System Engineering/IS&T Ideas


Have you heard of Lean Thinking? If you haven’t, let me quickly say it a process of minimizing waste in order to increase productivity in manufacturing and in every other activity that is accomplished through various steps. Lean thinking , has five principles which includes: Identifying value, mapping the value stream, creating flow, establishing pull and seeking perfection. There is always a constraint in every system which affects the overall productivity of the system; identify that constraints(bottleneck) , exploit, elevate it and keep on improving the process while being watchful for potential bottlenecks. When you think lean , there won’t be room for waste, hence resources will be well managed and productivity maximized. The slides posted below, describe the application of lean principles to school fees transaction. For further tutoring on Lean thinking do well to contact me here, to schedule an online session. Before then, I would recommend you read this masterpiece called THE GOAL by Eliyahu M. Goldratt and Jeff Cox.

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The theory of constraints is an important tool for improving process flows. The implications of the theory are far-reaching in terms of understanding bottlenecks to a process and better managing these bottlenecks to create an efficient process flow.

The theory of constraints is an important tool for operations managers to manage bottlenecks and improve process flows. Made famous by Eliyahu M. Goldratt in his book The Goal, the implications of the theory are far-reaching in terms of understanding bottlenecks to a process and better managing these bottlenecks to create an efficient process flow. Simply put the theory states, “the throughput of any system is determined by one constraint (bottleneck).” Thus, to increase the throughput, one must focus on identifying and improving the bottleneck or constraint.

Goldratt in another book, Theory of Constraints, outlines a five-step process to applying the theory:

1. Identify the process’ constraints

2. Decide how best to exploit the process constraints

3. Subordinate everything else to the above decisions

4. Evaluate the process constraint

5. Remove the constraint and re-evaluate the process


Long queues could be very frustrating in any bank and much more in Nigeria. Most times one must wait for more than 30 minutes  at the bank to withdraw money from the Automated Teller Machine (ATM) and this affects some other schedules for the day. During my last Holidays, while I was in the queue in one of the Banks in Nigeria, I made some useful observation which I thought could help our people and Banks especially in reducing the waste arising from long wait times at the ATM. On average, it takes 47 seconds to 1 minute of a single withdrawal, to withdraw money from the ATM in the US. Long queues build-up when customers do not follow the best practices or are not considerate of others and this could be seen here as excess inventory which slows efficiency of the ATM Banking system and which has a potential effect on other banking departments. So, this post offers some principles and ideas from “the goal” that could be applied to minimize and/or eliminate long wait times to make ATM transactions more efficient.


 To decongest long queues at the ATM to ensure customer satisfaction.


The major constraints identified in the process is poor customer attitude and occasionally, poor Internet service or machine downtime.  The constraints are observed in the following practice wrong practices:

1. Many who come to the ATM to transfer money and pay bills and struggle with their phones to retrieve information for the transaction.

2. Many come to activate their debit card Pins and spent time thinking on the new password to use.

3. Many elderly men and women with no knowledge of ATM operation, seek help from people around to carry out their transaction when it is their turn to use the ATM, this leads to waste of valuable time

4. Many come with cards that are worn out or bent because of misuse, and the machine keeps rejecting the card, while they keep trying.

 5. Problems arising from unstable Networks at the ATM (Out-of-service error display).

             Having identified the constraints, we shall apply the theory of constraints to improve the process.


Exploit the identified constraints ( bottlenecks) by  Customer re-orientation/ Education through mails and adverts. Improved banking services.


Every other Customer coming to the bank must be informed to comply with the best practices at the ATM, and the customer care must ensure compliance and offer support at all time to customers that need help.


 The following actions are necessary to eliminate the constraints:

 1. Self-service machines designated for other banking services other than withdrawing money and for the disabled. 

2. Queuing up in a row at the ATM helps minimize chaos and maintain a steady flow. 

3. Transaction details if not memorized,  should be copied out in a paper or ready on the phone when going to the ATM.

4. Withdrawals must be made in bulks(pre-set) or own the desired amount, to reduce the number of withdrawal cycle.

5. Counting money after withdrawal from the ATM should be avoided. The ATM is error proof.

6. Checking balances after withdrawal should be avoided.

7. Multiple card removal and insertion in a transaction must be avoided.

8. More education in using e-banking services can decongest long queues at the ATM. Why go to the ATM to pay bills, buy airtime or even make transfers when you can log into your mobile app or dial some code to carry it out at the comfort of your home? 95% of Nigerians who go to the ATM, go to Withdraw money so this should be given priority.


1. Provision of designated E-service ATM machines inside the banks or any secure place outside the bank to enable customers who come to the bank for any other business other than withdrawing money, like fund transfers and bills payments.

2. Improved ATM functionality by increasing internet bandwidth and preventive maintenance on the ATM to avoid long downtime.


Visual Stream Mapping

Value Stream mapping •

Value stream map for making pizza: •

Building process: •

4 May 2020
Qualitative Research – CGU IST 503.1 SP2020 1
Clement Aladi, Robert Marohn, and Zhaoxia (Grace) Yi

Customer Preferences between Self-service Technologies (SSTs) vs. Cashier Checkout in a Retail Store Setting

The introduction of self-service technologies (SSTs) into the retail shopping setting continues to grow. This is self-evident to anyone shopping at stores such as Vons, Ralphs, and Target in the greater Los Angeles area. While SSTs are now frequently found in retail settings (our research only considers brick-and-mortar stores), some shoppers may still not choose to use them (Darrow 2015).
In the past fifteen years, a growing body of research has explored the use and adoption of SSTs. The classification of SSTs was devised by Meuter et al. (2000) into two dimensions which are “interface” and “purpose.” This was confirmed by Curran and Meuter (2005) and Walker and Johnson (2006) when testing adoption factor models across the different SSTs. Many quantitative studies have been done using Technology adoption models to predict user’s adoption of SST’s, (Darrow 2015); but, we discovered from our literature review that there are few qualitative studies worth noting on predicting user intention in adopting SST’s in retail stores. Therefore, there are opportunities to further explore the factors and associated constructs (in different settings and cultures) that lead shoppers to use SSTs, and thereby add to the understanding in the literature of this phenomenon.
Research Question
Our theoretical framework is Technology Acceptance Model (TAM) developed by Davis (Davis et al. 1989). Substantial empirical and theoretical support has accumulated in favor of TAM, especially in modeling how users come to accept and use a technology. As our theory backdrop, we wish to test (Davis, 1989; Davis, Bagozzi, & Warshaw, 1989) a number of factors which can determine a new technology user’s decision about how and when they use TAM constructs. Particularly we wish to test Perceived Ease of Use (PEOU) which Davis described as “the degree to which a person believes that using a particular system would be free from effort” (Davis 1989). This means that if the technology is easy to use, then hurdles toward its use are overcome. And we wish to test Perceived Usefulness (PU) – Davis described this as “the degree to which a person believes that using a particular system would enhance his or her job performance”(Davis 1989). Essentially this means that a user perceives a technology to be helpful for what they want to achieve.
Preferences are, in a sense, an evaluative judgment between liking or disliking an object such as a technological artifact like SST (Scherer 2005). Our research provides useful information about what shoppers ‘ preferences are when choosing to use SST or a cashier, depending on their circumstances. Retailers will likely want to understand this phenomenon as they attempt to improve the checkout experience, making it more efficient and giving shoppers choices between a cashier or a SST.
Our research asks the question: In a brick-and-mortar retail setting when choosing between SST (automated check-out), a cashier during checkout, or either depending on their circumstances, why do shoppers prefer any of these choices?
We use the case study method to investigate our research question, because it is preferred when “how” and “why” questions are being posed; when the extent of control of the researcher is little; when the focus is on a contemporary phenomenon and not on historical events (Yin 2008); and when the focus is on understanding the dynamics within a single setting (Eisenhardt1989).
Data collection: In this research we apply an interpretive theory-testing case study methodology (Markus 1983, Myers 1995) through collection of 15 semi-structured interviews over a three-month period, held by telephone or Zoom video conference. All semi-structured interviews follow the Kvale and Charmaz format and the recommendations suggested by Myers and Newman (Myers and Newman 2007). Each interview lasted 10 to 15 minutes, and the interviews produced a total of 32 pages of transcripts. We chose convenience sampling, video conference/telephone interview data collection and a small sample size due to the impact of the Covid-19 pandemic which caused public lockdowns and social distancing. Our subjects are the community of shoppers found in the sociological setting of brick-and-mortar stores interacting with cashiers and SST’s to make socio-economic decisions.
Data analysis: The transcripts from these interviews were transformed by using free online text-to-speech software. Each author carried out independent open coding summarizing text to develop succinct codes, followed by axial coding done collectively refining conceptual constructs and the interaction between associated descriptive categories (Glaser 1978, 1992). The coding followed Straus and Corbin’s (Straus and Corbin 1990) grounded theory approach. We did not do theoretical coding because our approach is not to build a substantive theory of the phenomenon studied but to test an existing theory.
A hermeneutic approach is used to deduce meaning through a dialectic between the understanding of the interviews as a whole and the interpretation of their individual parts to discover if one or more major themes emerges (Radnitzky, 1970: 20; Gadamer, 1976a).

Figure 1 – methodology process
“Texts do ‘speak,’ but without speaking.” (Peter Haidu, 1990). Figure 1. depicts our methodology up to this point. As themes emerged from the coding process, we found ourselves in the middle of the hermeneutic circle, forcing us to question our coding and concepts. This caused us to go back to the source transcripts to look at the context and confirmation of ideas and themes in an effort to discover potential hidden meaning and nuance we may have missed. Finally, exiting the orbicular nature of the process was possible when saturation and consolidation of ideas and themes was achieved.
The empirical results are finally tested against our theory construct to answer our research question through a thorough interpretive discussion among all three researchers to draw our final conclusions.
Results and Findings
Based on the result of the data analysis, six major axial code categories emerged with 45 other code data points we grouped together as minor. See Table 1.

Table 1
In probing on one of our major interview questions:
“When you go into the store with self-service checkout technology are you interested in using it or prefer the cashier?”
We found that all of our subjects had used SSTs, and that none stated they would not use them because the technology was too difficult. This emerged as a major theme, in that “ perceived ease of use did significantly predict people’s preference to select an SST confirming Davis’ “Perceived ease-of-use construct.” See Figure 2 for representative subject quotes associated with this theme.

Figure 2
We looked further into what degree our subjects using SSTs would find these systems free from effort to use when deciding between a cashier and SST. We understood that for the shoppers, their major objective is to get through the checkout process. We treated the shopper’s decision to select the SST or Cashier related to the “Perceived Usefulness” construct to the degree to which a shopper believes that using a SST would enhance their checkout process. Four axial codes lead us to this construct: Fastness/Slowness, Personal Interaction, Convenience, and Personal Feelings. See Figure 3 for representative subject quotes associated with these categories. We determined these categories were the themes associated with this construct and should not be consolidated any further.

Figure 3
However, from our minor codes, additional sub-themes did spin-off as facilitating conditions, consumers’ perception of the resources and support available to perform a behavior (Venkatesh et al 2003), from our major themes related to the use of technology and when people chose to use Cashier or either. We did find a subset of cases where subjects were ambivalent about the use of either SST or Cashier or would choose between SST and Cashier simply based on how long the line was that day. We also found one case where the subject confirmed his perceived ease of use and perceived usefulness of SST, but still stated he would always prefer to use the cashier whenever possible demonstrating the need for more refined data collection techniques to uncover what may be psychological or sociological connections to a preference.
Finally, we found particular situations where subjects would choose the cashier because they perceived the SST as too difficult. The best example of this, was the necessity to lookup barcodes for fruits and vegetables. In almost all cases, our subjects felt this would cause them to use the cashier. The second best example of this was where the subjects had a large number of items, in which case they would consider using the cashier for various reasons, for example, such as to be courteous to other shoppers, or because they did not feel like scanning a large number of items and bagging them. Overall, we saw these last two example cases again confirmed the PEOU and PU inasmuch as when a subject perceived the technology to be too difficult or not useful, they would choose the cashier.
Our research has shown that “perceived ease of use” and “perceived usefulness” have a significant effect on the intention to use SST’s, but preference for SST’s is further moderated by facilitating conditions. Our research has also shown that the “perceived ease of use ” construct in TAM has a direct significant effect on the behavioral intention of a shopper, when it comes to preference for SST within the context of checkout in brick-and-mortar shops. However, in making preference between SST’s or cashiers within the context of shopping (which is a voluntary usage setting where shoppers have to make the choice of SST or the cashier), there is an interplay of situational factors such as; number of people in the queue (on both SST’s or cashiers), quantity or type of goods purchased, and personal factors such as: “convenience,” all of which significantly affect individual intentions to choose either SST or cashier.
The intended contribution of this work to the existing research would be to make designers of SST aware of the need to improve barcode scanners and streamline the design of the future generation of SST’s to make the shopping experience in every shop the same and easy for shoppers to use. It is also a call on brick-and-mortar shops to pay more attention to labelling the items sold in the shop with barcodes that can be easily scanned. Additional research should be carried out to explore the extent to which convenience could impact user preferences between an SST or cashier. Furthermore, sub-themes should be further analyzed to understand to what extent they have a moderating effect on the overall TAM construct effect.

Cheng Wang, Jennifer Harris, Paul G Patterson(2016). Modeling the habit of self-service technology usage. Volume: 42 issue: 3, 462-481
Corbin, J.M., Strauss, A. Grounded theory research: Procedures, canons, and evaluative criteria. Qual Sociol 13, 3–21 (1990).
Darrow, B. (October 20, 2015). Yay! Human cashiers prevail over automation at some CVS stores.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two. Management Science, 35(8), 982. Retrieved from
Fernandes, T., Pedroso, R. The effect of self-checkout quality on customer satisfaction and repatronage in a retail context. Serv Bus 11, 69–92 (2017).
The Semiotics of Alterity: A Comparison with Hermeneutics Author(s): Peter Haidu Source: New Literary History, Vol. 21, No. 3, New Historicisms, New Histories, and Others (Spring, 1990), pp. 671-691
Lee H.-J., Lyu J. Personal values as determinants of intentions to use self-service technology in retailing (2016) Computers in Human Behavior, 60, 322-332.
Meuter, M. L., Ostrom, A. L., Roundtree, R. I., & Bitner, M. J. (2000). Self-service technologies: understanding customer satisfaction with technology-based service encounters. Journal of Marketing, 64, 50–64.
Meuter, M. L., Bitner, M. J., Ostrom, A. L., & Brown, S. W. (2005). Choosing among alternative service delivery modes: an investigation of customer trial of self-service technologies. Journal of Marketing, 69(2), 61–83.
Scherer, K. R. (2005). What are emotions? And how can they be measured? Social Science Information, 44(4), 695–729.
Viswanath Venkatesh, Michael G. Morris, Gordon B. Davis and Fred D. Davis Source: MIS Quarterly, Vol. 27, No. 3 (Sep., 2003), pp. 425-478 Published by: Management Information Systems Research Center, University of Minnesota Stable URL: Accessed: 04-05-2020 18:42 UTC
Walker, R. H., & Johnson, L. W. (2006). Why consumers use and do not use technology-enabled services. Journal of Services Marketing, 20(2), 125–135.

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