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The concept of responsiveness


Responsiveness is the ability of a system or process to complete tasks within a given time frame. E.g. how quick can a business respond to customer demands? If customers are made to wait, they are turned into inventory, potentially resulting in a unpleasant customer experience. Any customer waiting time is also an indicator of a mismatch between supply and demand.

Concepts for solving waiting time problems can include increasing the capacity of the resource at the bottleneck as well as increasing process flexibility in order to ensure, that capacity is available at the right time. It has, however, to be kept in mind that waiting times are most often not driven by either the capacity or the flexibility of a process but rather by variability. Variability in the process flow (e.g. customers arriving at random) can lead to unwanted waiting times even when the implied utilization is clearly below 100%. If analysis builds solely on averages and fails to consider process variability, it can thus be wrongfully concluded that there is no waiting time, when, in fact, there is.

To solve this problem, new analysis methods are needed when dealing with process variability. It is noteworthy, that those methods are only requisite when a process has more capacity than demand – if demand exceeds capacity, it can be safely concluded that there will be waiting time even without looking at the process variability.

These lecture notes were taken during 2013 installment of the MOOC “An Introduction to Operations Management” taught by Prof. Dr. Christian Terwiesch of the Wharton Business School of the University of Pennsylvania at Coursera.org.

How to pick the optimal batch size?


If the batch size is so small, that the process step with the set-up time (assuming, that there is only one) becomes the bottleneck of the process, the process looses on overall efficiency. Thus, the batch size needs to be chosen in a way that assures, that it will not generate a new bottleneck.

If, however, the batch size is too big, any increase in capacity at the station with the set-up time (assuming, again, that there is only one) is ultimately of no use, because it will only lead to inventory piling up somewhere else in the process – wherever the bottleneck may be.

This goes to show, that the ideal batch size is one, in which the station with the set-up time has a processing time which is just identical to the process bottleneck. Only then will the batch size not lead to the creation of a new bottleneck or additional inventory pile-up. This is calculated as:

capacity determined by the batch size = capacity of the bottleneck

b / (s + b * p) = m / p

with:

b = batch size
s = set-up time
p = processing time
m = number of resources

These lecture notes were taken during 2013 installment of the MOOC “An Introduction to Operations Management” taught by Prof. Dr. Christian Terwiesch of the Wharton Business School of the University of Pennsylvania at Coursera.org.

The seven main sources of waste


During the first week, the concept of idle time was introduced. In general, idle time is the time during which a resource is not fully used because of low demand or bottleneck restraints, which, in turn, reduces productivity. Idle time is, however, not the only (and not even the biggest) source of waste. Taiichi Ohno – the father of the Toyota Production System – once stated that “moving is not really working”, which basically means that a loss of productivity does not necessarily need to be connected to idle time. While, for example, the re-configuration of a machine or the movement of materials is clearly “working time”, those activities are not directly adding value to the process.

The seven main sources of waste are:

(1) Overproduction: Producing sooner or in greater quantities than the customer actually demands. Overproduction leads to higher storage costs and material losses (e.g. because food products must be thrown away after a certain shelf time) and reduces the number of inventory turns. The solution to overproduction is to match supply and demand as closely as possible.

(2) Transportation: Unnecessary movement of people and / or materials between process steps. Transportation causes costs and production delays and thus often reduces the overall efficiency of a process (e.g. peeling crabs caught in the North Sea in Africa before shipping them back to Europe). The best way to reduce transportation waste is to optimize the process layout (“short ways”).

(3) Rework: Correction processes within the main process. Rework is always the result of a failure to do something right in the first place. Reworking something creates double labor costs while not actually producing more, thus productivity is reduced. It also requires holding additional resources just for reworking, so that normal production processes are not disrupted by reworking processes. The solution lies in – very simply put – making it right the first time as wells as in analysing and subsequently eliminating sources of failure.

(4) Over-processing: Doing more than the customer requires, e.g. keeping a patient in the hospital for a longer period of time than medically absolutely necessary. Over-processing is a form of waste that might have positive reasons such as workers having higher standards than the customers or employees being overly proud of their work. Still, over-processing adds to waste and thus to the reduction of productivity. One possible solution to this problem lies in the definition of quality and process standards, to which all employees then have to adhere.

(5) Motion: Unnecessary movement of people or parts within a process (similar to #2 but on a smaller scale), e.g. an office worker having to switch rooms every couple of minutes because the files are stored in different cabinets. One solution to this problem lies in optimizing the layout of workspaces (ergonomic design) in order to minimize unnecessary motion.

(6) Inventory: Too many flow units in the system. Inventory has already been discussed at length during the first week. It is by far the biggest source of waste in most companies and costs a lot of money because inventory requires costly storage space and drives down inventory turns. Possible solutions include “on time” production schemes and the reduction of so-called “comfort stocks”.

(7) Waiting: Employees or resources just sitting around waiting for something to happen, e.g. for a meeting to start, a customer to call or a customer waiting to be served. Per definition, waiting is an unproductive use of time. Waiting waste includes idle time as well as long flow times.

While the first five sources of waste are resource-centred (What did the employee do? Did it add value to the process?), the last two sources of waste are really an expression of Little’s law. Some scholars point out that waste of intellect (ignoring the ideas of employees for problem solving and process improvement because of hierarchical concerns) can very well be seen as an additional eighth source of waste. A production system that tries to reduce all types of waste at once is commonly called lean production.

These lecture notes were taken during 2013 installment of the MOOC “An Introduction to Operations Management” taught by Prof. Dr. Christian Terwiesch of the Wharton Business School of the University of Pennsylvania at Coursera.org.

Why do companies hold inventory?


There are five major reasons for holding inventory:

(1) Pipeline inventory

A pipeline inventory is the minimum inventory an organisation needs in order to function. E.g. a producer of wine that needs to age for two years in order to be sold needs a minimum inventory of wine for two years in order to exist.

(2) Seasonal inventory

A seasonal inventory is helpful, if an organisation wants to produce at a constant (cost-efficient) capacity, yet the demand varies with the seasons. E.g. a toy company can cheaply produce at at steady pace and build up a seasonal inventory for higher sales during the Christmas holidays.

(3) Cycle inventory

A cycle inventory is helpful if keeping an inventory saves costs associated with buying supplies on time. A private household will, for example, keep a box of water bottles in the cellar for practical reasons instead of satisfying the demand for water at the store every time it comes up again.

(4) Safety inventory

A safety inventory is a buffer agains high external demand, e.g. a burger chain keeping an inventory of pre-made burgers so that customers can be satisfied immediately. Safety inventories are closely associated with the meme “buffer or suffer”, meaning that if a process is not able to buffer for variabilities (such as an unexpected external demand) it will loose on flow rate.

(5) Decoupling inventory

Whereas the safety inventory can be seen as the buffer against heightened external demand, the decoupling inventory can be seen as the buffer against heightened internal demand. Such an inventory decouples supply from demand and supports a higher (and steadier) flow rate.

These lecture notes were taken during 2013 installment of the MOOC “An Introduction to Operations Management” taught by Prof. Dr. Christian Terwiesch of the Wharton Business School of the University of Pennsylvania at Coursera.org.

Inventory turns


One other important indicator for the evaluation of business organisations (not processes) is the inventory turnover rate (or number of inventory turns). The turnover rate answers the question of how much time a Dollar (or Euro) bill actually spends inside an organisation with the organisation being seen as a black box of sorts. A company has a competitive advantage if it can turn its inventory faster then the competitors can.

inventory turns = cost of goods sold (COGS) / average inventory

The inventory turnover rate is especially important because inventory creates costs. A business has to invest money in order to produce or buy an item and store it over a period of time, especially if the item might also loose value over time. The important indicator here are the inventory costs per unit, which are calculated as average inventory costs over inventory turns per unit time. If, for example, the annual inventory costs are 30% and there are 6 inventory turns per year, the per unit inventory costs are at 5%, meaning that for every unit sold the company has to calculate 5% inventory costs sort of as an internal tax rate. Inventory turns are therefore a good indicator on how productive an organisation uses its capital.

These lecture notes were taken during 2013 installment of the MOOC “An Introduction to Operations Management” taught by Prof. Dr. Christian Terwiesch of the Wharton Business School of the University of Pennsylvania at Coursera.org.

Little’s law


Little’s law was named after the American professor John Little (1950s). It defines the relationship between the inventory, the flow rate and the flow time, who have all been already defined previously.

inventory = number of flow units in the process
flow rate = rate at which flow units are being processed
flow time = time a single flow unit spends in the process

Little’s law: inventory (I) = flow Rate (R) * flow Time (T)

Little’s law is important, because it can help us calculate one of the three variables. Once two of the variables are known, the third one is set by the law. This also means that, form the standpoint of an executive, two variables can be picked by management while the third one then falls into place.

These lecture notes were taken during 2013 installment of the MOOC “An Introduction to Operations Management” taught by Prof. Dr. Christian Terwiesch of the Wharton Business School of the University of Pennsylvania at Coursera.org.

Flow rate / throughput, flow unit, inventory and flow time


The three most important performance measures of a business process are flow rate / throughput, inventory and flow time. In the following definitions, the term “flow unit” will be used a lot. A flow unit is the basic unit of analysis in any given scenario (customer, sandwich, phone call etc.).

Flow rate / throughput: The number of flow units (e.g. customers, money, produced goods/services) going through the business process per unit time, e.g served customers per hour or produced parts per minute. The flow rate usually is an average rate.

Flow time: The amount of time a flow unit spends in a business process from beginning to end, also known as the total processing time. If there is more than one path through the process, the flow time is equivalent to the length of the longest path.

Inventory: The number of flow units that are currently handled by a business process, e.g. the number of customers in a store, the number of enrolled students in an university etc. pp.

It should be kept in mind that the definition of inventory in Operations Management is different from the definition used in accounting. While the number of bottles on stock qualifies as inventory in both Operations Management and accounting, the number of patients waiting at a dentists office would not be seen as inventory in accounting – but is, in fact, inventory in Operations Management.

These lecture notes were taken during 2013 installment of the MOOC “An Introduction to Operations Management” taught by Prof. Dr. Christian Terwiesch of the Wharton Business School of the University of Pennsylvania at Coursera.org.
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