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Research Article
Open Access Peer-reviewed

Measuring Leanness and Agility of Job Shops: A Rating Scale Based on Expert Consensus

Zaki Kuruppalil
Journal of Business and Management Sciences. 2018, 6(3), 112-117. DOI: 10.12691/jbms-6-3-8
Published online: June 29, 2018

Abstract

The importance for job shops in manufacturing spectrum is increasing as the market requires low volume, high quality, custom and specific products. With global competition towards customization, job shops are striving to streamline their operations for better yield and exceed customer expectations by shorter speed to market and maintaining budgetary confinements of customer. In that scenario, both lean and agile manufacturing strategies are important to job shops for improving efficiencies and responding to rapidly changing customer needs. This paper presents a rapid assessment tool for job shops to determine where they stand in terms of exhibiting lean and agile characteristics.

1. Introduction to Job Shops

Job shops are manufacturing companies who make to order a variety of products in relatively low numbers and high variety in batch lots by the use of various general-purpose standard machine tools or machining centers 1. Because of batch processing, the possibility of waste or non-value-added activities occurring in their operations are relatively high. Conner compares job shops to restaurants where a chef will cook a piece of steak only after receiving the order 2. Job shops are likely to have hundreds of part numbers and can never accurately predict their future orders. Considering the unpredictable nature of business, turnaround time in order completion is critical in their business success. The importance of job shops is increasing as customer demands and market requirements are changing quickly and there is more demand towards customization. The market requires low volume, high quality, custom and specific products. With global competition towards customization, job shops are striving to streamline their operations for better yield and exceed customer expectations by shorter speed to market and maintaining budgetary confinements of customer 3.

2. Leanness Vs Agility

Leanness and agility refers to two different concepts even though there is some overlap between the two. Lean has its roots tied to Toyota Production System(TPS). Womack and Jones explain that Lean “provides a way to specify value, line up value-creating action in the best sequence, conduct these activities without interruption whenever someone requests them, and perform them more effectively. In short, Lean thinking is ‘Lean’ because it provides a way to do more with less – less human effort, less equipment, less time, and less space – while coming closer and closer to providing customers with what they really want” 4. Lean is comprised of operational practices and techniques that could improve efficiencies of the shop floor, provide better utilization of resources (both men and machine, and improved process methods). It emphasizes eliminating manufacturing wastes of overproduction, excess processing, excess motion, waiting to be processed, transportation, defects, and excess inventory. From a job shop perspective, lean manufacturing is more focused on continuously improving the existing manufacturing methods and shop floor practices to eliminate these wastes and create more value to the customer. Leanness have identified to make positive impact on performance measures such as work in process, lead time, cycle times productivity, work place layout and environment and customer service levels 5. Simmons, Holt, Dennis, & Walton have reported 600% increase in throughput and 83% reduction in defects is just one of the examples to take 6. In spite of its globally reported successes success stories as an operational strategy, several studies have been conducted regarding lean and its need to be applied differently when it comes to low volume high variety businesses such as job shops 3. Also, the author is of the opinion that lean’s ability as a broader business strategy to address innovation and tapping into opportunities such as niche market is limited.

Whereas Agile Manufacturing originated as result of an effort from Iacocca Institute at Lehigh University to develop a manufacturing framework that could give US companies an edge over their worldwide competitors 7 upon a United States Department of Defense (DOD) requested. Agile manufacturing is the ability to thrive and prosper in an environment of constant and unpredictable change by bringing technology, knowledge, skills, resources and people around clearly identified market opportunities 8. Goldman, Nagel & Preiss stated that “rapid, relentless and uncertain change is the most unsettling market place reality that companies and people must cope with today” 7 (p.3). The quicker and more effectively changes can be made, the better the enterprise will be able to survive and improve in this environment. It is important to note that agile manufacturing is often misinterpreted as flexible manufacturing. Agility refers to more than flexibility, flexible manufacturing is only one of the few components in agile manufacturing. According to Kidd the concept of Agile Manufacturing is built around the synthesis of a number of enterprises that each have some core skills or competencies which they bring to a joint venturing operation, which is based on using each partner’s facilities and resources 7. For this reason, these joint venture enterprises are called virtual corporations, because they do not own significant capital resources of their own. This helps to make them Agile, as they can be formed and changed very rapidly. The agility that arises can be used for competitive advantage, by being able to respond rapidly to changes occurring in the market environment and through the ability to use and exploit a fundamental resource or knowledge. People need to be brought together, in dynamic teams formed around clearly defined market opportunities, so that it becomes possible to lever one another's knowledge. Through this process is sought the transformation of knowledge into new products and services.

2.1. Co-existing Strategies

Lean is more focused on improvising or maximizing the efficiency of resources that are currently existing and within the control of the organization whereas agility deals with preparing the organizations to maximize their advantage in an environment of constant change and unpredictability. Both lean and agile manufacturing strategies can improve business. Agile manufacturing improves the ability of a job shop to quickly respond to market uncertainties, whereas lean manufacturing benefits job shops by improving their operational efficiencies and reduce manufacturing wastes. Agility prepares the organization to take maximum business advantage in a turbulent environment of change and unpredictability. Lean, as a strategy, deals much less with proactive business and exploration of new opportunities. The author is of the opinion that characteristics of agile manufacturing may help businesses fill this gap by encouraging them to become proactive and innovative. Lean as a strategy may be successful in maximizing the efficiency of resources that are within the control of the organization. Lean manufacturing has set practices and techniques which could sometimes serve as means to achieving agile characteristics. Therefore, lean techniques could sometimes serve as a foundation to achieving agility. This implied the need for coexistence of both the strategies.

2.2. The Need to Measure

Having concluded, that leanness and agility should coexist, it is important for job shops to know where they stand in terms of leanness and agility to continuously improve their capabilities. However, upon review of literature, only few set of assessment tools exist, specifically for job shops, to measure their leanness and agility. Djassemi has emphasized the importance of job shops to national economy and lack of published material regarding success of these businesses 9. The closest study found was “Read a Plant –fast” developed by Mr. Eugene Goodson, a professor at University of Michigan Business School. Goodson has developed a Rapid Plant Assessment Tool that could discern a plant’s strength and weakness in terms of lean 10. The assessment tool did not include characteristics of agile manufacturing. Another study of interest was by Rawabdeh that suggested a model for waste assessment in job shop environment 11. However, the theme of comprehensive tool for job shops was missing from the studies evaluated by the author.


2.2.1. Underlying Research

The underlying research for this manuscript was a study conducted by the author comparing key factors of leanness and agility in job shops 12. The results of that study were published in another manuscript which serves as the primary supporting document for this paper 13. The author in his study observed that both leanness and agility are important to job shops in terms of eliminating waste and rapidly responding to customer needs. At the end it was concluded that agile and lean manufacturing are two different strategies which address different aspects of a business. They are neither competing nor complementing strategies rather they should be coexisting strategies.


2.2.2. The Assessment Tool

The author’s study mentioned in the previous section of this document utilized Delphi method to bring collective knowledge of a panel of eleven experts and consonance was reached on the key indicators of leanness and agility. MacCarthy and Atthirawong define Delphi as a systematic, iterative process to elicit a consensus view from a panel of exports 14. They noted that Delphi process appeared to provide the individual with the greatest degree of individuality or freedom from restrictions on his/her expressions. It avoided the dominant influence of any one member of the group over the others. Two Delphi studies were conducted using two sets of experts (a panel of lean experts and panel of agile experts) and the results were combined. The researcher included in the panel a mix of experts from academia, industry and consultancy. These experts were located geographically in different countries including Israel, United Kingdom and United States. A scale was provided to experts to indicate towards each item as not relevant equaled to 0, somewhat relevant equaled to 1, relevant equaled to 2, Very relevant equaled to 3. The scale was provided under the impression that the experts will rate each indicator with their perception of relative importance. Table 1 has listed agile and lean indicators respectively along with the median scores (required scores) of expert responses as obtained from the Delphi study.

Column 1, is a numerical identification for each indicator. Column 2, represents broader categories or domains of leanness and agility as identified by the author. Column 3, represents description of the lean/agile indicator. Column 4, represents assessment question to be asked while rating eating each indicator. Column 5, represents the median score was renamed as required score as it represented consensus of experts on relevance of each indicator. Any response with a median score below two was omitted as it was indication that most experts considered that particular item below relevance. Column 6, the last column of the table was calculated to represent their relative importance to one another.

Since each of this indicator are weighed differently by the experts, an assessment tool utilizing a radar chart would help job shops assess where they stand in terms of leanness and agility compared to what is stated as required by the experts. This would help to associate each indicator differently based on the relative importance with which it was viewed by the experts. Such a chart is depicted below in Figure 1.

It should be noted that the company A and its scores mentioned in Figure 1 are hypothetical and was included with the intention of simplifying interpretation of the above rating scale. Each of the numbers 1 through 58 represents corresponding lean or agile indicators mentioned in Table 1. Job shops (such as Company A) could rate on a scale of 0 to 3 (not relevant to the company equaled to 0, somewhat relevant equaled to 1, relevant equaled to 2, Very relevant equaled to 3) to perform a self-analysis of where they stand in terms of leanness and agility compared to expert rating. The scale description could be altered to users convenience as long as relative importance (required score) is un altered.

3. Conclusions

The rating scale represented in Figure 1. could be used as an initial assessment tool to identify areas where management focus is needed to improve on leanness and agility. It should be noted this assessment tool is not meant to measure performances of job shops after implementing lean or agile tools and techniques. This tool would simply give an estimate of where a job shop stand in terms of exhibiting lean and agile characteristics. Also, the assessment is generic in nature and the effects of additional factors such as size of job shops, position in supply chain, geographic location could influence the assessment and should be considered as a limitation of this tool. The tool could serve as a quick reference to any company who is interested in knowing what comprises leanness and agility. The indicators listed under agility are generic in nature that could be utilized by other types of businesses in the manufacturing spectrum. The data collected could be analyzed using appropriate statistical techniques to deduce conclusions on the characteristics of the job shop under study. These results of such an analysis could also be utilized to reveal any correlation between lean and agile indicators. The 14 domains of the indicators are of great importance as a quick analysis tool. The comparison of these broader categories, for example, if companies score low in the items under domains “Proactive Business”, that could be identified as one of the areas which need attention to improve the business. The scope for future research with the indicators and identifying each of its metrics area abundant. Even though a variety of metrics exist to measure lean related indicators, evaluation metrics for agility related indicators are limited and is open to further research.

References

[1]  Kalpakjian, S., & Schmid, S. R. (2000). Manufacturing engineering and technology (4th ed.). Upper Saddle River, NJ: Prentice Hall
In article      View Article
 
[2]  Conner, G. (2001). Lean manufacturing for the small shop. Dearborn, MI: Society of Manufacturing Engineers
In article      View Article
 
[3]  Qudrat-Ullah, H., Seo Song B., & Mills B.L (2012). Improving high variable-low volume operations: an exploration into the lean product development. International Journal of Technology Management, 57(1/2/3), 65.
In article      View Article
 
[4]  Womack, J. P., & Jones, D. T. (1996). Lean thinking: banish waste and create wealth in your corporation. NY, New York: Simon & Schuster.
In article      View Article
 
[5]  Haider, A. & Mirza, J. (2015). An implementation of lean scheduling in a job shop environment. Advances in Production Engineering & Management, 10 (1), 8.
In article      View Article
 
[6]  Simmons, L., Holt, R., Dennis, G., & Walden, C. (2010). Lean implementation in a low volume manufacturing environment: a case study. Proceeding of the 2010 Industrial Engineering research Conference.
In article      View Article
 
[7]  Goldman, S. L., Nagel, R. N., & Preiss, K. (1995). Agile competitors and virtual organizations. New York, NY: Van Nostrand Reinhold.
In article      
 
[8]  Kidd, P. T. (1994). Agile manufacturing: forging new frontiers. Reading, MA: Addison- Wesley.
In article      View Article
 
[9]  Djassemi, M. (2014). Lean adoption in small manufacturing shoops. Attributes and challenges. The journal of Technology, Management, and Applied Engineering, 30 (1), 2-9.
In article      View Article
 
[10]  Goodson, E. R. (2002). Read a plant-Fast. Harvard Business Review,80(5), 105-113.
In article      View Article
 
[11]  Rawabdeh, H. (2005). A model for the assessment of waste in job shop environments. International Journal of Operations & Production Management, 25 (8), 800-822.
In article      View Article
 
[12]  Kuruppalil, Z. (2007). Leanness and agility in job shops: A framework for a survey instrument developed using the Delphi method. Terre Haute, IN. Indiana State University.
In article      View Article
 
[13]  Kuruppalil, Z. (2008). Key Domains of Leanness and Agility in Job Shops. Proceeding of 2008 Internation Conference on Agile Manufacturing.
In article      
 
[14]  MacCarthy, B.L, & Atthirawong, W. (2003). Factors affecting local decisions in an international operation: A Delphi study. International Journal of Operation and Production Management, 23(7/8), 794-817.
In article      View Article
 

Published with license by Science and Education Publishing, Copyright © 2018 Zaki Kuruppalil

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Cite this article:

Normal Style
Zaki Kuruppalil. Measuring Leanness and Agility of Job Shops: A Rating Scale Based on Expert Consensus. Journal of Business and Management Sciences. Vol. 6, No. 3, 2018, pp 112-117. http://pubs.sciepub.com/jbms/6/3/8
MLA Style
Kuruppalil, Zaki. "Measuring Leanness and Agility of Job Shops: A Rating Scale Based on Expert Consensus." Journal of Business and Management Sciences 6.3 (2018): 112-117.
APA Style
Kuruppalil, Z. (2018). Measuring Leanness and Agility of Job Shops: A Rating Scale Based on Expert Consensus. Journal of Business and Management Sciences, 6(3), 112-117.
Chicago Style
Kuruppalil, Zaki. "Measuring Leanness and Agility of Job Shops: A Rating Scale Based on Expert Consensus." Journal of Business and Management Sciences 6, no. 3 (2018): 112-117.
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[1]  Kalpakjian, S., & Schmid, S. R. (2000). Manufacturing engineering and technology (4th ed.). Upper Saddle River, NJ: Prentice Hall
In article      View Article
 
[2]  Conner, G. (2001). Lean manufacturing for the small shop. Dearborn, MI: Society of Manufacturing Engineers
In article      View Article
 
[3]  Qudrat-Ullah, H., Seo Song B., & Mills B.L (2012). Improving high variable-low volume operations: an exploration into the lean product development. International Journal of Technology Management, 57(1/2/3), 65.
In article      View Article
 
[4]  Womack, J. P., & Jones, D. T. (1996). Lean thinking: banish waste and create wealth in your corporation. NY, New York: Simon & Schuster.
In article      View Article
 
[5]  Haider, A. & Mirza, J. (2015). An implementation of lean scheduling in a job shop environment. Advances in Production Engineering & Management, 10 (1), 8.
In article      View Article
 
[6]  Simmons, L., Holt, R., Dennis, G., & Walden, C. (2010). Lean implementation in a low volume manufacturing environment: a case study. Proceeding of the 2010 Industrial Engineering research Conference.
In article      View Article
 
[7]  Goldman, S. L., Nagel, R. N., & Preiss, K. (1995). Agile competitors and virtual organizations. New York, NY: Van Nostrand Reinhold.
In article      
 
[8]  Kidd, P. T. (1994). Agile manufacturing: forging new frontiers. Reading, MA: Addison- Wesley.
In article      View Article
 
[9]  Djassemi, M. (2014). Lean adoption in small manufacturing shoops. Attributes and challenges. The journal of Technology, Management, and Applied Engineering, 30 (1), 2-9.
In article      View Article
 
[10]  Goodson, E. R. (2002). Read a plant-Fast. Harvard Business Review,80(5), 105-113.
In article      View Article
 
[11]  Rawabdeh, H. (2005). A model for the assessment of waste in job shop environments. International Journal of Operations & Production Management, 25 (8), 800-822.
In article      View Article
 
[12]  Kuruppalil, Z. (2007). Leanness and agility in job shops: A framework for a survey instrument developed using the Delphi method. Terre Haute, IN. Indiana State University.
In article      View Article
 
[13]  Kuruppalil, Z. (2008). Key Domains of Leanness and Agility in Job Shops. Proceeding of 2008 Internation Conference on Agile Manufacturing.
In article      
 
[14]  MacCarthy, B.L, & Atthirawong, W. (2003). Factors affecting local decisions in an international operation: A Delphi study. International Journal of Operation and Production Management, 23(7/8), 794-817.
In article      View Article