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Lectures Strategic Marketing Management
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Lectures - Strategic Marketing ManagementLecture 1 – Introduction
Marketing strategy is a thoughtful plan by a company to produce desired outcomes in the marketplace vis-a-vis customers,
channel members and competitors. Marketing strategy is an organization’s integrated pattern of decision that specify its crucial
choices concerning products, markets, marketing activities and marketing resources in the creation, communication, and/or delivery
of products that offer value to customers in exchanges with the organization and thereby enables the organization to achiever
specific objectives. Both definitions include that marketing strategy is about a plan/choice, it has to be coherent (integrated) and we
think about how we create value for the customers.
Your marketing strategy has to be unique, distinctive, coherent and dynamic. You must prevent that the marketing strategy is a
set of (uncoordinated) tactics, has similar characteristics or decisions as competing firms, or has a poor implementation of activities.
• Strategic marketing decisions are long-term holistic decisions concerning the future directions for the organizations. This
entails major resources commitments spread over long periods, result in a distinguishable competitive advantage, is
irreversible, entails trade-offs, and is made in context of other strategic decisions. Examples are a loyalty program or a
strategic partnership with another company.
• Tactical marketing decisions are short term (annual or quarterly) decisions to execute the strategic directions within the firm;
filling in the marketing mix of the individual product or brand to realize the company strategic goals
You should pay attention to the formation, implementation, content en process of the marketing decisions. It is important to include
inputs, environment (competition and market turbulence) and outputs.
Lecture 2 – Management Decision Making
1. Organizational learning & knowledge management
Nature of organizational knowledge
Organizational learning is the process of improving organizational actions through better knowledge and understanding or as the
outcome of such a process (Chadwick & Raver, 2015). Key concepts are:
1. Individual learnings vs organizational learning
Organizational knowledge is the accumulation of the knowledge bases of all the individuals within an organization and the
social knowledge embedded in the relationships between those individuals (Trott, 2005). Organizational learning assumes
individual learning, but individual learning is an insufficient condition for organizational learning – without sharing or
transferring the knowledge, the organization will not learn. It is more than the sum of the parts. It is also about exchanging and
sharing individual assumptions, models, knowledge across the organization at various levels: individual > group >
organization > inter organizational.
2. Explicit vs tacit knowledge
Firms formalize their explicit or ‘tangible’ knowledge through representations like e.g., manuals. Tacit knowledge has low
codifiability (= to what extent is it possible for the organization to structure knowledge into a set of identifiable rules and
relationships that can easily be communicated), is ‘know-how’ is ‘how things get done’, and often high complexity (science-
based). The transfer of tacit knowledge requires frequent social interaction, education, and training. It is difficult to transfer, but
therefore also difficult to imitate!
3. Single-loop learnings vs double-loop learning
Single-loop learning (adaptive learning) occurs within a set of recognized and unrecognized constraints (i.e., the learning
boundary) that reflect the organization’s assumptions about its environment and itself. This type of learning solves problems,
but ignores the question of why the problem arose in the first place.
Double-loop learning (generative learning) occurs when the organization is willing to question long-held assumptions about its
mission, customers, capabilities, or strategy. It uses feedback from past actions to question assumptions underlying current
views. A related example is students exam failure.
4. Measuring organizational learning
The organizational learning curve shows how much your costs are reduced, each time you double the output. This is quantity
* cost / unit, or Yt = a * Xtb, which is labour costs = labour hours for one unit * cumulative number of unitslearning rate
We can derive the progress ratio p from the estimate b (learning rate) in the learning curve equation (p = 2 b). This learning
curve can go down with training or automatization. Other outcome measures can be the number of patents, number of
complaints, service timelines, etc.
The learning process
Information…
1. Acquisition: formal market research, competitive intelligence, satisfaction surveys, etc.
, 2. Dissemination: formal (cross-functional teams, trainings, presentations etc) or informal (social interaction)
3. Shared interpretation: conflict resolution & information exchange by organizing formal meetings, discussing alternative options
4. Utilization: behavioural change
a. Conceptual (recognizing the importance of information, giving meaning to information, changing targets or routines,…)
b. Instrumental (direct use in production process or marketing-strategy activities: making, implementing or evaluating
marketing decisions)
Barriers & enablers to organizational learning
• Organizational culture & climate - How to organize your firm to foster organizational learning?
o Culture are deeply routed values and believes that drive organizational activities
o Climate are structures and processes that facilitate the achievement of the desired behaviour.
This needs to be complementary! Cultural values are the necessary foundation for organizational learning, e.g. market
orientation or entrepreneurship. Also, create a climate in which these cultural values can flourish: you need a facilitative
leader, adopt an organic organization form, decentralize strategic planning to foster creativity, and have compensation
systems and rewards
• Incentives and rewards to enhance organizational learning - How to compensate your employees to foster organizational
learning?
Individuals are the ‘prime movers’ of knowledge in an organization. Knowledge or expertise is the source of power to the
employee. They can be reluctant to share it with others. But, what incentives and rewards can foster knowledge sharing?
There are different knowledge sharing systems, e.g. Xerox engineers contribute their ideas and expertise to a database, Ernst
& Young emphasizes registering knowledge in databases, and McKinsey has person to person contacts.
Think about individual or group rewards? Monetary or other rewards? Immediate or delayed rewards? Structural (e.g., salary
raise, promotion) or one-time gratification/bonus? During or after learning? Etc.
How to choose? The reward should match knowledge sharing mechanism you want to foster (explicit knowledge: reward
registration in manual/database <> tacit knowledge: reward personal communication). Also, it should be clear for the recipient
what target outcome to achieve (reward for individual or group target; for own or others’ performance). There are some crude
guidelines:
Type of knowledge sharing to stimulate Suggested reward
Knowledge contribution to database Monetary individual rewards based on:
(only possible for explicit –not tacit knowledge) • Value of info to firm (e.g., R&D innovation)
e.g. Xerox engineers • How many employees use it (e.g., EY)
Knowledge sharing in social interactions Monetary group/team rewards such as profit
(to improve joint performance) sharing plans or employee stock ownership
e.g. Deloitte consultants
‘Communities of practice’ NO monetary rewards, but motivate people
(to help others improve…) intrinsically by:
e.g. university teachers, scientists, doctors • Organizational citizenship (e.g., proud to be a
doctor at the Erasmus MC)
• Create relationships with others (establish expert
image in the field)
• Achievement awards
• Tools that enable organizational learning - Can Marketing Management Support Systems facilitate organizational learning and
decision making?
Marketing Management Support Systems (MMSS) is NOT a data warehouse! Information is data that have been organized or
given structure – that is placed in context – and endowed with meaning. Software that helps in translating hard data into
meaningful information through summary statistics, equations, graphs, trends, etc. that may facilitate decision making
Use of plethora of marketing models. MMSS’s can help with problem recognition, avoid limitation of cognitive constraint,
model building, collecting/integrating/organizing/presenting knowledge, and selecting a problem-solving approach.
But, research shows that MMSS sometimes help, but sometimes also harm! Why? Wierenga and Van Bruggen (1997)
developed the ORAC model, which distinguishs between 4 different marketing problem-solving modes (MPSM):
o Optimizing (looking for optimal solution)
o Reasoning (using mental models)
o Analogizing (start from prior experience and solutions)
o Creating (think out of box)
Which decision mode is activated is function of: problem, decision environment, and the decision maker
Traditional MMSS are based on analytical optimization, whereas marketing decision making in practice often relies on
reasoning and analogizing. Optimization is preferred if much structured data is available for the
, problem; if decision environment is stable market; if decision maker is of analytical-cognitive kind. Some decisions are well-
suited for traditional (optimization-based) MMSS: sales force planning, media planning, shelf space allocation, sales
promotions planning. Some are not, depending on problem, decision environment, decision maker.
Other factors influencing the organizational learning, such as individual proficiency, social interactions, openness in
communication, trust, perception of knowledge, top management’s support, freedom vs control.
2. Rational decision making (weblecture)
Decision-making theory
Decision-making theory states that managers make rational decisions. It is an analytic and systematic approach to the study of
decision making. In the real market, at least risk involved (expressed by a probability). According to this theory, a good decision is
based on logic, uses (all) available information, considers all possible alternatives, and applies appropriate quantitative techniques.
There are six steps in decision making:
1. Define the problem
2. List the alternatives
3. Identify possible outcomes taking into account the ‘state of nature’
4. List the payoffs
5. Select a quantitative decision model
6. Apply the model to select a strategy
For example, if a firm wants to expend their product line, they can: construct large new plant, construct small new plant, or don’t
construct a new plant. This gives two possible states of nature with equal probability: favourable vs unfavourable markets. A
favourable market gives 200,000 profit for a large plant and 100,000 profit for a small plant. An unfavourable market gives a loss of
180,000 for a large plant and a loss of 20,000 for a small plant.
Alternative Favourable market (50%) Unfavourable market (50%)
Large new plant 200,000 - 180,000
Small new plant 100,000 - 20,000
Do nothing 0 0
We can calculate the Expected (Monetary) Value:
EMV(large plant) = (0.5 x $200,00) + (0.5 x $-180,000) = $10,000
EMV(small plant) = (0.5 x $100,00) + (0.5 x $-20,000) = $40,000 → So, they should go for this option
EMV(do nothing) = (0.5 x $0) + (0.5 x $0) = $0
Decision making under uncertainty
But, there is risk and uncertainty. There is a risk that the probability of each state of nature cannot be assessed reasonably well.
There is uncertainty, because managers cannot assess the probability of each state of nature.
Alternative Favourable market (α) Unfavourable market (1- α)
Large new plant 200,000 - 180,000
Small new plant 100,000 - 20,000
Do nothing 0 0
There are several possible decision criteria, based on α (coefficient of probability on the favourable state of nature):
• Maximax: if the managers take an optimistic view, they will only look at the favourable market and go for the large new plant.
• Maximin: if the managers take a pessimistic view, they will only look at the unfavourable market and do nothing.
• Criterion of realism: it is more realistic to look at the chance they assume one of the two markets will happen, e.g. with a α of
0.8, they will construct a large plant.
• Equally likely: there is assumed that both markets are equally likely to occur, so you will use α = 0.5 for both markets.
• Minimax regret: minimize ‘maximum opportunity loss’. This technique doesn’t need alpha and it can prevent managers to do
nothing to minimize risk. How much do you lose from not making a good or bad decision?
1. We start with determining the best/optimal decision per market: large new plant in favourable market (200,000) and do
nothing in an unfavourable market (0).
2. How much is lost for each strategy compared to the ‘best outcome’?
3. Determine maximum opportunity loss per strategy
4. We want to minimize the maximum opportunity loss, so we will go for a small new plant
Alternative Favourable market Unfavourable market Maximum opportunity loss
Large new plant 0 180,000 180,000
Small new plant 100,000 20,000 100,000
Do nothing 200,000 0 200,000
Game theory and marketing decision making
Game theory considers the impact of the strategies of competing firms on our own strategy outcome. Often, it is a zero sum game,
which means that if one firm is winning, the other firm is losing .For example, there are two firms, which can choose between radio
advertising or magazine advertising:
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