Alternative Measurement of Order Fulfillment Rate

Are you always able to meet all the demands of your customers? Or even if you frequently experience where your customers find products they want are not available in your place because the stock is empty? how much well you can meet your customer demands, but does it also have the right measurements?

I found a company that recognizes that the fulfillment of its customers up to 98% or more. However when I try to check through the survey it appears that the perception of customers said that they ordered the products are often empty. Although not many, but the 98% figure seems still questionable accuracy.
Definition

Order fulfillment rate (OFR) is one of the main measures in the field of logistics in the trading industry. Easy definition is what level of demand can be met against the total demand coming. For example, in 1000 there is recorded a month demand of a product A, but within a month the only company able to meet 900. This means that the fulfillment company to only 90% of market demand. It is very common when we want to buy a product of his stock was exhausted or was empty, so we request falls within the range of 10% of requests that can not be met.

Order Fulfillment Rate - OFR is a measure of the level of service, however it turns out there is a demand that can not be served and it is an "Error". Ideally a company wants to implement the Order Fulfillment Rate OFR is high, even up to 100%, but often it can not be achieved.
Causes of Low Order Fulfillment Rate OFR

The frequent occurrence to find customers in an empty stock outlet is caused by many things, but most often due to events such as:

1. Soaring demand exceeds the level of demand in the previous ordinary condition. For example, demand for product A is usually only about 100 per day, but due to certain conditions as a result of seasonal promotional requests per day to 200 and even 500 though. So that the sudden demand for many of these can not be anticipated in advance by the seller.
2. Bad inventory planning. Although no single theory that can guarantee 100% accuracy of demand in the future, but to face the demands of its ups and downs can be anticipated by a good inventory planning model. Rigidity can lead to inventory planning models can not fulfill the demand that suddenly appeared. As a result the customer is not satisfied and will not come back because they thought that the stock supplied is incomplete.
3. Scarcity of the product due to the limited production. The situation is similar to point number one, except that in these conditions the number of requests it but instead it decreased supply. Scarcity may be the result of problems in the production process or product is designed to be discontinued.

Looking at the above causes a lot of companies are setting the standard service level Order Fulfillment Rate OFR as a major. For that we need to see how such measurements may occur.
Measuring the OFR

To get the OFR is the most important component is the "Record of a request". If every customer who came to ordering we always record what they want, then we can easily obtain the total number of customer requests.

Keep track of all requests means good record of all requests are fulfilled and we can not be met. There is currently no technology that can really identify all the demand of customers, because it all depends on "the record" of the team "front liners" who serve customer demand. Unless otherwise noted their own customer needs and then delivered online directly connected with our system, then the recording can be done accurately.

The problem for Order Fulfillment Rate OFR is often also the front liners measuring the performance of the team, then came the reluctance of the front liners team to record a clear demand from customers of his stock is empty. Even if not directly measure the performance of the team front liners, but can also occur conspiracy between the sales team with the warehouse team to continue to generate appropriate performance measurement.

The problem lies not only in "error" of the human side, but also from the definition. If the same customer order are the same the next day and the stock is still empty, whether it will also be counted as a different query? For example, customer X messages yesterday 10 pieces of product A and the stock is not available, so ideally it would be calculated as there were 10 pieces of product A can not be met. The next day he did the same orders, but stocks are still empty, whether it will also be counted as another query so that the total demand that is recorded can not be met by 20 pieces. In fact we were not able to distinguish whether the 10 pieces of product A is indeed the same needs or different needs. Policy records unclear requests will result in the team's perception of different sales when they wanted to record the customer's request.
Alternative Measurement of Order Fulfillment RateOFR

By looking at the lack of perfection of the measurements the Order Fulfillment Rate (OFR), it would require additional measures to further assure the accuracy of the services provided to customers. If the Order Fulfillment Rate (OFR) is a variable that accounted for the total demand coming, so in this measurement will be seen from the point of view of stock availability to meet customer needs.

Alternative measures will be more complicated but is actually more accurate because it does not depend on the accuracy of the sales team noted that the request came. The logic is quite simple, because we simply look at the periodic / daily stock positions that are available compared with the average daily demand.

• The first component is the daily stock position should always be noted. Stock position can be an initial stock or stock end of the day. This election will be influential to the second component. But the most important on the first component of this stock is a stock which recorded that really can be sold, that is not a stock that is damaged or not yet ready for sale, even still on the way / order.
• The second component is the minimum stock levels should be available to meet some future period. Because the demand is often difficult to predict, then we may decide that the stock should be available to serve a minimum request up to 3 days. Conjunction with the first component is that if we set out to record the initial stock of the day, the calculation includes the next three days the same day or factor is 3. Meanwhile, if the note is the final stock, then the calculation of three days not included the same day or the multiplier was only 2. Where basically, it's a bit complicated but is actually quite logically explained to be understood.
• The third component is the average daily sales or daily demand can be met. We simply find the average daily demand can be met within the last 3 months for example. Determination of 3 months, 2 months, or only one month is highly dependent on the industry and also the comfort of our own to establish the average rate that is considered most appropriate to reflect the daily demand.

If the three components above are met, then we are ready with the calculations. If you provide a product range of more than one or even very many of the hundreds or even thousands of products, then I suggest to use the product as its multiplier in order to obtain a single figure. This calculation is performed for each type of product for later aggregated with other types of products.