Freeze Frame

Watching the TV programme ‘The Force’ last night (which follows the work of officers from Greater Manchester Police), I thought of yet another analogy to help explain why binary comparisons are rubbish. (Yes, I know I go on about this, but there are still people out there who appear to be ‘hard of learning’ when it comes to this subject).

Anyway, the episode featured the policing of a protest by the English Defence League, including sequences from a state-of-the-art control room where the officer in charge was able to watch events unfolding on banks of CCTV screens. This meant he was able to make decisions dynamically in response to changing events and fresh information, as it came in.

Freeze frame 1

Using the inevitable #StickPeople to contrive a tenuous link to the use of binary comparisons, here we can see the police boss running an operation to prevent disorder involving the fringe ‘S.D.L.’ (Stick Defence League) – an angry and directionless group who sometimes cause problems at their own events for no apparent reason.*

Freeze frame 2

The boss uses the live footage from the CCTV screens, radio messages and other incoming information to make decisions about what to do, and the event passes off peacefully. Everyone’s happy. This is because all he’s doing is the equivalent of using meaningful and multifaceted performance information to understand what’s occurring over time, so informed decisions can be made about how to respond (or not respond).

Contrast this with the situation below, where the real time information is switched off and all he has to go on are occasional isolated ‘freeze frames’.

Freeze frame 3

It’s pretty obvious really, but the latter case is equivalent to using binary comparisons, where isolated numbers are compared to ‘the same period last year’ etc.

Why anyone still does this is beyond me.

* Disclaimer: This blog is just a bit of light-hearted fun. The ‘SDL’ are entirely fictitious and even if they were weren’t, they would have the right to protest peacefully. Any similarity to anything else, ever, is purely coincidental. And binary comparisons are still rubbish.


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Short Circuit

This is Stick Boss. Stick Boss is basically a good guy who cares about his organisation and wants the best for people. Unfortunately, he has a problem with his brain. This means that just as he’s on the cusp of understanding how to make best use of his performance information, his brain short circuits and he reverts to the use of arbitrary numerical targets (and other associated abominations).

Let’s have a look inside his head to see what goes on in there…

Stick Boss brain

As you can see, the content of the different segments of his brain is pretty standard. Unfortunately, the ‘numerical targets’ quadrant interferes with his thought processes in certain circumstances. Take the following example…

Stick Boss is bright enough to understand that different parts of his organisational system influence each other, helping or hindering service delivery. Even some stuff that wouldn’t be obvious at first can affect how well the front line performs. Therefore, Stick Boss is keen to understand where the opportunities for improvement lie, so he ensures his performance measurement system reaches into these dark backlots to extract useful information that can aid his decision making.

This is good. He’s got a clear understanding of his organisation’s purpose and recognises the need to have access to performance information that measures the right things.

But then the brain defect kicks in.

Instead of using the right measures in the right way, the short circuit in his brain overrides the need to present performance information in a usable, contextualised format, and supplants it with an ill-conceived reflex that results in his potentially useful data being corrupted by arbitrary numerical targets and binary comparisons. What a missed opportunity.

Like I said, Stick Boss isn’t a bad guy, but his brain problem prevents him from realising the damage he is causing by relying on fundamentally illegitimate performance practices. So, if you know people like him, please help.

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Maths Class

Stick TeacherHere’s Stick Teacher. Today Stick Teacher is going to run through a few sums with the Stick Children. Adults might find his case studies useful too. Stick Teacher is going to demonstrate how to save money whilst providing a better service – what’s not to like? :-)

To do this, he’ll use the example of a generic public sector call centre (*police / ambulance / fire / tax office / housing department / other). *Delete as applicable.

The idea that these call centres save money seems to be based on the premise that if you put a lot of people in a central location and give them a specific function that forms part of the overall service provided, it’s cheaper.

Let’s try and understand how this concept works, using characters that Stick Teacher has invented to help explain things to the Stick Children…

Here’s Employee 1. Employee 1 is an enthusiastic call taker and a hard worker, who always assists the public the very best he can with his level of training and experience.

Employee 1

And this is Employee 2. She is also enthusiastic and hard-working, but more senior, more highly trained and experienced; plus, she is empowered by the organisation to make decisions about stuff.

Employee 2

Here we go then…

Case Study: Option One

For this example, Employee 1 answers a call, asks basic details and creates an electronic record. He is paid 10 Stick Coins per hour (this is the currency in Stick Land) and spends 15 minutes dealing with the call.

Time elapsed so far = 15 minutes.

Total cost so far = 2.50 Stick Coins.

Employee 1 then forwards the electronic record to Employee 2; being more senior, more highly trained and experienced, she is paid 20 Stick Coins per hour. Her role is to review the electronic records, identify any additional actions and make a decision about what to do.

On this occasion, she identifies that Employee 1 has covered most of the basics, but thinks it would be helpful to ask a few more questions and do some background checks before a resource is allocated to deal with the case, so she details these requirements on the electronic record and returns it to Employee 1 to complete.

She spends 15 minutes doing this (costing a further 5 Stick Coins).

Time elapsed so far = 30 minutes.

Total cost so far = 7.50 Stick Coins.

Employee 1 then completes these tasks and sends the case to the appropriate resource. This takes another 15 minutes, costing another 2.50 Stick Coins.

Total time elapsed = 45 minutes

Call rate per hour = 1.33

Total cost = 10 Stick Coins

So, that’s the traditional call centre model then.

Case Study: Option Two

An alternative approach would be put Employee 2 at the point of contact with service users, where she can maximise her skills and experience to do a more thorough job from the outset, thereby negating the requirement to pass the job backwards and forwards for review and remedial actions. Due to her enhanced ability, she is able to deal with the entire case in 15 minutes.

Total time elapsed = 15 minutes

Call rate per hour = 4

Total cost = 5 Stick Coins

So, although it costs twice as much to employ her, the job gets done more quickly and effectively. Oh, and the whole process costs half as much as in Option One.

Case Study: Option Three

But perhaps your organisation wouldn’t want to use a raft of ‘Employee 2s’ at a higher rate of pay, so a third option could be to employ Employee 3, who is just as enthusiastic and hard-working as his colleagues. Employee 3 is quite capable of handling 95% of calls without assistance; he is more highly trained than Employee 1, but isn’t trained to the highest level of specialism, like Employee 2.  This means he is paid 16 Stick Coins per hour. He is able to deal with most cases to the same level as Employee 2, and at the same rate.  Therefore, he deals with this call in 15 minutes, costing 4 Stick Coins.

Total time elapsed = 15 minutes

Call rate per hour = 4

Total cost = 4 Stick Coins

On those few occasions where Employee 2’s specialist training is required to make decisions on the most complex cases, this model would allow for a small number of such experts to be available, commensurate with the demand for their enhanced skills.

So, this model is also faster and costs much less than the traditional model; the only consideration is there will be a handful of occasions where some calls need to be passed to Employee 2 to complete. If the cost / benefit considerations of this model are acceptable, then this configuration could be the most cost-effective of all three.

Stick school

Stick Teacher’s Conclusions

Therefore, the result of today’s lesson for the Stick Children is that conventional wisdom about things like centralised functions is not always that wise. Whichever way you look at it, Option One is actually the slowest and most expensive to operate; Option Two is the ideal model from the caller’s perspective, and Option Three is probably the most cost-effective and suitable configuration for the real world.

The illusion of savings under Option One comes about because of the focus on cost-per-operator, without understanding end-to-end flow or whether purpose is achieved. It builds in waste, unnecessary handovers, disempowers staff, creates delays and COSTS MORE, whilst providing a WORSE service!

Therefore, maybe more people should try one of the other options instead.

If the Stick Children can understand this, so can you.

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Whilst flicking through TV channels recently, I came across a consumer advice programme, where the reporter was researching the effectiveness of self-administered ‘detox’ products. The TV crew followed her for three days as she consumed nothing but ‘specially formulated’ fruit and vegetable juice drinks of various colours. At the end of the experiment, she visited a nutrition expert to discuss the results.

I have recreated the conversation that followed, with the help of my Stick People…

Detox pic 1

The reporter seemed surprised…

Detox pic 2

The expert’s assessment wasn’t that well-received…

Detox pic 3

The exchange made me chuckle, as it reminded me of this sort of thing…

Detox pic 4 v2

Standby for the chap on the left to say, “Thanks Stick Child – that’s really helpful. I know what I must do!”

Or perhaps…

Detox pic 5 v2

Oh dear. As writer Aldous Huxley said in 1927:

“Facts do not cease to exist because they are ignored”.


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Comfort Blanket

When Stick Child was a bit younger, he had a little comfort blanket. Here he is with it, dreaming about smashing up some arbitrary numerical targets. (That’s supposed to be the moon in the window by the way – not a banana).

Stick Child dreaming

Stick Child believed that his comfort blanket had magical powers – it kept monsters away at night and helped him sleep soundly. It felt soft and warm, so if he was ever sad he would hold it against the side of his face. It was familiar and reassuring.

Some adults adopt a similar approach.

Despite evidence that binary comparisons are incapable of telling us anything about trends or trajectories, are prone to causing unwarranted assumptions, consistently impair decision making and lead to unnecessary action as a direct result, some adults still cling to them like a comfort blanket. (The same applies to numerical targets and league tables).

In case of any confusion, here’s a simple guide:

Two types of comfort blanket

So, to conclude: binary comparisons do not have magical powers and any ‘reassurance’ they appear to provide is false.

Comfort blankets can be great for children, but adults need to let go.

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The Wrong Conversation

Stick Child facepalmStick Child has been getting increasingly irritated by the slack methods some adults use to present information about really important stuff, such as how long it takes for patients to be seen in Accident and Emergency (A&E) departments. Many a time recently he’s had to do a facepalm at the way hospitals and other institutions are judged and compared against each other, supposedly to inform the public about how well each is performing.

The problem is that the starting point of the conversation – the frame by which performance is judged – is totally wrong. Plenty has been written about the arbitrary nature of numerical targets and their propensity for triggering dysfunctional behaviour, so we’ll leave that to one side for now, and just look at why using them as the focal point for judging performance simply means people engage in the wrong conversation.

Stick Child has drawn a couple of charts, which plot the distribution curves of A&E admission times for two hospitals.

Wrong conversation Hospital A


Wrong conversation Hospital B

As you can see, the curves are different. Hospital ‘A’ manages to get 95% of patients seen within 4 hours, after which, a steep drop off in the curve indicates the remaining 5% are seen before 4 hours and 30 minutes has elapsed.

Hospital ‘B’ also manages to see 95% of patients within 4 hours, but the tail of the curve beyond this point is much longer, meaning that the remaining 5% of patients take much longer to be seen – some waits are as long as 7 hours. It’s also apparent that Hospital ‘A’ sees more patients during the early stages of their wait than Hospital ‘B’. This is evidenced by the fact that Hospital ‘B’s curve is weighted more to the right.

So, its quite clear that the patterns of waiting times are different for the two hospitals.

Not according to the target.

According to the target, the two hospitals’ performance is exactly the same. This means that opportunities to understand why some patients wait up to 7 hours in Hospital ‘B’ are missed. It means that managers don’t get the chance to understand their system, as the usefulness of A&E admission time data is undermined by using the target as a focal point, thereby degrading potentially useful information into a simplistic PASS / FAIL scenario.

Now consider what would happen if Hospital ‘A’s distribution curve actually showed that 94.9% of patients were seen within 4 hours, whilst Hospital ‘B’ achieved 95.1%.

Wrong conversation table

Yep, despite the fact that Hospital ‘A’ demonstrates better overall performance, it FAILS, whilst Hospital ‘B’ PASSES. This fixation on the target and a binary definition of ‘good’ or ‘bad’ performance means no one learns anything about either hospital.

That’s the real FAIL.

Then there’s those convincing-looking charts which look authoritative, but actually spew out what can only be referred to as pseudo performance data, such as this:

Wrong conversation chart

Looks good, doesn’t it? Well it’s not. All it does is tell you the percentage of cases where performance has crossed that invisible and imaginary dividing line between ‘good’ and ‘bad’, as defined by the target. A chart that tells you about a target to hit a target. Utter waste of time.

If you’ve got the data, simply plot them and learn from them. Why throw in a target and thereby replace the richness of potentially useful performance information with a meaningless and mind-numbing YES / NO game? Seriously, why?

It drives the wrong conversation.

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Avoidable Harm

I recently had a conversation on Twitter about a national campaign called ‘Sign up to Safety’, which aims to reduce avoidable harm in the NHS. Now, avoidable harm is clearly something worth tackling. The sticking point for me was that they have a numerical target to reduce avoidable harm by 50%.

What I can’t understand is why anyone would aim to reduce avoidable harm by 50% – if it’s avoidable, we should avoid it! Not just some of it. Why would you want to be ‘half-safe’?

It’s like deliberately planning to retain the other 50% of harm! Which, of course, sounds silly – because it is silly.

There’s a lot that’s silly (and harmful) about such targets, such as the assumption that a target is necessary to make people want to reduce harm in the first place. If they know that reducing harm is important (i.e. a priority), then the target is irrelevant. It might even be possible to measure some types of harm reduction, so that’s good too, because then you have measures to help you understand how your harm reduction efforts are going. The target is still irrelevant though.

Angry Stick Child

Anyway, why is the target 50%? How was this determined? Why not 55%, or 70%, or 81.648%? If it was set at 50% because it was deemed attainable, then what’s the point of the target, because you’re gonna attain it anyway, right?

Why is a 49.999% reduction a failure, whereas a 50.001% reduction a success? These invisible dividing lines between ‘good’ and ‘bad’ simply don’t exist in the real world. If you could reduce more harm than 50% then you would, wouldn’t you? If so, the target is irrelevant. If you wouldn’t, then why not?

How about if you reduced all the harm you possibly could, but this only amounted to 35% less harm? Have you failed? Why? What about if you had it within your gift to reduce harm by around 80-90%, but only reduced it by 55%? You’ve exceeded the target, but is this good?

Then there’s the stuff about method. How does a numerical target set at any level help you identify and address harm reduction opportunities? It doesn’t, because targets don’t provide a method.

Also, as I’ve said before, it’s better to aim for 100% (i.e. perfection) than just a fraction of your true goal. You’d then measure, learn and improve as you go along. Yes, in many domains (such as harm or crime reduction) it may not ultimately be possible to completely eradicate the object of your reduction efforts, but this shouldn’t stop anyone from trying.

Let me give you a few examples using the Stick People, to try and demonstrate why numerical targets like the 50% target for avoidable harm are pointless (not to mention arbitrary and prone to causing dysfunctional behaviour).

Here’s Stick Doctor. Today, Stick Doctor encountered two opportunities to reduce harm in her hospital. Guess how many she addressed? (Clue: It wasn’t one).

Stick Doctor Avoidable Harm

This is Stick Cop. Stick Cop currently has four investigations in his in-tray. He’s decided to investigate all of them to the best of his ability. Not just two.

Stick Cop - Avoidable Harm

Here’s Stick Child. Stick Child saw one opportunity to help a group of under-10s get their heads around some basic performance management concepts. He didn’t stop half way through.

Stick Child - avoidable harm

Get  it now?

If you have a worthwhile priority, just focus on that. Measure your progress, using the right measures in the right way. Learn and improve. You don’t need the target.

Reduce avoidable harm by reducing numerical targets!

By 100%.

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