Quality Cycles Improvement

One particular section of the model deserves a closer look in the discussion of quality cycles. The flow of information in the upper left quadrant of the model changes depending on the type of quality improvement process involved. Two quality improvement terms borrowed from the Japanese are particularly relevant to this topic. The terms and their definitions are:
Hoshin:
A breakthrough innovation or dramatic change in level of performance. The Hoshin concept was developed in Japan to communicate company policy to everyone in the organization. Hoshin's primary benefit is to focus activity on the key things necessary for success. Japanese Deming Prize winners credit Hoshin as being a key contributor to their business success. Progressive US companies, like Hewlett-Packard and Xerox, have also adopted Hoshin as their strategic planning process. Hoshin plans, therefore, map out a framework for substantial increases in performance.
Kaizen:
Kaizen is the Japanese term for continuous improvement. It refers both to a statistical/quantitative evaluation of process performance and an adaptive framework of organizational values and beliefs that focuses workers and management alike on zero defects. Kaizen plans lay out an ongoing refinement process.
Hoshin and Kaizen, along with a Plan-Do-Check-Act (PDCA) cycle, will be used to describe the previously mentioned information flows and demonstrate the quality improvement cycles.
1. Breakthrough Innovation (Hoshin) Cycle
When Cp <=4/3, an unstable process is indicated and a major innovative change, or Hoshin, is suggested. A Hoshin could also be considered even when a process is stable. For a business firm to maintain its competitive edge and/or increase revenue, it may be necessary to initiate a Hoshin cycle for a process that is already at a high sigma level of quality. Figure 8 depicts the information flow within the model when a jump in productivity or level of performance is desired.
Through the use of the MBM component, a simulation of the physical layer is created so that the effects of altering process variables may be analyzed. It is probable that numerous simulations will be executed with differing variables until a path representing the breakthrough is discovered. At this point, the results of the simulation are implemented in the actual system with feedback flowing back through the management element for monitoring and adjustment. It may take a process several cycles to stabilize and begin the Kaizen cycles.

2. Continuous Improvement (Kaizen) Cycle
Generally speaking, when Cp >4/3 for a process, that process is considered stable [Mizuno, 1988]. Figure 9 depicts the information flow for Kaizen continuous improvement cycles. In this situation, feedback from the physical layer is monitored by the management component . Input from the MIS and DSS assist managers in making incremental improvements to the business processes.

3. PDCA Quality Cycles
In this view of quality improvement cycles, the upper and lower PDCA cycles of Figure 10 correspond to Hoshin and Kaizen respectively. For illustrative purposes we will assume an unstable process as a starting point and follow it through the 8 steps of this process improvement procedure [Eddlestone, 1992].
Beginning at the Plan element of the upper cycle, the steps are as follows:
Develop process innovation/breakthrough plans.
Implement plans.
Check impact on capability
Act on results (decision point). If Cp >4/3 , process has stabilized. Go to plan element of lower PDCA (Kaizen) cycle.
Develop process improvement plans.
Implement plans.
Check process variation.
Act on results (decision point). If Cp <=4/3 , process is now unstable. Go to plan element of upper PDCA (Hoshin) cycle.
4. A Simplified Example of Process Improvement
For the purpose of demonstrating a series of quality improvement cycles, the output of a modeling simulation under development at North Carolina State University will be presented1. It is beyond the scope of this paper to provide an in-depth description of the theory and formulae that form the basis of this simulation. The information provided here is for illustrative purposes only. The simulation requires variable values to be input for certain business competencies. The inputs are a decimal number ranging from 0 to 1and represent the percentage level of a particular competency. Of interest to this example are:
Information Technology Competencies: The business firm's level of competency in utilizing information technology. For this example, the variable has values of IT=0.45, IT=0.5, and IT=1.0.
Mission Critical Competencies: These are the core competencies vital to the success of critical business processes. This variable has values of MC=0.85, MC=0.5, and MC=1.0.
Learning Competency: The ability to incorporate learning from the changes to a business process. This variable has a value of L=0.5 for all three simulation runs.
The simulation scenario portrayed here is that of a major pharmaceutical company that has decided it must reduce the mean time for drug-to-market delivery. The delivery time units are in days and the company is seeking a reduction in mean delivery time from approximately 4000 to 2000 days over a period of four years.
Notice that the process is starting at a current level of six sigma. In essence, the trailing end of the distribution curve for longer delivery times is cut off. When the sigma level is recalculated under these conditions the result is that sigma = 3.
In the simulation, the start of each major Hoshin cycle corresponds with the beginning of a year. Four cycles are depicted within each major Hoshin cycle; each of these corresponds to a 3 month period (one quarter). During the period of four cycles (1 year), sigma builds from sigma =3 back to sigma = 6. Figure 11 is a graphic depiction of the simulation output for the mean delivery times over a period of four years. Each line on the graph represents the mean delivery time as impacted by the differing competency values.

The simulation shows that significant drops in mean delivery time occur at the beginning of each major Hoshin cycle. The values associated with business competencies also have a measurable effect on achieving the company goal. The main point here is that breakthrough innovation is a cyclic process with dependencies on business competency values.

1. Implementation of simulation model by T.L. Honeycutt and W.M. Waters, Department of Math, Science, and Technology Education

V. Conclusion
Quality improvement and information technology have an integral relationship in a business firm. The IT infrastructure is essential in tracking and monitoring the quality improvement process. The model of a business firm presented in this paper combines IT and quality improvement in an organized structure that exploits the synergy of the two concepts. Finally, the competency and quality of the management process carries more weight than the technology by which it is supported.

Distribution Requirements Planning

Definitions

DRP “…for tying the physical distribution system to the manufacturing planning and control (MPC) system.”

A set of techniques that can improve the linkages of the demand from the marketplace and manufacturing ability.

Advantages of DRP
DRP connects current inventory and forecasts of field demand to manufacturing’s MPS and MRP.
DRP can anticipate future requirements in the field.
Match material supply to demand, match inventory to customer service requirements.
Increase the speed the firm can react to the marketplace
Provide savings by better aggregation of transportation and dispatching.

The Basics
Basic idea: Time-phased order planning (TPOP)
Independent at field location, based on inventory level
Basic objective: Build a period-by-period plan for distribution of goods that provides the minimum inventory required to meet demand and satisfy safety stocks
Required SKU-level data for DRP:
Current balance on hand (BOH)
Target safety stock
Recommended lot size
Replenishment lead time
Forecasts of demand by period

Using DRP
Consolidating demand and supply information
Using the tables for distribution
Distribution center operations
Transportation load planning
Using the tables for plant activities
Shipping schedules
Production planning

The Value of DRP
“Perhaps DRP’s greatest payoff … is from integrating records and information” (Vollman et al.: p. 756)
DRP summarizes and integrates demand information “from the field” to coordinate distribution and production decisions
In comparison to (s,Q) inventory system
Use (s,Q) if only objective is to minimize inventory level of a specific item at a specific location
Specific advantages of DRP over (s,Q)
DRP not restricted by stable demand assumption
DRP shows planned shipments and thereby allows for planned coordination
DRP allows integration of demand from all sources (e.g, forecasts plus actual orders plus service parts demand)
Note that DRP “approaches” (s,Q) with stable demand and small time buckets

Optimizing Economic Order Quantity (EOQ)

Inventory models for calculating optimal order quantities and reorder points have been in existence long before the arrival of the computer. When the first Model T Fords were rolling off the assembly line, manufacturers were already reaping the financial benefits of inventory management by determining the most cost effective answers to the questions of When? and How much?. Yes long before JIT, TQM, TOC, and MRP, companies were using these same (then unnamed) concepts in managing their production and inventory. I recently read Purchasing and Storing, a textbook that was part of a “Modern Business Course” at the Alexander Hamilton Institute in New York. The textbook published in 1931 (that’s right 1931) was essentially a how to book on inventory management in a manufacturing environment. If you’re wondering why I would want to read a 70-year-old business text, my answer would be that the fundamental concepts of managing a business change very little with time, and reading about these concepts in a vintage text is a great way to reinforce the value of the fundamentals. The occasional reference to “The War” (referring to WWI) also keeps it interesting and the complete absence of acronyms is refreshing.
As you may have guessed, this 70-year-old book contained a section on Minimum Cost Quantity, which is what we now refer to as Economic Order Quantity (EOQ). I can imagine that in the 1930’s an accountant (or more likely a room full of accountants) would have calculated EOQ or other inventory related formulas one item at a time in a dimly lit office using the inventory books, a mechanical adding machine and a slide rule. Time consuming as this was, some manufacturers of the time recognized the financial benefits of taking a scientific approach to making these inventory decisions.
So why is it that, in these days of advanced information technology, many companies are still not taking advantage of these fundamental inventory models? Part of the answer lies in poor results received due to inaccurate data inputs. Accurate product costs, activity costs, forecasts, history, and lead times are crucial in making inventory models work. Ironically, software advancements may also in part to blame. Many ERP packages come with built in calculations for EOQ which calculate automatically. Often the users do not understand how it is calculated and therefore do not understand the data inputs and system setup which controls the output. When the output appears to be "out of whack" it is simply ignored. This sometimes creates a situation in which the executives who had purchased the software incorrectly assume the material planners and purchasing clerks are ordering based upon the systems recommendations. I should also note that many operations will find these built-in EOQ calculations inadequate and in need of modifications to deal with the diversity of their product groups and processes.
Corporate goals and strategies may sometimes conflict with EOQ. Measuring performance solely by inventory turns is one of the most prolific mistakes made in the name of inventory management. Many companies have achieved aggressive goals in increasing inventory turns only to find their bottom line has shrunk due to increased operational costs.
EOQ is essentially an accounting formula that determines the point at which the combination of order costs and inventory carrying costs are the least. The result is the most cost effective quantity to order. In purchasing this is known as the order quantity, in manufacturing it is known as the production lot size.
While EOQ may not apply to every inventory situation, most organizations will find it beneficial in at least some aspect of their operation. Anytime you have repetitive purchasing or planning of an item, EOQ should be considered. Obvious applications for EOQ are purchase-to-stock distributors and make-to-stock manufacturers, however, make-to-order manufacturers should also consider EOQ when they have multiple orders or release dates for the same items and when planning components and sub-assemblies. Repetitive buy maintenance, repair, and operating (MRO) inventory is also a good application for EOQ. Though EOQ is generally recommended in operations where demand is relatively steady, items with demand variability such as seasonality can still use the model by going to shorter time periods for the EOQ calculation. Just make sure your usage and carrying costs are based on the same time period.
Doesn’t EOQ conflict with Just-In-Time? While I don’t want to get into a long discussion on the misconceptions of what Just-In-Time (JIT) is, I will address the most common misunderstanding in which JIT is assumed to mean all components should arrive in the exact run quantities “just in time” for the production run. JIT is actually a quality initiative with the goal of eliminating wasted steps, wasted labor, and wasted cost. EOQ should be one of the tools used to achieve this. EOQ is used to determine which components fit into this JIT model and what level of JIT is economically advantageous for your operation. As an example, let us assume you are a lawn equipment manufacturer and you produce 100 units per day of a specific model of lawn mower. While it may be cost effective to have 100 engines arrive on your dock each day, it would certainly not be cost effective to have 500 screws (1 days supply) used to mount a plastic housing on the lawn mower shipped to you daily. To determine the most cost effective quantities of screws or other components you will need to use the EOQ formula.
The basic Economic Order Quantity (EOQ) formula is as follows:

The Inputs
While the calculation itself is fairly simple the task of determining the correct data inputs to accurately represent your inventory and operation is a bit of a project. Exaggerated order costs and carrying costs are common mistakes made in EOQ calculations. Using all costs associated with your purchasing and receiving departments to calculate order cost or using all costs associated with storage and material handling to calculate carrying cost will give you highly inflated costs resulting in inaccurate results from your EOQ calculation. I also caution against using benchmarks or published industry standards in calculations. I have frequently seen references to average purchase order costs of $100 to $150 in magazine articles and product brochures. Often these references trace back to studies performed by advocacy agencies working for business that directly benefit from these exaggerated (my opinion) costs used in ROI calculations for their products or services. I am not denying that some operations may have purchase costs in this range, especially if you are frequently re-sourcing, re-quoting, and/or buying from overseas vendors. However if your operation is primarily involved with repetitive buying from domestic vendors — which is more common — you’ll likely see your purchase order costs in the substantially lower $10 to $30 range.
As you prepare to undertake this project keep in mind that even though accuracy is crucial, small variances in the data inputs generally have very little effect on the outputs. The following breaks down the data inputs in more detail and gives insight into the aspects of each.

Annual Usage.
Expressed in units, this is generally the easiest part of the equation. You simply input your forecasted annual usage.

Order Cost.
Also known as purchase cost or set up cost, this is the sum of the fixed costs that are incurred each time an item is ordered. These costs are not associated with the quantity ordered but primarily with physical activities required to process the order.
For purchased items, these would include the cost to enter the purchase order and/or requisition, any approval steps, the cost to process the receipt, incoming inspection, invoice processing and vendor payment, and in some cases a portion of the inbound freight may also be included in order cost. It is important to understand that these are costs associated with the frequency of the orders and not the quantities ordered. For example, in your receiving department the time spent checking in the receipt, entering the receipt, and doing any other related paperwork would be included, while the time spent repacking materials, unloading trucks, and delivery to other departments would likely not be included. If you have inbound quality inspection where you inspect a percentage of the quantity received you would include the time to get the specs and process the paperwork and not include time spent actually inspecting, however if you inspect a fixed quantity per receipt you would then include the entire time including inspecting, repacking, etc. In the purchasing department you would include all time associated with creating the purchase order, approval steps, contacting the vendor, expediting, and reviewing order reports, you would not include time spent reviewing forecasts, sourcing, getting quotes (unless you get quotes each time you order), and setting up new items. All time spent dealing with vendor invoices would be included in order cost.
Associating actual costs to the activities associated with order cost is where many an EOQ formula runs afoul. Do not make a list of all of the activities and then ask the people performing the activities "how long does it take you to do this?" The results of this type of measurement are rarely even close to accurate. I have found it to be more effective to determine the percentage of time within the department consumed performing the specific activities and multiplying this by the total labor costs for a certain time period (usually a month) and then dividing by the line items processed during that same period.
It is extremely difficult to associate inbound freight costs with order costs in an automated EOQ program and I suggest it only if the inbound freight cost has a significant effect on unit cost and its effect on unit cost varies significantly based upon the order quantity.
In manufacturing, the order cost would include the time to initiate the work order, time associated with picking and issuing components excluding time associated with counting and handling specific quantities, all production scheduling time, machine set up time, and inspection time. Production scrap directly associated with the machine setup should also be included in order cost as would be any tooling that is discarded after each production run. There may be times when you want to artificially inflate or deflate set-up costs. If you lack the capacity to meet the production schedule using the EOQ, you may want to artificially increase set-up costs to increase lot sizes and reduce overall set up time. If you have excess capacity you may want to artificially decrease set up costs, this will increase overall set up time and reduce inventory investment. The idea being that if you are paying for the labor and machine overhead anyway it would make sense to take advantage of the savings in reduced inventories.
For the most part, order cost is primarily the labor associated with processing the order, however, you can include the other costs such as the costs of phone calls, faxes, postage, envelopes, etc.

Carrying cost.
Also called Holding cost, carrying cost is the cost associated with having inventory on hand. It is primarily made up of the costs associated with the inventory investment and storage cost. For the purpose of the EOQ calculation, if the cost does not change based upon the quantity of inventory on hand it should not be included in carrying cost. In the EOQ formula, carrying cost is represented as the annual cost per average on hand inventory unit. Below are the primary components of carrying cost.
Interest. If you had to borrow money to pay for your inventory, the interest rate would be part of the carrying cost. If you did not borrow on the inventory, but have loans on other capital items, you can use the interest rate on those loans since a reduction in inventory would free up money that could be used to pay these loans. If by some miracle you are debt free you would need to determine how much you could make if the money was invested.
Insurance. Since insurance costs are directly related to the total value of the inventory, you would include this as part of carrying cost.
Taxes. If you are required to pay any taxes on the value of your inventory they would also be included.
Storage Costs. Mistakes in calculating storage costs are common in EOQ implementations. Generally companies take all costs associated with the warehouse and divide it by the average inventory to determine a storage cost percentage for the EOQ calculation. This tends to include costs that are not directly affected by the inventory levels and does not compensate for storage characteristics. Carrying costs for the purpose of the EOQ calculation should only include costs that are variable based upon inventory levels.
If you are running a pick/pack operation where you have fixed picking locations assigned to each item where the locations are sized for picking efficiency and are not designed to hold the entire inventory, this portion of the warehouse should not be included in carrying cost since changes to inventory levels do not effect costs here. Your overflow storage areas would be included in carrying cost. Operations that use purely random storage for their product would include the entire storage area in the calculation. Areas such as shipping/receiving and staging areas are usually not included in the storage calculations. However. if you have to add an additional warehouse just for overflow inventory then you would include all areas of the second warehouse as well as freight and labor costs associated with moving the material between the warehouses.
Since storage costs are generally applied as a percentage of the inventory value you may need to classify your inventory based upon a ratio of storage space requirements to value in order to assess storage costs accurately. For example, let's say you have just opened a new E-business called "BobsWeSellEverything.com". You calculated that overall your annual storage costs were 5% of your average inventory value, and applied this to your entire inventory in the EOQ calculation. Your average inventory on a particular piece of software and on 80 lb. bags of concrete mix both came to $10,000. The EOQ formula applied a $500 storage cost to the average quantity of each of these items even though the software actually took up only 1 pallet position while the concrete mix consumed 75 pallet positions. Categorizing these items would place the software in a category with minimal storage costs (1% or less) and the concrete in a category with extreme storage costs (50%) that would then allow the EOQ formula to work correctly.
There are situations where you may not want to include any storage costs in your EOQ calculation. If your operation has excess storage space of which it has no other uses you may decide not to include storage costs since reducing your inventory does not provide any actual savings in storage costs. As your operation grows near a point at which you would need to expand your physical operations you may then start including storage in the calculation.
A portion of the time spent on cycle counting should also be included in carrying cost, remember to apply costs which change based upon changes to the average inventory level. So with cycle counting, you would include the time spent physically counting and not the time spent filling out paperwork, data entry, and travel time between locations.
Other costs that can be included in carrying cost are risk factors associated with obsolescence, damage, and theft. Do not factor in these costs unless they are a direct result of the inventory levels and are significant enough to change the results of the EOQ equation.

Variations
There are many variations on the basic EOQ model. I have listed the most useful ones below.
• Quantity discount logic can be programmed to work in conjunction with the EOQ formula to determine optimum order quantities. Most systems will require this additional programming.
• Additional logic can be programmed to determine max quantities for items subject to spoilage or to prevent obsolescence on items reaching the end of their product life cycle.
• When used in manufacturing to determine lot sizes where production runs are very long (weeks or months) and finished product is being released to stock and consumed/sold throughout the production run you may need to take into account the ratio of production to consumption to more accurately represent the average inventory level.
• Your safety stock calculation may take into account the order cycle time that is driven by the EOQ. If so, you may need to tie the cost of the change in safety stock levels into the formula.

Implementing EOQ
There are primarily two ways to implement EOQ. Both methods obviously require that you have already determined the associated costs. The simplest method is to set up your calculation in a spreadsheet program, manually calculate EOQ one item at a time, and then manually enter the order quantity into your inventory system. If your inventory has fairly steady demand and costs and you have less than one or two thousand SKUs you can probably get by using this method once per year. If you have more than a couple thousand SKUs and/or higher variability in demand and costs you will need to program the EOQ formula into your existing inventory system. This allows you to quickly re-calculate EOQ automatically as often as needed. You can also use a hybrid of the two systems by downloading your data to a spreadsheet or database program, perform the calculations and then update your inventory system either manually or through a batch program. Whichever method you use you should make sure to follow the following steps:
• Test the formula. Prior to final implementation you must test the programming and setup. Run the EOQ program and then manually check the results using sample items that are representative of the variations of your inventory base.
• Project results. You'll need to run a simulation or use a representative sampling of items to determine the overall short-term and long-term effects the EOQ calculation will have on warehouse space, cash flow, and operations. Dramatic increases in inventory levels may not be immediately feasible, if this is the case you may temporarily adjust the formula until arrangements can be made to handle the additional storage requirements and compensate for the effects on cash flow. If the projection shows inventory levels dropping and order frequency increasing, you may need to evaluate staffing, equipment, and process changes to handle the increased activity.
• Maintain EOQ. The values for Order cost and Carrying cost should be evaluated at least once per year taking into account any changes in interest rates, storage costs, and operational costs.
A related calculation is the Total Annual Cost calculation. This calculation can be used to prove the EOQ calculation. Total Annual Cost = [(annual usage in units)/(order quantity)(order cost)]+{[.5(order quantity)+(safety stock)]*(annual carrying cost per unit)}. This formula is also very useful when comparing quotes where vendors offer different minimum order quantities, price breaks, lead times, transportation costs.
Use it! The EOQ calculation is "Hard Science", if you have accurate inputs the output is the most cost-effective quantity to order based upon your current operational costs. To further increase inventory turns you will need to reduce the order costs. E-procurement, vendor-managed inventories, bar coding, and vendor certification programs can reduce the costs associated with processing an order. Equipment enhancements and process changes can reduce costs associated with manufacturing set up. Increasing forecast accuracy and reducing lead times which result in the ability to operate with reduced safety stock can also reduce inventory levels.

Source : Dave Piasecki, Logistic Management .

Optimizing Safety Stock

Optimizing Safety Stock levels by calculating the magical balance of minimal inventory while meeting variable customer demand is sometimes described as the Holy Grail of inventory management (ok, forecasting is probably the true holy grail but I thought this sounded good). Many companies look at their own demand fluctuations and assume that there is not enough consistency to predict future variability. They then fall back on the trial and error best guess weeks supply method or the over simplified 1/2 lead time usage method to manage their safety stock. Unfortunately, these methods prove to be less than effective in determining optimal inventory levels for many operations. If your goal is to reduce inventory levels while maintaining or increasing service levels you will need to investigate more complex calculations.
One of the most widely accepted methods of calculating safety stock uses the statistical model of Standard Deviations of a Normal Distribution of numbers to determine probability. This statistical tool has proven to be very effective in determining optimal safety stock levels in a variety of environments. The basis for this calculation is standardized, however, its successful implementation generally requires customization of the formula and inputs to meet the specific characteristics of your operation. Understanding the statistical theory behind the formula is necessary in correctly adapting it to meet your needs. Errors in implementation are usually the result of not factoring in variables which are not part of original statistical model

Terminology and calculations
The following is a list of the variables and the terminology used in this safety stock model:
Normal distribution. Term used in statistical analysis to describe a distribution of numbers in which the probability of an occurrence, if graphed, would follow the form of a bell shaped curve. This is the most popular distribution model for determining probability and has been found to work well in predicting demand variability based upon historical data.
Standard deviation. Used to describe the spread of the distribution of numbers. Standard deviation is calculated by the following steps:
determine the mean (average) of a set of numbers.
determine the difference of each number and the mean
square each difference
calculate the average of the squares
calculate the square root of the average.
You can also use Excel function STDEVPA to calculate standard deviation. In safety stock calculations, the forecast quantity is often used instead of the mean in determining standard deviation.
Lead time. Highly accurate lead times are essential in the safety stock/reorder point calculation. Lead time is the amount of time from the point at which you determine the need to order to the point at which the inventory is on hand and available for use. It should include supplier or manufacturing lead time, time to initiate the purchase order or work order including approval steps, time to notify the supplier, and the time to process through receiving and any inspection operations.
Lead-time demand. Forecasted demand during the lead-time period. For example, if your forecasted demand is 3 units per day and your lead time is 12 days your lead time demand would be 36 units.
Forecast. Consistent forecasts are also an essential part of the safety stock calculation. If you don't use a formal forecast, you can use average demand instead.
Forecast period. The period of time over which a forecast is based. The forecast period used in the safety stock calculation may differ from your formal forecast periods. For example, you may have a formal forecast period of four weeks while the forecast period you use for the safety stock calculation may be one week.
Demand history. A history of demand broken down into forecast periods. The amount of history needed depends on the nature of your business. Businesses with a lot of slower moving items will need to use more demand history to get an accurate model of the demand. Generally, the more history the better, as long as sales pattern remains the same.
Order cycle. Also called replenishment cycle, order cycle refers to the time between orders of a specific item. Most easily calculated by dividing the order quantity by the annual demand and multiplying by the number of days in the year.
Reorder point. Inventory level which initiates an order. Reorder Point = Lead Time Demand + Safety Stock.
Service level. Desired service level expressed as a percentage.
Service factor. Factor used as a multiplier with the Standard Deviation to calculate a specific quantity to meet the specified service level.

Understanding the statistical model and factoring in additional variables.
As mentioned previously, an understanding of the statistical theory behind this formula is necessary to ensure optimal results. The statistical model uses the standard deviation calculation to describe the probability of a number occurring in reference to the mean in a normal distribution. A table is then used to determine a multiplier to use along with the standard deviation to determine ranges of numbers which would account for a specified percentage of the occurrences. The multiplier is referred to as the number of standard deviations required to meet the percentage. The theory states that zero standard deviations added to the mean will result in a number in which 50% of the occurrences will occur below, one standard deviation added to the mean will result in a number in which 84% of the occurrences will occur below, 2 standard deviations added to the mean will result in a number in which 98% of the occurrences will occur below, and 3 standard deviations added to the mean will result in a number in which 99.85% of the occurrences will occur below.
In the safety stock calculation we will refer to the multiplier as the service factor and use the demand history to calculate standard deviation. In its simplest form this would yield a safety stock calculation of : safety stock = (standard deviation) * (service factor). If your lead time, order cycle time, and forecast period were all the same and if your forecast was the same for each period and equaled the mean of the actual demand for those periods, this simple formula would work great. Since this situation is highly unlikely to occur you must add factors to the formula to compensate for these variations. This is where the trouble lies. You must add factors to adapt this theory to work with your inventory, however, each factor you add compromises the integrity of the original theory. This isn't quite as bad as it sounds. While the factoring can get complicated you can keep tweaking it until you find an effective solution. Your final formula will look like: safety stock = (standard deviation)*(service factor)*(lead-time factor)*(order cycle factor)*(forecast-to-mean-demand factor).
There is not a general consensus on the formulas for these factors; in fact, many calculations do not even acknowledge the need for them. I will give some recommendations for these factors, however, I strongly suggest you test and tweak them with your numbers to arrive at something that works for you.
Lead-time factor. This is necessary to compensate for the differences between lead time and forecast period. The standard deviation was based on the forecast period, a factor is necessary to increase or decrease the safety stock to allow for this variance. A formula you can try is lead time factor = square root (lead time/forecast period).
Order cycle factor. Since longer order cycles result in an inherent higher service level you will need to use a factor to compensate for this. A formula you can try is Order cycle factor = square root (forecast period/order cycle).
Forecast-to-mean-demand factor. Remember that the original statistical model was based upon the mean of the distribution. Substituting a forecast for the mean in the calculation of standard deviation creates a problem if the forecast mean and the actual demand mean are not close and also if the forecast varies between forecast periods (seasonality, sales growth). Sorry but I don't have a canned formula for this one that I feel confident enough with to publish. The actual formula used will vary based upon the types of variances and the method for standard deviation calculation used.
Minimum Reorder Point. For slow moving products and especially if the lead time is short, you may want to program in a minimum reorder point which is the equivalent of one average sale.
Lead-time Variances. You may have noticed that I have only discussed demand variations in this model. While you can use this model for predicting variations in supply, I have found that supply variations tend to be far too random and unpredictable. Supply problems tend to be related more to a vendor than an item and the severity of the variations do not fall into the pattern of a normal distribution. The safety stock calculated for demand variation will also cover for some supply variations, however, the best way to deal with variable supply is to have a high level of communication with the vendor and not to count on safety stock. You may find that certain items which are critical to your operation may require a safety stock calculation based upon the nature of the supply chain of the specific item.
While all of these factors and their potentially detrimental effect upon the integrity of the original formula may leave you feeling less than confident with the results of this model, you should realize that these factors would be necessary in any method of calculating safety stock which takes a scientific approach to meeting service levels while maintaining minimal inventory levels. It is very important to thoroughly test the model prior to final implementation to ensure it is working correctly and to determine impact on inventory levels and cash flow. It's also a good idea to start with a higher service factor initially and gradually reduce it until your actual service levels meet your objectives. You will never find perfection in determining probability, however this type of formula is certainly more effective than the previously mentioned keep it simple approaches.

Source : Dave Piasecki, Logistic Management .

Guide to inventory accuracy

Having problems with inventory accuracy? Implementing technologies such as bar coding systems, RFID, and pick-to-light are often assumed to be the solutions to inaccurate inventories. If properly implemented these technologies can help reduce errors, however, none of them will eliminate all errors, and a poorly implemented system can leave you worse off than you were before. Whether you are planning on implementing additional systems or not you should consider taking care of the basics first.

The Basics
There is nothing revolutionary about my list of "The Basics", it's simply a series of steps which define a process for achieving higher levels of inventory accuracy. Your success or failure will be determined by your implementation of these steps. This is not something that should be rushed; throwing a quick fix approach together to alleviate an immediate need may be more damaging in the long run since the success of this plan requires a cooperative effort by many people within your organization. If your first attempt fails, you will find it more difficult to get a high level of cooperation for your next try. Take the time and do it right.
Attitude. Maintaining inventory accuracy must be an integral part of the attitude of the organization. Like quality, customer service, and plant safety, accuracy must be promoted throughout the organization as everyone's responsibility. This attitude must start at the top levels. Yeah I know all you managers and execs out there want an accurate inventory but are you doing your part through your decisions and business practices to promote it. Processes are often shortcut in the name of "Customer Service" (this also applies to processes for Quality, Inventory Management, and Production Plans) that reduce or eliminate the effectiveness of the plan, which in the long run will reduce your ability to service your customers. Remember that these plans are designed to meet the needs of the customer, don't compromise them.
Process Definition. You'll struggle to make any progress if you have not clearly defined the processes throughout the organization that affect inventory. While defining the processes, you should be looking for opportunities for errors and implementing changes to eliminate or reduce them. Even the most accurate employee will make errors, I suggest placing formal checks in place for critical operations. Get as many people involved in this step to ensure you have a complete and accurate understanding of the processes. Anything missed in this step will require new procedures and additional employee training later, so once again, "take the time and do it right".
Procedure Documentation. This is the part where you use the previously defined processes to document the procedures the employees will follow to maintain inventory integrity. The procedures documented here should not be limited to inventory issues; they should be the complete procedure including quality, physical aspects, and safety. This documentation should be as clear and comprehensive as possible. It should be written for a specific task within a specific job responsibility, it should include everything the employee needs to know to complete the task and nothing else. For example: if a stock clerk's responsibility is to notify the supervisor of any discrepancies, that is all it should state in the procedure for the stock clerk even though there will be additional procedures for dealing with the discrepancy. Procedures should also include the correct method for filling out and processing paperwork, the sequence and timing of entering data, and any checks that are required to be performed. If there are any exceptions to a procedure they should be specified in the document, allowing undocumented exceptions to a procedure will decrease its effectiveness. Be realistic, procedures are not a "wish list", they are the documentation of the requirements of a specific task. You must be prepared to enforce compliance to all procedures. Once you are completed with the documentation, I suggest you first distribute the procedures to a few key employees, then take a couple of weeks for you and the key employees to monitor existing operations to see if anything was missed or if anything is incorrect. Once this is done, the procedures should be officially put into effect and distributed to all employees.
Employee Training. Handing out a written procedure does not constitute employee training. It is important to set a training schedule to go through all the procedures with groups of employees. Take whatever time is necessary to ensure they have a thorough understanding of the procedures. Make it clear that the procedure document is the only way to perform the task. If you did your job correctly in defining the processes and documenting the procedures you shouldn't run into many surprises during the training. Try to refrain from making changes or exceptions to the documentation at this time (unless there is a critical error). Last minute changes or exceptions will cause confusion and diminish the value of the documents. Make notes for possible future revisions of the procedures instead. Set a timetable for publishing and putting into effect revisions (every quarter or six months). Frequent revisions of procedures tend to cause confusion and make it difficult to enforce adherence.
Employee Testing. I am a big advocate of formal testing of employees on procedures. This is the only way to know if they understand them (or have even read them). Be prepared, this will scare the hell out of your staff. Do not make the tests too difficult, I suggest multiple choice questions and maybe some true/false. You may also need testing which requires the employee to perform the task in the presence of the tester. Make a point to include items in the test that are known to have been issues in the past. There should not be any penalties for incorrect answers on the test. Any incorrectly answered questions should be discussed with the employee to ensure that he/she now understands the correct answer. You may need to make arrangements to conduct the test verbally for employees with inadequate reading skills or other arrangements if language is an issue.
Monitoring Processes for Compliance. You must begin to monitor the processes for compliance to the procedures immediately. Any actions observed which do not comply with the written procedures must be addressed immediately with the employees involved. As stated earlier, the written procedures are the only way to perform the task. Allowing employees to "do it their own way" (even if their way is a better way) will make it impossible to enforce compliance on other issues and will create problems when changes are made to processes. If they have a better way, consider it for the next revision at which point it would then become "the only way".
Setting Standards. I am also a big advocate of setting minimum accuracy and production standards wherever feasible. Do your research to ensure the standards set are high enough yet still achievable. You will have to enforce these standards so it is critical to set them correctly. If in doubt, set them lower, you can always increase them later when more data is available. If you set them too high you have put yourself in a difficult position when it comes time to enforce them. Standards should be set for the specific task being performed. For example, the accuracy standard for a stock clerk stocking in random storage area would be lower than for one stocking in fixed locations. Setting standards requires tracking of the accuracy and productivity of the tasks being performed which makes it more viable when you have several people performing the same tasks.
Tracking Accuracy. Whether you have set standards or not I still suggest you track accuracy organizationally and individually. Accuracy tracking should always be measured as a percentage of total transactions. Tracking accuracy as flat numbers (number of errors) puts your more productive employees at a disadvantage, and at an organizational level will be skewed by variances in business activity. Accuracy tracking should be communicated to staff in a positive manner; it is a tool to facilitate improvement in processes and people. I have found that by simply tracking and communicating accuracy to employees you will see immediate reductions in errors even if standards are not set. The fact is we all want to be accurate; the problem is we all think that we are accurate and it's always the other guy who is making all the mistakes.
Accountability. People must be held accountable for following documented procedures. You have spent the time to document the procedures, provide the training, and the testing. If someone is not following the procedures they must be dealt with applying appropriate disciplinary action. It's that simple. You may be amazed as to how much just one individual not following procedures can screw up your inventory. If you don't hold the employees accountable you may as well throw out everything you have done to this point. Mistakes are mistakes and everyone makes them, however, not following a specified procedure is a conscious decision made by the employee to not do what he/she was instructed to do.
Count, Count, Count. We would like to believe that since we have taken the above steps we should now assume our inventory is accurate. Not necessarily. You will have to count it to determine the accuracy, as well as determining areas needing additional evaluation. Year-end physical inventories are tools used by accountants and do very little for inventory accuracy. You should count your inventory on a continuous basis (cycle counting) to maintain high levels of accuracy. This is one of the best ways of identifying problem areas on a timely basis and providing an environment conducive to continuous improvement. The way you count and the frequency of your counts should be designed for your specific type of operation.
Reevaluate. You should be regularly reevaluating your processes and procedures. Results of your cycle count program should point you in the direction of areas where enhancements are needed. Business conditions often change and new processes are added which will require evaluation. As previously mentioned try to refrain from frequent revisions to procedures (the memo of the day), it is more effective to plan a revision date and group multiple revisions into a revised release of the procedures. These revisions should be implemented with the proper training and testing as was done during initial implementation.
As you may have noticed, each of the above steps is highly dependent on the successful implementation of the previous steps. Although this process for improving inventory accuracy is not very complicated, the implementation can prove to be demanding. Depending on the environment you are working in, it can sometimes seem to be an insurmountable task to change the attitudes of people towards inventory accuracy. It will require a high level of effort and diligence to ensure success.

Additional recommendations.
The following are some additional suggestions that may help in your quest for a more accurate inventory.
Dedicate positions for managing inventory. Make sure you have control of which employees are affecting your inventory. This is especially true in manufacturing operations where the priorities of machine operators and production supervisors are meeting the production schedule, keeping the machines running, and ensuring the quality of the product being produced. Inventory accuracy will never be a primary responsibility of these types of positions. Once you come to this realization, it is easy to see the benefits of putting your inventory and material handling responsibilities in the hands of people whose primary responsibility is inventory. Also, within your material handling/warehouse positions you should limit the people doing miscellaneous type inventory adjustments.
Control employee turnover. I know, easier said than done. You've invested the time into training them, now figure out what you need to do to keep them. Once you have your processes and procedures under control you will find that new employees will become your #1 source of errors. My experience shows a new employee generally makes 2 to 5 times as many mistakes as a one-year employee and 5 to 10 times as many mistakes as a five-year employee. These numbers are based on operations that track accuracy and promote continuous improvement. If you're not tracking accuracy, your five-year employees may be making as many mistakes as they did during their first year. Also high employee turnover results in operations that are frequently short staffed which will almost always lead to increased errors.
Be prepared to dismiss or reassign employees. May sound like a contradiction to the previous suggestion, however, if you have made every effort to assist an employee in improving their accuracy and insufficient progress is being made you will need to get them away from your inventory. Again, don't underestimate the damage that can result from just one employee's errors.
Don't be afraid to put Checks in place. Some people feel that checking or rechecking work is admitting failure or is a waste since it "should be done right the first time", so I'll say it once again, everyone makes mistakes, that means everyone. If you find there are certain areas that are highly prone to errors (such as random stocking areas) or critical parts of your operation where a mistake can have significant detrimental effect, consider putting checks in place. A check may be an employee checking their own work or a specific checking operation. Outbound shipments should always have some type of check in place, the specific type of check will vary from operation to operation. In a high-volume, low-value shipping operation a simple looking over the shipment may be all that's feasible, while in a lower-volume, high-value shipping operation I've had as many as three people performing redundant checks of each shipment prior to loading.
Storage Areas. How you store your product will also affect accuracy. Crowded unorganized areas become "black holes" for missing product. Crowded areas also cause increase damage to product that is often disposed of without inventory corrections being made. High-density storage makes it very difficult to accurately count the product. Maintaining proper lighting, shelf and product labeling, and organization makes it easier to stock, pick, and count product thus increasing levels of accuracy.
Know your inventory system. The more you know about how your specific inventory system works, the more successful you'll be in optimizing its features. Computer systems are regularly blamed for things that are usually turn out to be human error, however, occasionally your computer system can be the source of the problem. Bugs, glitches, hiccups or whatever you want to call them do occur and changes to system parameters to optimize functionality in one area can create havoc in a seemingly unrelated area. The only way to determine the source and correct these problems is to have a thorough understanding of how your system is set up and how the specific programs process the information. The bigger advantage to acquiring a high level of system knowledge lies in the amount of information you'll be able to extract from your system. Today's larger software systems maintain enormous amounts of data and contain far more functionality than most users realize. Managers need to be taking more active roles in system set up and implementations if they want to optimize the system to meet their business needs. The days of leaving it all up to the IS department are gone, the staffing levels of most IS departments are inadequate to deal with the complexity and the enormity of software packages today. IS personnel tend to spend the majority of their time making sure the system runs rather than optimizing its features.
The end result in accuracy improvement will be directly related to the effort put forth to achieve it. Building a sound consistent inventory accuracy plan will get people in the habit of being accurate, as the entire organization gets in the habit of being accurate you will find the accuracy plan starts to run itself. Until then, it will require a lot of work by those implementing it.

Source : Dave Piasecki, logistic management.

Order Picking: Methods and Equipment for Piece Pick, Case Pick, and Pallet Pick Operations.

Of all warehouse processes, order picking tends to get the most attention. It’s just the nature of distribution and fulfillment that you generally have more outbound transactions than inbound transactions, and the labor associated with the outbound transactions is likely a big piece of the total warehouse labor budget. Another reason for the high level of importance placed on order picking operations is its direct connection to customer satisfaction. The ability to quickly and accurately process customer orders has become an essential part of doing business.
The methods for order picking vary greatly and the level of difficulty in choosing the best method for your operation will depend on the type of operation you have. The characteristics of the product being handled, total number of transactions, total number of orders, picks per order, quantity per pick, picks per SKU, total number of SKUs, value-added processing such as private labeling, and whether you are handling piece pick, case pick, or full-pallet loads are all factors that will affect your decision on a method for order picking. Many times a combination of picking methods is needed to handle diverse product and order characteristics.
Key objectives in designing an order picking operation include increases in productivity, reduction of cycle time, and increases in accuracy. Often times these objectives may conflict with one another in that a method that focuses on productivity may not provide a short enough cycle time, or a method that focuses on accuracy may sacrifice productivity.
Productivity. Productivity in order picking is measured by the pick rate. Piece pick operations usually measure the pick rate in line items picked per hour while case pick operations may measure cases per hour and line items per hour. In pallet pick operations the best measure is actual pallets picked per hour. Since the actual amount of time it takes to physically remove the product from the location tends to be fixed regardless of the picking method used, productivity gains are usually in the form of reducing the travel time.
Cycle Time. Cycle time is the amount of time it takes to get an order from order entry to the shipping dock. In recent years, customer’s expectations of companies to provide same day shipment has put greater emphasis on reducing cycle times from days to hours or minutes. Immediate release of orders to the warehouse for picking and methods that provide concurrent picking of items within large orders are ways to reduce cycle times.
Accuracy. Regardless of the type of operation you are running, accuracy will be a key objective. Virtually every decision you make in setting up a warehouse will have some impact on accuracy, from the product numbering scheme, to the design of product labels, product packaging, the design of picking documents, location numbering scheme, storage equipment, lighting conditions, and picking method used. Technologies that aide in picking accuracy include pick-to-light systems, counting scales, and bar code scanners. Beyond the design aspects of an order picking operation, employee training, accuracy tracking, and accountability are essential to achieving high levels of accuracy.

Piece Picking
Piece-picking methods. Piece picking, also known as broken case picking or pick/pack operations, describes systems where individual items are picked. Piece pick operations usually have a large sku base in the thousands or tens of thousands of items, small quantities per pick, and short cycle times. Mail order catalog companies and repair parts distributors are good examples of piece pick operations.
Basic order picking. In the most basic order-picking method, product is stored in fixed locations on static shelving or pallet rack. An order picker picks one order at a time following a route up and down each aisle until the entire order is picked. The order picker will usually use some type of picking cart. The design of the picking flow should be such that the order picker ends up fairly close to the original starting point. The picking document should have the picks sorted in the same sequence as the picking flow. Fast moving product should be stored close to the main cross aisle and additional cross aisles put in to allow short cuts. Larger bulkier items would be stored towards the end of the pick flow. This basic order picking method can work well in operations with a small total number of orders and a high number of picks per order. Operations with low picks per order will find the travel time excessive in this type of picking and operations with large numbers of orders will find that the congestion from many pickers working in the same areas slows down the processing.
Batch picking / Multi-order picking In batch picking, multiple orders are grouped into small batches. An order picker will pick all orders within the batch in one pass using a consolidated pick list. Usually the picker will use a multi-tiered picking cart maintaining a separate tote or carton on the cart for each order. Batch sizes usually run from 4 to 12 orders per batch depending on the average picks per order in that specific operation. Batch picking systems may use extensive logic programmed to consolidate orders with the same items. In operations with low picks per order, batch picking can greatly reduce travel time by allowing the picker to make additional picks while in the same area. Since you are picking multiple orders at the same time, systems and procedures will be required to prevent mixing of orders. In very busy operations, batch picking is often used in conjunction with zone picking and automated material handling equipment. In order to get maximum productivity in batch pick operations, orders must be accumulated in the system until there are enough similar picks to create the batches. This delay in processing may not be acceptable in same day shipping operations.
Zone picking. Zone picking is the order picking version of the assembly line. In zone picking, the picking area is broken up into individual pick zones. Order pickers are assigned a specific zone, and only pick items within that zone. Orders are moved from one zone to the next as the picking from the previous zone is completed (also known as "pick-and-pass"). Usually, conveyor systems are used to move orders from zone to zone. In zone picking it’s important to balance the number of picks from zone to zone to maintain a consistent flow. Zones are usually sized to accommodate enough picks for one or two order pickers. Creating fast pick areas close to the conveyor is essential in achieving high productivity in zone picking. Zone picking is most effective in large operations with high total numbers of skus, high total numbers of orders, and low to moderate picks per order. Separate zones also provide for specialization of picking techniques such as having automated material handling systems in one zone and manual handling in the next.
Wave picking. A variation on zone picking and batch picking where rather than orders moving from one zone to the next for picking, all zones are picked at the same time and the items are later sorted and consolidated into individual orders/shipments. Wave picking is the quickest method (shortest cycle time) for picking multi item orders however the sorting and consolidation process can be tricky. Operations with high total number of SKUs and moderate to high picks per order may benefit from wave picking. Wave picking may be used to isolate orders by specific carriers, routes, or zones.

Piece-picking equipment: As with the picking methods, the picking equipment used will also depend on a variety of factors.
Static shelving. The most common equipment for storage in piece pick operations, static shelving is designed with depths from 12” to 24”. Product is either placed directly on the shelving or in corrugated, plastic, or steel parts bins. Static shelving is economical and is the best method where there are few picks per SKU or where parts are very small.
Carton flow rack. Carton flow rack is similar to static shelving with the exception that rather than shelves, there are small sections of gravity conveyor mounted at a slight angle. Product is stocked from the rear of the flow rack and picking is done from the face. Product can be stocked in cartons or small totes or bins. As a carton or tote is emptied, it is removed from the rack and another one will roll into place. Carton flow rack is most useful where there is a very high number of picks per SKU.
Carousels. Horizontal carousels are a version of the same equipment used by dry cleaners to store and retrieve clothing. They have racks hanging from them that can be configured to accommodate various size storage bins. Generally an operator will run 2 to 4 carousels at a time avoiding the need for the operator to wait while one unit is turning. Picking is usually performed in batches with orders downloaded from the host system to the carousel software. Horizontal carousels are most common in picking operations with very high number of orders, low to moderate picks per order, and low to moderate picks per sku. Horizontal carousels provide very high pick rates as well as high storage density. Pick-to-light systems are often integrated into carousels. Vertical Carousels are frequently used in laboratories and specialty manufacturing operations and are rarely used in regular order picking operations.
Automatic storage and retrieval systems (ASRS). An ASRS is a system of rows of rack, each row having a dedicated retrieval unit that moves vertically and horizontally along the rack, picking and putting away loads. ASRS systems are available in mini-load types that store and transfer product on some type of tray or in bins, and unit-load types that transfer and store pallet loads or other large unitized loads. In addition to the automation features, ASRS units can provide extremely high storage density with capabilities to work in racking up to 100 feet high. Unfortunately the high costs of ASRS equipment and the length of the retrieval times make it difficult to incorporate into a piece picking operation.
Automatic picking machines. Fully automated picking machines (such as A-frames) are still pretty rare and are used only where very high volumes of similar products are picked such as music CDs, or, where high volume in combination with high accuracy requirements exist such as pharmaceutical fulfillment.
Pick-to-light. Pick-to light systems consist of lights and LED displays for each pick location. The system uses software to light the next pick and display the quantity to pick. Pick-to-light systems have the advantage of not only increasing accuracy, but also increasing productivity. Since hardware is required for each pick location, pick-to-light systems are easier to cost justify where very high picks per SKU occur. Carton flow rack and horizontal carousels are good applications for pick to light. In batch picking, put-to-light is also incorporated into the cart or rack that holds the cartons or totes that you are picking in to. The light will designate which order you should be placing the picked items in.
Bar-code scanners. Though very useful in increasing accuracy levels, bar-code scanners in a fast-paced piece-pick operation tend to become cumbersome and can significantly reduce your pick rates. With proper training, tracking, and accountability, you can get very high accuracy rates in order picking without scanners. I find they are better suited to case pick, pallet load, putaway, and order checking operations.
Voice-directed picking. Voice technology has come of age in recent years and is now a very viable solution for piece pick, case pick, or pallet pick operations.
Automated conveyor and sortation Systems. Automated conveyor systems and sortation systems will be integral to any large-scale piece pick operation. The variety of equipment and system designs is enormous.

Case Picking
Case-picking methods. Case picking operations tend to have less diversity in product characteristics than piece picking operations, with fewer SKUs and higher picks per SKU.
Basic case-picking method. This is the most common method for case-picking operations. Rather than product stored on static shelving, case-pick operations will have the product stored in pallet rack or in bulk in floor locations. The simplest picking method is to use a hand pallet jack (or motorized pallet truck) and pick cases out of bulk floor locations however many operations will find that going to very narrow aisle (VNA) pallet racking and using man-up order selectors or turret trucks will provide high storage density and high pick rates.
Batch picking. Batch picking is rarely used in case pick operations primarily because of the physical size of the picks. You are unlikely to have enough room on a pallet to pick multiple orders.
Zone picking. Zone picking can be used in case-picking operations, however, like batch picking, the size of the picks and the size of the orders in most case-pick operations do not lend themselves well to zone picking. If you do have a case pick operation where you have a large number of SKUs, and orders with small quantities per SKU, or where you have enough cases per order per zone to fill a pallet, you may find zone picking applicable.
Wave picking. Wave picking can be applied to case picking operations where you have very large orders with many picks per order and are looking for ways to reduce cycle time.
Case-picking equipment.
Pallet rack. Pallet rack is the most common storage system for case pick operations.
Flow rack. Although carton flow rack rarely applies to case pick operations, pallet flow rack or push back rack can be useful.
Carousels. Although you can incorporate unit-load carousels into a case pick operation, it tends to be an unlikely match-up. If doing batch picking where you have many picks per SKU and few pieces per pick you can pick from an ASRS unit onto a unit-load carousel.
Automated storage and retrieval systems (ASRS). Unit-load ASRS systems can be useful in case-pick operations, especially if you can provide storage heights of 40 to 100 feet.
Pick-to-light. Pick-to-light can be used in case-pick operations, however, its application is significantly less than in piece pick operations.
Bar-code scanners. Bar-code scanners are frequently used in case-pick operations. Since the time to physically pick the product is higher in case-pick operations, the time spent scanning tends to have little impact on productivity and therefore the accuracy benefits will usually outweigh any reduction in productivity.
Voice-directed picking. Voice technology has come of age in recent years and is now a very viable solution for piece pick, case pick, or pallet pick operations.
Automated conveyor and sortation systems. If using zone or wave picking, automated conveyor and sortation systems will likely be a part of your system. In case picking, you may use standard conveyors to transport individual cases or unit-load conveyors to transport pallets.
Lift trucks. As previously mentioned, motorized pallet trucks, man-up order selectors, and man-up turret trucks are the vehicles of choice for case-pick operations.

Pallet Picking
Full-pallet-picking methods. Full-pallet picking is also known as unit-load picking. The systematic methods for full-pallet picking are much simpler that either piece pick or case pick, however, the choices in storage equipment, storage configurations, and types of lift trucks used are many.
Basic pallet picking. This is the most common method for full-pallet picking. Orders are picked one at a time. The order picker will use some type of lift truck, retrieve the pallet load and stage it in a shipping area in a staging lane designated for that order, or just pick and load directly into an outbound trailer or container..
Batch picking. Since the nature of pallet picking is a single pick per trip, batch picking has no application in pallet-picking operations.
Zone and wave picking. Although the normal definition of zone picking where an order is moved from zone to zone as picks are accumulated doesn’t apply to pallet picking, pick zones are used in wave picking in pallet-picking operations. The storage area is broken into zones to eliminate multiple lift-truck operators from picking in the same aisle. The lift truck operator may pick the pallet and deliver it directly to the designated staging lane or place it on a unit-load conveyor that will deliver it to the sorting/staging area.
Task interleaving. Task interleaving is a method of combining picking and putaway. Warehouse Management Systems (WMS) use logic to direct a lift truck operator to put away a pallet en route to the next pick.

Pallet-picking equipment.
Pallet rack. There are numerous pallet rack configurations used in full pallet operations, from standard back-to-back single pallet depth configurations to double-deep rack, push-back rack, drive-in/drive-thru rack, and flow rack. The best racking configuration for your operation will be based on the total number of pallets per sku, pallets per pick, and the length of time the product is in the rack prior to shipment. There are a lot of tradeoffs in choosing a racking configuration including storage density, picking productivity, equipment costs, and the ability to maintain first-in first-out.
ASRS. Unit-load ASRS units when combined with unit-load conveyors and sortation systems can provide fully automatic pallet picking operations. And again, the ability to store product in racking up to 100 feet high gives excellent storage density.
Automated conveyor and sortation systems. Automated conveyor and sortation systems can be combined with ASRS units or used in conjunction with manual picking with lift trucks in zone/wave picking systems. Either the ASRS or the lift truck operator delivers the pallet load to the conveyor. The conveyor system then delivers the pallet to the shipping area where it is either manually sorted by lift trucks into the designated staging lane, or a sortation system automatically sorts into a staging lane. Staging lanes can be equipped with automated or gravity fed unit-load conveyor.
Bar-code scanners. Bar-code scanners are very commonly used in pallet-pick operations.
Voice-directed picking. Voice technology has come of age in recent years and is now a very viable solution for piece pick, case pick, or pallet pick operations.
Lift trucks. The lift trucks used for pallet picking will depend upon the storage configuration. Standard lift trucks are used in bulk floor storage and wide-aisle pallet rack storage in singe-depth, push-back, drive-in/drive-thru, and flow rack. Reach trucks are used in narrow-aisle storage in single-depth, double-deep, push-back, drive-in/drive-thru, and flow rack. Swing mast and turret trucks are used in very narrow aisle storage in single depth pallet rack.

General Information
Regardless of the product handled, or the picking method and equipment used, locating product by the frequency of picks should be incorporated into the system design. The fastest moving product should be stocked as close to the pick point as possible and at the levels that are easiest to pick from. Even if you are using an ASRS unit, the retrieval time will be less the closer the location is to the pick point, and in a horizontal carousel, the picking time will be less if the order picker does not need to bend down or reach up to pick.
In fixed location picking, you designate a specific picking location for each SKU. Fixed picking locations are most commonly used in piece-pick operations, however, they may also be used in case picking and pallet picking where flow rack is incorporated. Slotting in fixed picking locations needs to be reviewed on a regular bases to ensure high levels of productivity. The frequency of review will depend upon product life cycles and seasonality. In random storage operations, a WMS system can direct fast movers to the closest open location to the pick point.
Operations using fixed picking locations will generally also have a reserve or overflow storage area. The overflow storage area will usually use a system of random storage. A replenishment system will need to be put in place to move product to the fixed picking locations as inventory levels drop to predetermined levels.
Outbound shipments should always have some type of a check in place. The type of check will vary from operation to operation. In a high-volume low-value shipping operation, a simple "looking over" the shipment may be all that's feasible, while in a lower-volume high-value shipping operation, I've had as many as three people performing redundant checks of each shipment prior to loading.
Extensive data analysis is necessary in determining the best methods for order picking. Historical data on picks per SKU, quantity per pick, picks per order, total picks, total orders, orders received by time of day, etc. will be important in not only the initial plan, but also in the ongoing operation of the system.
It will also be very important to project growth, especially in automated systems. While you can throw more people into a manual system when transactions increase, automated systems such as carousels and ASRS units will have capacity limits.
Order-picking systems can be very simple systems in small operations or become very complex systems using a little bit of everything. In a large operation you may have totes start as batch pick in a carousel picking area for your medium moving piece-pick items, and then move individually to a manual picking area for slow moving small-parts piece picking out of static shelving (possibly in a mezzanine). Then move to a carton-flow rack area for your fastest moving items, and finally to a shipping staging/consolidation area where it is matched up with cases and bulkier items from a case-pick ASRS unit and full pallets from a racked warehouse.

Source : Dave Piasecki, Logistic Management.

Warehouse Management Systems (WMS).

The evolution of warehouse management systems (WMS) is very similar to that of many other software solutions. Initially a system to control movement and storage of materials within a warehouse, the role of WMS is expanding to including light manufacturing, transportation management, order management, and complete accounting systems. To use the grandfather of operations-related software, MRP, as a comparison, material requirements planning (MRP) started as a system for planning raw material requirements in a manufacturing environment. Soon MRP evolved into manufacturing resource planning (MRPII), which took the basic MRP system and added scheduling and capacity planning logic. Eventually MRPII evolved into enterprise resource planning (ERP), incorporating all the MRPII functionality with full financials and customer and vendor management functionality. Now, whether WMS evolving into a warehouse-focused ERP system is a good thing or not is up to debate. What is clear is that the expansion of the overlap in functionality between Warehouse Management Systems, Enterprise Resource Planning, Distribution Requirements Planning, Transportation Management Systems, Supply Chain Planning, Advanced Planning and Scheduling, and Manufacturing Execution Systems will only increase the level of confusion among companies looking for software solutions for their operations.
Even though WMS continues to gain added functionality, the initial core functionality of a WMS has not really changed. The primary purpose of a WMS is to control the movement and storage of materials within an operation and process the associated transactions. Directed picking, directed replenishment, and directed putaway are the key to WMS. The detailed setup and processing within a WMS can vary significantly from one software vendor to another, however the basic logic will use a combination of item, location, quantity, unit of measure, and order information to determine where to stock, where to pick, and in what sequence to perform these operations.

Do You Really Need WMS?
Not every warehouse needs a WMS. Certainly any warehouse could benefit from some of the functionality but is the benefit great enough to justify the initial and ongoing costs associated with WMS? Warehouse Management Systems are big, complex, data intensive, applications. They tend to require a lot of initial setup, a lot of system resources to run, and a lot of ongoing data management to continue to run. That’s right, you need to "manage" your warehouse "management" system. Often times, large operations will end up creating a new IS department with the sole responsibility of managing the WMS.
The Claims:
WMS will reduce inventory!
WMS will reduce labor costs!
WMS will increase storage capacity!
WMS will increase customer service!
WMS will increase inventory accuracy!
The Reality:
The implementation of a WMS along with automated data collection will likely give you increases in accuracy, reduction in labor costs (provided the labor required to maintain the system is less than the labor saved on the warehouse floor), and a greater ability to service the customer by reducing cycle times. Expectations of inventory reduction and increased storage capacity are less likely. While increased accuracy and efficiencies in the receiving process may reduce the level of safety stock required, the impact of this reduction will likely be negligible in comparison to overall inventory levels. The predominant factors that control inventory levels are lot sizing, lead times, and demand variability. It is unlikely that a WMS will have a significant impact on any of these factors. And while a WMS certainly provides the tools for more organized storage which may result in increased storage capacity, this improvement will be relative to just how sloppy your pre-WMS processes were.
Beyond labor efficiencies, the determining factors in deciding to implement a WMS tend to be more often associated with the need to do something to service your customers that your current system does not support (or does not support well) such as first-in-first-out, cross-docking, automated pick replenishment, wave picking, lot tracking, yard management, automated data collection, automated material handling equipment, etc.

Setup
The setup requirements of WMS can be extensive. The characteristics of each item and location must be maintained either at the detail level or by grouping similar items and locations into categories. An example of item characteristics at the detail level would include exact dimensions and weight of each item in each unit of measure the item is stocked (eaches, cases, pallets, etc) as well as information such as whether it can be mixed with other items in a location, whether it is rackable, max stack height, max quantity per location, hazard classifications, finished goods or raw material, fast versus slow mover, etc. Although some operations will need to set up each item this way, most operations will benefit by creating groups of similar products. For example, if you are a distributor of music CDs you would create groups for single CDs, and double CDs, maintaining the detailed dimension and weight information at the group level and only needing to attach the group code to each item. You would likely need to maintain detailed information on special items such as boxed sets or CDs in special packaging. You would also create groups for the different types of locations within your warehouse. An example would be to create three different groups (P1, P2, P3) for the three different sized forward picking locations you use for your CD picking. You then set up the quantity of single CDs that will fit in a P1, P2, and P3 location, quantity of double CDs that fit in a P1, P2, P3 location etc. You would likely also be setting up case quantities, and pallet quantities of each CD group and quantities of cases and pallets per each reserve storage location group.
If this sounds simple, it is…well… sort of. In reality most operations have a much more diverse product mix and will require much more system setup. And setting up the physical characteristics of the product and locations is only part of the picture. You have set up enough so that the system knows where a product can fit and how many will fit in that location. You now need to set up the information needed to let the system decide exactly which location to pick from, replenish from/to, and putaway to, and in what sequence these events should occur (remember WMS is all about “directed” movement). You do this by assigning specific logic to the various combinations of item/order/quantity/location information that will occur.
Below I have listed some of the logic used in determining actual locations and sequences.
Location Sequence. This is the simplest logic; you simply define a flow through your warehouse and assign a sequence number to each location. In order picking this is used to sequence your picks to flow through the warehouse, in putaway the logic would look for the first location in the sequence in which the product would fit.
Zone Logic. By breaking down your storage locations into zones you can direct picking, putaway, or replenishment to or from specific areas of your warehouse. Since zone logic only designates an area, you will need to combine this with some other type of logic to determine exact location within the zone.
Fixed Location. Logic uses predetermined fixed locations per item in picking, putaway, and replenishment. Fixed locations are most often used as the primary picking location in piece pick and case-pick operations, however, they can also be used for secondary storage.
Random Location. Since computers cannot be truly random (nor would you want them to be) the term random location is a little misleading. Random locations generally refer to areas where products are not stored in designated fixed locations. Like zone logic, you will need some additional logic to determine exact locations.
First-in-first-out (FIFO). Directs picking from the oldest inventory first.
Last-in-first-out (LIFO). Opposite of FIFO. I didn't think there were any real applications for this logic until a visitor to my site sent an email describing their operation that distributes perishable goods domestically and overseas. They use LIFO for their overseas customers (because of longer in-transit times) and FIFO for their domestic customers.
Quantity or Unit-of-measure. Allows you to direct picking from different locations of the same item based upon the quantity or unit-of-measured ordered. For example, pick quantities less than 25 units would pick directly from the primary picking location while quantities greater than 25 would pick from reserve storage locations.
Fewest Locations. This logic is used primarily for productivity. Pick-from-fewest logic will use quantity information to determine least number of locations needed to pick the entire pick quantity. Put-to-fewest logic will attempt to direct putaway to the fewest number of locations needed to stock the entire quantity. While this logic sounds great from a productivity standpoint, it generally results in very poor space utilization. The pick-from-fewest logic will leave small quantities of an item scattered all over your warehouse, and the put-to-fewest logic will ignore small and partially used locations.
Pick-to-clear. Logic directs picking to the locations with the smallest quantities on hand. This logic is great for space utilization.
Reserved Locations. This is used when you want to predetermine specific locations to putaway to or pick from. An application for reserved locations would be cross-docking, where you may specify certain quantities of an inbound shipment be moved to specific outbound staging locations or directly to an awaiting outbound trailer.
Nearest Location. Also called proximity picking/putaway, this logic looks to the closest available location to that of the previous putaway or pick. You need to look at the setup and test this type of logic to verify that it is picking the shortest route and not the actual nearest location. Since the shortest distance between two points is a straight line, this logic may pick a location 30 feet away (thinking it’s closest) that requires the worker to travel 200 feet up and down aisles to get to it while there was another available location 50 feet away in the same aisle (50 is longer than 30).
Maximize Cube. Cube logic is found in most WMS systems however it is seldom used. Cube logic basically uses unit dimensions to calculate cube (cubic inches per unit) and then compares this to the cube capacity of the location to determine how much will fit. Now if the units are capable of being stacked into the location in a manner that fills every cubic inch of space in the location, cube logic will work. Since this rarely happens in the real world, cube logic tends to be impractical.
Consolidate. Looks to see if there is already a location with the same product stored in it with available capacity. May also create additional moves to consolidate like product stored in multiple locations.
Lot Sequence. Used for picking or replenishment, this will use the lot number or lot date to determine locations to pick from or replenish from.
It’s very common to combine multiple logic methods to determine the best location. For example you may chose to use pick-to-clear logic within first-in-first-out logic when there are multiple locations with the same receipt date. You also may change the logic based upon current workload. During busy periods you may chose logic that optimizes productivity while during slower periods you switch to logic that optimizes space utilization.

Other Functionality/Considerations
Wave Picking/Batch Picking/Zone Picking. Support for various picking methods varies from one system to another. In high-volume fulfillment operations, picking logic can be a critical factor in WMS selection.
Task Interleaving. Task interleaving describes functionality that mixes dissimilar tasks such as picking and putaway to obtain maximum productivity. Used primarily in full-pallet-load operations, task interleaving will direct a lift truck operator to put away a pallet on his/her way to the next pick. In large warehouses this can greatly reduce travel time, not only increasing productivity, but also reducing wear on the lift trucks and saving on energy costs by reducing lift truck fuel consumption. Task interleaving is also used with cycle counting programs to coordinate a cycle count with a picking or putaway task.
Automated Data Collection (ADC). It is generally assumed when you implement WMS that you will also be implementing automatic data collection, usually in the form of radio-frequency (RF) portable terminals with bar code scanners. I recommend incorporating your ADC hardware selection and your software selection into a single process. This is especially true if you are planning on incorporating alternate technologies such as voice systems, RFID, or light-directed systems. You may find that a higher priced WMS package will actually be less expensive in the end since it has a greater level of support for the types of ADC hardware you will be using. In researching WMS packages you may see references like “supports”, “easily integrates with”, “works with”, “seamlessly interfaces with” in describing the software’s functionality related to ADC. Since these statements can mean just about anything, you’ll find it important to ask specific questions related to exactly how the WMS system has been programmed to accommodate ADC equipment. Some WMS products have created specific versions of programs designed to interface with specific ADC devices from specific manufacturers. If this WMS/ADC device combination works for your operation you can save yourself some programming/setup time. If the WMS system does not have this specific functionality, it does not mean that you should not buy the system, it just means that you will have to do some programming either on the WMS system or on the ADC devices. Since programming costs can easily put you over budget you’ll want to have an estimate of these costs up front. As long as you are working closely with the WMS vendor and the ADC hardware supplier at an early stage in the process you should be able to avoid any major surprises here.
Integration with Automated Material Handling Equipment. If you are planning on using automated material handling equipment such as carousels, ASRS units, AGVs, pick-to-light systems, or sortation systems, you’ll want to consider this during the software selection process. Since these types of automation are very expensive and are usually a core component of your warehouse, you may find that the equipment will drive the selection of the WMS. As with automated data collection, you should be working closely with the equipment manufacturers during the software selection process.
Advanced Shipment Notifications (ASN). If your vendors are capable of sending advanced shipment notifications (preferably electronically) and attaching compliance labels to the shipments you will want to make sure that the WMS can use this to automate your receiving process. In addition, if you have requirements to provide ASNs for customers, you will also want to verify this functionality.
Cycle Counting. Most WMS will have some cycle counting functionality. Modifications to cycle counting systems are common to meet specific operational needs.
Cross Docking. In its purest form cross-docking is the action of unloading materials from an incoming trailer or rail car and immediately loading these materials in outbound trailers or rail cars thus eliminating the need for warehousing (storage). In reality pure cross-docking is less common; most "cross-docking" operations require large staging areas where inbound materials are sorted, consolidated, and stored until the outbound shipment is complete and ready to ship. If cross docking is part of your operation you will need to verify the logic the WMS uses to facilitate this.
Pick-to-Carton. For parcel shippers pick-to-carton logic uses item dimensions/weights to select the shipping carton prior to the order picking process. Items are then picked directly into the shipping carton. When picking is complete, dunnage is added and the carton sealed eliminating a formal packing operation. This logic works best when picking/packing products with similar size/weight characteristics. In operations with a very diverse product mix it's much more difficult to get this type of logic to work effectively.
Slotting. Slotting describes the activities associated with optimizing product placement in pick locations in a warehouse. There are software packages designed just for slotting, and many WMS packages will also have slotting functionality. Slotting software will generally use item velocity (times picked), cube usage, and minimum pick face dimensions to determine best location.
Yard Management. Yard management describes the function of managing the contents (inventory) of trailers parked outside the warehouse, or the empty trailers themselves. Yard management is generally associated with cross docking operations and may include the management of both inbound and outbound trailers.
Labor Tracking/Capacity Planning. Some WMS systems provide functionality related to labor reporting and capacity planning. Anyone that has worked in manufacturing should be familiar with this type of logic. Basically, you set up standard labor hours and machine (usually lift trucks) hours per task and set the available labor and machine hours per shift. The WMS system will use this info to determine capacity and load. Manufacturing has been using capacity planning for decades with mixed results. The need to factor in efficiency and utilization to determine rated capacity is an example of the shortcomings of this process. Not that I’m necessarily against capacity planning in warehousing, I just think most operations don’t really need it and can avoid the disappointment of trying to make it work. I am, however, a big advocate of labor tracking for individual productivity measurement. Most WMS maintain enough data to create productivity reporting. Since productivity is measured differently from one operation to another you can assume you will have to do some minor modifications here .
Activity-based costing/billing. This functionality is primarily designed for third-party logistics operators. Activity-based billing allows them to calculate billable fees based upon specific activities. For example, a 3PL can assign transaction fees for each receipt, and shipment transaction, as well as fees for storage and other value-added activities.
Integration with existing accounting/ERP systems. Unless the WMS vendor has already created a specific interface with your accounting/ERP system (such as those provided by an approved business partner) you can expect to spend some significant programming dollars here. While we are all hoping that integration issues will be magically resolved someday by a standardized interface, we ain’t there yet. Ideally you’ll want an integrator that has already integrated the WMS you chose with the business software you are using. Since this is not always possible you at least want an integrator that is very familiar with one of the systems.
WMS + everything else = ? As I mentioned at the beginning of this article, a lot of other modules are being added to WMS packages. These would include full financials, light manufacturing, transportation management, purchasing, and sales order management. I don’t see this as a unilateral move of WMS from an add-on module to a core system, but rather an optional approach that has applications in specific industries such as 3PLs. Using ERP systems as a point of reference, it is unlikely that this add-on functionality will match the functionality of best-of-breed applications available separately. If warehousing/distribution is your core business function and you don’t want to have to deal with the integration issues of incorporating separate financials, order processing, etc. you may find these WMS based business systems are a good fit.

Source : Dave Piasecki, Logistic Management.