of the act of re-hanging towels.
So, let’s try another approach. This time based at least in part on the ‘ABC-M gets better’ heuristic:
These approaches do a better job of re-framing the Belonging part of the story. We’re now in effect asked to become part of the majority of people that re-hang their towels. I can imagine that it had the impact that it had. 26% more people hang their towels.
Now how about this one:
Autonomy – the guest is in control. They even get to write on the card and tell the hotel management what to do with the money they save.
Belonging – the guest gets to be part of the (majority) tribe of towel re-hangers. Plus they get to pass the money the hotel saves onto a tribe of their choice.
Competence – by telling the guest what the towel re-hanging exchange rate is in terms of environmental benefit and cost saving, the hotel helped make them better informed and therefore their competence went up.
Meaning – by connecting the trivial act of re-hanging my towel to a financial gain to something the guest cares about, the hotel just made the act a meaningful one.
Big Data is great for finding correlations. The Bigger the Data, the better the correlation.
But correlation, no matter how good, has nothing at all to do with causation.
Which is a pity, because causation is the only stuff that any of us ought to act upon. When we confuse correlation and causation, the only certain result is we make matters worse.
When we talk about looking for needles in haystacks, correlation is hay. Needle is causation. Causal relationships between things. Contradictions. Insight. Insight is contradiction is causal relationship.
When we talk about enterprises being able to act with confidence, what we mean is we have found an actual needle, that we have uncovered a meaningful causal relationship that no-one spotted before.
As the world gets ever more complex, busy and interdependent, hay becomes easier and easier to find. Needles, conversely, do not. Moreover, if we believe all of the findings of TRIZ since 1946, that insight is causation is contradiction is needles, the number of needles is finite. And if we already found most of them, there’s not a lot of point in gathering more hay.
Big Data is hay. The best way to find needles is to find them before they get dropped in the hay. Better yet, is go visit the needle factory. You’ll recognize it when you see it, it has a big ‘TRIZ’ sign outside.
I broke one of my main rules today. I went on TripAdvisor to look up a hotel I’m scheduled to stay at. Sometimes it’s good to break rules. Sometimes breaking the rules confirms why you had the rule in the first place.
The no-TripAdvisor rule exists because I spend most of my life in hotels, and have never yet met anyone with anything sensible to say about their stay. Not that I’m blaming or criticizing, just that unless you visit too many hotels than is good for your sanity, you don’t really have a means of calibrating how good one is relative to the other fifty in town.
The reason I broke the rule is because I wasn’t going to be alone on this trip, and my better half told me I had better not let her down.
The hotel I’d chosen had 306 reviews posted. Surprise, surprise, the average rating was a shade over 4 stars. I thought I’d better look at one of the non-4-star efforts. Like this one, posted a few days ago by ‘Penelope27’ (name changed)
This hotel was well sited for my work purpose. I arrived and checked in with the usual formalities, my room was spacious and clean. No view. Usual facilities ….. tea/coffee, UHT milk, nice cookies but only on first night. I ate on my first evening, a simple soup, well presented, cheap and cheerful. Was hot and had flavour. Came with fresh bread. The menu was basic pub grub which I guess people want. I prefer whole healthy foods. There was a salad bar but included lots of mayo ….. I don’t do dairy. Two bar staff, male, were really friendly and helpful. I asked if they sold chocolate, I fancied after my soup, the young man behind the bar suggested a few shops I could visit, then after a few minutes came to my table with a chocolate flake (obviously for deserts) and a big smile. I was impressed with his thoughtfulness and acted upon his instincts to please. In the morning I was treated to a huge breakfast bacon and mushroom bap. the young lady serving was helpful and friendly. I asked for herbal tea and was told there wasn’t any, then I was offered some loose tea on the shelf, peppermint which was lovely. My second morning was different, my breakfast bap was 4/5 mushrooms less, and I was told abruptly by a different server that peppermint isn’t in the breakfast deal and therefore was denied it, despite my saying I had it the previous morning. What a shame ……. I felt quite upset that the “special loose tea” was not included in the breakfast. A small spoonful of tea leaves which would have completed my morning breakfast was denied by an indignant young man, who did not offer an alternative tea, just smirked and walked off. Other diners refused a hot drink in the morning, surely one small of tea is not too much to ask???? Other than that …… it was ok, some staff were really kind and friendly especially the lad who offered chocolate. made my stay really warm and welcoming ….. isn’t that what counts????????
So the question now is should Penelope27 influence my decision to stay at the hotel?
The three-star rating Panelope27 offered suggested I should probably think about changing my booking to another hotel.
But, just who is Penelope27?
I thought I should run her review through the PanSensic tools.
This is what I learned:
She is a Myers-Briggs ENTP, and so therefore quite unusual.
She is great at finding problems.
She has some rather fixed ideas about what ‘good’ and ‘bad’ are.
She is extremely naïve and innocent.
She is rather self-absorbed and ‘entitled’, and therefore probably GenY, although, if I had to speculate, at the older end of the scale, higher than ‘27’, but lower than 34.
Should I listen to her review?
Answer: no.
Ditto the other 305 reviews.
In fact the only vaguely useful content out of all of the reviews came from the hotel’s proprietors. Where they had occasion to respond to a comment, they revealed themselves to be:
Diligent, paying a lot of attention to detail, probably ESTP.
Flexible.
Calm and unphased by idiots.
Empathic enough to know when to stay out of the way.
I think I will like our stay at the hotel.
I think, too, that my no TripAdvisor rule stands firm. Although I might see if we can set up a TripAdivsor API that strips out all the reviews and just leaves behind the responses from the staff. That seems to be the only meaningful stuff.
Hmm. I wonder if TripAdvisor know about this? Maybe they already know the only point of encouraging millions of Penelope27’s to write meaningless reviews is to provoke meaningful responses from the hotel staff? That’s what I’d call borderline genius.
Every organisation on the planet these days seems to be wanting an ‘innovation culture’. Or at least they do until they understand what they’re asking for. The first problem is being able to make any kind of meaningful measurement of the prevailing ‘culture’. The second is knowing what the measurement needs to change to.
The biggest programme of PanSensic R&D activity at the moment is creating a suite of psychometric tools. Although initially conceived as a means of allowing individuals to assess themselves through the various different lenses (Belbin, Kirton, DISCUS, etc), because the system needs only a pile of narrative to do its job, it means we’re able to do things that the traditionally questionnaire-based assessment tools have never been able to. Like measuring the Myers-Briggs profile of a whole enterprise.
At first, we thought that when we analysed masses and masses of narrative authored by many different individuals within an enterprise, we’d end up with a meaningless cancelling out of the various different measurement axes. Such that, for example, all of the ‘extroverts’ in the enterprise would be matched by an equivalent number of ‘introverts. So far that hasn’t been the case. Here’s the sort of picture we seem to end up with:
The picture is typically constructed by feeding company reports, website content, and ideally (anonymized) email traffic into the PanSensic engine. What it then spits out is a set of psychometric profiles of the overall organisation. In the case of the image presented above, we can say previously inconceivable things like ‘this organisation is an ISTJ’.
And what that in turn allows us to do is to correlate to the types of change that kind of ‘person’ tends to be comfortable with. The following image plots the sixteen different Myers-Briggs profiles relative to the seven main types of change needed at different stages of an evolutionary s-curve:
ISTJ’s are your great ‘do things the right way’ optimisers. They’re not innovators, and the expression ‘innovation culture’ tends not to be part of their vocabulary. Unless it’s something like when they say, ‘innovation culture? Isn’t that when they make everyone wear facepaint and dance like a tree?’
This ISTJ organisation, in other words, is going to find the journey to an ‘innovation culture’ a long and probably tortuous one. But at least we now know where we’re starting from and, once we’ve also psychometrically profiled their competitors and aspirations, we know where their destination should be. And that the journey, initially at least, should keep the tree choreography instructions in a triple-padlocked cupboard.
