When implementing some solutions, like in continuous improvement, project managers better take care about the frustrations related to the S curve.
The “S curve” is the shape of the performance curve over time. It describes a latency (t1) before the performance p1 takes off after the improvements have been implemented, then a more or less steep rise before stabilization at the new level of performance p2.
This latency time after the first improvements until improvements become noticeable has several possible causes and can pose different problems.
The most trivial reason for a lack of significant effects after a while is that the solutions put in place do not produce the expected effects. It is therefore advised to estimate in advance, at the moment improvements are implemented, when the effects should be noticeable, in order to have an alert when the estimated time is elapsed.
Another trivial reason is a long cycle time. This may be the case with lengthy process of transformation, processing time or latency inherent to the process before the success of the operation can be judged. Typically, these are technical lead times, time required for chemical or biological transformation processes or “responsiveness” from third-party organizations, etc.
Let’s assume that in the process below the improvement is a new setting at machine R1 and the effect can only be measured or assessed before the entrance of machine R6, it will take all the time for a sample to travel the whole process from R1 to R6, including the buffer between R2 and R3.
Similar cases can be found in chemistry or biology when reactions need some time to happen, in curing or drying processes, etc.
The delay may be due to the improvement process itself, which may require several steps such as initial training, implementation of the first improvements, measurement of their effects and time to analyze them.
Another reason, that may be coupled with the previous one, is Little’s law. It states that the lead time through an inventory or queue of work in progress (WIP) is equal to the value of this inventory divided by the average consumption. This means that if the improvement occurs at a point decoupled from the measurement point of its effectiveness by either inventory or WIP, the effect must first propagate through the queue before it can be detected. Everything else being kept equal.
Please note that this delayed improvement phenomenon or “S curve” described here in the context of continuous improvement can be found in the implementation of any project.
This discrepancy can be a problem for Top Management awaiting return on investment and wishing it as quick as possible. This is all the more true if the activity is highly competitive because an improvement can determine the competitiveness and/or profitability of a project, an offer or even of the whole organization.
It is therefore recommended that the project leader reminds the likeness or certainty of the S curve, even to the managers pretending to know it. Under pressure of business they tend to “forget” it.
The second problem with delayed effects concerns those closer to execution who expect some benefits from improvement, such as problem solving, elimination of irritants, better ergonomics, etc.
Assuming that the operational, shopfloor staff have been associated with the improvement, their frustration and their impatience to see changes is even more important. Without promptly demonstrating that “it works”, there is a significant risk of losing their fate, attention and motivation.
In order to prevent this, the project manager must choose intermediate objectives in short intervals in order to be able to communicate frequently on small successes.
The recommendation is to look for a weekly interval and not exceed the month. The week represents a familiar time frame to operational staff, and the month being, in my opinion, the maximum limit. Beyond the month it usually becomes an abstraction and attention gets lost.