designing and implementing a csr strategy - module 1

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Implementation of Social Responsibility: Improving the Quality of Life for Humanity

© 2014 BES Business Excellence Solutions, Ltd. 1

Gregory H. Watson

Management Seminar China (Shanghai) Pilot Free Trade Zone 24 July 2014


• These lectures describe the socialization of quality and integration of social responsibility into an organizational quality framework for a process of management which will implement plans to create a more highly responsible organization.

• Corporate Social Responsibility (CSR) has become increasingly important in the last two decades. It applies to mechanisms in self-regulation of an organization’s business model for the benefit of society and includes active compliance with the letter and spirit of the law and their governing regulations as well as the morals and ethics held by society in the natural communities where the corporation operates.

• This extends responsibility of a firm beyond financial achievements or the ability of a firm to comply toward an active effort to achieve what is the “good” of society. Emphasis on the “social good” means that a firm will deliver positive value to all stakeholders (beyond the financial stockholders or owners, to include the broad public (e.g., clients, customers, constituents, communities, employees and suppliers as well as the global natural environment and human race as a integrated, systemic whole).

• CSR emphasizes human dimensions in developing organizational performance which makes it difficult to quantify its benefit (especially as compared to productivity and financial performance) because there is no accepted indicator that applies for quantifying the benefits of a CSR strategy.

• Additionally, CSR has different emphases in different cultures. In China, CSR focuses on safety and product quality while in Germany it assures job security for workers while emphasizing environment or moral issues in other nations.

• An starting point to understand CSR is to conduct an inquiry into the subjective nature of the cultural foundations of organizations to gain understanding of requirements to be developed to achieve a global recognition for excellence in CSR. This is an imperative in building a global brand.


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What do most organizations believe that CSR involves?

Related international standards and business guidelines:

• ISO26000/SA8000 – Social Accountability

• ISO14000 – Environmental Management

• ISO45001/OHSAS18001 – Occupational Safety and Health

• United Nations Global Compact – Moral Imperatives

However: • There is no global agreement on the specific content of CSR elements

• Minimum international agreement – CSR company makes safe, quality products; while others add:

– Positive contribution to social needs (e.g., health care and education)

– Secure employment for employees

– Corporate philanthropy and charitable projects

– Fair trade and labor practices

– Creating Shared Value (CSV) – corporate success and social welfare will operate in an interdependent manner (e.g., the “triple bottom line” of profit, people and planet)



• Module 1: Understanding how Corporate Social Responsibility Relates to the Obligations of Organizations

• Module 2: Implementing the Principles of Social Responsibility Using the Methods of Quality Management


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Organizations decide how to act collectively in society:

Premise: Mankind has trouble in making truly objective decisions and this is especially true when it comes to value-based decisions! Therefore:

• We need to reconsider our approach to making decisions.

• We must reconsider how we prioritize our activities to achieve results.

• We must determine how to focus on what is most important for us to achieve for the sake of humanity in our global organizations.


Module 1: Understanding how Corporate Social Responsibility Relates to the Obligations of Organizations

UNDERSTANDING HOW CORPORATE SOCIAL RESPONSIBILITY RELATES TO THE OBLIGATIONS OF ORGANIZATIONS


Module 1:

IMPLEMENTATION OF SOCIAL RESPONSIBILITY: IMPROVING THE QUALITY OF LIFE FOR HUMANITY

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How does social responsibility apply to a global firm?

7 © 2014 BES Business Excellence Solutions, Ltd.

Laozi or Lao Tzu [老子] Zhou Dynasty [6th Century BCE)

“Disaster is that on which good fortune depends.

Good fortune is that in which disaster’s concealed.

Who knows where it will end?

For there is no fixed ‘correct.’

The ‘correct’ turns into the ‘deviant;’

And ‘good’ turns into ‘evil.’

People’s state of confusion

Has certainly existed for a long time!”

Lao-Tzu

Te-Tao Ching, Chapter 58

UNDERSTANDING THE BAYESIAN MOMENT OF DECISION


Part 1:


http://en.wikipedia.org/wiki/Image:Laozi.jpg

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Knowledge-based issues in rational decision making:

• What can we discover in a scientific inquiry into a disruptive event or situation in an organization?

• We need to learn about the sources of variation; relationships to the physical world; relationships to cultural components; interactions of the various physical components; sequencing, duration, and coupling of flows among the activities; and the degree of clarity and integrity that the information available is able to provide.

• It is also important to determine if the problem relates to the lack of accuracy in our knowledge (which makes it appropriate for a DMAIC-type of inquiry) or if the situation is related to inherent ambiguity (in which case a more innovative approach is needed such as DMADV).

• Essential to the approach also is the understanding of the dynamics of the activity and ability to make strategic sense out of the current state in order to develop a clear understanding of the management decisions necessary to create a more positive future state.


Foresight Realm

of Science

Hindsight

Realm of

History

Insight

Realm of Psychology

The process flow of scientific inquiry:

DEFINITIONS • Hindsight: how we use historical

data to discover causal systems from past experience.

• Foresight: how we project what future potential is possible as a function of past experience and knowledge.

• Insight: how we perceive data of past experience and interpret its meaning in decision-making as an individual decision-maker.

Bayesian Moment

• Bayesian Moment: a point in existential time when an observation is made of the phenomena, perceived and interpreted as an individual and represented through a mental model as an actual entity and decisions drawn based using a constrained level of knowledge, time or consciousness (as bounded reality).


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What happens in the “Bayesian Moment” of deciding?

• The Bayesian moment represents a brief instance in time when an executive decision must be made and implemented operationally based on the facts that are available.

• The implications of this decision will carry an organization toward its forward-seeking strategy in pursuit of future success.

• However, poor decisions in this moment can restrain opportunities for success in the future.

• Management judgment must be based upon the available data that supports the decision and is subject to a several decision conditions which may be examined to determine the quality of the decision that is made in terms of its potential future impact.

• Question to consider: What drives the quality of these decisions?


How much is available to know about a subject?


Chester I. Barnard (1886-1961) President, New Jersey Bell Telephone (1927-1949) Functions of the Executive (1938) Mind in Everyday Affairs (1938)

There are distinct categories of facts that bias proposed problem solutions. We can observe facts using one perspective (e.g., physical), but interpret from another perspective (e.g., political). Thus, “managing by facts” may become distorted due to subjective manipulation by those who lack perspective. The level of confidence with which we may draw conclusions from data is limited by the characteristics inherent to the data itself. Our ability to explain phenomena of actual entities is a function of the type of data contained in our observations.

Degree of knowledge that is available from the different types of data:

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How much control may we exercise over any subject?


“To indicate the relationship which the theory of control bears to exact science, it is interesting to consider six stages in the development of better ways and means of making use of past experience. They are:

“1. Belief that the future cannot be predicted in terms of the past. “2. Belief that the future is pre-ordained. “3. Inefficient use of past experience in the sense that experiences

are not systematized into laws. “4. Control within limits. “5. Maximum control. “6. Knowledge of all laws of nature – exact science.”

Statistical Process Control

Walter A. Shewhart (1891-1967) The Economic Control of Quality of Manufactured Product (1931) Statistical Method from the Viewpoint of Quality Control (1939) Shewhart is called the “father of statistical quality control” who developed a “Theory of Control” and the statistical process control chart.

There are three choices we make in judging:

• A “gestalt” is our personal world view – the set of beliefs and experiences that formulates a personal moral code of the way we interpret our experiences in life. *

• William K. Clifford: “It is wrong always, everywhere, and for anyone, to believe anything upon insufficient evidence.”

• William James: If we choose to think something we exercise our “will to believe” or an acceptance of interpretations about ideas or facts based on personal choice, with or without any specific evidence of the truth of such facts or ideas. There are three levels at which we actually have beliefs:

1. Belief: so-called “blind faith” or belief without justification

2. Justified Belief: belief based on rationally-defined premises

3. Justified True Belief: belief based on validated premises

• Essays by William K. Clifford (1877) “The Ethics of Belief” and William James (1896) “Will to Believe.”


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Personal probability defines our preference: Theory O!

• Developed the idea of personal and subjective probability in inferential statistics as compared to frequency theories based on mathematics and logical analysis applicable to just objective and repetitive events.

• Proposed (in collaboration with Nobel Laureate economist Milton Friedman) a subjective utility theory for rational decision-making and choice under conditions of uncertainty.

“Statistics is the art of dealing with the vagueness and interpersonal differences in decision situations.”

“Experiments, as opposed to observations, are characterized by reproducibility and repeatability.”


Leonard J. Savage (1917-1971)

Foundations of Statistics (1954)

We use three probability levels in making judgments: • Truth is only absolute when we can establish a scientific law,

and even then it is subject to ‘confirmation.’ Thus, perception in judgment, is a matter of degree of probability alignment in meeting our personal criteria for “goodness” and here there are three levels that we can observe:*

1. Personal Probability – subjective estimate that is based on the feelings of the believer – 100% would be “blind faith.”

2. Objective Probability – objective based on calculations by use of frequency distributions from observed events. Truth is only as valid as the ability to observe and measure.

3. Scientific Probability – deterministic analyses that use the principles of scientific experiments to establish causality.

• Leonard J. Savage (1954), Foundations of Statistics (New York: John Wiley & Sons). 16 © 2014 BES Business Excellence Solutions, Ltd.

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Where does the data come from? • Initial data is almost always murky, fuzzy, or just plain wrong.

People tend to report “benchmarks” based on their personal opinion regarding work performance. Over-reliance on personal observation and subjective sources of probability estimates is called “Theory O” – Theory Opinion.

• People tend to mix into their so-called “objective reports” the combination of judgments, inferences and reports – each with a differing degree of objective validity. Sometimes the outcome is not only statistically invalid, it may also be greatly wrong!

• True benchmarks are scientifically rigorous and the terms have been operationally defined to assure clarity (lack of ambiguity) and these measures are evaluated for their integrity – ability to describe accurately what they are supposed to report. There is no “gaming” possible with a good benchmark measure.

• Finally, a good measure will be openly reported and accepted within the industry that is being studied.


Theory “O” drives many management decisions:

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• We build our knowledge as individuals; one experience at a time.

• Education serves to accelerate our experience and expose us to a broader base of situations.

• However, each experience represents only one potential way of working out a problem and results in either success or failure, so there are many lessons that go unlearned because they have not been experienced.

• Conclusions drawn based upon personal experience are a limited, not comprehensive, approach to decision-making.

• Experience-based decision-making degenerates into a subjective approach if it is not supported by facts or a sound approach to data analysis.

Theory Opinion: An opinion based on knowledge gained from previous experience, usually unsupported by data but expressed as a statement of fact.

Designing processes based on “Theory O” often creates process mess! © 2014 BES Business Excellence Solutions, Ltd.

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Seeking profound knowledge in the Bayesian Moment:


W. Edwards Deming (1900-1993) Out of the Crisis (1986) The New Economics (1992, 1994)

Deming proposed a “System of Profound Knowledge” but he only outlined its structure without a theoretical justification for his belief regarding its basis. So what is profound knowledge?

PROFOUND KNOWELDGE = Statistical knowledge about process performance

There are identified four dimensions to profound knowledge:

• Structure of Systems: understanding the system in which work is being done and decisions are being made (process management).

• Statistical Thinking about Process Variation: knowledge of system operation comes from a study of performance variation, improvement requires the control of the sources of variation (statistical thinking).

• Development of Knowledge: knowledge comes by observing work, defining a theory, testing and confirming it (measurement system).

• Psychological Impact: human behavior must be understood, motivated and coordinated to achieve results (collaborative culture).

The “statistical component” in improvement:


Special cause variation is any deviation from standard process performance that can be assigned an identifiable cause. Common cause variation is the natural level of variation that exists in a process – it has no specifically identifiable cause but represents variation that is inherent in the system design and it is not possible to improve this variation by making changes in a work process.

When common cause variation is too great to obtain performance results expected of the process, then a transformation or redesign of the process is required. This is the job of management and it will typically require a reallocation of organizational resources.

Statistical Thinking: A process of learning and then taking action based on three following principles:

1. All work occurs in a system of interconnected processes.

2. Variation exists in all processes – use data to learn about processes.

3. Understanding and reducing variation are the keys to performance management and business improvement.

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How does using “averages” distort process knowledge? Measuring and reporting performance using averages…

Performance Indicator:

Daily averages of call answering time: In average the call center answered phone calls

between 3-9 minutes during this week!

Let’s use a very simple example

to illustrate a key point on using

statistics!

Here is call center data from a

company which was reported to its management.

What can they do with this data?

Does this information help managers know WHAT to improve?

Using statistical process analysis we see the long tail:

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B 5 seconds A Average: 4 minutes

1 hour 10 minutes C

Systemic Result Performance that fits the natural process variation and may be improved using data analysis

Long Tails Performance results that are well out of the ordinary.

Measuring and reporting these facts observing full process statistics:

Using averages alone creates optimism and distorts quality in our business decisions!


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Solving problems using statistical analysis:

• The average outcome (mean, median, or mode) of a factor is a necessary condition to describe performance of a process, but it is not sufficient to fully characterize its performance without a related measure of process variation or degree of consistency (e.g., variance, standard deviation, or range, etc.).

• When both measures are used to characterize the set of data, then process improvement is possible by following a simple statistical objective to improve the process performance: any work process may be improved by either shifting its mean, reducing its variation, or doing both at the same time.

• The easiest way to improve a process is to discover the factors that reduce a ‘long tail’ in an outcome metric and eliminate those factors that are identifiable causes of process variation.

Developing a scientific approach to process analysis:


• Historical data must be collected in a way that preserves its meaningfulness.

• The data must be grouped using various rational sub-groups that will display relationships in the overall performance to variance in the sub-group actions which may be further analyzed.

• Pattern analysis using graphical representations and underlying probability for pattern occurrence isolate variables for more detailed statistical analysis.

• Confirmatory analysis through hypothesis testing demonstrates that there is a statistical basis for interrelationships among process factors.

• Experimentation demonstrates that the relationships are or are not causal.

Historical

Process Data

Rational Sub-group

Decision

Filters

Confirmatory

Analysis

Pattern

Analysis

Representation of a problem occurs by decomposition:

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Defining the task and responsibility of management:

• “Management must produce economic results.” • “Management is concerned with decisions for actions.” • “Productivity [results] means that balance occurs between all factors of

production that will give the greatest output for the smallest effort.” • “The guiding principle of business economics … is not the maximization of

profits; it is the avoidance of losses.” • “The more a management creates economic conditions or changes them

rather than passively adapts to them, the more it manages the business.” • Management must reflect: “what will our business be?” and “what should

our business be?”

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Peter F. Drucker (1909-2005)

The Concept of the Corporation (1946) The Practice of Management (1954) Managing for Results (1964) The Effective Executive (1967) Management, Tasks, Responsibilities (1973) Innovation and Entrepreneurship (1987)

© 2014 BES Business Excellence Solutions, Ltd.

Decisions are constrained by “bounded rationality:”

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Herbert A. Simon (1916-2001), Nobel Laureate Administrative Behavior (1947) Organizations (with James G. March, 1958) Models of Bounded Rationality (1982, 1997) Reason in Human Affairs (1983) The Sciences of the Artificial (1996) An Empirically-based Microeconomics (1997)

“Boundedly rational agents experience limits in formulating and solving complex problems and in processing (receiving, storing, retrieving, transmitting) information.”

“The human being striving for rationality and restricted within the limits of his knowledge has developed some working procedures that partially overcome these difficulties. These procedures consist in assuming that he can isolate from the rest of the world a closed system containing a limited number of variables and a limited range of consequences.”

Complete “truth” is not possible, but decisions must be made under constraints of (1) quality of available information; (2) competence of decision-makers; and (3) urgency of timeframe for decision-making.


http://fistikyesili.com/2011/07/24/krizde-ust-duzey-yoneticilere-tuyolar-firtinali-donemlerde-yonetim/

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Sensemaking is different from problem solving: Karl E. Weick (1936 – )

Rensis Likert Distinguished Professor of Psychology

University of Michigan

The Social Psychology of Organizing (1969) Sense Making in Organizations (1995)

• Introduced the concepts of Loose and tight coupling, mindfulness and sense making as elements of rational decision making.


• Not every type of concern or undesirable situation is a problem that needs to be fixed. Some divergent conditions are issues that must be managed; others are dilemmas that need to be resolved; paradoxes that need to be challenged; conflicts that need to be settled; constraints that need to be removed; or opportunities that need to be taken.

• Sensemaking requires the perceiving, interpreting, and understanding of observations within a given cultural setting and it is imperative that all these dimensions are understood during any comprehensive inquiry.

Developing innovative, dynamic capability of the firm: David J. Teece (1948 – ) Professor of Business, Haas School of Business, UC Berkeley

Economic Performance and the Theory of the Firm (1992) Technology, Organizational Capability and Strategy (2008) Strategy, Innovation and Theory of the Firm (2011)

• Developed the concept of “dynamic capability” as a way to describe the relationship of innovation and competition to new product development for advancing technology.


• Dynamic capabilities are threefold: (1) the capacity to sense and shape the opportunities and threats that face an organization; (2) the ability to seize opportunities and make decisions that will implement the needed change for the organization to remain competitive; and (3) the stamina to maintain competitiveness through the continual enhancing, combining, protecting, and when necessary, reconfiguring the business enterprise’s tangible and intangible assets.

• The development and exercise of internal dynamic capabilities is at the core of sustainable success for an enterprise.

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Application: organizational executive decision making

• How do these seemingly diverse ideas relate to each other? They are all integral components of the strategy management process and are critical aspects of the decision-making activities that shape choices made about organizational futures in a “Bayesian Moment.”

• Key questions need to be address with respect to the combining or executing of these ideas: what decisions need to be made at what point of the organization? Who needs what degree of authority to make choices and have they been developed with the right degree of competence to make truly informed decisions? Do these people have the requisite resources to support their decision (both tangible and intangible)?

• Responsible manager avoid creating organizational loss – waste! It is important to make decisions that avoid loss in both the short and long term decision horizons and to assure that the processes have a dynamic capability to perform and also make sense across a variety of foreseeable future business case scenarios.


Differing cultures may require unique process designs:


Joseph M. Juran (1904-2008) American Quality Consultant • Quality Handbook (1951, 1962, 1974, 1988, 1999) • Managerial Breakthrough (1964) • Management of Quality Control (1967) • Quality Planning and Analysis (1970) • Upper Management and Quality (1980)

• Often there is a single variable that will dominate in its contribution to the performance of an overall process. In a physical process the usual forms of dominance are elements such as: setup-dominance, time-dominance, component-dominance, worker-dominance, and information-dominance.

• Processes will vary in terms of the appropriate performance measures as well as the degree of ability to self-regulate or control quality in their results.

• Patterns of activities that dominate a process will also provide the key for their effective control and each dominance pattern will employ different types of control mechanisms to produce effectively stable results.

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Information is the answer to a question: “If only I had the right question … if only I had the right question … the formulation of a problem is often more important than its solution. The raising of new questions requires creative imagination … imagination is more important than knowledge.”

~ Albert Einstein

What are the right questions? There are two ways to improve: (1) Eliminate waste, or (2) Improve efficiency

Questions to ask about waste include:

• Where is there waste in our process?

• What are we doing inefficiently or ineffectively?

• Where have we invested too much in assets? Can we make them more efficient?

• Do managers contribute through wasteful decisions?

• How can we improve the way that we do our routine work?


We learn about waste by internal assessment; we innovate in efficiency when we learn the practices or processes of excellently performing organizations.

But, experience varies in interpretation by culture!

“There is no question of theory versus practice but rather of intelligent practice versus uninformed practice.”

“Every great advance in science issues from audacity of imagination.” “Failure is instructive. The person who really thinks learns quite as much from his failures as from his successes.”

Experience is the ultimate test of truth and by explaining connections and gaining meaning that we develop an understanding of the reality that we observe, so experiential verification is the criteria that is both necessary and sufficient for validating theory.

John Dewey (1859-1952) Professor, Columbia University American Educator, Philosopher, and Psychologist

• How We Think (1910) • The Quest for Certainty (1929) • Logic: The Theory of Inquiry (1938) • Knowing and the Known (1949)


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Reflective Introspection about our Pursuit of Quality:

• Have we become so focused on learning more and more about less and less that we have missed the big picture? Have we forgotten the holistic aspects of the human in our thinking and concentration on problems?

• Have we become too focused on addressing problems and forgotten how to deal with other issues? How do we deal with non-problems – like ambiguity?

• Have we become so focused on implementing tools and methods that we have forgotten how the whole system of work must work together? How can we integrate the philosophy and methods of quality into a coherent management system that satisfies the need for continual improvement and is globally viable?


REVISITING THE MEANING OF THE PARETO EFFECT


Part 2:


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How do we establish our priorities for improvement? • Often we prioritize our work based on the Pareto Principle: it says

that 80% of the success events in a process are caused or contributed by just 20% of the individuals involved (a standard 80-20 Pareto rule for distribution of result and participants).

• But this implies that the categories of success and individuals are drawn from the same population and that these success events are independent of each other. The vital portion of the contributors to success however sometimes changes from the 20% that is identified by this base rule.

• However, we see in some start-up organizations that almost everything depends only one or two organizational members (this would be a 95-5 rule instead of an 80-20 rule).

• Also in some highly integrated team activities the case may be that 80% of the success depends upon 90% of the people (or an 80-90 rule).

• Crowd-sourcing also indicates that there is power in the mass or the miscellaneous category – this is called the “restaurant bill effect.”


What is the logic behind the “Pareto Effect”?

• Pareto charts display frequency of occurrence information about attribute data (e.g., the most frequently occurring type of quality defect or relative magnitude of different types of product orders received by a sales group).

• The Pareto principle assumes that there is independence among the data observations (e.g., all types of failure are equally likely to occur) and when this is true, then the “80-20” rule holds: 80% of the problems come from 20% of the events (the vital proportion of events).

• However, if the data is not independent, then the “80-20” rule (or Pareto effect) is not valid as one particular type of failure may cause all observed defects (e.g., bearing failure in a motor causes multiple failures; however, the resultant failures are conditional upon the prior failure of the bearing).

• The “80-20” rule is used to distinguish the “vital few” events that create the majority of the problems from the “trivial many” events that possess only a minor influence on the total result.

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Pareto Chart

Named for Vilfredo Pareto (1848–1923), an Italian industrialist, sociologist, and economist who first observed this effect in economic income data.


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Interpreting a Pareto chart to see relative frequency:

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Count 7 7 7 6 5 5 5 5 5 517 4 4 4 3 3 2 2 2 2 213 2 2 1 1 912 10 8 8 8 8

Percent 4 4 4 3 3 3 3 3 3 39 2 2 2 2 2 1 1 1 1 17 1 1 1 1 57 5 4 4 4 4

Cum % 49 53 57 60 63 66 68 71 74 779 79 81 83 85 86 88 89 90 91 9216 93 94 95 9510023 28 33 37 41 46

Co

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Lead Time

Oth

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18

16

14

12

10

8

6

4

2

0

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7075HE2008553HE200

7286HE2007592HE2007411HE2017411HE2017506HE2007434HE2007434HE200

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7423HE2007411HE2007411HE200

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Pareto Chart of Lead TimeThe Vital Few Performance Contributors

The Trivial Many Process

Performance Contributors

Last 5% is grouped

together.

Priority for corrective action?

The Pareto Chart identifies the mode within a statistical distribution!

Pareto Principle (80-20 Rule): Approximately 80% of the effects observed in performance are generated by about 20% of the causes.


Deming’s description of organizational responsibility:


According to Dr W. Edwards Deming, approximately 15% of all work-related defects made by operators are the responsibility of the operator (where these defects arise from a single population of failure possibilities).

This observation raises some pertinent questions:

• Who is responsible for the other 85% of these problems?

• Then, under what conditions should workers be held accountable and responsible individually for the quality of his or her work?

• How does this discussion correspond to the two types of process variation that occur: special cause and common cause variation?

This observation about organizational responsibility for problems follows the Pareto Principle!

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Restaurant Bill Syndrome *

• The “restaurant bill syndrome” describes what happens when a wide variety of “small extras” are added to the base price of a meal – the cost impact of these extras will often far outweigh the base price (this is drive by selection of the appetizer, drinks and desert portions of the bill!).

• In this case the total of all the miscellaneous items generates a cumulative effect that far exceeds their individual contribution. Here these items have been added one-at-a-time, each item consists of a single low cost decision; however, the net result of all these low-cost decisions is a substantial increase to the total cost of the bill.

• This increase in risk is a similar effect to the risk increase to a person who is “tortured” using the “death-by-1,000-cuts” method!


We must remain alert to the incremental increase in effect that

may occur through the multitude of small decisions that are made

during the design and execution of our work processes.

* Credit for developing the “restaurant bill syndrome” belongs to Zigmund Bluvband (2014).

How does this apply to implementing CSR? • In business often the financial impact of the “trivial many” will

become the most significant contributor to overall cost.

• Many of the CSR decisions that an organization makes are not made at the executive level but are made at the level of their implementation. This means that these decisions and the risks form their implementation are largely invisible to management at the highest level of the organization (e.g., decisions may be embedded in supplier sourcing decisions by purchasing agents, benefit designs by human resource managers, or in technology selection or design by R&D engineers).

• The “trivial many” become ignored through application of the “Deming Logic” or “Pareto Principle” to decision-making.

• However, it is at the point of process detail where important CSR issues are decided which have an overall implication on the outcome of the organization’s total social responsibility.


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UNDERSTANDING SOCIAL CHOICE IN SETTING CSR STRATEGY


Part 3:


The nature of global organizations and their cultures: • Global organizations have a special challenge – how to define their

ways of working so that they are aligned with the diversity among the national cultures and moral value systems of their subsidiaries?

• Achieving sensitivity to diverse issues of informal cultures within an organization is not a clearly defined process and requires that each organization develop a sensitive awareness to the subtleties of their constituent sub-cultures.

• In fact, some of the belief systems of organizational sub-systems may operate in conflict with each other and generate systematic interaction effects that confound progress across the organization.

• Identifying cross-cultural conflicts and appropriately dealing with them requires cultural awareness and astute sensitivity to all of the challenges that are inherent within the organization.

• The approach to develop a “robust social system” within a global organization is to maintain a core identity (corporate culture) that is relatively rigid and remain flexible in permitting development of the local sub-cultures that are aligned with local implementation issues.


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Distinctions between “BIG Q” and “little q” quality:


Big Q – Strategic Quality Little Q – Operational Quality

Culture (Company) Vision, Mission and Values Policy and Philosophy Competition (Business Learning) Innovation Leverage Benchmarking Change (Renewal) Strategic Operational Cascade (Alignment) Improvement Projects Objectives and Targets Measures Communication (Awareness) Message Media

Competence (People) Individual and team development Training/development program Capability (Process) Daily process management Data bases and analytic software Compliance (Product) Quality management system Performance agreements Certification (Standardization) System certifications/standards Functional certifications/standards Industry certifications/standards Conformity (Learning) Business and operational reviews Correction (Repair & Improvement) Corrective / Preventive Actions

Business Excellence Operations Excellence

Insight: Quality is both content as well as process …

Thus quality must be defined comprehensively and interactively:

• Content – the output that is produced by an organization (its products and/or services).

• Process – the means by which these deliverables are designed, developed, produced and delivered.

• Content and process are not separable – they interact and one depends implicitly upon the other for its context and meaning.


Quality is inclusive (it applies complementary logic of “both/and” not an exclusive approach using divisive logic of “either/or”).

Quality is holistic and not separable into components as any sort of blemish on one’s quality reputation destroys the foundation.

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Implementing CSR: Effect and engagement of culture

• The recommended approach for development of a global CSR system is to develop global processes but to populate them with performance details that are aligned to national or local cultures.

• Creating such an approach can be accomplished through the creative application of quality philosophies, principals, and methods – this will be the topic of our second CSR lecture.



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designing and implementing a csr strategy - module 1

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