Assignment 2

Assignment

Within your analyses on the first - Data-driven decision-making aka data analytics and third - your choice of one from among

Decision support systems

Outsourcing to include offshoring, re-shoring, and next-shoring

Sustainable supply chain management- techniques, address the following:

Q1. What is the general purpose of the technique?

A1: The general purpose of linear programming technique is to identify best suitable decision variable so that we get the optimize objectives (e.g. least possible cost, max profit etc)Q2. How does or should this help operations in general?

A2: By using linear programming technique, we take the efforts of manually selecting decision variables. Also the results are optimized and hence, we get the maximum possible savings or least possible cost.

Q3. What are the limitations of the technique?

A3: The technique depends heavily on the given datas accuracy. If the data in real life is going to be slightly fuzzy, then the technique might not provide optimized solution. In other words, if the given schedule is followed as it is, only then we will get optimized costs.

Q4. What are the costs involved? What training is needed to use the technique? What else is needed?A4: It costs time to formulate and solve the problem on MS excel or any other spread sheet program.

The operator need training in using linear programming, basic computing skills and use of Spread sheet programs.

Apart from that, we would need accurate data to start with the model formulations.

Q5. At Acme Mexico City, what is the problem, opportunity, or challenge that this technique can address?

A5: In Acme Mexico City the problem is managing on flour service personals. Due to obvious reasons, cost need to be minimized, best services need to be given to customers, legal and human resource requirements too need to be followed and company policies to be followed as well.

The opportunity that this techniques can address is optimizing manpower scheduling and derive the minimum costs and hence maximum savings.

Q6. How will the technique help Acme Mexico City's operations? Why?

A6: The technique and its application gave a best solution of manpower planning across the day. It shows how many employees need to join when and when they should take their lunch/dinner breaks. Hence decision making process on the whole case is automated. Also, the provided decision by the techniques is guarantee to be the lowest cost solution. And hence there can be minimum cost of employees in following the given schedule. Q7.What would be the areas that present challenges in the approach (e.g., cost, personnel, training, culture, technology, management commitment, etc.?)A7: There are several challenges to derive the optimized cost structure as provided by the linear programming technique.

1. Personnel need to be trained well to fulfill each others positions and need to be flexible in their skill sets

2. The culture of the organization should be customer friendly and the whole process should be designed with customer as focus. Otherwise it will not be as impactful as it would be planned. Also to take lunch/dinner at designated time should be compatible with the organizational culture.

3. Management commitment comes for developing such solutions and then implementing it full heartedly. If the solution cannot be applied completely, the developers and decision makers will lose faith.Within your analysis on linear programming applied at Acme Mexico City, address the following:

1. What is the recommended low-cost (not necessarily the minimum cost) customer service employee daily assignment schedule?Ans: The solution is shown at the attached excel file. The brief of the manpower planning solution is as follows:

Full Time1st shift2nd shiftTotal

Joined111223

1st lunch6511

2nd lunch5712

Time7am-8am8am-9am9am-10am10am-1am11am-12n12n-1pm1pm-2pm2pm-3pm3pm-4pm4pm-5pm5pm-6pm6pm-7pm7pm-8pmTotal

PT join016860106782045

2. What are your underlying assumptions and any qualitative factors that you believe are involved?

Ans: The assumptions and qualitative factors are as follows: The schedule given will be exactly followed by all employees (no late coming-early going, no change in lunch/dinner breaks)

The requirements given would be exactly like this and there would be no changes in that during the day

All employees are equally capable and each can match capabilities of others

All employees skills are flexible enough to substitute for any other employees.3. How might non-typical days affect the schedule?

Ans: The solution provided assumes the demand for personal remains as given data. However, there can be some non-typical days (Sundays or holidays) where demand would be shifted across the day. And it is also possible that it cannot be predicted in real time. At such times, we cannot use the schedule created here. As it will not meet the demand of a non-typical day. For those days, a separate problem with correct demand data need to be used.Optionally, and for extra points to be determined by your section professor, provide a sensitivity analysis that shows how relaxation of the 50% constraint on the hours worked by part-time customer service employees might affect the daily personnel costs.

By relaxing the 50% of hours worked by part time employees, we get completely different result. The outcome is shown in the 2nd sheet named optional.Here, the highlight of the result is like this:

Only 1 full time employee need to be hired. He will come in 2nd shift and take 1st dinner break There will be total 85 part time employees would be hired at different point in time. The joining schedule is as below:

Time7am-8am8am-9am9am-10am10am-11am11am-12noon12noon-1pm1pm-2pm2pm-3pm3pm-4pm4pm-5pm5pm-6pm6pm-7pm7pm-8pmTotal

PT joined1116411563151921185

Total 340 out of 348 hours would be worked by part time employees only

The total cost of employees would be $ 43,600. Lower by $ 4200 then earlier solution with 50% constraint.The following information is provided for your use in this linear programming analysis:

To the extent permitted by local law, each Acme Home Improvements store, including Acme Mexico City, is open from 7 am - 11 pm every day. Acme Mexico City advance planners in North Carolina have provided the following table, which identifies the minimum number of customer service employees estimated to be needed on the floor of the store each hour of a typical work day:

Customer Service Employees

Time Period Minimum number needed on the floor

7 am - 8 am 10

8 am - 9 am 12

9 am - 10 am 18

10 am - 11 am 22

11 am - 12 pm 22

12 pm - 1 pm 26

1 pm - 2 pm 26

2 pm - 3 pm 26

3 pm - 4 pm 26

4 pm - 5 pm 26

5 pm - 6 pm 28

6 pm - 7 pm 28

7 pm - 8 pm 24

8 pm - 9 pm 22

9 pm - 10 pm 14

10 pm - 11 pm 12

In the interest of cost control, the planners have also imposed a not-to-exceed maximum of 30 customer service employees on the floor at any time.

Full-time customer service employees at AMC work a 9 hour shift (8 hours of work plus a 1 hour meal break) either from 7 am to 4 pm or from 2 pm to 11 pm.

Workers on the 7-4 shift are assigned an hour-long lunch break at either 11 am or 12 noon. Workers on the 2-11 shift are assigned an hour-long dinner break at either 5 pm or 6 pm.

Part-time customer service employees work four consecutive hours per day and their shifts can start any hour between 7 am and 7 pm. They receive no meal breaks.

By corporate policy, which is consistent with Mexican labor law, the company limits the hours worked by part-time customer service employees to 50% of the day's total scheduled hours.

Part-time customer service employees earn $500 per day, and full-time customer service employees earn $1100 per day in salary and benefits (here, $ = Moneda Nacional, i.e., the Mexican peso).Acme operations analysts working in North Carolina, working with the AMC advance planners, have used linear programming to propose in accordance with the foregoing factors, an employee assignment schedule for a typical day. Their proposed schedule is the following item in Course Content. You may elect to recommend this schedule or to recommend one that is different.AnswerThe linear programming model is developed in the attached spread sheet. Please refer to it for further explanation

Model Explanation:

Given data: Cells in column A:B shows given data on employee requirement at each hour of the operation of AMC since 7 AM to 11 PM Decision Variables: Cells in column D:G represents decision variables. 1. Cells D2:G5 represents the number of employees joining in 1st or 2nd shift as full time, and when would they take their lunch breaks according to the data given in the case. 2. Cells D7:E21 represents the number of employees joining at 7 AM to 7 PM work hours as part time Calculations: Cells in column I:N shows the calculations of employees on the floor at any given point of time The calculation of full time employees are explained in detail here:1. The number of full time employees between 7 AM to 11 AM, and 1 PM to 2 PM are those who joined in the first shift2. The number of full time employees between 11 AM to 12 noon are those who joined in the first shift minus those having 1st lunch break3. The number of full time employees between 12 noon to 1 PM are those who joined in the first shift minus those having 2nd lunch break4. The number of full the employees between 2 PM to 4 PM is sum of employees joined in 1st and 2nd shifts5. The number of full the employees between 4 PM to 5 PM and 7 PM to 11 PM is sum of employees joined in 1st and 2nd shifts6. The number of full the employees between 5 PM to 6 PM are employees joined in 2nd shifts minus those having their 1st dinner break7. The number of full the employees between 6 PM to 7 PM are employees joined in 2nd shifts minus those having their 2nd dinner break The calculations of part time employees are explained in detail here:1. The number of part time employees in any hours are sum of the part time employees joined in last 4 hours The total employees on floor is sum of full time and part time employees at any given time The total hours worked by both full time and part time employees are shown in cells I20:L20 Column N represents the required employees on floor at any given point of time. The total employees must be greater than or equal to required employees Constraints: Cells P1:U5 shows the constraints of the model1. Total part time work hours (Cell K20) must not exceed 50% of total work hours (Cell L20)2. Max total no of employees at any point of time must not exceed 303. Total no of present employees at any given time must be greater than or equal to the requirements4. All number of employees are integers Costings: Cells P7:U10 shows the costings calculations1. Total no of Full time employees (Cell G3) x $ 1100 will give full time employees costing per day2. Total no of Part time employees (Cell E21) x $ 500 will give part time employees costing per day3. Total costing is sum of full time and part time employees costingsOutcome:

By optimizing the model using in build solver engine, we get following output:

Objective function = min total cost per day is $ 47,800

Full time employees schedule:

Full Time1st shift2nd shiftTotal

Joined111223

1st lunch6511

2nd lunch5712

Part time employees schedule:

TimePT joined

7am-8am0

8am-9am1

9am-10am6

10am-11am8

11am-12noon6

12noon-1pm0

1pm-2pm1

2pm-3pm0

3pm-4pm6

4pm-5pm7

5pm-6pm8

6pm-7pm2

7pm-8pm0

Total45

CostingsCostingssalaryCost

1FT Employees23 $ 1,100 $ 25,300

2PT employees45 $ 500 $ 22,500

Total68$ 47,800

Executive Summery

Acme Mexico City provides solutions for home improvements. They need customer service employees to fulfill needs of the customers. The store is open from 7 AM to 11 PM. And the requirements of number of customer service employees each hour is different. On the supply side, they can have full time employees and part time employees. Both category have their own working hour patterns, salary packs and other limitations.

The problem statement hence is to schedule the customer service employees in such a way that it fulfills all the requirements

It should meet company policy for no more than 30 employees on floor at a time

Part time employees should not contribute more than 50% of working hours

At all working hours, requirements of customer service employees must be met

Apart from this, the cost of whole scheduling operation should be minimized.

To solve this, we used Linear Programming techniques. Here, we use existing data given in the case and then create an optimization model in a spread sheet. We incorporated various constraints: both given in the case and mathematically required. And derive a set of decision variables for scheduling purpose. The solution can be seen in the excel file. The model is flexible so that any possible changes in policies can be easily inculcate and results can be seen immediately.

By following these decision variables, we get an employee schedule which not only fulfill all the requirements but also optimizes costs and delivers results at least possible cost.