It is important to become comfortable receiving and giving constructive criticisms, since this is an important component in one’s professional growth and development and a core competency for leaders. Students will be expected to read the initial posting of at least TWO peers, and then provide thoughtful comments addressing the following:
- Point out what you perceived to be the strengths of the initial posting along with supporting rationale.
- Identify specific opportunities for improvement with regard to the content in the initial posting. Furthermore, you should provide supporting rationale for your stated position, as well as concrete suggestions and guidance intended to strengthen the effectiveness of the content.
Peer responses should be typed directly into the discussion thread and not attached to a posting. For these responses, should outside sources be used to support the content within the postings, proper in-text citations and correctly formatted references should be prepared consistent with the APA. The list of references should be physically positioned at the end of the postings.
Week 2 Discussion
MBA576 Operations Management
Dr. Kevin J. Loy
This paper will include creating a forecasting plan with the intent of forecasting production output for Kibby and Strand. The plan includes forecasting objectives, the data to be used in forecasting, and the quantitative methods the staff is to use in creating the production output forecast.
Week 2 Discussion
The forecasting objectives for Kibby and Strand include ensuring that there are materials available to begin and complete work on the contracts. In order to accomplish this objective in forecasting the associative forecasting technique will be used. The time horizon on this particular forecasting plan would be the 20 week span of completing contracts.
Data to be used are the amount of a specific raw material being purchased and delivery to to Kibby and Strand. Additional data are the number of goods being produced from that raw material. Since Kibby and Strand has the ability to make multiple different types of products using the same raw materials, it is vital to correct forecast the amount of raw material needed to produce the products.
This is a forecast based on time-series because the data measured is production output. Output is one of the data measurements listed by Stevenson (2021). The naive method, quantitative, can be used because by the staff of the seasonality of products produced by Kibby and Strand. For example, forecasts to purchase less of a raw material used to make summer clothing may be utilized. The weighted average method can also be used by staff because we should analyze the most recent values in the series. In terms of forecasting output, an accurate representation of raw materials converted to products would be vital by not being as concerned with previous results but rather the most recent.
Stevenson, W. J. (2021). Operations management. McGraw-Hill Education.
Kibby and Strand Operational Process Manual
Luis Osorio Garcia
MBA 576 Operations Management
Kibby and Strand Production Forecast
The purpose of this document is to established guidelines for decision making process when it comes to decide about future demand. The primary goal of this is to match supply to demand and everything in between such as workforce, marketing activities, schedules, funding, equipment, etc., (Stevenson, 2021). In regards production, the forecast needs to make sure the process of converting raw material into finished product and the lead-time to deliver the good meet contract deadlines. It entails raw material input necessary to have in stock to work non-stop the time necessary throughout the time horizon, machinery maintenance, workforce necessary to operate the machinery, hiring activities and work schedule (including holidays). Kibby and Strand production forecast need to be revised at least every six months to make sure the production for the next season (6 moths) will match company’s capacity.
Production forecasting objectives:
· Make sure of a raw material input for the production process.
· Provide to Human Resources workforce need long time in advance.
· Articulate the production and shipping department so the lead-time matches the contract specifications.
· Foresee the need to new machinery acquisition.
· Last-year’s contract units produced
· Business relations and odds to get new contracts (built reputation over the past year)
· Machinery’s maintenance schedule
· Man-labor needed
· Holidays throughout the season to forecast
· Market trends during the past year
· Seasonal predictable factors: product/feature releases throughout the year
Quantitative Method per product
The quantitative method to calculate production output (units) is the straight-line method (Marcotullio, 2020). The purpose of calculate increase (or decrease) of units from one year to another is to know by how much to increase or reduce production capacity from one season to another for certain goods. Production of goods will vary according to the time of the year as summer and winter collections demand happen during different times of the year.
Last year period’s units sold x (1 + % rate of sales growth) = next year period’s units
Such analysis must be done for each product separately, then assign priority as far as raw material obtaining and production schedule. The price unit will tell how much a single product drives the company’s revenue and it will determine also how important is that product over the others.
Gaille, B. (2020). Apple’s Mission Statement and Vision Statement Explained. Retrieved 23 August 2021, from https://brandongaille.com/apples-mission-statement/
Marcotullio, N. (2020). The Top 5 Methods for Quantitative Sales Forecasting. Retrieved 24 August 2021, from https://mapmycustomers.me/blog/the-top-3-methods-for-quantitative-sales-forecasting/
Rowland, C. (2019). Apple Inc. Operations Management: 10 Decisions, Productivity – Panmore Institute. Retrieved 23 August 2021, from http://panmore.com/apple-inc-operations-management-10-decisions-areas-productivity
Stevenson, W. (2021). Operations management (14th ed.). New York: McGraw-Hill Education.