Targets Don’t Work!

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A management education

21 years ago I was a bright young thing.  I was single, had a good job and I was determined to make my way in the world.  I am a strong believer in education so I decided to study for an MBA.  I learnt about:

  • Operations
  • Marketing
  • Information Technology
  • Human Resources
  • Finance

I also learnt some more esoteric stuff.  Macroeconomics and International Business Strategy spring to mind.  As I said, it was fascinating…  Mostly.

Things I wasn’t taught

There was one obvious omission from the syllabus.  I wasn’t taught about Management by Objectives.  For some reason, target setting wasn’t on the list.  This was odd, because target setting is one of (if not the) primary tools used by managers.

An academic perspective

Coincidentally, target setting was a hot topic 21 years ago.  In 1995 the economist Peter Smith wrote an oft-referenced paper about targets. It has a rather catchy title:

On the unintended consequences of publishing performance data in the public sector

Doctor — now Professor — Smith was particularly interested in the Health Service and the way politicians managed performance by setting targets.  He wrote a list of all the problems he could find with this approach.  It was a long list.  Read it here.  To simplify it he grouped the problems.  They went like this:

1. Tunnel vision:

Focusing on the variables within a performance indicator, whilst excluding anything that is outside it.

An example was the practice employing a “Hello Nurse” in accident and emergency.  Her primary job was to meet and log the arrival of every new patient.  Managers could then be sure that the waiting time target in A&E wasn’t exceeded.   Unfortunately this took the nurses away from more traditional nursing tasks.

2. Sub-optimisation:

Making sure that local objectives are hit regardless of the impact on the wider organisation.

Local authorities had targets to keep the cost of elderly care homes down.  They did this by keeping bed occupancy levels high.  This resulted in a waiting list of patients. 

These elderly patients often end up “Bed Blocking”; spending long periods of time in hospital beds because there was nowhere else to go. 

Needless to say a hospital bed was more expensive than one in a care home.  

3. Myopia:

Focusing on the immediate issues whilst ignoring the long-term implications.

Reducing the money spent training doctors helped the authorities to hit their short-term budgetary goals.  The ensuing shortage of doctors was a problem for another year.

4. Misrepresentation:

Manipulating the numbers so things look better than they really were.

“Finished Consultant Episodes” was a measure of productivity.  The more F.C.E.s there were the more productive a hospital was.  But how do you define “finished”?  If a patient is passed from one consultant to another because the first couldn’t treat them, was that one episode or two?

5. Gaming:

Changing your approach to create a strategic advantage

Possibly the most insidious way to deal with targets.

The NHS “efficiency” target ratcheted up every year that a health authority met it.  This was a way of ensuring that cost benefits were locked in and performance continued to improve.

Consequently it was in managers interests to make sure that they fell short of the target every year, but only just.  The trick was to be close enough not to receive any “help”, but not so close that you inadvertently beat the target and created a higher bar for the following year.  Why create yourself a problem?

Ground breaking research?

Now this is fascinating stuff (if only when compared to a 6kg tome on international business strategy).

It is the sort of material a bright young thing would like to learn about on his management programme.  I guess I was just unlucky in terms of timing.  If I had done the course a couple of years later perhaps this would have been included in the syllabus…

Probably not

Let’s be honest, knowledge is built on knowledge, Professor Smith’s ideas were not newfangled thinking. Twenty years earlier in 1975 (I was in shorts then) Steven Kerr wrote an article for the academy of management entitled: On the Folly of Rewarding A While Hoping for B.

The paper covers very similar ground.

Targets don’t work

This isn’t new news, nor was it new 21 years ago, 41 years ago or I suspect 101 years ago.  It is human nature.

So why do we continue to manage by targets and objectives?

I have two theories:

  1. Most people don’t think too hard and assume that management by objectives works.
  2. The act of target setting is gaming in its own right.  Any politician or senior manager who sets a target hopes fervently that his team will beat it so he can show what a great job he has done.  So it is in the target setters interest to turn a blind eye to any “strange” behaviour.  That way he can declare success and move on.

Targets don’t work.  Or do they?

No, we don’t cheat. And even if we did, I’d never tell you ~ Tommy Lasorda

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Image by Craig Sunter

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Republished with author's permission from original post.

James Lawther
James Lawther is a middle-aged middle manager. To reach this highly elevated position he has worked for many organisations, from supermarkets to tax collectors and has had multiple roles from running a night shift to doing operational research. He gets upset by operations that don't work and mildly apoplectic about poor customer service.

3 COMMENTS

  1. Interesting, and fun, post. Lots to agree with here, especially regarding problems associated with targeting (all true). But, bigger picture, targets can work – if they are truly consequential, can be monitored as to (potential and actual) negative domino or ripple effect within the organization, and can be supported by all. Some of this is certainly situational and industry-specific. One example of a worthwhile enterprise target is reduction of voluntary customer churn, a big issue in subscription services, and in industries like ISP, cable, and telecom.

  2. Agree with you James. Imposed targets – or metrics – don’t often work because they’re agreed upon from the business perspective, or upper management. They come from the top down, which is a place that’s often disconnected from everyday interactions with customers. My experience with two large metric-driven companies showed an intent to create business results rather than customer-desired results. “In order to get x renewals, you must get y numbers of interactions.” Or, “Average call time does not exceed 30 seconds.” Inevitably, once those kinds of metrics are laid out, employees will figure out ways to “game them” – meet them without producing the intended business result (keeping customers).
    On the other hand, I’ve seen favorable results when the customer-facing team co-creates the metrics.

  3. Managers can be misguided when creating performance metrics. I read specific situations and often think, ‘be careful what you wish for, you might get it.’ And when it comes to pay-for-performance, the same applies. Just swap ‘wish’ for ‘pay.’

    The Cobra Effect https://en.wikipedia.org/wiki/Cobra_effect is probably the best documented instance of performance metrics that backfired. To solve a cobra infestation problem in colonial India, the British government put a bounty on the snakes. That encouraged people to breed cobras so they could be killed for money, which produced . . . more snakes.

    As much as anything else, targets are an essential way for management to communicate to employees which behaviors and activities are valuable to the company. All the more reason they must be carefully defined, checked and double-checked. For example, when companies establish a performance target of two minutes for call resolution, they are communicating to employees to behave in ways that might be antithetical to customer happiness. In pursuit of that target, employees believe that, no matter what, make calls short! Who can blame them? Again, managers must always exercise care in what they wish for.

    Further, companies can wrongly create some targets as proxy measures when the underlying logic is flawed. This occurs frequently, and the instances can sometimes be difficult to smoke out. Common examples are metrics such as – Ridership as a proxy for Passenger loyalty in a transit system. Grade point average as a proxy for student effort in a school. Quota attainment as a proxy for skill level in a salesperson. In each of these instances, the latter cannot be inferred from the former. But they often are.

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