To investigate or not to investigate before management decides whether or not to investigate a particular variance, there are a number of factors that ought to be considered.
o Materiality. Small variations in a single time are bound to occur and are unlikely to be significant. Obtaining and’explanation’is likely to be time-consuming and irritating from the manager concerned. The explanation will offer be’chance’which is not, in any case, particularly helpful. For such variations further investigation is not worthwhile.
o Controllable. Controllable must also influence the decision whether to investigate further. When there is general global price increase in the price increase in the price of an important raw material there is not anything that can be done internally to control the effect of this. In case a central decision is made to award all examples a 10% increase in salary, staff costs in division A will increase by this amount and variance is not controllable by division A’s manager. Uncontrollable

If, say, an efficiency variance is $ 1,000 adverse per month 1, the obvious conclusion is that the process is out of control and that corrective action must be taken. This may be right but what if the same variance is $1,000 adverse every month? The trend indicates that the process is in control and the standard has been wrongly set. Suppose, however, that the same variance is consistently $1,000 advise for each of the first six months of the year but that manufacturing has steadily fallen form 100 units per month 1 to 2 65 units by month6.The variance trend in absolute terms is constant, but relative to the number of units generated, efficiency has tot steadily worse.
Management signals from variances trend information.
Variance analysis is a mend of assessing performance, but it is only a method of signaling to management areas of possible weakness where control action might be necessary. It doesn’t provide a ready-made diagnosis of faults, nor does it supply management with a reedy made indication of what action has to be taken. It only highlights things for potential investigation.
Individual variances should not be looked at in isolation. We now know in addition that set of variances must be scrutinized for a variety of successive periods if their entire significance is to be appreciated.
Here are some of the signals that may be extracted form variance trend information,
O Materials price variances may be favorable for a few months, then shift to adverse variances in the upcoming few weeks and so on. This may indicate that process are seasonal and perhaps stock can be built up it cheap seasons.
O Regular, perhaps fairly slight, increase in adverse rice variances usually indicates the functioning of general inflation. If desirable allowance can be made for general inflation when flexing the budget.
O Rapidly large increases in adverse price variances may suggest a scudded scarcity of a source.
O Gradually improving labour efficiency variances may signal the existences of a learning curve, or the success of a productivity bonus scheme. In either case opportunities must be sought to encourage the trend.
O Worsening trends in machine operating expenditures may show up that gear is deteriorating and will need repair or even replacement.
Interrelationships between variances
Quite possible, individual variances should not be looked at in isolation. calculate variance might be inter-related with another, and much of it could have happened only because the other, inter-related variance occurred too. When tow varies is interdependent (interrelated) one will usually be adverse and the other one favorable.

O Material price and usage-if cheaper materials are purchased to be able to obtain a favorable price variance, materials wastage may be higher and an adverse usage variance may occur. If the cheaper material is more difficult to handle, there might be an adverse labour efficiency variance too. If more expensive material is purchased, however the price variance will be adverse but the usage variance might favorable.