The use of International Operational management

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Omya Hustadmarmor is mainly producing calcium carbonate slurry situated on west coast in Norway, which supplies the filler and coating pigment to the papermaking companies. Omya Hustadmarmor group is the main group and its major stakeholder is Omya Group. Company transport its slurry variants from plants to paper mills, then store them in UK, Sweden, Germany, Finland and Netherland based 10 first tier tank farms by shipments. The range of chemical tank vessel is from 2400 to 16000 metric tons.

Company is facing some problems in expansion of its business with other potential countries, especially the company is expecting to do business with North America but company will face the on time supply and routing issues. To overcome on these issues the company must take the consultation of their key people in organisation, rather than to use the large vessel to resolve the problem, but it will limit the available space for storage. The only solution of this problem to involve the key people who have the power to affect the strategic planning and decisions in the organisation, which solve the transportation and routing issues. For the identification of key people Power Interest Grid will be used, so;

Power-Interest Grid:

"The grid usually shows those who have both the interest and power to ensure success or failure". (Narayanan and Armstrong, 2005, p.268)

It is very obvious from the above statement that the Power Interest Grid gives clear idea about the identification of stakeholders in organisation. Power Interest Grid is the main resource which identifies the key people and issues/problems with best solutions, and also influences the decisions and management.

Subject

Players

Crowd

Strategy Context Setters

Interest Stakeholders

in strategy

making

organisation Unaffected

Bystanders Actors

Source: Eden C. and Ackermann F. (1998, p.130)

Subjects:

Bryson (2004) stated that the people in organisation who have high interest in organisational goals and actions i.e. employees, but have low power to influence the decisions and other aspects.

It is clear from the above statement of Bryson, that the group who have less power to affect the decision process in an organisation are most likely employees, having high interest. To apply this theory on the Omya Hustadmarmor employees, it is evident that the employees of Omya Hustadmarmor always trying to do their job in better way, to secure their employment, but on the other hand they are more interested in smooth routing and other organisational objectives but having less power to implement the recommendation . The another shareholder (AUR) is a shipping company, who has less power to affect the company decision making process, objectives and routing issue's. It is also obvious in case study on page 24 that when the shipping company (AUR) received any demand for spot market activity, they contact the group who are making the planes for the distribution, to know whether their calendar/schedule is flexible or not. It is clear from the case study of Omya Hustadmarmor that the shipping company (AUR) is managing and responsible for the transportation of vessels on short period notice, it gives an idea that AUR is

giving more importance to Omya Hustadmarmor, and clearly shows that Omya Hustadmarmor is the backbone of shipping company (AUR). From the above discussion in light of case study that AUR have low power to influence the company decision making process but have more interest in company strategic issues. Also influence its niche market revenues.

Crowd:

Bryson (2004, p.112) states that, "It shows the people who have low interest and low power in an organisational problem and actions to solve it".

Supplier of raw material (Marble) and the ready slurries would come under subjects as they have low interest and low power to influence Company's decision and strategies. As long as they are providing services to the Omya group, they have concerns with the company's policy but they cannot change their policy. On the other side, when they will stop providing services to the company there will be no interest at all.

Strategy Context Setters:

Bryson (2004) stated that the people who have low interest but high power in organisation.

Strategy context setters are the important part of power interest grid, which play fundamental role in the accomplishment of every organisation. It is clear from the above theory that the planners will be counting in this category. In the case study of Omya Hustadmarmor it is evident that whenever the planner makes the plans for production, distribution etc. they must consider all the issues to avoid the upcoming problems to the organisation. In the case study of Omya Hustadmarmor it is clear that planners have the power to decide for the transportation to utilize the capacity of each vessel, and also to ensure that the inventory reach in good condition, and also the planners have to plan about the material should arrive on time to avoid breakage in production. Omya group is the major shareholder of Omya Hustadmarmor, who has more power than interest, which can influence the decision at any stage, but having less interest in routing, which is solved by company management.

Players:

Omya Hustadmarmor case study further highlights and gives a clear idea about the players, who have high interest and high power. Who are playing a vital role and have the power to influence the decision in an organisation, which also influence the strategic success or failure in an organisation. In the power interest grid players are the most important part of this section. The above theory accurately fit on the sales department, they have the power to affect the decision, and also are the key indicators for solution of production and routing issues. Company management can take few steps towards routing problems, which leads company to its goals. From the power and interest level of the players it is evident that they have the authority to solve the existing problems. It is more obvious that sales department is the key department for the forecasting of sale, and also gives an idea to the production department to produce the right quantity completely depends on correct sales forecast. If there is inaccuracy in forecasting lot of problems will face by departments in a company, like stock out, delays in production and distribution.

Cognitive Map:

Customer Satisfaction

Improved Productivity Route and Transport

Low cost Smooth Distribution Low running cost

Improved competence

Management of stored inventories

Better communication

Management of production Better level of service combination among departments

Administration Enhanced Sales forecast

Effective Computerised Planning system

(ECPS)

Sales Forecast Management of inventories Transportation Production

Accurate sales Forecast follow the stock schedule

Raw material on time delivery

Correct determination enhance figure of suppliers

of industry trend

Substitute suppliers improved storage capability

Weather Prediction

Increase supplies

Distribution Use of large vessels

Daily accumulation counting on time finishing of

Slurry from manufacture site

Order Forecasting Augmented Number of Deliveries

Trained Staff

Explanation:

The above cognitive map is entirely consisting on the five main strategic issues along with the best possible actions towards achieving the goals. Cognitive map clearly shows that how the goals/objectives are achieved and it gives outcomes. These goals, actions are linked with one another with arrows.

In Cognitive map it evident that sales forecast is the main strategic issue and can be solved by five possible options. It can be solved by the accurate sales forecast, for this it is compulsory to consider the accurate determination of industry trend. True weather forecast and trained staff (employees) will give accurate result for the forecast sale and accurate determination of industry trend. It is clear from the above discussed theories that above options are the best solution of sales forecast issues to achieve the objectives.

The next issue is stock inventory management, which can be solved by direct and indirect actions. The schedule stock is giving an idea about the management of stock and substitute suppliers give a clear idea about schedule stock (inventory) and indirectly to the stock management and enhanced numbers of suppliers. Daily stock counting give a direct lead to stock inventory management and other one the enhanced numbers of suppliers.

The next issue is transportation, which is resolved by the two possible actions. The use of large vessels and increased number of deliveries. Because the case study of company clearly says, that large vessels are cost effective than small vessels. And the increased number of deliveries will be effective for the company stock, because company faced stock out as mentioned in case study.

The second last issue is production, which can be solved by three possible actions. The on time delivery of raw material, increased capacity of storage and on time carrying out of slurry from the site will increase the production.

Last strategic issue is distribution, identified in the cognitive map, can be solving by two major actions. First of all to forecast the accurate demand leads best possible

distribution. And the second action which is indirect but important to forecast accurate demand is trained staff (labour).

The above strategic issues and actions leads to the combined goals of a successful computerised planning, cognitive map is playing a vital role in the identification of main issues and provide the best possible options for the solution of these issues.

To discussed the strategic issues more in detail, one of the issue e.g. sales forecast, which is briefly discussed above with its four option of solution like correct sales forecast, correct weather forecast, accurate determination of industry trend and expert and trained staff.

Accurate sales forecast avoid the stock out situation in company, as it is quite clear that correct sale forecast is playing important role in the management of forecast sales issues, because false forecast result in stock out due to unexpected sales. It could be gained by critical check on weather and industry trend, and the most evident option is trained staff who can forecast correctly about the above discussed points.

Cognitive map shows that when the objectives of the effective computerised planning system are implemented it will give the following results.

Effective computerised planning system (ECPS) will guide to incorporate among the departments, because the computerised system gives an understanding to people to keep in touch all time. This incorporation is beat solution of communication, by this people can deal with the day to day issues with best possible solutions, in result leads to increased productivity. Also the effective computerised planning system provides understanding about the management of production which indicates the relationship of stock inventory management, is valuable, on time distribution and satisfied customer. Trained staff is part of administration which will also increased the administration cost. By the implementation of effective computerised planning system it will solve the transportation problem.

Skilled and trained staff is vital for utilisation and implementation which is clearly indicated by efficient computerised system.

Effective computerised planning system solves the issue of incorporation among all departments, stock inventory, production and distribution which affect/decreased the running cost. Which in result reduce running cost, save time and avoid waste of stock, Also it guides to correct sales forecast and improved level of service. It is now more accurate to say that effective computerised planning system provides broad extent of improved and accurate forecasting.

Q.3

The problem has been identified in the given case study that there are two products (heavy slurry and very heavy slurry) need to be delivered on three different destinations namely Germany, Finland and Sweden. It needs to be decided that how much slurry can be distributed to those destinations in two scheduled days.

In other words allocation of heavy slurry and very heavy slurry's capacity is required that can fulfil the demand of Germany, Finland and Sweden in two scheduled days. It is also required that, capacity should be allocated in a way that can minimize the distribution cost while considering the demand of those destination in those specified two scheduled days.

Therefore, linier programming will be used for allocation of specific amount of heavy and very heavy slurry to be sent on each destination. The total required demand of heavy slurry and very heavy slurry over two days is 60,000 kilo and 65,000 kilo respectively.

Demand of three destinations is;

Countries

Demand

Heavy Slurry (Kilo)

Very Heavy Slurry (Kilo)

Germany

20,000

30,000

Sweden

15,000

15,000

Finland

25,000

20,000

Total Demand

60,000

65,000

The table below shows the capacity allocation of the heavy and v. heavy slurry which can meet the required demand of three different destinations (by using linear programming). Additionally, given linier programming solution gave the scope to Omya Hustadmarmor to manage its slurry's distribution on two scheduled days with minimum cost. The result of linier programming has shown that, if the distribution (heavy and very heavy slurry) is managed as shown below will be cost effective.

Day 1

Kilo

Day 2

Kilo

Heavy Slurry to Germany

25,000

Very Heavy Slurry to Germany

25,000

Heavy Slurry to Sweden

20,000

Very Heavy Slurry to Sweden

10,000

Heavy Slurry to Finland

30,000

Very Heavy Slurry to Finland

15,000

Total

75,000

Total

50,000

The total distribution cost of heavy and very slurry

£197,500

As it has been discussed that it will be cost effective as linier programming helps to solve the problem by using cost minimization function. The result shows that it will cost £197,500 to Omya Hustadmarmor for the distribution of 125,000 kilo slurry.

It can be seen from above tables that linear programming has changed the quantity of heavy and v. heavy slurry distribution. It has been assumed that, supply of heavy slurry to Germany should be 20,000 kilo on day 1 and 30,000 kilo v. heavy slurry on day 2. By using the linear programming this quantity has been changed to 20,000 kilo of heavy slurry and 25,000 kilo of v. heavy slurry. It has also changed the quantities of slurries distribution to Sweden and Finland too.

The quantity of heavy slurry to Sweden is changed from 15,000 kilo to 20,000 on day 1 and v. heavy slurry from 15,000 to 10,000 kilo on day 2. On the other side, the quantity of heavy slurry to Finland is changed to 30,000 kilo from 25,000 and v. heavy slurry from 20,000 to 15,000 kilo.

Function (Involved in Linear programming):

There are three main functions involved in linear programming which are known as Decision variables, Objective function and Constraints. Therefore, to solve the distribution problem identified in the given case study six (6) decision variables in linear programming are involved. These decision variables gave the scope to identify the capacity allocation of slurry. These decision variables are as follow

Decision Variables

Heavy slurry to Germany

Very heavy Slurry to Germany

Heavy slurry to Sweden

Very heavy slurry to Sweden

Heavy slurry to Finland

Very heavy slurry to Finland

Objective Function:

The objective function of linear programming shows that what is need to be solved or needs to be done. It has been discussed earlier that the problem is to distribute the heavy and v. heavy slurry to three different destinations in two days. Additionally, the major problem is to be determined that how much heavy and v. Heavy slurry should be distributed to each destination on each day. Therefore, the objective function in this linear programming is to fulfil the (heavy and v. heavy slurry) demand of three destinations while keeping the cost minimum.

Constraints:

The formulation of problem in linear programming involves the function of constraints. There are two sorts of constraints used in it namely binding and not binding. The change in binding constraint changes the possible solution but on the other side, change in not binding constraint does not affect on the solutions. After having the solution one can change those binding constraints and can look for improved results.

There are six different constraints have been used in this linear programming are shown below and it is referred to see the details of binding and not binding constraints in appendix 1.

Heavy slurry to Germany

Very heavy Slurry to Germany

Heavy slurry to Sweden

Very heavy slurry to Sweden

Heavy slurry to Finland

Very heavy slurry to Finland

=>75000

=>50000

This model could be extended to find out best possible distribution plan if they are specified in real, as the requirement of slurries to be delivered has been assumed. So probably there will not be a realistic result as it is based on assumptions.

It has been discussed in the given case study that weather condition does affect on delivery timing. Therefore, it can be said that by considering weather condition the results could be different than it is. Additionally, the production capacity of slurries has not been considered in this linear programming but it has vital importance and can change the whole result.

As, the results show that 25,000 kilo heavy slurry should send to Germany on day 1 but if the production department is unable to produce it. So, it will affect all the decision made which are based on the linear programming. Therefore, it can be said that by adding weather conditions, production capabilities and accurate demand or requirement of slurries could help in the extension of the model and the results will be more realistic.

Q.4

Decision Support System (DSS):

There are many definitions available to define Decision support system but it is best defined by Kersten E. G. (2000, p.330) who explains that, " A Decision support system is an information system combining a range of technologies, such as database and modelling for complex planning and management task".

Today businesses are developing rapidly and the competition among them forces to perform at their best. It is necessary for any organisation to manage their operations in a way that can make them able to compete in the market. The above definition of DSS shows the importance of DSS that can perform vital role and help an organisation to manage its operations, database, planning and several management task. It can be defined as that it is a collection of different information system technologies. As it has been said that this is what can help an organisation's to plan future strategies, resolve their issues on daily basis and can make optimum decisions.

There are some major requirements defined by the author to implement decision support system to make an organisation able to utilise the benefits of it. By considering distribution planning issue of Omya Hustadmarmor to be resolved some of the key requirements are:

1: Collected data from Distribution department, forecasting department and market research.

2: compilation and configuration of data.

3: For evaluation of decision the suitable and correct data always play a vital role.

4: For the analysis of report and data, the monitoring tools should be strengthening.

Omya Hustadmarmor case study clearly mentioned that the storage capacity is limited in the company, and are affecting its production. So the planners at Omya Hustadmarmor should look to the complex issue of distribution, to the uncertainty faced to the production and storage in company. Company produces some products for which the consumer demands change time to time, and to forecast that uncertainty it needs more attention from the planners. Because the company has only one loading bay and time consumption on one quay is 5 to minutes, to avoid the above uncertainty they should avoid more than two vessels at one day. For the

operation of system in regards to identify the main characteristics, hypothesis about the system needs to be developed. The soft system methodology will be the best possible methodology for appropriate root definition.

Pidd , M.(1999) stated that root definition is an attempt to capture the real meaning of a system, will be useful for solution of problems, its situation. Root definition is a comprehensive explanation of a system, will be more acquainted with the solution of problems. In more detail of root definition the six components "CATWOE", it will be discussed for the planning of distribution.

Customer: According to Stahl G. R et al (p.95), "Customer, who benefits from the system or who is affected by the system". Pidd M. (1999, p.137) explains customers as "those are the immediate beneficiary or what the system does. It can be individuals, several people, group or groups".

Actors: According to the Checkland P (1999) that these groups provide the transformation to the customers.

Transformation: checkland P. stated that transformation is the process of beginning and finishing.

Weltanschauung: According to checkland P.(1999) that it gives more strength to the process of transformation, it makes the process of transformation more valuable.

Owner: According to the checkland P.(1999) that owner is to whom the the complete system is responsible to give answer.

Environment: According to the checkland P.(1999) that environment influence the process but cannot control the system.

Soft system methodology (SSM): According to Checkland P.(1999) that SSM is the a learning and development tool, because it develop models and it is not necessary to represent the real world, but using the system rules and principles which allow you to structure your thinking about the real world. The presented models it is not necessary to show both normative and descriptive, they may have both elements as well.

AUR shipping company production planner

Forecasting close communication and forecasting

DISTRIBUTION PLANNER

Critical route checking

Omya sales office administration

(Conceptual model)

Explanation: from the case study of Omya Hustadmarmor it is evident that the company faces the distribution problem in its networking, from the above conceptual model it is clear that distribution planning is mostly influenced any of the above elements missing.

The true forecasting and communication between the all departments helps to plan for the future production, when at the production Site Company have the enough storage of product there will be no uncertainty in demand and supply. It means that the distribution will not affect the production and produced objects will not stay longer in the storage, it leads to reduce the running cost.

The another important aspect of this model is the proper checking from the sales office on the production and shipment, and to plan ahead about the route for shipment of slurries, will reduce the cost of transportation, and it will be time consuming for the company and in that consume time company will do more transportation, distribution and production.

The administration at the company when direct indulge their self in decision making about the planning for production gained by the analysis of experienced staff, will beneficial for the company.

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