How traditional funding would ruin something good

I've been doing some work looking at how we support people who experience domestic violence or abuse, and how we might improve that support.  

During this work, I've gotten to know a fantastic local place that helps women who've broken free of domestic abuse to stay free.  Don't take my word for how great it is – here's what some of the women I spoke with there said about it:

• "Of all the services I've dealt with, this is the only one that works."
• "You are actually helped and understood.  They treat you as a person as a whole."
• "It's welcoming, and you are listened to.  It's like a family working together."
• "When you experience domestic abuse and leave the relationship, you don't know what you don't know.  They take you through it one step at a time.  They help with all the applications."
• "You get peer-to-peer support.  It's compassionate, and survivor led."
• "It's informal.  There's lots to be said for a cup of tea and a chat."
• "They pull out every stop for the children.  They helped get my child diagnosed for ADHD."

They don't turn people away because of thresholds.  No one completes an assessment form.  They don't work to targets, KPIs, or other metrics.  They build relationships with people, understand what really matters to them, and support them in achieving what matters.  The support is 'bespoke-by-default', responding to each person as an individual.  They have a network of friends and volunteers on hand with all sorts of skills – a handyperson, locksmith, experts on the law, housing, immigration, benefits, etc.  The support isn't time limited, and some of the women have been coming for years.  Many turn their experiences in to 'gifts' they can support their peers with, or have become volunteers themselves.

They've created a safe, welcoming, compassionate, and supportive atmosphere.  There's a real sense of community among the women – at times I struggled to work out who were volunteers or paid workers, and who weren't.   

And it works!  In five years none of the women they've supported have returned to the abusive relationship. 

How might traditional funding ruin it?

In my naivety, I asked one of the people who runs it "Do you get any funding – from the council or health or anyone else?"  The answer was a resounding "No".  The place is funded unconditionally by a charitable organisation, through local donations, and through the work of its friends and volunteers.  

I started to speculate on how this place might be ruined if they were commissioned or funded in the traditional and prevailing way.

• Traditional commissioning starts from an assumption that competitive markets work for public services, giving greater choice and efficiency.  To understand why this assumption is so flawed, read this book chapter from Kathy Evans, Chief Executive of Children England.  
• This means, in practice, the focus is on price.  To compete and compare on price, the service needs to be specified.
• Specification means a standardised service response.  This is where things really start to go wrong.  People are people shaped – they don't fit in to neat little boxes.  A standardised response cannot cope with the huge variety of people's need.  As Mark Smith writes in his blog, "[Standardisation] takes away an opportunity to apply judgement and nuance, borne from experience and an appraisal of what matters to whomever needs help"
• Once you standardise you have functional specialisms or silos.  Each service or provider is commissioned to only do specific things, and therefore won't do others.  The people who come to that service are looked at and labelled through the lens of whatever that service is commissioned to do.  Then they're referred or 'sign-posted' to the next service, who repeats the process again. 
• When providers are commissioned only to do certain things, they introduce thresholds or assessment criteria – essentially gate-keeping.  The thinking here is there's only a scarce resource available, so you need to ration what you do.  
• But, when people get turned away (or referred, or sign-posted), it means they either present elsewhere in the system, or come back later when their needs are higher.  Thresholds can be a false economy, as when people get worse they are more expensive to support.  
• Instead of building trust and relationships with their partners, commissioners and funders are typically interested in accountability (which is a nicer way of saying management by fear).  It means providers becomes concerned with external approval, which undermines intrinsic motivation and responsible practice.   
• To hold providers to account, commissioners use monitoring and performance management.  They ask for detailed information about how workers are spending their time, what activities they're doing, or if they are working to the standard.  A damaging example is 'time and task' commissioning in homecare services.  
• Another way to hold people to account is by setting numerical targets.  I've written about the problems with targets in a previous post.  They change the focus from doing the right thing to making the numbers look good, even if that means doing the wrong thing.  
• The undesirable effects of targets can be made even worse by payment by results.  They are a way to financially reward providers for producing data about targets, and not for helping the people they exist to help.  

Imagine what the place I visited might look like if it were commissioned in the traditional way?  What would it be like for the women who go there?  What would it be like for the staff and volunteers?  Would it be any more efficient?

Why do we fund and commission in this way?

As business writer Aaron Dignan puts it, "The way we work is broken.  It was invented 100 years ago on a factory floor for a world that no longer exists".  Commissioning is a symptom of these outdated ways of working, grounded in mass-production and 'Taylorism', which results in treating people as though they are parts in a production line.

In the 1980s, public services started to embrace what was subsequently called New Public Management.  This meant running public services as though they were private sector organisations, being more 'business-like', treating citizens as customers, and attempting to use competitive markets to reduce costs.   This led to policies like Compulsory Competitive Tendering (CCT), later replaced by Best Value, which are is still with us today.  

What are the alternatives?

There are many folks who know much more than me about how to improve funding and commissioning practices.

My go-to person for this is usually Toby Lowe.  He's an academic, who's previously been a provider of commissioned services, and has done loads of research in to this area with voluntary and public sector organisations. With his colleague Dawn Plimmer, he's put all of this into a brilliant report called Exploring the new world: Practical insights for funding, commissioning, and managing in complexity.  You can watch him speaking about it in this 13 minute video.

Andy Brogan, co-founder of Easier Inc, has recently written an accessible 'how' to report.  It gives lots of insight and helpful advice on how to put what he calls 'Commissioning 2.0' in to practice.

Jo Gibson from Vanguard has been doing some great work in this area too.  You can watch one of her students speaking about how they changed the way they commissioned homecare services in this 20 minute talk.  Jo is co-hosting a one-day commissioning event in London on 5 May 2020 which is worth checking out.

Over to you...

Do you work for a an organisation that provides commissioned or funded services?  How accurately  does what I've written here reflect your world?

Likewise, if you're at an organisation that commissions or funds services, are you still doing it in a traditional way, or have you started to look at some of the alternatives?

I'd love to read your thoughts in a comment below.  And please do feel free to share this with anyone who might be interested.  

Review: Beyond Command and Control (in people-centred services)

"Paul's life fell off the rails.  Over a period of 10 months, he was subject to 179 activity records by public servants, involving 91 staff from 20 different teams.  He experienced 12 assessments and 11 referrals, leading to six hospital admissions with total stays of 81 days, while staff generated seven support plans.  At no time did anyone spend time with Paul to understand what mattered and what 'success' might mean to him."

This is from the people-centred services chapter of John Seddon's new book, Beyond Command and Control.  It sums up much of what I've found when looking at these types of services.

I'm already a fan of John's writing, and have read many of his other books.  It was one of John's books that first got me thinking differently about improving services.

I've kindly been sent an advanced copy of the book.  Rather than covering all of it, I'm going to attempt to review the chapter on 'people-centred services', as it's an area I've worked with in local government.

What are people-centred services?

This is a term John uses to describe services that respond when "people's lives fall off the rails in a variety of ways". For example, services such as social care, domestic abuse, and homelessness are some people-centred services I've worked with.

They differ to transactional services as they usually require a relationship with the person first, in order to understand them and their situation.  How an organisation responds to "can I book a squash court" should be different to its response to "I'm struggling with my debt and my health".

Sadly, as John describes in this chapter, we too often see a transactional response when a people-centred one is needed, causing all sorts of things to go wrong.

What's wrong with the current design of these services?

The chapter highlights many of the problems with the prevailing "command and control" approach to designing and managing people-centred services.  Here are some of them.

• Targets. I've written about the problems with targets before. They're often set by politicians, hide the truth, and lead to sub-optimisation: "the time taken to get 'on target' is actually a reflection of the time it took public-sector managers' ingenuity to work out how to at least appear to be on target by gaming the system". 

In the example of care assessments, meeting targets "simply covers up the terrible truth: the extraordinary time it takes people to get through the red tape, mind-boggling number of people involved, the forms, assessments, reminders..." 

• Functional specialisms.  If you approach a council for help you "may be seen by a dozen or more people" each "considering your needs through their own specialist lens". 

I've seen this myself.  People get assessed and referred all over the place – like in a game of pass the parcel.  Each professional is only allowed to do their 'bit'.  All the activity going on here costs so much money, without really helping anyone.

• Standardisation.  A one size fits all approach which means "services inevitably fail to match the variety of people's needs, providing some things that don't help and others that go further than necessary".  Care services are commissioned on a "time and task" basis, meaning you get "30 minutes regardless of whether 10 or 40 might be better".  

This two minute video powerfully highlights many of the problems with this approach.  

• Managing demand. Or as John puts it "rationing by another name: limiting services, finding excuses to turn people away".  This is done in the name of reducing cost.  But when people's needs don't meet the criteria, they are left for the condition to get worse, meaning they cost more to support later.  

This was backed up recently by some superb research by Dr Rick Hood and colleagues.  It found children "screened out" of social care services are more likely to re-enter the system later on, with more complicated (and therefore costly) problems.  This is an example of failure demand, an important term originally coined by John in previous books.  

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The chapter also explains a number of other flaws with typical people-centred services, including budget management, cost-cutting, commissioning, and a belief in market forces.  

Is there a better way?

Yes.  John describes a more effective design.  It starts with understanding demand and doing only the work that's of value to the citizen.  This consists of understanding the citizen and their need in context, helping them establish what a good life would look like for them, discovering what they can do for themselves to live a good life, and lastly looking at what support they may need from elsewhere.  

By focusing on doing only this, and cutting out the forms, signposting, remote assessment, rationing, standardised assessments, etc: "Lives get put back on rails... costs of services provided fall dramatically... and... as individuals and families are straightened out... overall demand begins to fall away".  

There are examples of where this has been achieved from a number of places, including a county council, a Swedish municipality, and some encouraging work done in Wales between a commissioner and care provider.  

In summary

This is an important read for anyone who works with people-centred services, or is concerned about increasing costs and demand in the public sector.  

It gives a crystal clear account of the problems with the current command and control design, valuable insights in to why that design is flawed, and demonstrates an alternative that's better for citizens, better for people working with citizens, and one that greatly reduces costs and demand.  

For a perspective of other parts of the book – especially the chapter on Agile – I highly recommend reading this review from Bob Marshall.

You can find more about the book, including how to order it, here.

Do 40 points mean your football team is safe from relegation?

This post is about football (soccer) and variation of data over time.  I hope you're a fan of both!  If you're not, you're still likely to find at least some of what follows useful in the workplace.

In the English Premier League, it's a commonly held assumption that when a team reaches 40 points they will be safe from getting relegated to the next league down.

I recently read an article from the Guardian newspaper that challenged this belief.  It suggested around 36 points would mean safety.  If you're not familiar with this 'rule of thumb', I recommend reading the article before continuing.  You'll find it here.

Like at work, when people start throwing single numbers around, I started to wonder:  "how have they come up with that number?"  "have they understood the variation?" and "what would it tell us if we put it in a control chart?"  I did that, and here's what it looks like:

As you can see, it's a type of line chart, and I've plotted it as a time series.  Each dot shows the points needed to escape relegation (one point more than the relegated team) each season.

Like just about any data, there is variation.  In some seasons more points would have been needed than in others.  The three coloured lines on the chart help us make sense of that variation.

Average line

The red line in the middle is the mean average.  Although it's useful, there are problems when people only report on the average.  In my experience, the average becomes the number.  This is how they came up with 36 points in the Guardian article.  But the average doesn't take in to account variation.

For example, what's the average of 1 and 19?  And what's the average of 9 and 11?  The answer to both is 10, but the average doesn't tell us how much variation there is.  9 and 11 are much closer together than 1 and 19, but the average alone hides this information.   The same point is nicely made with this picture.

An average of 36 points (or 37 in my calculation) tells us nothing about how many points are needed to avoid relegation.  Roughly half the time more than 36 points will be needed, and the other half fewer will be needed.

Upper limit and lower limit lines

These are sometimes called the UCL (upper control limit) and LCL (lower control limit).

Data points going up and down between these lines are 'common cause' variation – the normal changes in the points needed for safety between seasons.  You shouldn't pay too much attention to the differences between these points.  They represent the 'noise' in the data.  The 43 points needed in 2002-03 is just as likely as needing 31 points in 2009-10.

A mistake I often see people make is to pay attention to common cause variation, and act as if something out of the ordinary has happened when it hasn't.

These lines also help with prediction.  If you want to be confident your Premier League team avoids relegation this coming season, 44 points should be enough.  And as long as you've got 29 points you've still got a chance.  Anything less than that and you're most likely doing down to the next division.

You might have spotted a couple of data points – 1992-93 and 1994-5 – above these lines.  That's what's called 'special cause' or 'assignable cause' variation.  It's a signal that something is different.  How you react to this would be different to how you'd react to common cause variation.  With special causes you'd ask "what's different?" or "why the change?"

In this case, there was a change.  For the first four seasons on the chart, the league was made up of 22 teams.  After then, it goes down to 20.  From 1995-96 onwards, teams are playing fewer games and therefore accumulating fewer points.

To show the change, the chart should really look like this:

Here are some handy 'rules' for spotting other signals in control charts.  This is where the average line becomes particularly useful.

Should football clubs set themselves a points target?

Probably not!  When you set a target, making the number becomes the focus, rather than doing the right thing – in this case, the right thing for the football club and its fans.  It can also encourage a behaviour where people ease off when the targets is met, or looks like being met.  

In the 2012-13 season, Barnet Football Club were relegated from their division.  Their then manager, Edgar Davids was quoted as saying: 

"It's even more disappointing because we have reached all the objectives that the chairman set and reached the 51 points target but we've still gone down."

They would have probably have fared better if they'd focused on winning as many games as possible, rather than achieving an arbitrary number.

How does this relate to work?

This is all well and good when looking at sports league tables, but this blog is supposed to be about work and improving services.  With that in mind, there are some lessons we can take away from this post.

1. Be suspicious when people quote a single number – often the average.  For example, I've seen the average time it takes to process benefit claims become the only figure used.  It was about 17 days.  Managers thought this was good performance.  Customers and stakeholders were given this figure, and they came to expect that's how long they'd be waiting for.   But a control chart revealed the predictable variation to be anywhere between 0 and over 100 days.  The average alone tells you almost nothing about performance.

2. Be careful not to confuse common cause with special cause variation.  I was once at a meeting where a department's figures were all 'red' because they were worse than the previous month.  The manager was asked to go away, investigate what had happened, and write a report to bring to next month's meeting.  This was a complete waste of time.  I put the data in to a control chart, and it was just normal common cause variation.  The senior managers had unwittingly reacted to is as though it was a special cause.  The next month they were back to 'green' – possibly because of regression toward the mean.

3. Comparing just two data points tells you almost nothing – certainly not about variation.  Although not covered in the above example, we see performance reports that compare this month to last month, now to this time last year, etc.  They might have arrows or colours applied, to indicate if performance if 'good' or 'bad' in relation to a target.  People are supposed to make judgements or decisions based on this information, with absolutely no context.  Displaying the same amount of information in a control chart would look like this:

If you took this chart to a meeting, people would probably laugh at you or tell you to leave.  Yet it's seen as perfectly acceptable to present the same inadequate amount of information in a 'scorecard' or 'dashboard' report.

4.  If in doubt, plot the data in a control chart.  Or at the very least plot it over time.  This post has hopefully made it clear that data has no meaning without context, and that you need a way to separate signals (special causes) from noise (common cause variation).  That's why control charts were invented!

5. Don't use numerical targets.  They're arbitrary and make performance worse.  If you want to know why, have a read of my previous post on the subject.


Further reading

• I cannot recommend Understanding Variation by Donald Wheeler highly enough.  It will change how you look at and interpret performance information forever.
• Samantha Riley from NHS Improvement has been doing some fantastic campaigning for better measurement in healthcare, highlighting the many benefits of control charts.  You can find her on Twitter @samriley
• Police Inspector Simon Guilfoyle used to write a superb blog, and also a book, on using the right measures, measured right.  This is one of my favourites of his posts.
• Lean expert and writer Mark Graban recently wrote an excellent article on how to React Less and Improve More by Using SPC More Effectively.  His recent 15 minute talk on the same subject is also well worth a watch.
• Vanguard have written a clear and concise guide to understanding and creating control charts (or 'capability charts' as they prefer to call them).

9 reasons why targets make performance worse

"When management sets targets and makes people's jobs dependant on meeting them, they will likely meet the targets  – even if they have to destroy the enterprise to do it" 

– W Edwards Deming

If you're in the UK, you'll be aware of the Windrush Scandal. The Home Office threatened the children of Commonwealth immigrants (mainly from the Caribbean) who arrived before 1973 with possible deportation if they couldn't prove their immigration status.

Something that contributed to the scandal was the Home Office setting "a target of achieving 12,800 enforced returns in 2017-18".  Much has been written about whether the targets existed, and if certain people in charge know about them. 

This post isn't about that.  Today I'm writing about the problems with targets themselves.  When organisations set arbitrary numerical 'performance' targets, which people or teams are judged by. 

Here are 9 reasons why targets make performance worse:

1. They narrow focus, so people concentrate on doing only what achieves the target.  This isn't the same as doing the right thing for the customer or citizen. 

For example, schools would give disproportionate attention to pupils expected to get a C or a D grade, as their target is pupils getting C or above. 

In hospitals, doctors were diverted from treating seriously ill patients to ones with minor problems in order to meet 4-hour waiting time targets.  As a result "people were left for hours covered in blood and without pain relief".   

Or Police didn't act upon warnings about child sex grooming because they were told by management to prioritise robbery and car theft, as that's what achieves the targets. 

2. People cheat so they meet their targets.  Studies have shown this.

Staff at an outsourced Police control room were making 999 calls at quiet times in order to meet their target of answering 92% of calls within 10 seconds. 

Confession time – in my formative years I did something similar.  I was working on a call centre, and we had an average call handling target.  Me and a couple of colleagues worked out that calling each other and quickly hanging up was an easy way to meet our targets.  We were using our ingenuity to meet arbitrary numbers, instead of helping the customer.

3. Cherry picking. I was working with a housing repairs service.  Tradespeople were set targets for how many jobs they get through in a day.  This created a behaviour called 'sponge knocking'.  If a job looked like it would take a long time – and risk not achieving the daily target – they'd silently push a 'sorry we missed you' card through the letterbox, and scarper.

The UK government's troubled families programme was reported to have a 99% success rate of turning lives around.  However, investigations showed some councils were picking the families most likely to meet the success criteria, and not working with the ones that needed the most support. 

4. People lie.  For example, traffic wardens were fabricating evidence in order to issue parking tickets, for fear of losing their jobs if they didn't meet their target.   

5. Statistics are manipulated.  In the brilliant US crime drama The Wire they use the term 'juking the stats'.  This is brought to life in the 1.5 minute clip below (contains swearing).

This isn't just the stuff of TV drama.  For example, juking the stats has happened in the UK Police force, and at hospitals.  

6. They cause student syndrome (when a student only starts writing an essay at the last possible moment before it's deadline).  When you apply for planning permission at your local council, they'll have a government target to meet of 8 weeks to decide your application.  The chart below – from one council I worked at – shows the large proportion of applications were decided in week 7 or 8. 

It might be possible to decide the application earlier, but as far as performance measures are concerned, it doesn't matter as long as it was done in under 8 weeks. 

As a different council found: "to meet these targets, applications would get refused if they were unacceptable and the deadline was approaching. [This] meant that the applicant suffered delay, additional costs and frustration.... The Council in turn incurred additional costs either defending planning appeals or processing a second planning application”.

I once did similar analysis looking at complaints, with a 15 day response target.  No prizes for guessing which day most of the complaints were responded to on.   

7. Staff get sick.  Targets put people under pressure to meet arbitrary numbers, which causes stress. Police Officers felt "almost continually under threat of being blamed and subsequently punished for failing to hit targets".  This does not create an environment that's good for people's health. 

I've worked with call centre staff who had average call handling targets to meet.  They hated not being able to help the customer because their manager wanted them to end the call. 

At a target-driven DWP call centre, mental health-related absences tripled.  At the same government department, staff went on strike because "We are being prevented from providing good quality service because of unnecessary and unrealistic targets."

8. People do unethical stuff.  Targets are an extrinsic motivator (coming from outside the individual).  Studies have shown that extrinsic motivators undermine intrinsic motivation. 

Sometimes people do the wrong thing in order to avoid punitive consequences.  Like in this DWP example, where the employee is clearly upset.  They want to do the right thing, but at the same time they need to survive in a bad system.  

There are other examples, such as PPI mis-selling, where people are doing the wrong thing because the target is attached to a bonus (financial incentives act like a turbo-boost to targets). 

Then there was the Wells Fargo fraud in the US, where staff at the bank sold customers things they didn't ask for, in order to meet targets.  This also shows how arbitrary numerical targets are.  When John Stumpf, the CEO, was questioned about why staff had a sales target of eight financial products per customer, he said he chose the number because "eight rhymes with great". 

9. Targets can kill people.  A study looking at targets in the NHS found patients were required "to wait in queues of ambulances outside A&E Departments until the hospital in question was confident that that patient could be seen within four hours [the waiting time target]".  In one tragic instance, this practice led to the death of a 16 year old boy. 

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I'm not blaming the people who are working to the targets.  When a manager, government, or someone in authority sets a target, people will tend to presume it's right.  The Milgram experiment showed us that.

People focus on meeting targets to avoid getting grief from their boss, to make sure they don't get sacked, or to secure a bonus.  We all have bills to pay, and can't afford to risk losing our income. 

To quote again from Deming: "A bad system will beat a good person every time".  Or to quote from John Little: "Targets turn good people in to liars and cheats". 

My question to anyone reading this is – given all the points above – why do people continue to think it's a good idea to set targets?

What are your thoughts?  Please feel free to comment below, or share this post with someone who could be interested.