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Article Notes 3

Bendle, N. T., & Bagga, C. K. (2016). The metrics that marketers muddle. MIT Sloan Management Review, 57(3), 73-82.

Despite their widely acknowledged importance, some popular marketing metrics are regularly misunderstood and misused. One major reason for marketing’s diminishing role is the difficulty of meaning its impact: The value marketers generate is often difficult to quantify. The main goals of this article are to understand how these marketing metrics are used and understood and to develop ideas to help marketers unmuddle their metrics. The authors conducted surveys from managers from all functions across the business-to-business and business-to-consumer industries.

5 Best Known Marketing Metrics:

-       Market share

-       Net Promoter Score (NPS)

-       The Value of a ‘Like’

-       Consumer Lifetime Value (CLV)

-       Return on Investment (ROI)

Market Share

Market share is a popular marketing metric. One reason for why manager value market share is that research from the 1970s suggested a link between market share and ROI; however, the linkage may be less clear: the studies have found it is often correlational rather than causal. The survey found that there were two ways managers used market share: as an ultimate objective or as an intermediate measure of success. Increasing market share is not a meaningful ultimate objective for maximizing shareholder value and stakeholder management: If the aim is to maximize the returns to shareholders, increased market share offers no benefits unless it eventually generates profits. In some markets, bigger can be better; however, economies of scale do not automatically apply all markets.

Unmuddling Market Share:

The authors suggest a simple set of rules for the appropriate use of the market share metric:

-       Managers should not consider market share as the ultimate objective or as a proxy for absolute size.

-       Managers should evaluate it from the competitors’ and consumers’ point of view. If an increase in market share is not going to get positive feedback from competitors and consumers, then an increase in market share will not lead to a productive result.

-       Managers should analyze whether market share drives profitability in your industry. Companies with superior products tend to have high market share and high profitability because product superiority causes both.

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This means that the two metrics are correlated, BUT it does not necessarily mean that increasing market share will increase profits.

Net Promoter Score (NPS)

This metric is used to measure customer loyalty to a firm. Companies among diverse industries have embraced NPS as a way to monitor their customer service operations while NPS also has been seen as a system that allows managers to use the scores to shape managerial actions.

One of the advantages of NPS is its simplicity: It is easy for managers and employees to understand the goal of having more promoters and fewer detractors. However, there are weaknesses: E.g., in the net promoter literature, a customer’s worth to Apple has been described as the customer’s spending, ignoring the costs associated with serving the customer. It is also easy to imagine how to increase the net promoter score (such as making customers happier) while destroying even to-line growth (by slashing prices). Another problem with NPS as a metric is the classification system: The boundaries between scores of 6 and 7 (detractors and passives) and 8 and 9 (passive and promoters) seem somewhat arbitrary and culturally specific.

Unmuddling NPS:

The value of NPS depends on whether a manager sees it as a metric or as a system. The authors suggest that the NPS metric cannot change the marketing performance. However, they advise using this metric as a part of a system employed in evaluating the performance which might lead to a cultural shift within the organization.

The Value of a ‘Like’

This metric is used for measuring the social media capital of the company. New approaches are being developed all the time and they have the potential to aid understanding of how social media creates value. It is measured as the difference between the average value of customers endorsing the company and the average value of the customers who are not endorsing the company. The majority of managers link between their social media spending the value of a ‘like’. However, it does not mean that the cause of the differences in users’ value is attributable to a company’s social media strategy. And the reason that social media strategy shouldn’t be seen as the driver of value difference between fans and nonfans is because customers who are social media fans will differ from nonfans for reasons unrelated to the company’s social media strategy.

Unmuddling the Value of a ‘Like’:

This difference between two groups of consumers does not suggest an effect of online marketing activity or lack thereof. It should be investigated thoroughly by the managers. If the management is using the revenue to measure customer value, then this marketing metric does not give a good estimate. However, if the company does want to understand the impact of social media marketing, they should use randomized control experiments to derive causal answers.

Consumer Lifetime Value (CLV)

Consumer lifetime value (CLV), which is the present value of cash flows from a customer relationship, can help managers in decision making related to investment in developing customer relationships, as it is used to measure the value of the current customer base. If the management is using the customer value in their decision-making process, then CLV is a useful tool for them.

Unmuddling CLV:

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The authors suggest that CLV calculations should not include the customer acquisition cost and the estimated CLV should be compared to the estimated acquisition cost to derive conclusions. The bigger the difference between the estimated CLV and the estimated acquisition cost, the better the acquisition campaign.

Return on Investment (ROI)

Return on investment is a popular and potentially important metric allowing for the comparison of disparate investments. A critical requirement for calculating ROI is knowing the net profit generated by a specific investment decision. According to the authors, there is confusion within management over the use of ROI. However, as ROI is understood across disciplines, it is a powerful metric to communicate across the organization.

Unmuddling ROI:

The authors advise that if a manager is assessing the financial return on an investment, then ROI is an appropriate metric and can be calculated by dividing the incremental profits by the investments. Agribusiness marketing managers who are passionate about establishing the credibility of the value created through marketing should be thorough in their use of metrics. Most importantly, they should be able to understand the metric, its use and what it represents.

Evolution and future of total quality

management: management control and

organisational learning Jens Jörn Dahlgaard, Lidia Reyes, Chi-Kuang Chen and Su Mi Dahlgaard-Park

The self-archived postprint version of this journal article is available at Linköping

University Institutional Repository (DiVA):

http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160588

N.B.: When citing this work, cite the original publication. This is an electronic version of an article published in:

Dahlgaard, J. J., Reyes, L., Chen, C., Dahlgaard-Park, Su Mi, (2019), Evolution and future of total quality management: management control and organisational learning, Total quality management and business excellence (Online). https://doi.org/10.1080/14783363.2019.1665776

Original publication available at: https://doi.org/10.1080/14783363.2019.1665776 Copyright: Taylor & Francis (Routledge) (SSH Titles) http://www.routledge.com/

Evolution and Future of Total Quality Management: Management Control and Organizational Learning

Jens J. Dahlgaard

Professor, Department of Management and Engineering, Linköping University, Sweden [email protected]

Lidia Reyes PhD Student, Department of Industrial Engineering and Management, Yuan Ze University,

Taiwan, [email protected] Chi-Kuang Chen (corresponding author)

Professor, Department of Industrial Engineering and Management, Yuan Ze University, Taiwan, [email protected]

Department of Industrial Engineering and Management, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li 320, Taiwan, ROC

Su Mi Dahlgaard-Park Professor, Department of Service Management and Service Studies, Lund University, Sweden

[email protected]

Abstract The competitive position achieved by the Japanese and Western industries during the

1970s to mid-1990s, and 1980s to mid-1990s, respectively, derived from understanding,

implementing, and developing Total Quality Management (TQM) as a comprehensive

management philosophy. Several research and/or company studies provided evidence of this

development and its impact on leading companies’ efficiency and effectiveness.

Despite that, research on TQM seemed on the surface, after a boom from about 1990 to

1995, to have declined. However, one recent detailed study from 2013 concluded that TQM is

now at a more mature stage where focuses have shifted from being initially on TQM to the

methods, tools, techniques and core values which are needed to implement TQM and to build a

quality and BE (Business Excellence) culture.

This study is an extension of the 2013 study, where we extend the previous study on

TQM publications to 2017, and further analyse more detailed not only which methods, tools and

techniques are used, but also at what organisational level they are used – strategical, tactical or

the operational level. We collect data on research about TQM and its methods, tools and

techniques, and we analyse further the shift of focus from TQM as a comprehensive management

theory/ philosophy to a focus on the TQM methods, tools and techniques to be used at various

management levels of a company.

We use two of management's basic functions – management control (MC) and

organizational learning (OL) – to unveil the challenges faced by TQM and to help converting

these challenges into new research opportunities to be jointly addressed by companies and

research communities such as the Quality Management and Organisational Development

(QMOD) Research Community.

In light of the findings in this research it became clear that MC and OL are two sides of

the same coin. MC can never be effectively implemented without OL, and OL needs to be

supported by a comprehensive MC system. Keywords: Total Quality Management, Management Control, Organizational Learning, Strategic Quality Management 1. Introduction

The origins of the theory and practice of Total Quality Management (TQM) can be traced back

to the 1920s where Walter Shewhart in 1924 began to apply statistical process control (SPC) in

the Bell Telephone Company’s Hawthorne Plant. He stated that SPC is a good way to learn and

understand why and how performance changes over time (Lovitt, 1997). This adoption and

promotion of SPC, which uses data as evidence of knowledge, helped to establish the importance

of having a management control function and a related learning process as a necessary part of

quality improvement efforts.

Later, in the 1950s and 1960s, the Japanese – with support from experts like W. Edward

Deming, Armand V. Feigenbaum, Kaoru Ishikawa, and Joseph Juran – interpreted, understood,

practiced, and further developed the concepts of SQC (Statistical Quality Control) and TQC

(Total Quality Control). This term is coined by Feigenbaum (1961), and Prof. Ishikawa

(Ishikawa, 1985 p. 91) who created the new term Company Wide Quality Control (CWQC) for

the Japanese version of TQC. CWQC was further developed and re-branded in the West as TQM

(Total Quality Management) during the 1980s (Dahlgaard-Park, 2013). The above mentioned

quality experts/ gurus as well as others contributed and helped transitioning the movement from

SQC to TQM carrying over the learning methodologies developed in Japan, such as the basic

quality tools, quality control circles (QCC), and quality control stories (Gitlow, 1994).

The job loss in the US and Europe during the last part of the 1970s and the 1980s,

triggered by Japan’s success, forced American and European companies to become interested in

understanding, learning, and adapting the concept of CWQC (Deming 1986). This interest led to

further academic research and the introduction of new principles, tools, and methods such as

Business Excellence (BE), Six Sigma and Lean (Dahlgaard-Park, 2011; Lawler III et al., 1992;

Port et al., 1992; Seymour & Collett, 1991). Consequently, the principles and theories behind

TQM evolved from quality inspection, quality control, quality assurance, and CWQC into the

modern version of TQM, where the content expanded to include all functional areas of a business

(Dahlgaard-Park et al., 2018; Dahlgaard et al., 2003).

As it evolved, TQM incorporated three managerial arenas: process management, human

resource management, and strategic management. Thereby, TQM developed into a

comprehensive management theory with multiple layers and elements/components within its

framework, and many leading companies showed impressive results after having successfully

implemented TQM (Dahlgaard-Park et al, 2018, pp. 1108-1128). However, many companies

experienced that TQM didn’t provide the expected results on economic returns and

competitiveness. Hence, TQM lost its appeal for many company managers who started to use

other competing managerial methods such as Balanced Score Card, Performance Management

etc. hoping that they would give better results.

From the mid-1990s, research publications on TQM & BE as a new and general

management philosophy diminished drastically to the point where the number of articles

published in 2011 was only one-third of those published in 1995 (Dahlgaard-Park et al., 2013).

This was a surprise for many researchers within the quality management area because several

large studies showed that it pays very well for companies to invest in those areas (Hendricks and

Singhal, 1997; Boulter et al, 2013). Some researchers even proclaimed that TQM is dead or

dying (no name references here).

However, as Dahlgard-Park et al concluded in their detailed research study to understand

and explain the dramatic decrease in the number of research publication on TQM and BE (2013

p. 15):

“…we will also understand that data on the number of articles published on TQM and

BE are too narrow to conclude as above. Because TQM and BEM comprise multiple numbers of

tools and techniques as well as culture and core values/principles then we should also collect

and analyse data about these areas before we come up with a quick conclusion about the current

state and expected future directions.

The results showed that the total number of articles under the subject of TQM has been

decreasing since 1995 after having reached its peak. On the other hand, papers focusing on

methods, tools and techniques within the QM framework, in terms of Self-Assessment, Lean, Six

Sigma, SPC, Benchmarking etc. have been increasing. Papers focusing on the core

values/principles needed to build a quality culture in terms of leadership, people-based

management, continuous improvement, management based on facts, and customer focus have

been slightly increasing during the last decade.

These findings indicate that TQM is now at a more mature stage where focuses have

shifted from being initially on TQM to the tools, techniques and core values which are needed to

implement TQM and build a quality and BE culture”.

Trying to have all this in mind, this study aims to explain why research on TQM has

changed its focus to especially methods, tools, techniques, and how this change of focus may

affect the future of the quality movement.

We first do, in section 2, a timeline-based literature review of management control and

organizational learning within the areas of TQM, regarding TQM as a sustainable long-term

management approach derived from a set of values or principles that are control and learning

oriented (Sitkin et al., 1994). Subsequently, in section 3, we analyse how research on

management control and organizational learning have evolved in terms of the most popular TQM

methods, tools and techniques. Discussions of the identified research trends will then follow in

section 4, and our final conclusions and recommendations will end up the article in section 5.

2. Evolution of Management Control and Organizational Learning under TQM

Management Control and Organization Learning processes are interdependent managerial

processes that are seldom considered together in the TQM literature even if they should be

regarded as two sides of the same coin. In the following literature review we will focus on when

and how those two concepts evolved under the TQM evolution and try to find evidence or

indications on the practice or non-practice of the two sides of the same coin principle. First, we

will focus on the evolution related to the operational or process level, and after that we will focus

on the organizational management level and then end up with some preliminary conclusions.

2.1 Operational (process) Level

Management Control is a systematic process to define and implement performance standards to

achieve organizational objectives. It is based on planning/ setting objectives and designing

information feedback systems that help to find deviations and taking action to ensure that

resources are used effectively and efficiently (Mockler, 1984, p.2).

The roots of MC go back to the basic principles of scientific management, where

managers were engaged in planning, training, and follow up activities, allowing workers to

perform their tasks, i.e. “to do” efficiently (Taylor, 1914). As Taylor sought to increase

productivity and employees’ skills while concurrently reducing waste, the further development

of scientific management intertwined with the development of Statistical Quality Control (SQC).

The framework known as Operational Control (Robert, 1965) emerged when Japanese

stakeholders understood the definition, meaning and practice of quality control: “… to develop,

design, produce and service a quality product which is most economical, most useful, and always

satisfactory to the consumer” (Ishikawa, 1985 p. 44).

Prof. Kaoru Ishikawa, who shaped the Japanese version of Total Quality Control (TQC),

suggested quality control circles (QCC) and the seven basic quality improvement tools (7QC) to

be used by the QCC members in their continuous suggestions for new process and product

improvements. As said above, he coined in 1968 the new concept company-wide quality control

(CWQC), a concept in which QC requires everybody’s participation, in other words,

participation of employees to become responsible for operational control (Ishikawa,1974;

Martínez-Lorente et al., 1998).

Most of the methods, tools and techniques for product design and process improvement

used today emerged from observing Japanese quality improvement procedures and best practices.

For example, the Taguchi method (Taguchi, 1986), used for product design, applies statistical

methods to ensure good performance in the design stage of products or processes. Hoshin Kanri

(policy deployment) is a form of corporate-wide management technique that combines strategic

management and operational management by linking the achievement of top management goals

with daily management at the operational level (Kondo, 1995, p. 89). Hoshin Kanri is a

framework for policy-based objectives that translates into QCDE (quality, cost, delivery,

education) targets that drive progress (Witcher & Butterworth, 2001).

From this development another important concept/method emerged, operational learning,

which is defined as learning at the process level, which helps to understand and describe “how to

get things done around a specific process/task or project” (Hoffman & Donaldson, 2004, p. 452).

2.2. Organizational Management Level

Organizational Learning (OL) is about an organization perceiving the environment and using its

experience-based shared knowledge to adapt to changes and threats as well as defining future

strategies. One of the most popular definitions of OL was provided by Senge (1990 p. 13-14), as:

“a shift or movement of mind”, where the environment is perceived differently by finding

problems, proposing solutions, and recreating the organization’s future.

Influenced by the focus mentioned previously, TQM was re-defined by several authors

during the 1990s, and organizational learning (OL) was promoted more and more to the

managerial level because the redefinition of TQM changed its theoretical scope and application.

The new scope of TQM included more stakeholders (customers, employees, suppliers, business

partners, and society), and its applications were widened to become more outcome or result

oriented. New methods, tools and techniques such as Six Sigma, Self-assessment, Balanced

Score Card, and Lean came into play and a more strategic and competitive perspective was

applied (Svensson & Klefsjö, 2006).

Peter Senge’s book (1990) “The Fifth Discipline – The Art & Practice of The Learning

Organization” became a key contributor to this development, influencing EFQM (European

Foundation for Quality Management) to change the wordings and other contents of the EFQM

Excellence Model from 1997 to fit better to this development. For example, the feed-back loop

from Results to Enablers in the 1997 model showed clearly the following two key words to

address: Innovation and Learning (see Figure 1).

Figure 1: EFQM Excellence Model (1997)

In EFQM’s 2013 version of the Excellence Model, shown in Figure 2, the importance of

organizational learning (OL) was stressed even further, indicated by the feedback loop’s focus on

“Learning, Creativity, and Innovation”. The importance of OL is shown furthermore in the sub-

criterions and potential areas to address.

However, the new mechanical logic, or rational orientation, from enablers to results

tended to put aside the soft aspects of management such as organizational culture, values,

people’s motivation, training, and education (Dahlgaard-Park, 2011) even if the EFQM

Excellence Models, as well as other leading excellence models such as the Malcolm Baldridge

Model, requested a balance between the soft and the hard side of management as indicated in

Figure 2. Companies worldwide adopted these new excellence models and its related methods,

tools and techniques, and particularly the process of self-assessment (SA) as a learni