An eight-step process for improving logistics activities
David R. Gibson
Logistics activities are searching constantly for ways to improve process capabilities, shorten throughput times, improve quality, and cut costs. Many manufacturing and quality engineering books describe the specifics of defining process capabilities or optimally designing logistics systems. In many cases, the need for improvements may be obvious. In fact, to many private or public sector organizations, these improvements may be necessities. Unfortunately, most private sector businesses and Government activities do not have the luxury of starting from square one. Therefore, most activities require interventions that are synchronized with ongoing operations. So, where is one to start, and what methodology should be used? This article describes an eight-step methodology that can be used to guide decisionmakers through an activity design or redesign to improve operations, increase capacity, or shorten system time requirements.
Step 1: Define Logistics Activity Interrelationships
What materials, products, or information come into the activity? What materials, products, or information flow out of the activity? What interactions does the activity have with other activities?
Before initiating or reworking an activity’s design, it is crucial to understand the role the activity plays with other activities. This will help decisionmakers avoid the trap of suboptimizing an interrelated system or chain of activities; that is, making a change that benefits one activity but actually degrades overall system performance. This can be mapped with a method called interrelationship diagramming. Developing an interrelationship diagram can be as simple as showing all of the associated activities on a chart and drawing in lines to represent the flow of functional or information interactions. (See diagram on page 31.)
Defining an activity’s “as is” and proposed “to be” interrelationships serves as a precursor to activity design or redesign. If the activity is already in operation, this will simply require mapping the known relationships. If the activity is not in operation, a knowledgeable, cross-functional team should draft and troubleshoot a few options to ensure material, function, and information dynamics are addressed.
Once interrelationships are laid out, the analysts can review the relationships to better understand the activity’s role and its inputs and outputs–whether physical or informational. This review may help identify opportunities to eliminate unnecessary redundancies, or it may illustrate opportunities to combine functions within activities. At a minimum, analysts will better understand the environment in which the activity functions.
Step 2: Conduct a Logistics Audit
A logistics audit is a crucial prerequisite to task, process, or system modification. The logistics audit will determine or validate the “as is” baselines by which intervention successes are measured.
The audit should answer the following questions: What resources are available, such as storage, production, and throughput capacities; buildings by size; number of personnel by type; materials-handling equipment by type; conveying systems; and budgeted capital expenditures? What constraints does the activity face, such as building layouts, storage capacities, time allotted for given production requirements, use of certain automation systems, regulatory compliance requirements, surge requirements, and capital expenditure budget? What processes does the activity use, and what are the current standards governing those processes?
Ideally, an activity should use flow charts to demonstrate the processes used to perform tasks, the performance standards required for those processes, and the metrics employed to monitor success. If flow charts are not used, the processes must be documented to ensure that tasks are being performed consistently.
The logistics audit provides a foundation for understanding an activity, analyzing feasible solutions, and measuring the value of implemented solutions.
Quality engineers use the DMAIC (define, measure, analyze, improve, and control) model to document processes before beginning process improvement. If processes are documented, another series of logical questions apply: Are the processes being followed? Are they within acceptable control and performance parameters? Are they outdated? Can they be improved?
It is important to note that processes being performed consistently and within statistical control still may be well outside required performance standards. Processes that appear to be outside the tolerance of established performance parameters must be analyzed for the factors that contribute to inconsistencies. This may be a result of process deviations or inconsistencies in process measurement. Each process analyzed must have a process owner who must be able to demonstrate the performance data that validate process control. Controlling processes within preestablished performance parameters should be part of the activity’s ongoing quality control.
Once processes are documented, analysts can diagram process and system relationships in order to investigate task relationships within processes and process relationships within systems. This approach is called network diagramming. Although network diagramming is most commonly used in the construction industry for project management, the concept also can be helpful in designing a logistics activity. Network diagramming is useful for determining a comprehensive cycle time of more than one task, process, or activity.
Network diagramming helps to identify the time required to complete a given process, activity, or project. This technique provides an ability to identify those tasks on the critical path–a task or process for which any deviation in time will affect the overall process, activity, or project time. Those tasks not on the critical path may have a degree of float time, or system slack, associated with them and may slip forward or backward based on the amount of float time. As long as a task does not slip past the amount of float time, it will not affect the overall process or project time. Changes in the relationships among tasks can affect the critical path and the overall cycle time. For example, if two tasks are performed simultaneously rather than sequentially, the time required to complete the process will be shorter. (See chart)
If the relationships of a given process, activity, or project are fixed, all efforts to decrease the time must focus on critical path tasks, processes, or activities. This approach is known as system “crashing,” or system compression. Efforts to shorten time by compressing tasks not on the critical path will not produce results until all system float time is eliminated. Therefore, the most effective approach requires a focus on critical path activities. This can be done by modernizing equipment, changing task or process performance, or adding resources. Ideally, the system is only compressed to a point of optimal investment. Often the cost to compress outweighs the amount saved by the compression; however, other drivers, such as time constraints, may necessitate the addition of compression.
The boxes used in network diagramming typically show the task to be performed, the task duration, early and late starts, and early and late finishes. Determining float time requires two passes through the network, one forward and one backward. Once complete, subtracting the late start and finish times from the early start and finish times will show the amount of float time. (See chart on page 33.)
Step 3: Define Desired Operational Baselines
This step builds on step 2 when a performance change is determined to be necessary. The change may be an increase in production requirements, a reduction in time to perform a chain of activities, or a reduction of defect variation within existing operations.
To complete this step, analysts must work with the activity’s managers to determine the desired activity performance benchmarks. Performance standards generally reflect cumulative amounts of process or system cycle times. Any task, relationship, or resource modification to a given process usually results in the requirement to modify the performance standard for that process or system.
Several books have been written on benchmarking organizational performance. Therefore, the complexity of this step should not be underestimated. Analyzing the difference between the “as is” performance of an existing activity (step 2) and defining its operational requirements (step 3) is also known as “gap analysis” The gap must be identified in order to investigate feasible solutions.
Step 4: Analyze Systems and Determine Options
The resources and constraints identified in step 2 will directly affect this step of the analysis. Although many methods are available for determining feasible options, simulation technology is often used because of its unquestionable value in identifying or validating potential solution sets. Simulating the interrelationships of an activity’s current systems can identify functional bottlenecks. These bottlenecks are the areas that will require the most focus if the intent is to increase production capability. Simulations may use queuing theory and portray the impact of materials or products that converge at system points for necessary process tasks to be performed. [Queuing theory addresses how systems with limited resources distribute those resources to elements waiting in line and how those elements waiting in line respond.]
Other simulations may focus on linear programming, or “optimization.” These types of simulations try to maximize or minimize something (a given function) subject to a set of constraints (the decision or control variables). The optimal solution is referred to as the objective function because it is always a function of the decision variables. Analysts may find many acceptable, although not optimal, solution sets within the region of feasibility.
Identified solution sets can be placed in simulation software to measure the forecasted value of given interventions, either alone or when combined with others. This gives decisionmakers the ability to experiment with thousands of combinations of interventions without making changes to equipment, numbers of personnel, their schedules, the equipment they use, or other infra–and suprastructure enhancements. Forecasting the value of an intervention can be critical in an environment of limited resources and gives decisionmakers the ability to program capital investments in a manner that makes the most sense for their given constraints.
Step 5: Define Required Decision Criteria
Military decisionmakers use both screening and decision criteria. Screening criteria allow decisionmakers to identify solutions that are impracticable or too costly. Screening criteria should be applied in step 4 to avoid wasting time designing solution sets that hinge on unreasonable interventions. For example, an intervention that requires resources that the organization cannot obtain may not be feasible. Legal, physical, cultural, or sociological constraints may also make an intervention unfeasible.
Applying decision criteria allows decisionmakers to categorize various interventions. For example, if the capital investment plan targets a high return on investment before an intervention’s implementation, analysts should associate interventions with a net initial investment. Additionally, a summary of each net initial investment computation should be documented to ensure that stakeholders understand the computation. For public sector organizations, these values often are determined by cost avoidance. To determine the cash flows associated with cost avoidance, analysts should be able to demonstrate the amount of time or money saved, the increase in production, or the decrease in errors resulting from the intervention. This allows a value to be associated with each improvement.
Interventions may need to be divided into categories if all are not given equal consideration. The criteria in the example on page 34 were provided in order to conduct a cost/benefit analysis using the payback computation. Depending on the organization, use of other financial measures, such as the internal rate of return, profitability index, or net present value, may improve the analysis. All recommendations in the example were provided to enhance a Government warehousing operation. The analysis was conducted in conjunction with computer simulation technology.
Step 6: Decide Which Interventions to Implement
The complexity of this step is determined by the criteria defined and the documentation of interventions after completing analyses of feasible solutions. Once decisionmakers receive the analysis results, they must apply relevant qualitative information to make final decisions for intervention programming.
Step 7: Identify Owners and Make Plans
For interventions to be successful, they must have upper management’s support and someone must “own” the implementation plan. When implementation strategies are personnel intensive, organizational change management considerations should be addressed before the intervention begins. The value of creating personal buy-in and a sense of urgency, establishing ownership, and generating early success should not be underestimated.
Step 8: Implement and Monitor
Once implementation of the solution is underway, interventions should be monitored to validate their success. Measuring implementation progress against the implementation plan will provide the organization with valuable knowledge for future process improvements.
Change is a constant in all organizations. Conceptual models can provide a valuable roadmap to those charged with designing or reengineering an activity. The eight-step methodology described here is one such roadmap that, when followed, will produce pleasing results. An infinite number of management systems and tools can be used with this conceptual model, depending on the specific nature of the problem being addressed. Sometimes merely beginning is the most difficult stage of problem solving. As an old Chinese proverb states, “A journey of a thousand miles begins with a single step.”
RELATED ARTICLE: Sample cost/benefit analysis using the payback computation.
I. Life, health, and safety improvements. Recommendations in this category must include items that address current or potential hazards within the scope of warehouse operations. These may be based on specific Occupational Safety and Health Administration (OSHA) violations or items that contribute to a healthy work environment; for example, painting hazard marks on the floor to separate foot traffic from materials-handling equipment traffic or adding safety rails to prevent damage to shelving. These items must have order-of-magnitude costs identified. The benefits must be self-evident or required by published safety guidance or regulations. Calculating probable damage or expenses associated with accidents is not necessary.
II. Low-cost improvements. Recommendations in this category must include items such as process or minor functional changes that improve operations with little or no cost to the organization. Two examples are building a small storage rack to accommodate the organization and storage of packing materials and adding small clipboard devices to hold paper materiel release orders while pickers select stock. These items must have orders-of-magnitude costs identified. The benefits must be self-evident because of functional or ergonomic enhancements if cost savings or increased capabilities cannot be readily quantified.
III. Capital investments to improve operations. This category must address procurement of additional components, systems, technology, hardware, or other items that will improve operations or significantly increase capabilities to improve operations. These recommendations must be justified using the simulation model in order to demonstrate the functional feasibility of the recommendation.
The cost/benefit analysis must be based on the payback computation, which is used to demonstrate the viability of a given investment. The shorter the payback, the higher the investment should be ranked. This analysis will be computed as follows:
payback = net initial investment /
annual cash flows
Since the Federal Government generally does not include profit on services or materials, it is difficult to compute cash flows in these terms. Therefore, these investments will be reviewed in terms of cost avoidance. For example, if the purchase of an additional stock selection device is recommended, the simulation model must demonstrate that the addition of this device will result in saving a given amount of time. Again, this must be within the required throughput production threshold objective of processing 3,000 materiel release orders a day with the recommended intervention. The final recommendation must show a total number of dollars saved per year. The computations used to arrive at the result must be itemized.
The figure used to represent the cost will be the net initial investment and must be computed as follows:
Net initial investment = the purchase
price + the installation cost + delivery fees +
any initial training required to operate this
device + any increase required for labor,
maintenance, or materials required on hand
for a 1-year period beginning the (lay the
investment is placed into operation.
For example, if a recommended item requires a certain battery, a charging station, and special weekly maintenance, these costs must be itemized, computed for the first year of operation and included in the net initial investment.
Cost avoidance will serve as the annual cash flow and will be computed based on the funds currently spent or required to meet the same level of output. For example, if moving a conveyor belt from A bay to B bay eliminates the use of three forklifts, this must be demonstrated and validated in the model. The cost of these forklifts and their associated costs also should be included in the annual cash flow. The associated costs should include forecasted maintenance expenses and possibly adjustments if the recommendation includes the elimination of a maintenance contract or full-time support personnel who currently maintain a unique component or system. After analysis of the recommendations, the following must be provided–
* A summary of recommendations, rank-ordered by category in a table.
* A brief description of each recommendation, the technical data required for procurement, and the data used to arrive at the recommendation.
* A recommendation for the method or sequence of implementation if different from that shown in the prioritization matrix.
Simulation technology can be helpful in this area by validating time saved with process intervention or the addition of capital investments. The more quantifiable the criteria and the analysis of the intervention, the better.
MAJOR DAVID R. GIBSON IS THE EXECUTIVE OFFICER OF THE 226TH MEDICAL LOGISTICS BATTALION IN MIESAU, GERMANY. HE HAS A BACHELOR’S DEGREE IN BUSINESS FROM THE UNIVERSITY OF CENTRAL OKLAHOMA, A MASTER’S DEGREE IN PUBLIC ADMINISTRATION FROM MURRAY STATE UNIVERSITY IN KENTUCKY, AND MASTER’S DEGREES IN CONSTRUCTION MANAGEMENT AND IN BUSINESS ADMINISTRATION AND FINANCE FROM THE UNIVERSITY OF DENVER. HE/S A GRADUATE OF THE ARMY MEDICAL DEPARTMENT OFFICER BASIC AND ADVANCED COURSES, THE COMBINED ARMS AND SERVICES STAFF SCHOOL, AND THE ARMY COMMAND AND GENERAL STAFF COLLEGE.
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