The Bee Hive

Traditional measures of accuracy can be a double-edged sword. While their objective is to confirm cost or inventory accuracy, these methods often serve as a disincentive by inadvertently discouraging an all-out effort to find and eliminate the real root of the problem. When too many inaccuracies are found, the company’s calculated inventory accuracy drops, and this reflects poorly on the worker or workers responsible.

In this instance, the manufacturer needs to understand that inventory accuracy is only an indicator of performance and is not a true measure of the actual process. By definition, performance measures track a process, but something must have been performed in order to have a performance measure. Cycle counting is a process and has a performance measure related to its effectiveness.

Traditionally, companies judge a cycle-counting process based upon a measure of inventory accuracy. The more the process confirms the accuracy of the company’s inventory, the higher the process’ measure of effectiveness - or so it would seem.

Challenging The Traditional Measures

Consider the results of the cycle counts shown below. The mix of counts is representative of the category mix in order to suggest a level of inventory accuracy across all parts. Compare the total calculated accuracy of 98.7% with the following weighted calculation (there is more than one way to calculate accuracy):

Weighted Inventory Accuracy=[(99.9% * 1,000) + (99.0% * 3000) + (97.5% * 16,000)] / 20000 = 97.8%

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The major problem with the traditional process is that the measure confirms the inventory is already accurate. In fact, the highest measure is obtained only by not finding any inaccurate parts. The company’s inventory accuracy measure is actually penalized if inaccurate parts are found. Everyone knows more inaccurate parts exist than are being found, but there is no incentive to identify the causes of inaccuracy.

Consider the following scenario: Management has set a goal of 99.0% accuracy by count for category B. For an inventory containing 3,000 items, a minimum of 2,970 parts must be 100% accurate by count (or 990 0f 1,000 when counted each month to meet a quarterly cycle.) If an inventory manager discovers more than 10 inaccurate parts during any month, the B-item accuracy level will fall below 99%. Therefore, it is to this manager’s benefit to ensure that the cycle count team never discovers more than 1% inaccurate parts based on the number of parts counted.

In turn, the lack of incentive to find more than a given number of inaccurate parts then restricts production’s ability to schedule effectively; from experience, production knows that more than 10 inaccurate B-item parts are on hand at any given time. Some companies would rather delude themselves about their inventory accuracy level rather than acknowledge their processes are out of control.

Using dollar accuracy targets - rather than item accuracy counts - can mitigate the situation. When dollar overages (too much inventory) offset shortages (too little inventory), invemtory control can locate and correct more incorrect parts than is possible with an absolute count measure - as long as the dollars offset. The problem with this logic is that parts with an excess quantity don’t cause scheduling problems, but parts with shortages do. The inventory manager knows this but cannot risk exceeding the minimum boundary established by the measure. In effect, the measure restricts the number of inaccurate parts that can be discovered and fixed during any counting period. The measure drives the process - to the detriment of the company.

The real goal of an accuracy improvement program (as opposed to the cycle couonting program) is not to achieve a management-specified minimum level of inventory accuracy by ABC category. The goal is to achieve 100% accuracy of all parts by eliminating the possibility of inaccuracy in the first place. This means systematically identifying and eliminating all causes of inaccuracy.

With a traditional counting program, a 99% B-item inventory accuracy measure implies that 99% of the B-item parts are 100% accurate, based on the number of B-item parts samples counted during the previous period. In reality, that 99% is less a measure of inventory accuracy and more a measure of how diligent the inventory manager is at translating job performance measurements into a perception of inventory accuracy.

Finding The Causes

To maximize inventory accuracy, companies must measure the process itself. This requires establishing a performance measure that evaluates the inventory manager based on his or her ability to identify and eliminate causes of inventory accuracy. The more the causes of inaccuracy that are found and eliminated, the higher the performance of the process.

The performance measure must focus on identifying and resolving problems, crossing functional areas and even organizational boundaries in the process. Therefore, a team made up of a few hourly employees who do cycle counting everyday is inappropriate; the causes of errors are not restricted to the storeroom.

Actively identifying the causes of inaccuracy and tracking down their effect on inventory is a key difference between a performance measure and an indicator of inventory accuracy. The former focuses directly on the problems, while the latter simply monitors the results of counting a sample each period. When the emphasis is placed on identifying and eliminating errors, rather than the actual counting process itself, inventory accuracy becomes a byproduct of the process, not the sole measure of its effectiveness.

Changing the emphasis of a cycle counting program can uncover conflicting views of inventory accuracy within the company itself, as identified in the table below.

 

As shown, production benefits the most from an aggressive process aimed at eliminating inventory inaccuracies, compared to a traditional cycle counting process. As far as production is concerned, any accuracy level less than 100% means they never know which parts are likely to be inaccurate of all of those permitted to be inaccurate. In such an environment, all parts become suspect.

In contrast, as the first table indocates, 1000 counts per month are required for the B-item parts. No more than 10 inaccurate parts can be detected in order to maintain a B-item inventory accuracy level of 99%. At six minutes per count and $15 per operator per hour, the cost to not find more than 10 inaccurate B-item parts during the month and still meet the cyclical counting requirements is $1,500 (1,000 counts @ $15 per hour /10 counts per hour). The company is spending $150 ($1,500/10 inaccurate parts) to find and correct each B-item inaccuracy. This is the equivalent of investing 10 hours per incidence of inaccuracy.

Put another way, the company is wasting $4,934 each month (3,289 counts @ $15 per hoour/10 counts per hour) to simply confirm what it believes to be true. This calculation points to the ineffectiveness of the traditional process. Senior management should view this as a dismal indicator of the company’s effectiveness at spending valuable resources to identify and correct causes of inaccuracy.

A Real Measure

As these numbers demonstrate, indiscriminate counting is not the answer to permanently improving inventory accuracy. Counting is simply too random to be cost-effective once a company’s accuracy reaches a level that supports ERP and MRPII.

Measuring the effectiveness of the process itself is much more indicative of how effectively the inventory manager is targetting parts for counting. The lower the value, the more the company is wasting time and money because inaccurate parts are being missed.

Eliminating the causes of inaccuracies must be the true focus, and control groups are the means by which a company can identify those causes.  Imagine the progress that could be made by counting 3,334 parts in a month’s time, all of which were associated with control groups that targetted particular causes of inaccuracy.

Improving the inventory inaccuracy reduction measure is the target of an inventory accuracy improvement process, and is calculated as follows:

Inventory Inaccuracy Reduction= Inaccurate Parts Corrected/100% of Parts Counted

This measure works because the inventory manager is forced to concentrate on inaccurate parts and make a commitment to identifying and eliminating the causes of inaccuracy. It is in sharp contrast to counting known accurate parts, such as A-items or stockout parts that provide a false measure of accuracy. When done correctly, the inventory accuracy process will improve and sustain itself under normal operating conditions, at what may be a fraction of the cost of a cyclical counting program.