Current productivity fog

All managers need to get the most out of all costly input resources they employ:

  1. In the private sector, to beat their competition in meeting customers’ needs whilst minimising unit costs and maximising sales and profit margins
  2. In the public sector, to optimise the number and quality of services on offer

However, most managers do not measure productivity well – they have plenty of financial productivity measures, perhaps too many, but little else – the result is most of them are far from getting the most out of their existing input resources

Why so – why should simple ratios of outputs over inputs not be found everywhere?

Survey after survey produce the same results – managers think productivity is too difficult to measure, not a boardroom issue, not the main determinant of their financial success, relevant only to the shop-floor or someone else’s problem

At the same time, leading management organisations and business schools ignore the subject – there’s no productivity headings or focus on their websites, nor any courses offered on it either – a sure indicator of the true importance they attach to the subject

So, given this paucity of measures and lack of interest at the top, is it any wonder that current productivity growth in most organisations and nations is (apparently) flat-lining

A big change in management attitudes is urgently needed

And, for this to happen, six major failings with existing productivity measures need to be addressed:

  1. A partial, not total, productivity picture painted:
  • Valued outputs nowadays are not just sales volumes (cars or insurance policies, say) but quality and service level outcomes for customers that go with those sales – yet performance measures that cover the latter are as rare as hens’ teeth
  • Wasted outputs i.e. repairs or replacements for no extra revenue, say – are often included in total output figures
  • Costly inputs include labour, materials, capex and IT systems – however, labour volumes (hours or FTEs) are the only ones measured – labour quality (i.e. skills, experience, education levels, qualifications) can make a big difference to productivity levels but is ignored
  • Wasted inputs – the time and resources spent on work which was not right first time, say, are usually submerged in total input figures
  • Hence, most productivity measures quoted can be seriously flawed and offer only a fraction of the ‘big performance picture’ needed – as a result, many productivity problems and improvement opportunities pass by unseen

2. A lack of useful benchmarks:

  • External best practice information is usually only sought by better private sector companies – and rarely by any public sector unit, even though such information should be in the public domain and readily available to them
  • However, caution is needed before copying another firm’s best practices – there will always be differences preventing exact copying but knowing others do things differently with better results should make managers ask whether they could be doing as well
  • Most organisations have no idea what their overall output capacity is because of the variety of goods and/ or services they offer – this means they don’t know how much more they could do with the resources they’ve already got – as a result, many invest big money in extra capacity well before needed

3. A lack of regular, timely measures:

  • Important performance information is often produced quarterly yet a manager may need it weekly, say, for her to take appropriate action in good time

4. Few clear links down/ up to lower/ higher levels of management:

  • Managers cannot drill down their set of measures to identify problem causes – nor up and across to those of others and check on the impact of any proposed changes
  • Different management levels often use quite different performance measures, so they don’t talk the same language, so they don’t understand each others’ problems
  • There should be just one set of performance measures linking all managers to all levels

5. Too short a time horizon often used:

  • Some companies have to invest heavily upfront (e.g. oil wells, coal mines), make big money with stuff that’s easy to extract, then less and less per barrel or ton as extraction becomes more difficult until all peters out
  • In such cases, whole-life productivity measures are needed

6. Too much aggregation destroys value of information:

  • One cannot mix quite different outputs, or inputs, to calculate overall productivity levels unless they’re converted into cash
  • This aggregation problem increases the higher one goes in any organisation
  • It’s worse still at national level where official productivity measures have been described as ‘pointless and unusable’ – they spread misinformation, not knowledge

Conclusions:

  • Overall, productivity must be measured well if it is to be managed well
  • At present, few managers do this well – most are ‘flying blind’ and so not in good control
  • Managers need to make their decisions based on good performance data, not opinions
  • It’s at organisation level where most (80%?) national productivity improvement potential lies – and it’s managers, not workers, at that level who have the power to make the improvements necessary
  • But, to do this, they first need to know where, when and how to act

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