Managing Uncertainty , various perspectives and a case study using SAP-LAP. 1) Product-Process Change Compulsions in the industry perspective 2) Project Management Perspective 3) Systems Perspective

1. CAN UNCERTAINTY BE MANAGED?
Pallav Vikash Chatterjee
Competitive Strategy
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2. INDEX OF CHAPTERS
Chapter Description Page No
Chapter 1 Uncertainty 5
Chapter 2 Managing Uncertainty: Generic Responses 9
Chapter 3 Managing Product & Process Variations 14
Chapter 4 Managing Uncertainty in Projects 20
Chapter 5 Systems Approach to Uncertainty Management 24
Chapter 6 Case Study: Ex-Ante Strategy 27
Annexure Bibliography 46
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3. INDEX OF FIGURES
Figure Page No.
Figure 1.1 Change Continuum over various variables 6
Figure 1.2 Selection of various methods of research to understand reality 8
Figure 2.1 Corporate Culture 11
Figure 3.1 Technology evolutions in the industry from one technology to next 16
Figure 3.2 Double loop learning 16
Figure 3.3 Products – Process Change Matrix 17
Figure 4.1 Knowing the uncertainty profile of the project 21
Figure 4.2 Managing Uncertainties In Projects 23
Figure 5.1 A Risk model in an example supply chain 24
Figure 5.2 Developing Risk Scores 25
Figure 5.3 Risk Management Plan development 25
Figure 6.1 Case Study: Situation Paradigm 29
Figure 6.2 Case Study: Actors Matrix 30
Figure 6.3 Case Study: Processes Matrix 31
Figure 6.4 Case Study: Learning Matrix 32
Figure 6.5 Case Study: Actions Matrix 33
Figure 6.6 Case Study: Performance Matrix 33
Figure 6.7 Situations: Binary & Interpretive 34
Figure 6.8 Actors: Binary 34
Figure 6.9 Actors: Interpretive 35
Figure 6.10 Processes 35
Figure 6.11 Learning Issues: Binary & Interpretive 36
Figure 6.12 Suggested Actions: Binary & Interpretive 36
Figure 6.13 Performance Areas: Binary & Interpretive 36
Figure 6.14 Situation Elements 37
Figure 6.15 Actors Score Matrix 37
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4. Figure Page No.
Figure 6.16 Relative Process Score Matrix 38
Figure 6.17 Situation-Actor: Binary Cross Interaction Matrix 38
Figure 6.18 Situation-Actor: Interpretive Cross Interaction Matrix 39
Figure 6.19 Actors-Performance Binary Cross Interaction Matrix 40
Figure 6.20 Actors-Performance Interpretive Cross Interaction Matrix 40
Figure 6.21 Process-Learning: Binary Cross Interaction Matrix 41
Figure 6.22 Process-Learning: Interpretive Cross Interaction Matrix 41
Figure 6.23 Learning-Actions: Binary Cross Interaction Matrix 41
Figure 6.24 Learning-Actions: Interpretive Cross Interaction Matrix 42
Figure 6.25 Actions-Performance: Binary Cross Interaction Matrix 42
Figure 6.26 Actions-Performance: Interpretive Cross Interaction Matrix 43
Figure 6.27 Process-Performance: Cross Interaction Matrices 43
Figure 6.28 Actors-Performance: Cross Interaction Matrices 43
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5. Chapter 1. Uncertainty
1.1 The Dimensions of Uncertainty
1.1 (i) Characteristics of Uncertainty
Uncertainty exists in all areas of life, and humans react to it in various ways. Human behavior
in the presence of uncertainty is not always rational. Nonetheless efforts can be made to
understand the possible range of such behavior so that it can be managed as appropriately as
possible. Organizational efforts are needed to be able to reflect on such behavior in order to
effectively be able to manage uncertainty faced. The management of these extraordinary,
uncertain situations has become a discipline in its own right over the past decade ,
particularly in a business context, but increasingly also in a social setting (Hillson & Webster
2005).
The above classical statement elaborates two aspects about uncertainty. Firstly, uncertainty
has two dimensions – uncertainty in the environment & organization’s response to such
uncertainty. Secondly, the importance of the organization’s range of responses in terms of its
behavior under uncertainty which highlights the importance of analytics to assess uncertain
situations and their impact on the organization, organization culture that determines its
responses to uncertainties, flexibility & management style of the organization. To answer to
the question of whether Uncertainty can be managed these two aspects have eclectic
importance in the organization’s ability to manage risk arising out of the uncertainty and
turbulence in the business environment.
1.1 (ii) Uncertainties in a continuum of dimensions
If we dissect organizational work, we observe that the organizational work (or in other words
the business process) can be categorized into two broad categories although a mix between
the two categories may exist in a continuum, one is a regular repetitive routine work that the
organization undertakes which is stable in nature and other is a project based activity that the
organization undertakes. The organization undertakes project-based activity because it can
not produce or achieve the benefits by doing routine things and the expected benefits derived
from the project outweighs the risks. So on one end of the organization’s style of business
can be categorized as relatively stable & routine with relatively lesser frequency of change
while on the other end of the continuum lies a highly dynamic nature of work manifest in
Project based organizational activity.
Further, on product or services front, that the organization delivers to its customers it can also
be dissected and categorized on a continuum where in one extreme lay products or services
with relatively stable and long life-cycles with less frequency of changes while on the
extreme end there are products and service which demand fast-cycles of changes owing to
dynamic industry patterns.
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6. Therefore, apart from the two dimensions of business environment uncertainty – changes in
organization’s business environment & expected response range of the organization, there are
two other dimensions which needs to be carefully evaluated to assess its ability to manage
uncertainty, that is the relative dynamism in its products & services and also as well , the
dynamism in its organizational processes.
To summarize therefore, we conclude four dimensions which vary along with a continuum of
uncertainty and certainness that holds the key to management of uncertainty.
1. Dynamism in External Business Environment
2. The Organizational Response in Face of stimuli of change in environment.
3. Product & Services Dynamism
4. Process Dynamism
Variable Stable Dynamic
Environment Placid / Predictable Turbulent
Internal Response Simple Complex
Product Low Variation High Variation
Processes Routine Project Based
Figure 1.1 – Change Continuum over various variables
1.1 (iii) Environmental Uncertainty
Miliken (1987) specifies three types of environmental uncertainty, viz.,
a) State uncertainty : referring to uncertainty in predicting how environment itself will
change
b) Effect uncertainty : referring to difficulty in predicting the impact of the
environmental changes on the organization
c) Response uncertainty: refers to the difficulty in assessing what choices or responses
are available to the organization in the face of an uncertainty.
This segregation of uncertainty into the above three typology is very useful in the sense of
understanding the behavior of uncertainty in multi-dimensional perspective and lays
emphasis on the influence of the actors involved in the process of managing uncertainty in an
organization, specially those who form a dominant coalition in the organization (those
responsible to make strategic choices and the path that the organization chooses).
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7. 1.2 Defining Uncertainty
There are many definitions of uncertainty in the literature, which essentially takes different
view points on the way uncertainty is understood and interpreted
1.2 (i) Information View
Galbraith (1977: 36-7) takes the information processing approach and defines uncertainty as
the difference in the amount of information needed to perform the task and the amount of
information already possessed by the organization
1.2 (ii) Choice Approach
Burns & Stalker (1961: 112) defines uncertainty as the ignorance of the person who is
confronted with a choice about the future in general, and in particular about the outcomes
which may follow from any of his possible lines of action
1.2 (iii) Interpretation Approach
Marach (1994: 174) defined uncertainty as imprecision in the estimates of future
consequences conditional on present action
1.2 (iv) Uncertainty in terms of Positivism or Hermeneutic Paradigm
Further study of literature and theory of science suggests that there are many views of
looking at management of uncertainty as a research problem to be solved and in essence there
are different causal understandings of uncertainty. Like for instance, Arbnor & Berke (1997)
propose three methodological approaches in business research
- The analytical approach
- The systems approach
- The actors approach
Since there are different views about the reality dependant on different paradigms taken on
developing understanding and interpretation, there are different approaches taken in
understanding of uncertainty as well. While the Positivist approach views reality as concrete
and conformable to laws the Hermeneutic approach sees reality as a manifestation of human
intentionality, their perceptions and differing interpretations. While Analytical approach of
research is applied in developing understanding about reality or a natural phenomenon it is
the underlying Actors who need to be studied to develop understanding in complex human
behavior that defines the cause-effect of the reality.
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8. Figure 1.2 Selection of various methods of research to understand reality - Adapted from
Arbnor & Bjerke (1997))
The definitions of uncertainty varies due to different views and paradigms taken to
understand the phenomenon, while the Information approach of the definition takes the
concrete view of the problem of uncertainty and attempts to define uncertainty as absence or
deficit of information which other-wise exists. On the other hand, the choice approach is
more inclined towards the system view of the organization where the consequences in terms
of impact on the organization is dependent on the choices the organization makes and lack of
understanding of the possible impact each choice would have on the organization is seen as
uncertainty. Yet on the other end, the actors approach sees uncertainty as a result of
imprecision in predicting human behavior in terms of interpretation of reality and in terms of
possible response to external environment, therefore uncertainty is dependant on the actors
involved in the situation.
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9. Chapter 2. Managing Uncertainty: Generic
Responses
2.1 The generic response frameworks provide answers to the questions of managing
uncertainty in case of its first two dimensions (see section 1.1 (ii))
1. Dynamism in External Business Environment
2. The Organizational Response in Face of stimuli of change in environment.
3. Product & Services Dynamism
4. Process Dynamism
The dynamism or turbulence in external business environment necessitates the organization
to tailor itself to the external environment, while it is important for the organization to choose
its approach of how to deal with turbulent environment, the responses determines its impact
of the choices made to deal with such turbulence. There are three generic response
frameworks, as the research on the subject suggests, they principally deal with the aspects of
tailoring the organization to the need of the environment and the choice that the organization
has on the philosophy of how it would choose its decisions alternatives. The three
frameworks that apply are a) response based on contingency effect b) information seeking
response and c) response based on sense-making behavior (or interpretation).
Regarding managing other dimensions of uncertainty, viz. the changes in the product /
services in the industry or the changes due to technology / processes in the competitive
landscape require further framework in addition from these three generic strategies.
The first framework is essentially a systems based approach that views an organization as a
system of inter-related complex structures that determines its behavior of responses as an
outcome and therefore the need of tailoring the structure of the organization according to the
class of uncertainty.
The second framework is an analytical approach towards uncertainty, which essentially deals
with elaborate information seeking and processing of such information to arrive at the choice
of alternatives that are available to the organization in course of its business while facing
uncertainties and turbulence.
The third and last framework is essentially and actors based approach which essentially
focuses on the social and cultural notions that exists in an organization and their complex
inter-relations in organization decision making. This framework essentially focuses on the
people element and rather treats uncertainty in an emergent response behavior of the
organization.
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10. 2.2 Framework of Response Based on Contingency Effect (Systems Approach)
Contingency theory argues (e.g. Burns and Stalker, 1961; Lawrence and Lorsch, 1967;
Galbraith, 1977) that there requires different organizational fits to cope and manage
uncertainties dependent on the position on various dimensions of uncertainty. For instance,
for relatively placid external business environment, there requires to have incremental
changes to adapt to slow changes in the environment that the firm deals with. While there are
situations when the firm or an organization deals with turbulent environment where the
organization should develop culture & organization behavior in such a way that it can quickly
adapt & implement radical changes which are necessitated to cope with environmental
flexibility (Tushman and Romanelli, 1985)
Based on the contingency theory, the organization must respond by fitting their organization
by building in required capabilities to manage them. For instance, greater flexible structure is
required to manage complex environmental uncertainties that they face. The organization
may decide to form their organization based on the industry environment of uncertainty that
they face, for example:
- Hierarchical organization ; or
- Divisional structure; or
- Amoeba structure of organization; or
- Network structure of organization; or
- Matrix structure of organization; or
Also, with structures the corporate cultures also need to be tailored according to the response
capabilities required to cope with the changes in the environment, decision structures in the
organization tailored according to the needs that the business environment dynamics require.
The cultures in the organization can be any of the following forms (see exhibit below)
- Family oriented culture; or
- Eiffel tower metaphor ; or
- Guided missile metaphor; or
- Incubator
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11. Corporate Culture
Characteristic Family Eiffel Tower Guided missile Incubator
Relationships Diffuse relationships Specific role in Specific tasks in Diffuse, spontaneous
between to organic whole to mechanical system of cybernetic system relationships growing
employees which one is bonded required interaction targeted on shared out of shared creative
objectives process
Attitude toward Status is ascribed to Status is ascribed to Status is achieved by Status is achieved by
authority parent figures who superior roles that are project group members individual exemplifying
are close and distant yet powerful who contribute to creativity and growth
powerful targeted goal
Ways of thinking Intuitive, holistic, Logical, analytical, Problem centered, Process oriented,
and learning lateral and error- vertical, and rationally professional, practical, creative, ad hoc,
correcting efficient cross-disciplinary inspirational
Attitudes toward Family members Human resources Specialists and experts Co-creators
people
Ways of changing “Father” changes Change rules and Shift aim as target Improvise and attune
course procedures moves
Ways of Intrinsic satisfaction Promotion to greater Pay or credit for Participation in the
motivating and in being loved and position, larger role performance and process of creating
rewarding respected Management by job problems solved new realities
Management by description Management by Management by
subjective objectives enthusiasm
Criticism and Turn other cheek, Criticism is accusation or Constructive task- Improve creative idea,
conflict resolution save other’s face, do irrationalism unless there related only, then admit not negate it.
not lose power game are procedures to error and correct fast
arbitrate conflicts
Figure 2.1 – Corporate Culture
The contingency approach suggests that the organization copes with uncertainty creating
certain parts within it specially to deal with it, while making other parts specializing in other
activities where there are conditions of certainty or near certainty. The uncertain environment
necessitates a need for more flexible structures in order to increase responsiveness (Burns and
Stalkers, 1961; Thomson, 1967)
The ‘law of requisite variety’ (Ashby, 1960) argues that the organizations need to develop
greater complexity where they are facing uncertain and turbulent environments. A very
pertinent example of this case is the networked structure of complex supply chains where the
risks of uncertain supplies owing to variety of factors are mitigated by a complex chain of
sourcing of materials. The network structure mitigates risks arising out of uncertainties are
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12. managed by parallel nodes in the supply chain structure which can take care of the supplies
should one among the alternative nodes fails to deliver as per the requirements of the supply
chain. The complexity helps in mitigating risks of failure arising out of environmental
turbulence.
Unstructured or semi-structured organizations tend to deal with uncertainties or
environmental turbulence much more effectively by developing flexible and evolving
approaches to situations including rapid scanning of the environment and rapid action in
response to changes. Therefore the organization fit, is very important to deal with
uncertainties and the organization response is contingent to what the situation demands.
Therefore the contingent approach to uncertainty management is more about flexibility and
fitting the organization to the need arising due to the level of changes that business
environment witnesses and therefore the levels of uncertainties the organization witnesses.
2.3 Framework of Response Based on Information Seeking Approach (Analytical
Approach)
This framework assumes the information view towards uncertainty (section 1.2 (i); definition
of uncertainty). The framework suggests managing uncertainty on the basis of information
gathering. The framework therefore aims to seek out greater degree of awareness about the
environment, more and better information and therefore mitigating the risk arising out of the
uncertainties that are generated due to lack of information.
Organizations need to develop strategies and activities to collect, analyse and use more and
better information on the assumption that this will help them deal with the environmental
uncertainty and also help them clarify the choices open to them to manage such uncertainties.
Therefore, using this approach the organization enables itself to a greater extent to have better
and more accurate predictions towards the possible environmental situations and therefore
make informed and better choices to manage uncertainty.
Pertinent example for such risk mitigating strategies to manage uncertainty could be seen in
data-analytics utilized by retailers to predict trends in shopper-behavior and therefore
customize their offerings in their stores to the customers. Mega Retailers like Amazon, E-Bay
& Walmart etc are actively utilizing data-mining & advanced analytics on a continual basis to
assess shopper trends. The decisions of pricing, store-location, staffing, inventory, logistics
and supply chain are based on the data collected and gathered. The retailers respond to the
market level changes dynamically to ensure optimum resource utilization, profitability and
competitive advantage.
2.4 Framework of Response Based on Sense-Making Behavior (Actors Approach)
‘This approach assumes that information alone cannot be adequate in responding to
uncertainty, since interpretation, sense-making & social construction is more influential in the
settings of uncertainty’ (Weick, 1995: 177). The approach therefore is about developing
concurrent interpretation and assessment of different choice alternatives that the organization
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13. has while facing uncertain situations. This also anxiety and boosts confidence of senior
managers. Delphi technique of arriving on business forecasts and decision making is one
such approach used by industry, where there are concurrent interpretations of the scenario
and development of decision alternatives done with experts in the organization. This is a
more hermeneutic approach (see section 1.2 (iv), on different paradigms of research) and
stresses on understanding the knowledge rather than stressing on explanatory knowledge
about the reality facing the organization. Further, the Hermeneutic paradigm is more
appropriate in the complex interactions in the social structures and interpreting reality as a
manifestation of human intentionality.
The approach focuses not just on gathering information but also ensuring concurrence in the
organization in interpretation of the information to decide the future course of action.
Ambiguity, which is the lack of clarity or having two or more interpretations of the same
situation, is a problematic phenomenon for an organization dealing with uncertainty and
focussing on utilizing available information to reduce ambiguity by developing concurrence
in response choices and therefore predictability in the organization response, the impact of
the response in face of uncertainty.
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14. Chapter 3. Managing Product & Process
Variations
3.1 Organization face uncertainty in two broad ways, as suggested by empirical research.
Firstly changes that lead to change in products or services brought about because of shifting
consumer tastes and preferences, new geographic areas or markets entered and / or
necessitated by competition moves. Secondly, changes in technology that necessitates
changes in the operational processes through which the organization carries out its business.
Summarily therefore, the two broad uncertainties are as below
a) Product Changes
b) Process Changes
The above two changes as discussed in section 1.1 (ii) varies along the continuum of change
from being stable and placid environment where changes are too little or too few to a highly
dynamic environment where the changes are rapid and frequent.
3.2 Product Changes
Product changes are brought about by following drivers
a) Shifts in consumer tastes and preferences. These are determined by changing
switching costs among substitutes and innovations in the market-place that
necessitates the organization to keep up or keep itself ahead of the market-place in
product innovation. The product changes referred to in this section includes services
as well, unless otherwise mentioned. Also there are complementary industries as well
that determine the relevance of the product.
For instance, under the Oil crisis in the USA, entire home grown automobile industry
in the US faced the heat of slow-down because of the pre-dominantly gas-guzzling
products that it had to offer to the market-place while there was a significant shift
from gas-guzzlers to more fuel efficient and frugal Japanese Cars. There was a crisis
of Titanic proportions faced by automotive giants like General Motors, Ford &
Chrysler in face of the crisis in the complementary industry of Oil. The pressures led
to auto-manufacturers aggressively spend on R&D and New Product Development
(NPD) activities to ensure that they ensure product changes to keep up with the shift
in consumer preferences.
Further, similar pressures of uncertainty are felt in Information Technology &
telecommunications landscape with frequent disruptive innovations leading to
absolute change in consumer tastes and therefore rendering older products irrelevant.
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15. While the industries like automotive, airlines manufacture etc have relatively larger
Product Life Cycle (PLC) and gestation periods on products, industries like IT,
Wireless telephony etc have relatively shorter PLCs and higher innovation cycles. In
automotive industry, there is a slow but discernible trend towards environment
consciousness, rising preference towards fuel economy and stringent emission
standards, whereas, in Information Technology / Telephony there are massive shifts in
quick space of time (e.g., Moore’s law of doubling of computing speed and cut-down
of computing costs to half of previously existing standards every eighteen months).
The above two examples provide the understanding of range of variation in
uncertainties in product changes across a continuum of stable to dynamic.
b) New Markets. A company may choose by necessity to enter new markets, and as the
classic Ansoff’s decision making matrix suggests there are situations when an
organization may feel the need of evolving right strategies for market development,
which may involve Old product-New market strategy or market extension strategy or
New Product-New Market or the Market Diversification strategies as necessitated by
the competitive realities. The Market Diversification strategy necessitates new
products in the new markets and helps the organization to diversify its market
concentration risk and product concentration risks and therefore reduce dependencies
that may threaten its competitive advantage.
c) Competitor Moves. A competitor may be continuously innovating or following an
imitation strategy, in either case there is a risk of dilution of competitive advantage
and therefore long term sustained advantage that the organization enjoys. As the law
of nemesis correctly foretells that today’s competitive advantage may render itself as
tomorrow’s strategic inflexibility. Therefore, in light of competitive moves, it is
necessary to continuously innovate in terms of products / services and bring about
new offerings that lead the organization ahead in terms of competition.
3.3 Process Changes
With rapid advent of technology, it is imperative on the organization to keep up with the
latest technological advance to keep itself abreast in competition. Further, technological
advances provides the learning curve advantage to the organization resulting in lower
operational costs, economies of scope and scale, product superiority in terms of
performance etc. over a period of time. Therefore innovation, both in terms of
incremental as well as rapid are important in the competitive landscape (see exhibit).
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16. Figure 3.1 – Technology evolution in the industry from one technology to next
Also technological advancement is a result of learning curve effects on the economies of an
organization resulting in lowering in average costs and therefore higher profitability, better
competitive advantages. These forces necessitate change in technology & processes.
Figure 3.2 – Double loop learning, to evolve new approaches (technologies) in use to carry
out business: Kolb’s learning cycle, modified with a double loop (Argyris and Shön, 1978)
3.4 The Change Matrix
One such generic strategy framework to manage product and process changes can be depicted
as below. Where in each of the quadrant applicable to the relevant uncertainty situation as
depicted in the matrix there are suggested decision alternatives to manage with the situation
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17. Figure 3.3 Products – Process Change Matrix
The generic positions are as follows dependant on the uncertainty environment in Product &
Processes Change dynamics faced by the organization
Quadrant I : Stable Product and Stable Process Changes
Quadrant II: Dynamic Product and Dynamic Process Changes
Quadrant III: Dynamic Product and Stable Process Changes
Quadrant IV: Stable Product and Stable Process Changes
For each of the above generic positions there are different strategies
3.4 (i) Quadrant I Strategy
The Quadrant I scenario is about an environment which has stable and relatively less frequent
product changes while also on process / technology front as well the environment doesn’t call
for frequent changes, therefore the process environment is stable. Under such scenarios, the
strategies suggested are essentially standardization and focus on scale economies. The
suggested strategies to effectively manage profitable and ensure competitive advantage are as
follows.
Standardized Products
Centralized Decision making
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18. High Specialization to ensure economies
Standard rules & procedures
Mass Production
The key business strategy under such scenario is Cost minimization. Under such scenario
also, it is literally impossible to maintain status-quo in product and technology for a long time
and therefore there arises need of change in products and processes. However, under such
circumstances, the cost of change is very high. In case of product changes the entire process
of production is rendered obsolete. Furthermore, process changes are very complicated,
raising error rates and increase unit costs. Therefore the best alternative to stabilize the
business operations, it is imperative for the organization to build in some amount of
flexibility in the products and processes and limit product variety.
3.4 (ii) Quadrant II Strategy
Quadrant II is about dynamic product changes and dynamic process changes at the same
time. If there are very rapid changes in products, the rate of process change also equals the
rate with which changes in products are introduced. Such a situation when product changes
are very rapid, there needs to be equally rapid changes in the process with which the products
are produced.
The suggested strategy of uncertainty management under such situations is as below
Short production runs
Small volumes planned for each product
Constant Innovation in Product & Process to maintain competitive edge.
Building the “Idea” organization, focusing on new ideas and innovation rather than
being strictly cost-focussed.
Decentralized organization
Limited rules and procedures
Distributed technology of providing specialized knowledge independently
3.4 (iii) Quadrant III Strategy
Quadrant III highlights the scenario when there are dynamic product changes and stable
process changes. Over a period of time, there are patterns which are visible in the otherwise
seemingly unpredictable product changes at the outset. These patterns when recognized give
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19. opportunity to the organization to build highly flexible platforms of process capabilities or
know-how over a period of time.
The strategies adopted under such situations are
Mass-customization
Flexible manufacturing systems
Incremental process innovations or continuous improvement (Kaizen principle)
Highly networked organization structure with interchangeable, inter-compatible units
or teams networked with each other, building in flexibility in terms of human resource
capabilities.
The key strategy is to build flexibility and variety in the products produced, while also
at the same time maintaining specialization to a certain extent. Platform strategy of
automobile companies, Group Technology for manufacture of high variety of goods
through similar processes (e.g., Heavy Electricals Industry) are such example.
3.4 (iv) Quadrant IV Strategy
The Quadrant IV relates to a situation when there are stable products while the processes
change dynamically in the environment.
Rapid process changes
Continuous improvement design, focusing on rapid and continous improvement in
processes utilizing learning experience of product characteristics.
Team structure in the organization to ensure collaborative work culture focusing on
process changes implementation
Cross-Functional-Teams (CFTs) to work on process change plans & product
improvement plans
Process-innovation in Invention Design & Process Efficiency in Mass Production
Design
Mass-production strategy
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20. Chapter 4. Managing Uncertainty in Projects
“There are known knowns; there are things we know we know. We also know there are known
unknowns; that is to say we know there are some things we do not know. But there are also
unknown unknowns – the ones we don’t know we don’t know.” Donald Rumsfeld, US Defence
Secretary, 2001-06
4.1 As elaborated in section 1.1 (ii), the operations of an organization varies in one very
important aspect on the basis of routine & repetition in the nature of operations. In one case
when the nature of operations are routine and repetitive, as in for example, in a
manufacturing organization it is the repetitive nature of the work which enhances learning
about the characteristics of the process and therefore higher level of learning about the
processes and therefore lesser unpredictability. Whereas, project based nature of work is
rather on the other end riskier and less predictable in its nature. Therefore a separate attention
needs to be given in managing uncertainty in a Project based environment.
The above observation of Mr. Donald Rumsfeld is prophetically right while managing
uncertainties. The real worry for a manager lies in Unknown-Unknowns or “unks-unks” as
colloquially termed, that often comes out as surprise and adding to the risk element in a
project.
Projects can be defined as a unique interrelated set of tasks with a beginning, and an end and
a well defined outcome. The commonly used definition of the project assumes that every one
can identify the tasks at the outset, provide contingency alternatives and keep to the same
overall project vision throughout. These assumptions are quite fair to certain extent in routine
or well-understood projects but not for innovative projects or novel projects where there
always looms the possibility of Unknown-Unknowns, the term as Mr. Donald Rumsfeld had
famously coined, which threatens to build risks revolving around the project. The
characteristics of uncertainty in projects are primarily due to the inter-related nature of the
sequence of activities involved in the project. As completion of one constituent activity
determines the start and finish of the next set of activities, the overall uncertainty in the
project is the net summation of the uncertainties involved with each constituent activity.
While, the planners conceive and plan the project on the basis of inter-relatedness of the
constituent activities the possibilities of uncertainties which are not known possess the
highest risk. There can be four kinds of uncertainties involved, based on the matrix of
prediction level possibilities of occurrence of uncertainties and prediction level of the
possible impact of the uncertainties on the final outcome. Therefore we can summarize the
various levels of uncertainties as “known-knowns”, “known-unknowns”, “unknown-knowns”
and “unknown-unknowns” ; it is the last kind which poses the highest risk. It is the
“unknown-unknowns” which Donald Rumsfeld was referring to.
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21. 4.2 Components of Project Uncertainty
Theory suggests that each project has an uncertainty profiles constituting various levels of the
different kinds of constituent uncertainties those are involved. The constituents are at
different levels of prediction difficulties starting with variation with most predictable
uncertainties, Foreseen Uncertainty, Unforeseen Uncertainty & finally Chaos.
4.2 (i) Variation: Variation comes from many small influences and yields a range of values
on a particular activity. Activity ABC, may take a time of 40-45 weeks where the range of
variation is clearly known based on experience and known factors which may cause the
delays, for example. The project plan is detailed and stable under situations of variation and
the variation is built in the budgets to manage the uncertainty.
4.2 (ii) Foreseen Uncertainty: Foreseen Uncertainties are identifiable and understood
influences on the outcome of the project, however the probabilities of occurrences of such
uncertainties are not known. While variation which comes from combined small influences
foreseen uncertainties are distinct and may require full-blown risk management and
alternative plans in the event of occurrence of such uncertain events, that may pose risk to the
project.
4.2 (iii) Unforeseen Uncertainty: In case of unforeseen uncertainty, as the name itself
suggests, there can’t be any way to determine and identify such uncertainties during the
project planning. There are no contingencies prepared as the team either is not aware of such
uncertainties or treats such uncertainties are so less likely that they are not accounted for in
the project planning.
4.2 (iv) Chaos: Whereas even projects with unforeseen uncertainty environment start with
fairly stable project plans, the projects with Chaos cannot. Even the basic structure of the
project plan doesn’t exist and is uncertain. For example, when there is very high level of
technology turbulence, or when the project is research not development. Often the project
outcome is different from the intial intended outcome.
Figure 4.1 – Knowing the uncertainty profile of the project
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22. 4.3 Managing Uncertainty
4.3 (i) Managing Variation
In projects subject to variations, the variations should be budgeted into the overall project
plan unless otherwise done, the project will be leading to unnecessary fire-fighting putting on
drain to resources and compromising on the final outcome. In such situations there needs to
be put buffers of variation ranges in the constituent activities, a critical path be formed for the
overall project. For managing such uncertainties, the manager must closely monitor the
advance of the project and the variations should be kept under explainable limits. The buffers
such kept in the project plan owing to the variation nature of the uncertainties should be
treated as a bargaining chip for the negotiation process of the project plan, on the contrary
they should be established with scientific explanation of the variation, using statistical charts
and historical data.
4.3 (ii) Managing Foreseen Uncertainties
Ignorance to foreseen uncertainties is a sure recipe of disaster; In such projects subject to
foreseen uncertainties the approach needs to follow is to develop contingency plans in place
with careful evaluation of each such foreseen uncertainty that looms over the project. One
common & effective approach for managing and developing right contingency plan for
foreseen uncertainty is the decision-tree approach. The branches of the decision trees would
lead the manager to assess the impact of each scenario on the overall project outcome. With
decision-tree approach in planning will enable the manager to plan and set-out contingency
activities to be in place for each such branched out scenario to occur.
4.4 (iii) Managing Unforeseen Uncertainties
It is difficult to plan for unforeseen occurrences, while they can have significant on the
overall behavior of the project progress, it is important to have the right strategy in place for
managing this constituent uncertainty element in the project. Since the uncertainties under
such scenario cannot be predicted, the manager should follow the approach of an evolving
strategy rather than a planned strategy. As the project proceeds and the events unfold, re-
visiting , planning and fine-tuning the action plan of the project, bit-by-bit and in small
pieces, so that the objectives are delivered to the closest and contingencies closely kept under
check.
4.4 (iv) Managing Chaos
Chaos call for constant change. Under the scenario of chaos, the manager must constantly
assess, define and redefine the project based on the learnings developed in the due course of
progression of the project. Learning provides the feedback loop to correct and redefine the
project itself. Under Chaos, in order to ensure success fundamental changes need to be
brought in the basic assumptions the project is implemented. There has to be alternative
approaches, newer assumptions developed either sequentially or parallel, as and when the
situation necessitates. Success under chaos requires great degree of flexibility, empowerment
and hard decisions to be made. Also, under such situations there needs to be involvement of
22 | P a g e

23. the top management of the company to ensure speedy decisions and quick action as and when
the fundamental assumptions of the project need to be changed.
Figure 4.2: Managing Uncertainties In Projects: MIT Sloan Management Review
(Winter 2002)
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24. Chapter 5. Systems Approach to Uncertainty
Management: SAP-LAP Synthesis
5.1 Systems Approach
System Approach is considering a business as a simple-system with cause and effect
relationship, with the operational processes and activities that the firm undertakes as
the one that converts inputs into outputs. The system approach of managing risks is
analyzing the business ecosystem as a system that responds to the stimuli of the
environment and therefore results into variations in the output. Any flux in the
business environment as an input would resultantly impact the overall output of the
business, which eventually will affect the Economic Value Added (EVA). As shown
in the below exhibit that explains the risk model of a supply-chain due to various
environmental (internal & external) factors resulting into the overall impact on the
EVA.
Figure 5.1 - A Risk model in an example supply chain (J.Oehmen et al., Feb 2009)
The system approach deals with carefully analyzing each uncertainty element and
associated risks attached to the overall performance. Owing to the inter-linkages and
24 | P a g e

25. networked structures of supply-chains, often the systems approach is used in
mitigating and managing supply chain uncertainties. The situations of uncertainties
are analyzed and the risks arising due to them are found out and classified. The
impacts of those risks are understood and evaluated. The probabilities of each such
risks are found out, the risks are weighted with the probabilities of occurrence and
based on the same prioritization is done by developing a prioritization score.
Figure 5.2 Developing Risk Scores
The system approach is based on the understanding that the complex inter-
relationships underlying in the structure of business systems determine the pattern of
behavior of the system leading to the events that determine the impact of uncertainty.
SAP-LAP synthesis is one such tool to understand the impacts of complex inter-
relationships
Figure 5.3 – Risk Management Plan development
25 | P a g e

26. 5.2 SAP-LAP Approach
SAP-LAP is an integrative framework which comprises of 6 components, The
Situation to be dealt with, The Actors involved in the situation – they can be both
internal as well as external, the Processes dealing with the situation which again can
be both internal and external, the key Learning issues, the Actions to be initiated
post acquiring these learnings, the Performance areas in terms of KRAs (Key Result
Areas) or objectives to be achieved.
The framework involves study of SAP & LAP issues with help of three types of
matrices
Self interaction matrices
Cross interaction matrices
Assessment matrices
The framework of SAP-LAP analysis can be utilized in any managerial context;
however in this work we utilize this framework in context of after-market services
supply chain risk management. The steps involved in the processes are
Define elements in SAP-LAP
Select relevant matrices
Develop scales and assess the elements in framework
Develop binary as well as interpretive self-interaction matrices
Develop binary as well as interpretive cross-interaction matrices
Interpret the relationships
Drawing Conclusions.
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27. Chapter 6. Case Study: Uncertainty Management
(Using Ex-Ante Strategy / Systems Approach)*
In summers of 2011, a multinational company faced losses to the extent of $30 million in a
providential incident of fire in their central after-market components warehouse. Most of
the components that were stored in their warehouse were primarily meant for after-market
service purposes. Also, lot of essential materials meant for marketing and internal-
consumption purposes were damaged or lost in the accident. The cause of fire was un-
known, but assessments suggest that it could have caused due to voltage surges in power
supplies and some materials due to their inflammable nature had caused the fire to spread
to proportions that resulted in approximately 80% of the ware-house getting destroyed.
The MNC being based offshore and are present in the country with their niche offerings
portfolio are managing operations through their subsidiary operations. With foreign
sourcing of about approximately 10% (by unit volume) of their critical proprietory
components, with large lead times, inventories of over three months are maintained
exclusively for after-market consumptions. While there are over three hundred line-items
which are fast moving maintenance components for after-market purposes are essentially
of indigenous origins, however inventory levels of month equivalent are maintained for
effectively maintaining a first-fill ratio of over 80% (orders which are executed completely
on first picking itself) and balance after-market orders getting executed with a delay of
maximum of two weeks. The management till the incident was quite impressive with over
95% service ratio. However, with the incidence of the accident the serving ratio dipped
drastically generating practically a waiting period in repairs across the market. The impact
of the incident was of very high veracity as the company was flooded with accumulated
backlog orders and the much unexpected nature of the accident had resulted delays in
serving the after-market needs.
After-market divisions are essentially dealing with components for post-sales maintenance
demand. Also the companies in India are contractually obliged to provide free of cost
maintenance for first two years for warranty purposes and legally obliged to provide for the
after-market supplies for next five year for the goods sold, even if the product they had sold
has been withdrawn from the market. While the revenues from after-market supplies also
add to the bottom-line of, it also has impact on the competitiveness of the organization.
MNCs with large lead times in aftermarket component supplies and lesser predictability in
their service levels often find themselves being rated poorly among the users affecting sales
which form nearly about 90% of their total revenues. Therefore the performance in after-
market though in itself contributes to a smaller portion to the overall revenues, indirectly
impacts the largest revenue source of the organization –sales and thereby has straight
correlation with the economic value that they create.
There are other situations also that may result into similar outages or disruptions in after-
market supplies, some of them covering the entire range of SKUs in after-market
components while some of them resulting in critical shortages in some SKUs alone;
however, there can be high impacts on company’s brand image, sales or financials. The
important and likely such situations may be as follows (non-exhaustive list)
27 | P a g e

28. a) Floods, earthquake or natural calamities / disasters.
b) Fire accidents, riots, political disturbances leading to temporary snapping of logistics.
c) Seasonal surges in demand of certain range of components – for example, during
rainy season there is a surge of rusting complains, leading to surge of certain
components.
d) Sudden demand of some specific component for product campaigns or to keep up
with the warranty obligations – essential for customer satisfaction and legal
compliances.
The MNC in the subject of this case study, have outsourced the logistics of after-market
supplies to a national level carrying & forwarding agency (Distributor) that offers its services
of account management and logistics with over 100 service dealers across the country. The
distributor in turn engages with 3PL service providers at national level for managing the
logistics of supplies across to the 100 points of consumption of these supplies.
The management of the organization is working out a risk mitigation plan to ensure smooth
continuity of after-market business which is critical for ensuring customer satisfaction,
company image and growth in after-market services business. The organization not only
plans to ensure mitigation of risks such as the fire accident which has happened recently,
but also other issues that may have high impact on smooth continuity of business, ensure
profitability of operations. A good risk mitigation and management strategy will fulfil these
objectives and will also help the image of the company providing good serviceability and
reliability of its products through responsive after-sales services as after-market supplies
form a very important aspect of after-sales. In this study we propose to do a SAP-LAP
synthesis of the problem in the context of after-market supplies of the company and
propose & evaluate solutions for risk management and mitigation. Also, we propose to
apply force-field method to evaluate the supporting and restraining forces applicable on
implementation of any such strategy.
SAP-LAP synthesis
SAP-LAP analysis as described in previous section involves starting with identifying current
Situations, study the Actors involved and the Processes involved. Subsequently, the analysis
deals with analysis of Learning issues, suggested Actions and Performance objectives.
Prevalent Situation
• S1: MNC is a niche market player with over 100 service dealers
• S3: Customer responsiveness improvement required for customer satisfaction.
• S2: High competition in Indian industry, the segments where the company operates
in.
• S4: Sourcing from foreign vendors has lead times of over 3 months. Any disruption or
incidents like fire in warehouse, inbound issues may result in issues of responding to
market requirements and affect service-ratio for orders, recovery for which may take
time of over 6 months.
28 | P a g e

29. • S5: Widely spread service dealer network and due to niche market policy low
component consumption per dealer, resulting into LTL issues in logistics rendering
small regional transporters unviable.
• S6: In order to contain administration expenses and to remain cost-competitive the
down-stream function of service dealer account management & logistics have been
outsourced to a national distributor. Resulting, low control & visibility of field
operations & higher lead time in information flow
Summary
The summary of situation issues are listed with denotations are as mentioned in the below
table. (figure – 6.1)
Situation Paradigm
S1 Niche market player with 100 service dealers
Customer responsiveness required for customer
S2
satisfaction
S3 High competition in Indian industry
High lead times in sourcing esp. foreign vendors.
S4
Disruption leads to large response times
Thinly spread after-market components consumption
S5 per service dealer, due to LTL issues small
transporters cannot be used for logistics
Downstream functions - logistics, dealer account
management
S6
delegated to national level distributor – Distributor
Control & Information lead time
Figure 6.1
Main Actors
• A1: Top Management of the company as the main decision makers.
• A2: Purchase function team for terms and conditions with suppliers.
• A3: Marketing function team for drawing up marketing strategies, cost and value
propositions for products, services and after-market supplies of components.
• A4: Production function for drawing up production schedules, together with after-
sales function procurement schedules are decided.
29 | P a g e

30. • A5: Engineering teams - Quality assurance, R&D & service functions for determining
component requirements, product up-gradations & updates, etc.
• A6: Components team for managing of warehouse and inventory operations.
• A7: National distributor, responsible for service dealer account management, order
generation, order management & logistics.
• A8: Service dealers, for right ordering policy, inventory decision, order frequency and
quality of forecasts.
Summary (figure – 6.2)
Actors
A1 Top Management
A2 Purchase function
A3 Marketing team
A4 Production team
A5 Engineering teams
A6 Inventory administration team
A7 National level distributor
A8 Service dealers - 100 nos.
Figure 6.2
Processes
• P1: Procurement process – choice of suppliers; indigenization.
• P2: Service and Components marketing Strategy
• P3: Warehouse management & administration - up-keep, material handling,
software etc.
• P4: Inventory management system at service dealers
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31. Summary
The key processes involved in supply chain design for risk mitigation are as follows (figure –
6.3)
Processes
P1 Procurement process – Localization
P2 Marketing Strategy
P3 Warehouse management & administration
Service dealer - inventory management
P4
systems
Figure 6.3
Learning Issues
• L1*: Crisis management strategy is missing. In absence of such practices, any
disruptive event can paralyze smooth functioning of the supply chain.
• L2*: Inventory decisions in supply chain -decisions on the basis of strategic trade-off
between flexibility v/s cost-efficiency, cost-leadership v/s differentiated services in
service supply chain.
• L3*: Prediction and forecasting surges in demand or expected shortages
• L4*: Training and service dealer up-gradation
• L5*: Competition benchmarking and positioning for after-sales services for
competitive advantage.
Summary
The summary learning issues in risk management decision of the organization are
mentioned as below (figure – 6.4).
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32. Learning
L1* Crisis Management Strategy
Inventory decision by taking strategic trade-
L2* off, flexibility v/s efficiency, cost leadership v/s
differentiation
L3* Forecasting for surges in demand, shortages
L4* Training , dealer service level up-gradation
L5* Competition benchmarking
Figure 6.4
Suggested Actions
• A1*: Safety (Fire Safety, Earthquake safety, Flooding safety etc) policy, drills to
enhance responsiveness to such crisis situation to contain damage and loss to
property.
• A2*: Increasing localization of components.
• A3*: Cross functional crisis management team for analysis of field level product
performance and failure analysis statistics to determine and forecast & draw up
quick response strategy for after-sales supplies requirements in crisis situation.
• A4*: Multiple ware-houses at different locations across the country nearer to the
points of consumption for diversifying and hedging risk arising due to criticality of
one centralized warehouse.
• A5*: Regional stockists for CF&A and warehousing requirements to cater to regional
consumption requirements.
32 | P a g e

33. Summary (figure – 6.5)
Suggested Actions
A1* Making a safety policy, safety drills
A2* Increasing localization - purchase policy
A3* CFT on crisis management
A4* Multiple warehouses, company owned at strategic locations
Regional stockists, CF&A to facilitate smaller order quantities
A5*
and improved field responsiveness
Figure 6.5
Expected Performance:
• P1*: Improved responsiveness of the after-market supply chain & reduced
probability of disruption of components activities – Crisis preparedness
• P2*: Enhanced customer satisfaction
• P3*: Improved competitive advantage of the company
Summary (figure – 6.6)
Performance
P1* Crisis Preparedness & Improved responsiveness
P2* Localization %age (Degree of localization)
P3* Improved competitiveness, market share
Figure 6.6
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34. 1. Self-interaction matrices (Binary & Interpretive)
a. Situation (Binary and Interpretive – figure 6.7)
External Internal External
Internal
adds multiplies influences
0 1 0 1 1 S1 -
risk
-
risk risk
S1
adds contributes contributes multiplies
1 1 1 1 S2 uncertainty to risk to risk risk
S2
adds adds
0 1 1 S3 -
risk uncertainty
S3
adds adds
1 1 S4 uncertainty risk
S4
adds
1 S5 uncertainty
S5
S6 S6
Figure 6.7
b. Actors (Binary & Interpretive)
Binary matrix (figure – 6.8)
External Internal
0 0 0 1 1 1 1 A1
0 0 1 1 1 0 A2
1 1 1 1 1 A3
0 0 1 1 A4
0 0 1 A5
1 1 A6
1 A7
A8
Figure 6.8
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35. Interpretive matrix (figure – 6.9)
External Internal
Reporting, Reporting, Reporting, Reporting,
- - - strategy & strategy & strategy & strategy & A1
Decision Decision Decision Decision
Inventory Quality Dependance
- -
Decision concerns on operation
- A2
Control Control Distribution
Forecast
& & Strategy & Feedback
& Scheduling
A3
Coordination Coordination Feedback
Coordination
- - Coordination
& Feedback
A4
- - Feedback A5
Control Control
& & A6
Coordination Coordination
Control &
Coordination
A7
A8
Figure 6.9
c. Processes (figure – 6.10)
External Internal External
Internal
Information
Material, Order & Flow &
1 1 1 P1 Order Flow
Money flow coordination P1
on cost
requirments
Information
1 0 P2 Flow - Guidelines - P2
& Process design
Order &
1 P3 Money Flow
P3
P4 P4
Figure 6.10
35 | P a g e

36. d. Learning Issues (figure – 6.11)
External Internal External
Internal
Support
Provides
1 1 1 1 L1* Evidence Synergy
Support
to meet L1*
strategy
Provides Provides
1 1 1 L2* Synergy
Support Support
L2*
1 1 L3* Evidence Synergy L3*
Provide
1 L4* Support
L4*
L5* L5*
Figure 6.11
e. Suggested Actions (figure – 6.12)
External Internal External Internal
Information
0 1 1 0 A1* - Synergy
Exchange
- A1*
1 1 1 A2* Synergy Synergy Synergy A2*
1 1 A3* Synergy Synergy A3*
1 A4* Precedence A4*
A5* A5*
Figure 6.12
f. Performance areas (figure - 6.13)
Will help
1 0 P1* achieve
- P1*
1 P2* Will enable P2*
P3* P3*
Figure 6.13
36 | P a g e

37. 2. Assessment Matrices
a. Situation Elements (figure – 6.14)
Situation Elements Current State
S1 Niche market player with over 100 service dealers 3
S2 Customer responsiveness required for customer satisfaction 4
S3 High competition in Indian industry 4
High lead times in sourcing esp foreign vendors. Disruption
S4 3
leads to large response times
Thinly spread after-market components consumption per
S5 service dealer, due to LTL issues small transporters can not be 4.5
used for logistics
Downstream functions - logistics, dealer account management
S6 delegated to national level distributor 4
(Distributor Control of Field Operations)
Figure 6.14
b. Actors (figure- 6.15)
The assessment is based on feedback from practitioners from industry, on
parameters of current situation prevalent. For instance top management has been
assessed and given a scaled ranking based on their experience of uncertainties
Indian domestic market. The newer OE players being subsidiaries of foreign MNCs
score lesser compared to MNCs present in domestic industry for a longer period.
Key Competitors
Actors Own C1 C2 C3
A1 Top Management 3.0 4.5 3.5 3.0
A2 Purchase function 4.0 Not relevant Not relevant Not relevant
A3 Marketing team 3.5 3.5 4.0 4.5
A4 Production team 4.0 4.5 4.0 4.0
A5 Engineering teams 3.5 4.5 3.5 4.5
A6 Warehousing administration team 2.5 4.5 3.5 2.5
National level distributor for spare
A7
parts / Spares Distribution 2.5 4.5 3.5 3.0
A8 Service dealers - 100 nos. 3.0 5.0 5.0 3.5
Figure 6.15
37 | P a g e

38. c. Processes (figure – 6.16)
Key Competitors
Processes Own C1 C2 C3
Procurement process -
P1
Localization 4.0 5 5 5
P2 Marketing Strategy
3.0 5 5 5
Warehouse management
P3
& administration 2.5 5 4 3
Service dealer - inventory
P4
management systems 2.5 5 3 2.5
Figure 6.16
3. Cross Interaction Matrices
a. Situation - Actors
Binary cross interaction matrix – figure 6.17
Interpretive cross interaction matrix – figure 6.18
Internal External
S1 1 0 1 0 0 1 0 1
S2 1 1 1 1 0 1 1 1
S3 1 1 1 0 1 1 1 1
S4 1 1 0 1 1 1 0 1
S5 1 0 1 0 0 1 1 1
S6 1 0 1 0 0 1 0 0
A1 A2 A3 A4 A5 A6 A7 A8
Figure 6.17
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39. 39 | P a g e
Differentiation & eff ective
India-Business communication for
S1 - - - Market analysis, forecast - Market Coverage
Strategy volumes & cost constraint
reduction
Prioritization strategy-
Performance review
New supply Cost-benef it constraints team w ork w ith Fill-rate, service ratio Customer response policy
Multiple sourcing for sales-loss review
S2 chain design - agreement for multi-layered after market for - target setting, functional - Inventory / consumption
critical elements customer satisf action
and partnerships distribution prioritization of after market KRA setting analysis, ordering policy
review
requirements
Constraint of Competition Warehousing operations Market Share &
Competitive cost Respective region
S3 competition / profitability Competition constraints - Benchmarking cost reduction strategy, Customer retention
considerations market share
concerns on localization / design continuity monitoring KRA
Localization - technology Integration w ith
Regular ordering,
Technology transfer Gradual escalation Inventory Decisions - transfer facilitation foreign suppliers, inventory
scheduled ordering
Figure 6.18
S4 for development of localization, new - Integration w ith suppliers Vendor development, and ordering policyf or -
for high lead time parts,
of local sourcing base vendor development (VMI) Quality Review for foreign sourced
consumption forecast
domestic suppliers components
Engaging 3PL, mik routing
New transport policy / Minimum Order
Netw ork strategy in key cities, multiple Dealer administration,
S5 alternatively volume - - - Quantity, Volume
review and correction w arehouses in strategic training & dealer systems
expansion strategy build-up
locations
Partnership review Distributor relations
S6 Partnership & Agreement - - - - -
and recommendation & alignment
A1 A2 A3 A4 A5 A6 A7 A8

40. b. Actor-Performance
Binary (figure – 6.19)
A1 1 1 1 0
A2 1 0 1 0
A3 1 1 0 0
A4 1 1 1 0
A5 1 1 1 0
A6 1 1 1 0
A7 0 1 1 1
A8 0 1 1 1
P1 P2 P3 P4
Figure 6.19
Interpretive (figure – 6.20)
Approvals on Business Performance
A1 -
cost / benefit basis Strategy - vision Review
Procurement Speed to fulfill
A2 - -
decisions po requirements
Marketing
A3 Cost/Price targets - -
strategy
Ordering / Bill of
Budget Synergy
A4 Materials - -
confirmation, synergy in forecasts
Schedules
Quality review
Quality feedback Quality standards
A5 information -
Quality review as per marketing
sharing on market
After-market
Ordering / Matl Administration
A6 support, network -
reqiuremnt plan order management
speed to market
response Synergy/information Dealer training,
Negotiation, Purchase
A7 - sharing , dealer service
Order - gross level
performance review improvement
Policy adherence,
Synergy, information Policy adherence
A8 - alignment with
sharing, ordering alignment
marketing objective
P1 P2 P3 P4
Figure 6.20
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41. c. Process - Learning
Binary (figure – 6.21)
P1 1 1 1 0 1
P2 1 1 1 1 1
P3 1 1 1 1 0
P4 1 1 1 1 1
L1* L2* L3* L4* L5*
Figure – 6.21
Interpretive (figure – 6.22)
Crisis response Procurement Advance
P1 strategy policy development PO
- Guidelines
Customer Accuracy Feedback
P2 Satisfaction
Strategic advantage
in forecast - KRA
Dealer alignment
and learning
Safety Advance Ordering
Advance order,
P3 compliance - risk Response Targets Inventory policy
synergy
-
reduction framework
Inventory &
Integration Improved Market Share,
P4 Reliable services Ordering policies,
for forecasting Inventory & systems Feedback, Learning
aligned targets
L1* L2* L3* L4* L5*
Figure – 6.22
d. Learnings – Suggested Actions
Binary (figure – 6.23)
L1* 1 1 1 1 1
L2* 1 1 1 1 1
L3* 1 1 1 1 1
L4* 1 1 1 1 1
L5* 1 1 1 1 1
A1* A2* A3* A4* A5*
Figure – 6.23
41 | P a g e

42. Interpretive (figure – 6.24)
Development
L1* Synergy Support
& Support
Support Support
Influence, Influence,
L2* Feedback & Feedback & Synergy, influence Support Support
learning Learning
Continuity, risk Improved Synergy, Feedback
L3* reduction Response
Synergy, influence
Feedback & support
Support
Continuity, risk Synergy reduction in
L4* reduction
Support
required
Support
response
time
Feedback & Feedback & Feedback & Feedback & Feedback &
L5* Learning Learning Learning Learning Learning
A1* A2* A3* A4* A5*
Figure – 6.24
e. Actions – Performance
Binary (figure – 6.25)
A1* 1 0 1
A2* 1 1 1
A3* 1 1 1
A4* 1 1 1
External
A5* 1 1 1
P1* P2* P3*
Figure – 6.25
42 | P a g e

43. Interpretive (figure – 6.26)
Support &
A1* Influence
- Support
Support &
A2* Influence
Improve Support
Support & Influence
A3* Influence decision
Influence
Support,
Support , Feedback Feedback
A4* & Learning & Learning
feedback
& Learning
External
Support,
Support , Feedback Feedback
A5* & Learning & Learning
feedback
& Learning
P1* P2* P3*
Figure – 6.26
f. Process – Performance
Binary & Interpretive (Figure – 6.27)
Contribute
P1 Synergize
& Support
- P1 1 1 0
Build-in
P2 & support
- Support P2 1 0 1
Support by
Support
P3 Support reducing
& Influence P3 1 1 1
inventory
Support &
P4 Support -
Influence P4 1 0 1
P1* P2* P3* P1* P2* P3*
Figure -6.27
g. Actors – Performance
Binary & Interpretive (Figure – 6.28)
Contribute & Contribute& Contribute & Set
A1 Objective setting Decide Objectives
A1 1 1 1
A2 Contribute Decide - A2 1 1 0
A3 Contribute - monitor objectives A3 1 0 1
A4 Contribute - - A4 1 0 0
Feedback &
A5 Contribute
Learning
- A5 1 1 0
A6 Contribute Support monitor objectives A6 1 1 1
A7 Contribute - monitor objectives A7 1 0 1
monitor & support
A8 Contribute -
objectives
A8 1 0 1
P1* P2* P3* P1* P2* P3*
Figure – 6.28
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