Improvement science provides the theory, techniques and tools to reduce the cost of waste and to re-invest the savings in further improvement. But how much does waste cost us? How much can we expect to release to re-invest? The answer is deceptively simple to work out and decidedly alarming when we do.
We start with the conventional measurement of cost – the expenses – be they materials, direct labour, indirect labour, whatever. We just add up all the costs for a period of time to give the total spend – let us call that the stage cost. The next step requires some new thinking – it requires looking from the perspective of the job or customer – and following the path backwards from the intended outcome, recording what was done, how much resource-time and material it required and how much that required work actually cost. This is what one satisfied customer is prepared to pay for; so let us call this the required stream cost. We now just multiply the output or activity for the period of time by the required stream cost and we will call that the total stream cost. We now just compare the stage cost and the stream cost – the difference is the cost of waste – the cost of all the resources consumed that did not contribute to the intended outcome. The difference is usually large; the stream cost is typically only 20%-50% of the stage cost!
This may sound unbelieveable but it is true – and the only way to prove it to go and observe the process and do the calculation – just looking at our conventional finanical reports will not give us the answer. Once we do this simple experiment we will see the opportunity that Improvement Science offers – to reduce the cost of waste in a planned and predictable manner.
But if we are not prepared to challenge our assumptions by testing them against reality then we will deny ourselves that opportunity. The choice is ours.
One of the commonest assumptions we make is called the Flaw of Averages: the assumption that it is always valid to use averages when developing business cases. This assumption is incorrect. But it is not immediately obvious why it is incorrect and the explanation sounds counter-intuitive. So, one way to illustrate is with a real example and here is one that has been created using a process simulation tool – virtual reality: