4.4 Formulating the system dynamics model
4.4.4 Area 4: Customer
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94 Convertors:
customer order placement = INT (RANDOM (697, 229894, 12)) inventory check = INVENTORY LEVEL - customer order placement Dimensional analysis:
Left hand side: [units/week]
Right hand side: [units/week – units/week] = [units/week]
Figure 4.29: Initial Customer orders and inventory checks
On analysis of the customer ordering data, it was found that there was a lot of variability with a standard deviation of 36799 units. As you would have noticed this variance is extremely high and caused some concern initially. The values however were obtained from historical data and validated against the mental database of individuals closely involved in the customer order taking process. Whilst it is recognized that there are behaviours which drives sales higher in certain parts of the month, quarter or year there exists randomness in the ordering process which is supported by the business experiencing a forecast accuracy lower then 50%. It was therefore decided that the equation used would be a random number generator with the minimum order size being 697 units and the maximum order size being 229894 units with a seed value of 12 as reflected within the equation found in Figure 4.29. The minimum and maximum values selected were derived from the numerical database that was used which covered data points spanning a 52 week period.
This was further assessed against the mental database of individuals interviewed who validated that this type of extreme values reflects reality. Given we are dealing with consumer units, no customer would order less then a full unit, hence the INT at the front end of the equation signifies that only integer values must be generated.
95 An inventory check is done to determine what portion of the order can be fulfilled from existing stock that is available. This is a straightforward subtraction of what stock is available in inventory versus what the customer required. This leads into the next portion of the sector, which looks at order confirmation. The units of measure used in the equations are consistent and hence dimensionally balanced.
order confirmation = IF (inventory check > 0) THEN customer order placement ELSE INVENTORY LEVEL
Dimensional analysis:
Left hand side: [units/week]
Right hand side: IF[units/week > 0] THEN[units/week] ELSE [units/week] = units/week Figure 4.30: Order confirmation
Order confirmation by definition describes the action taken by the organisation to verify to the customer the amount of stock that they would be receiving. As described by the equation in Figure 4:31 this can only be done once the inventory check is complete and is available in inventory is understood. Based on this either the full, partial or none of the order is confirmed.
In discussions with individuals during the data collection process, one of the strong themes that was communicated was that the variability seen in customer ordering is also a function of the behaviour seen from the sales team and customers. This behaviour is mostly driven by the organisations attempt to fulfill short term sales and turnover targets. This is more often then not achieved by selecting certain products across a multi-category organisation as these products
96 typically have a higher turnover. Later in this Chapter, I speak about working capital implications and forecast accuracy, which sits in the region of 50% to 60%. This type of behaviour will have a direct impact on these two leading organisational KPI’s. Whilst as a business it is understood that this is not per S&OP processes the attraction to meet short term goals is high. This short term focus then detracts from the core of S&OP, which is to focus on the 2 year period.
Once a customer order is confirmed, the distribution teams which includes both warehousing and transport logistics are required to execute the order. This leg of the process is illustrated in Figure 4.31.
Figure 4.31: Inside the distribution sector
At first glance, this sector seems to have two identical halves, which on closer examination can be seen to be different in that the left side has a convertor called standard deliveries and the right hand side has a convertor called special deliveries. The driver for this is a particular behavior that surfaces within the business. In most instances when a customer places an order a standard lead time to delivery is followed but in certain instances, normally when there is a sales drive, special deliveries are required in a shorter time frame and normally results in higher costs being incurred.
Both “customer deliveries1” and “customer deliveries2” feed into the outflow found in Figure 4.6.
97 I will start by explaining the “customer deliveries1” portion found on the left hand side.
Distribution of any product will have a lead time from the customer placing the order to the delivery of that order. Figure 4:32 highlights the inputs into the “lead time” convertor.
loading and delivery = 0.07 transport planning = 0.14 warehouse lead time = 0.14
lead time = loading and delivery + transport planning + warehouse lead time Dimensional analysis:
Left hand side: [weeks]
Right hand side: [weeks] + [weeks] + [weeks] = [weeks]
Figure 4.32: Understanding the lead time in a standard situation
The three main activities that make up the operation is the time taken within the warehouse to get the stock ready for dispatch, time taken to do transport planning and get a vehicle at the warehouse and the time taken to load the vehicle and deliver the products to the customer. Determining the lead time is therefore a summation of these three factors. The Figures used for the above are all constants, acquired from the numerical database of the organisation and validated against the mental database of the individuals interviewed. All Figures used have been converted to weeks as the uniform measure of time that ensures that the lead time equation is dimensionally balanced.
98 distribution service loss = 0.989
standard deliveries = 0.95
customer deliveries1= DELAY (order confirmation * distribution service loss * standard deliveries, lead time)
Dimensional analysis:
Left hand side: [units/week]
Right hand side: [units/week] * [factor] * [factor] = [units/week]
Figure 4.33: Customer deliveries under standard conditions
In order for the customer to get their delivery there are other factors besides the lead time, which needs to be taken into consideration. Given that no operation is perfect, losses are experienced during the process. The “distribution service loss” is a constant of 98.9% or 0.989, which essentially means that 98.9% of the customer order confirmed is actually delivered. The balance of 1.1% are losses experienced due to damages, stock not being found within the warehouse, theft, stock being delivered to the incorrect customer or stock not found in the vehicle on delivery. As explained previously most deliveries follows the standard process but there are occurrences when a special delivery is required. Based on the mental databases of individuals it was found that approximately 95% of the time a standard delivery was done, with the balance of 5% resulting in a special delivery. Figures used for the “distribution service loss” and “standard deliveries” are constants obtained from the numerical and mental databases. “customer deliveries1” is hence a multiplication of the order, service loss factor and standard delivery factor. The equation reflects a delay equivalent to the lead time as well.
99 The dimensional analysis check reflect that equation is balanced given the UoM in both the right hand and left hand side of the equation are equivalent making it credible.
We now get to the right hand side of the sector in which we find the “customer deliveries2”
convertor. Figure 4.34 below reflects the lead time make up in special situations and structurally looks identical to Figure 4.32.
loading and delivery 2 = 0.07
transport planning 2 = 0.07
warehouse lead time 2 = 0.07
lead time 2= loading and delivery 2 + transport planning 2 + warehouse lead time 2 Dimensional analysis:
Left hand side: [weeks]
Right hand side: [weeks] + [weeks] + [weeks] = [weeks]
Figure 4.34: Understanding the lead time in a special situation
A key difference in a special situation is that the lead times for transport planning and the warehouse are reduced by half. The overall lead is hence still a summation of the three elements shown in Figure 4.32 and is dimensionally balance.
100 distribution service loss = 0.989
special deliveries = 0.05
customer deliveries 2= DELAY (order confirmation * distribution service loss * special deliveries, lead time 2)
Dimensional analysis:
Left hand side: [units]
Right hand side: [units]*[factor]*[factor] = [units]
Figure 4.35: Customer deliveries under special conditions
As mentioned above it can be seen that 5% of the time special deliveries occur hence the shortened lead times in the warehouse and transport elements. These special deliveries are largely a factor of the organisation just coming into a positive stock balance and have to expedite orders or are attempting to reach a sales target in a given period of time. “customer deliveries2” is again a multiplication of the order, service loss factor and special delivery factor. The equation reflects a delay equivalent to the lead time as well. This equation follows the same format as that of
“customer deliveries1” and is dimensionally balanced.
The efficiency with which the customer ordering and distribution process is carried out to ensure delivery of the order on time and in full, is a measure of the service level achieved which will be discussed further in the management information system area.
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