Twitter user @Wiggies13 responded to this rallying cry and sent me the following gem from a council website…
‘Percentage of relevant land and highway assessed as having deposits of dog fouling that fall below an acceptable level’.
And just to prove I didn’t make it up, here’s the screen shot:
As, you can see, this particular council has apparently excelled in keeping its ‘relevant land and highway’ completely free of dog muck. Quarterly performance figures indicate they consistently SMASH their 1% target. I would be confident in skipping barefoot along their roadside verges any day of the week with performance like that. It must be a dump-free Utopia.
On a serious note, you can’t knock anyone for wanting to rid the streets of steaming dog turds, but why have a numerical target for it? How does the target’s existence help those charged with locating and eliminating said detritus?
Other questions that spring to mind are:
- What is an ‘acceptable level’ of dog fouling? (I’d suggest ‘none’ if you’re the unlucky person who steps in it, especially if wearing flip-flops).
- Who decides where the surveys are carried out and how extensive are they?
- How is the percentage score calculated from the four national Keep Britain Tidy survey classifications of ‘None’ / ‘Light’ / ‘Significant’ / Heavy’, which this council says form the basis of its turd inspection criteria?
- Has a dog poo ever been sighted pre 2011?
Well rather than speculate, I thought I’d phone up the department in question to find out more…
I spoke to a most helpful chap who told me that apparently it all emanates from government data requirements. Unfortunately, he was unable to be more specific or answer any of my questions about the origins of the target. He did however say he’d get someone who could answer my queries to phone me back. When they do, I’ll update the blog.
I suppose the ultimate test of this pooey performance indicator is whether it meets the criteria for an effective measure, i.e. -
- Do the data as presented provide useful information about the current performance of the system?
- Does the performance indicator help identify opportunities for improving the system?
- Does it help the workers to achieve purpose from the service user’s perspective? (i.e. finding the offending material and removing it quickly. Perhaps even preventing a reoccurrence. There’s a thought).
In other words, does the screenshot tell us anything useful, or help the council continually improve their efforts to rid our verges of this horrible brown scourge (or white, if you remember those ones)?
I leave you to decide for yourself.
On a separate note, the same council also posts performance data relating to planning applications. Here’s the screenshot:
As you can see, the planning department works to an eight week target. Oh wait – the target isn’t eight weeks after all; it’s to hit the eight week target 87% of the time! (Or 88% if the application was made before the first quarter of the 2011-2012 performance year). What’s that all about then? An arbitrary numerical target against an arbitrary numerical target. Genius.
Typically, nothing about this mode of performance measurement takes into account the actual capabilities of the system or aids the planning department in meeting predictable levels of demand. (The fact that the department seems to consistently perform at a rate well below the arbitrary target certainly appears to indicate this). The problem is that data ignore such frivolities as numerical targets, and nothing about the target’s existence increases the capacity of the department, or improves service delivery.
Contrast this with a council planning department I visited this week in Wolverhampton, where they have done away with their targets and redesigned their system, simply aiming to achieve purpose as quickly and effectively as possible. What used to happen was that applications tended to be ratified immediately before the target date. Guess what happens now? Well, their total end-to-end time has been obliterated and one member of the team told me that the last application he handled was done and dusted in four days.
It goes to show that such astounding improvements in performance require a different approach, along with a different mindset. Tinkering around the edges of the system, playing with definitions, or introducing arbitrary numerical targets do not help achieve purpose.
As they say, you can’t polish a turd.