In order to improve the exchange between organizations and clients, it is essential to adopt the Marketing approach in decision-making processes, which includes not only a philosophy of action, but also the use of a set of tools that can facilitate said process.
Marketing Engineering is a new conception to focus Marketing decisions, where both the experience and knowledge of the decision makers are combined, as well as the relevant information that the organization has, through the use of traditional mathematical tools.
This work shows a case study where the aforementioned conception was used: the modeling of a Marketing decision-making process that involves two organizations belonging to the Cuban consumer goods marketing sector.
The advantages are explored, and the usefulness of adopting Marketing Engineering as support for this type of decision is demonstrated through ex-post validation.
Introduction
Decision-making, understood as “the process of identifying and selecting actions to deal with a problem or to take advantage of an opportunity”, is an inseparable function in managerial work. Mintzberg, in her research on administrative roles, includes the role of decision maker as one of the three fundamental roles that the manager plays in the organization.
Decision-making runs through the entire organization from strategic levels to operational levels, and according to the level at which the decision is made, its complexity varies and therefore, its ability to produce the desired results and side effects. more convenient.
Operational decisions are classified as structured decisions, since the decision problem is similar on all occasions. However, strategic decisions are classified as unstructured decisions, because the problem or decision opportunity varies from one occasion to another, so a decision is not valid at all times.
Strategic decisions in an organization can be very varied. In 1976 Mintzberg presented the results of a field study carried out in several companies for more than two years in which he identified 25 strategic decision processes, which were grouped into 7 types of strategic decision configurations, one of them being the related with marketing.
Marketing decisions, specifically those related to market orientation, should be considered the starting point in the development of an organization's Strategy, as they will define the success or failure of said strategy before its clients.
On the other hand, the Marketing process comprises “… the analysis of Marketing opportunities, the search and selection of the target audience and positioning of the offer, the design of strategies, the planning of programs and the organization, management and control of the effort Marketing ”, which shows the strategic nature of the decisions associated with it.
Maier recommends that in order to estimate the effectiveness of a decision, it is necessary to consider an objective and a subjective dimension of the same: the objective or impersonal quality of the decision, which depends on the information available; and the acceptance or impression that the decision makes on the people who must implement it.
On the other hand, the Marketing approach is also a good point of reference that allows evaluating the effectiveness of a strategic Marketing decision, since it must allow, simultaneously, the achievement of organizational objectives; the satisfaction of the needs, desires and demands of the market; and superior execution to the competition.
Therefore, the integration of these two perspectives allows evaluating as an effective strategic marketing decision that which:
- Its result satisfies the needs, desires and demands of the market, allows the achievement of the organization's objectives, takes into account the strategic marketing decisions of the competition, is based on objective information, and enjoys the acceptance of decision makers.
However, strategic marketing decision making can be executed according to five possible methods described by Michel de Chollet through a continuum:
- Subjective or egocentric method: consists of unconsciously projecting one's own motivations and perceptions, transferring them to the market for free. Intuitive or allocentric method: abstracting from the ego, consists of imagining what the market wants, intuitively sensing market expectations and complying with them. Objective method based on market studies: decisions are made based on what the decision maker knows, objectively, thanks to their market studies Experimental method: it is supported by laboratory tests or pilot tests by directly operating on a sample representative of the market.Model-based method: it is supported by mathematical models where the possible results of a decision are projected.
The first two methods do not favor effective strategic marketing decision-making, because although they enjoy the acceptance of the decision maker, they are not based on objective information, so the scope of organizational results cannot be guaranteed in their whole.
In the remaining three methods, objective information gradually increases, so that market satisfaction can be achieved by taking into account the actions of the competition. In this way, the results of the organization are maximized. However, the acceptance of decision makers by these methods is lower, due to their complexity and, sometimes, to the costs involved in their application.
In this work, the advantages of the method based on models, currently called: Marketing Engineering, will be analyzed through a case study.
Marketing Engineering. Background and main concepts.
A decision model can be defined as "… a stylized representation of reality that is easier to explore and work for a specific purpose, than reality itself."
Models serve managerial decision making in the following senses: “develop and understand the decision environment; provide a basis for the measurement of important variables and their relationships; transform data into useful and meaningful information; predict changes in the environment and the consequences of alternative courses of action; control the activities of the organization; make decisions and establish policies ”.
The development of a decision model incorporates a specific statement of purpose, is based on assumptions, contains variables, and establishes the relationships of interest between variables.
The process of modeling a decision consists of the following stages: (1) Identification of the relevant variables; (2) Formulation of functional relationships; (3) Definition of an objective function and (4) Implementation of the decision model.
Mathematical modeling, contemplated by Operations Research, was applied in the management area after World War II, due to the potential of tools that could be extrapolated from the area of war to the sphere of management.
The application of mathematical models to organizational management was greatly favored with the emergence of computers, which greatly facilitated the performance of mathematical calculations in a faster way and with less probability of error.
The issue of mathematical models as support for managerial decision-making has been much discussed since the middle of the last century. Sometimes it was thought that models and computers could replace the human being in decision-making, which was evidenced in the area of Information Systems by the emergence of the term “Decision-Making Systems”.
However, so far the machine has not surpassed the human being in this process, so the term was adjusted to what is currently known as "Decision Support Systems", which reflects its value real: support for decision making.
The area of strategic decision-making in Marketing was one of the most benefited and that most quickly took over the technological advance and mathematical modeling.
In 1966 Kotler made the first description of how Marketing managers could make use of the power of electronic computers to support Marketing decision making, through what he called: “Marketing Information and Analysis Center” (MIAC).
Kotler conceived the MIAC as an “… organizational unit that will function as the central nerve of Marketing for the company, which will not only provide instant information to satisfy the various needs of executives, but also develop all kinds of analytical and decision aids for executives, starting from forecasting computer programs, to complex simulations of the company's markets. MIAC is designed to meet all of the planning, implementation and control needs of a modern marketing executive. ”
Since then and up to the present, numerous computerized mathematical models have been proposed to facilitate strategic marketing decision-making. The review of specialized publications in Marketing such as the Journal of Marketing Research and Marketing Management, both of the American Marketing Association, evidence this approach with the abundance of numerous articles dedicated to the subject.
The models used in making strategic Marketing decisions can be classified as follows:
According to the Objective:
- Descriptive Models: Markov Model; Queuing model Decision models: Differential calculus; Mathematical programming; Statistical decision theory; Games theory
According to the Technique Used:
- Verbal ModelsGraphic Models: Model of logical flows; Critical path model; Causal model; Decision tree model; Functional relationship model; Systems model with feed-back. Mathematical Models: Linear and non-linear models; Static and dynamic models; Deterministic and stochastic models.
Such has been the development achieved in the sphere of the application of mathematical modeling as a support for strategic marketing decision-making, that in 1997 Lilien and Rangaswamy coined the term Marketing Engineering to the discipline that studies the "use of mathematical decision models to support the transformation of objective and subjective information from the Marketing environment into Marketing decisions and their implementation. "
These authors, aware of the limitations of mathematical models with regard to the acceptance of decision makers, argue that Marketing engineering is based on the combination of conceptual Marketing, the mental models of decision makers or their experience, and mathematical models.
In this way, the application of Marketing Engineering to strategic Marketing decision-making allows increasing the effectiveness of these Marketing decisions, satisfying the five criteria mentioned in the introduction of this work.
Case Study in the Cuban Consumer Goods Marketing Sector.
Research Object
The object of this investigation was constituted by two commercial organizations based in Cuban territory: a wholesale company (hereinafter: the wholesaler), and a retail company (hereinafter, the retailer), between which there are purchase relationships - sale of consumer goods.
Problem situation
By carrying out a diagnosis of the informational processes of Marketing and decisions of the wholesaler, it was possible to know the existence of several problems in the strategic decision-making processes of Marketing, one of which is related to the negotiation of the Offer Commercial for Mixed Order of Products.
The fundamental decisions associated with this process are:
- What will be the product mix proposed to the retailer (variety and quantity)? What will be the price of the products that will be offered to the retailer? What will be the packaging to be used? What delivery conditions will be offered to the retailer (concepts included in the price, place of delivery, delivery time, transportation and insurance)? What services will be offered to the retailer? What payment options will be offered to the retailer?
In Figure 1 it is observed that the process tends to be repeated several times due to disagreement between the parties regarding the product mix.
The product mix, to be made under a Marketing approach, must take into account the end customer and the consumer, the need to optimize the use of the retailer's budget as well as the amount of products to be included in the order, the prices competitive in the market, and the profitability objectives of the wholesaler.
Therefore, achieving the satisfaction of the expectations of all the parties, sometimes greatly delays the process due to negotiations and consecutive renegotiations of the Commercial Offer, and finally, does not lead to decisions whose consequences favor all those involved.
Figure 1. Negotiation Process of the Commercial Offer. Source: self made
For all the above, (after the diagnosis) the study consisted of the design and validation of a support model for this strategic Marketing decision for the wholesaler that allows meeting the expectations of all parties involved and minimizing time execution of the process and its associated decisions.
Research techniques used
The research techniques used in the study were the bibliographic analysis, the Marketing Information Systems Audit based on the McLeod, Li and Rogers guide, the survey, the interview, the diagnosis of information needs, the flow diagrams of information, linear programming and cost-benefit analysis.
Model Design
Starting from the decision problem of this study, it was found that the use of a linear mathematical decision model was adequate to the decision requirements, since this technique allows defining an objective function for the wholesale company, subject to the restrictions of the customers and consumers, those of the retailer and those of the wholesaler.
Unquestionably, according to the Marketing approach, the wholesaler's main objective with this Marketing decision is to obtain the maximum profit from the transaction. Therefore, the objective function of the model is a profit maximization function:
Max Z = B1X1 + B2X2 +… + BnXn
where:
B = profit; X = quantity of product
B1 = PV1 - PC1
PV = sale price; PC = cost price
Second, the correspondence of the model to the Marketing approach is achieved through the establishment of the model's restrictions, which respond, in conjunction, to the profitability criteria of the wholesaler and the expectations of the retailer and the end customer. The restrictions are listed below.
1. Retailer budget constraint:
PV1X1 + PV2X2 +… + PVnXn ≤ A
where:
A = budget available from the retailer for the operation
The generality of mixed sales responds to a budget assigned by the top management of the retailer for the purchase. This restriction seeks that the total value of the purchase is less than or equal to the budget that the retailer has assigned.
2. Restriction of maximum quantities of the total order:
Y1X1 + Y2X2 +… + YnXn ≤ D
where:
Y = cubic capacity of the package; D = total cubic capacity of the order
Another generality of mixed orders is that, in addition to having to adjust to a budget, the retailer expects to acquire a specific quantity of products referred, generally to a container with a cubic capacity oscillating between 20 ”; 40 ”and 40” HQ. Therefore, the objective of this restriction is that the sum of the cubic capacity of all the packages to be purchased corresponds to the cubic capacity of the container that the retailer wants.
3. Maximum quantity restrictions per product that the retailer accepts:
X1 ≤ B
where:
B = maximum quantity that the retailer is willing to buy of the product
This restriction, together with restriction number 5, seeks to establish the range of merchandise that the retailer knows that it has the capacity to sell, according to its knowledge of the needs, desires and demands of the end customer and the consumer, and between which could oscillate the order, being this the one of the maximum quantities.
If market criteria are not taken into account when drawing up this restriction, stock of unwanted merchandise may be generated in the retailer's warehouse.
4. Restriction of profitability that the wholesaler seeks:
PC1X1 + PC2X2 +… + PCnXn ≤ E
where:
E = maximum value that the wholesaler is willing to pay for the purchase of products to be sold
E = A / (1 + minimum desired profit margin).
By means of this restriction, the wholesaler establishes the minimum profitability he wishes to obtain from the total transaction, which is independent of the profitability that each product offers. This is because the establishment of the sale price per product does not have to have a standard profit margin. This particular topic will be taken up later.
5. Wholesaler Minimum Order Quantity Restrictions:
X1 ≥ C
where:
C = minimum order quantity that the wholesaler can market
By means of this restriction, the wholesaler establishes the minimum for products that the organization can sell, and this is in direct relation to the minimum order quantities that its suppliers offer and the combinations of orders that can be made at the same time.
Assumptions and requirements of the model for correct support to Marketing decision making:
- The retailer must have clarity in the relationship that exists between the budget assigned to him and the total quantity of the order (type of container) that can be purchased with said budget. The retailer has the obligation to know the quantities of products that his market is capable of. to assimilate and declare it to the wholesaler, so that the model proposes the appropriate proportions that maximize both the expectations of the retailer and those of the wholesaler.However, the model proposes an amount that the retailer does not consider adequate, and as long as this is higher than the minimum of the wholesaler, the retailer can agree with the wholesaler to set a specific quantity for the product as an additional restriction, which is a good model.The wholesaler must be clear from the beginning of the minimum profitability that he is willing to obtain with the transaction, assessing the risk of the same and the conditions of payment, delivery, dates, etc. It is essential to have a close wholesaler-supplier relationship to know exactly the cost prices, the minimum quantities, the pieces per package, and the minimum orders, without which the physical preparation of the order may not correspond to the output of the model and therefore, with the contract accepted by the retailer The wholesaler can get closer to the marketing approach, through a specific knowledge by product of the competitor's prices, which allows them to set prices, sometimes more competitive for them or more suitable for the retail and the market;This also depends on the selection of suppliers and their purchasing management. Similarly, the wholesaler must seek to know the commercial margin applied by competitors to the specific market to get closer to the marketing approach.
Application process of the model once the request or order is received from the retailer, following a Marketing approach:
- Determine the optimal price per product for the wholesale market, taking into account the offer prices of the competition and their purchase prices Determine the optimal commercial margin of the transaction, taking into account the objectives of the organization and the commercial margins with that the competition works. Request information from the retailer regarding the amount of the budget assigned to it, the type of container that it expects to buy with said budget and the maximum quantities that its market can accept per product. Once you have the above information you can Run the model. Once the model has been obtained, the commercial offer can be formed and sent to the retailer. If the retailer's answer is yes, proceed to the next step in the negotiation.If the answer is negative and the retailer has expressed the desired quantities, it must be assessed whether they are contemplated within the slack offered by the model output, so a decision can be made without the need to modify the output. Otherwise, the retailer's criteria must be added as an additional restriction and the model run again, which would take again to step 5.
Model validation
The validation of the model was carried out taking into account the Marketing criteria of the retailer and the profitability of the wholesaler. For this, an ex post analysis was carried out, taking as the unit of analysis an invoice corresponding to a purchase - sale between both organizations, carried out under the problematic conditions prior to the design of the model, and in which sufficient time has elapsed (1,5 years) to assess consumer satisfaction and the retailer's inventory levels, among other aspects.
We proceeded to assess, for said purchase - sale, what would have been the maximum levels of product that the market would have accepted, taking into account the level of turnover of the real inventories of said transaction and the sales projections up to that date of the retailer as well as the goods for which it would have been a better decision not to acquire them.
In the case of the wholesaler, the minimum order levels for the date of the transaction were taken into account, as well as the same initial profitability criterion, so that the comparison could be made as real as possible.
It is necessary to clarify the appropriateness of the ex post analysis with respect to an ex ante analysis. The first has the advantage of allowing the real decision to be compared with the ideal decision (model proposal). However, its fundamental disadvantage is that the ideal decision cannot be evaluated as it has never taken place. However, an ex ante analysis would not allow the comparison between both decisions, since the wrong decision would not take place.
The model was run using Microsoft Office Excel 2007 as a computing tool, specifically the Solver application, developed for solving mathematical problems by Leon Lasdon (University of Texas at Austin) and Alan Waren (Cleveland State University), using a method of solving Linear problems developed by John Watson and Dan Fylstra of Frontline Systems, Inc.
The advantages of using this software is that the organization did not have to incur any additional cost for this concept, since it had this program installed on its machines. In addition, the application is very user-friendly and no programming knowledge is required for its use.
The computer equipment used to run the model was a microcomputer with a 3.0 GHz AMD Sempron ™ microprocessor and 480 MB of RAM. The size of the model in memory was 233 KB.
The results obtained in the validation of the model, through the cost-benefit analysis are shown in the following table 1 and are discussed below.
Table 1. Cost-Benefit Analysis of the application of the model.
| Concept | Buy - Real Sale | Buy - Ideal Sale (modeling) |
| Retailer's Budget | $ 75,000.00 | $ 75,000.00 |
| Allowable Cubic Capacity 40 ″ HQ | 68,000 m3 | 68,000 m3 |
| Total cubic capacity | 65,034 m3 | 66,826 m3 |
| Total Packages | 725 | 744 |
| Amount of Cost of Goods | $ 38,842.58 | $ 37,246.41 |
| Sale Amount of the Goods | USD 74,390.45 | USD 69,661.28 |
| Profit for the Transaction | $ 35,547.86 | $ 32,414.88 |
| Loss of Profit by modeling | $ 3,132.99 | |
| Loss due to application of Credit Note | $ 4,022.39 | |
| Net saving per modeling | $ 889.40 |
Source: Author's elaboration.
As can be seen, for the same level of the retailer's budget, the model allowed to increase the use of the purchasing capacity both due to the cubic capacity used, as well as the number of possible packages to buy.
The model yielded, taking into account the market restrictions, the budget of the retailer and those of the wholesaler, lower amounts, both for the purchase and for the sale, in such a way that the actual purchase took more advantage of the retailer's budget. For this reason, the profitability for the wholesaler decreased by $ 3,132.99 using the model.
However, it is important to note that the actual purchase was subject to a Wholesaler Credit Note for Slow Turnover in the retailer's warehouses for USD 4,022.39. Regardless of the financial value that this concept contains, it is necessary to recognize the implications that the Slow Rotation of products brings to the Retailer and the end customer and the consumer: the products on the shelf in the store do not meet the customer's expectations, this causes that the products do not they rotate in the warehouse and therefore occupy a space that cannot be used for new products; non-sale and non-rotation imply financial expenses to the retailer and, finally, the retailer transfers part of its loss to the wholesaler through the application of the Credit Note.
Because the model includes in its restrictions the criteria of the end customer and the consumer to whom the products are directed and the value itself and the products for which the Credit Note was applied, it does not have to expose itself to the application of this loss to which the actual purchase was made, which means savings for the ideal purchase.
In this way, when the loss due to the decrease in amounts of the ideal purchase is compared with the savings due to the non-application of the Credit Note, the second exceeds the first and the final balance of the application of the model becomes a wholesaler savings of $ 889.40 and assumed higher retailer, end customer, and consumer satisfaction.
Implications of applying the model
The application of the model eliminates the intuitive conformation of the Commercial Offer for Mixed Order of Products; allows linking both the wholesaler's objectives and the expectations of the retailer and the end customer and consumer; It allows saving time and human and financial resources for all the parties involved, making the strategic decision-making process of Marketing more effective.
Although the model was applied for the conformation of the order from the point of view of the wholesaler, that is to say, the seller; the model is easily and effectively applicable from the point of view of the retailer, that is, the buyer, for the realization of requests for a Mixed Product Order to its wholesale suppliers.
Conclusions and Future Research Directions
- Given the complexity of strategic Marketing decision making, those in charge of these processes would do well to take Marketing Engineering into account to anticipate, identify and respond creatively to the needs, desires and demands of the market, ensuring the achievement of their financial objectives The application of Marketing Engineering requires a deep knowledge of the problematic situation of Marketing decision facing the organization, and specific knowledge in the different methods and modeling techniques available to the strategic decision maker of Marketing.Although sometimes the application of a Marketing decision model requires specialized computer tools,managers can make use of the tools they already have in order to exploit them to the maximum and profitably.The application of Marketing Engineering requires the existence of Marketing Information Systems that provide useful and high-quality information for food of the mathematical models on which this discipline is based. Future research is required in the Cuban context that allow us to know the real possibilities of application of Marketing Engineering. Similarly, it is necessary to study the state of Marketing Information Systems and the use of relevant information for strategic marketing decision making.The application of Marketing Engineering requires the existence of Marketing Information Systems that provide useful and high-quality information to feed the mathematical models on which this discipline is based. Future research is required in the Cuban context that allow to know the real possibilities of application of Marketing Engineering. Similarly, it is necessary to study the state of Marketing Information Systems and the use of relevant information for making strategic Marketing decisions.The application of Marketing Engineering requires the existence of Marketing Information Systems that provide useful and high-quality information to feed the mathematical models on which this discipline is based. Future research is required in the Cuban context that allow to know the real possibilities of application of Marketing Engineering. Likewise, it is necessary to study the state of Marketing Information Systems and the use of relevant information for making strategic Marketing decisions.Likewise, it is necessary to study the state of Marketing Information Systems and the use of relevant information for making strategic Marketing decisions.Likewise, it is necessary to study the state of Marketing Information Systems and the use of relevant information for making strategic Marketing decisions.
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