Reference no: EM13975872

A-CAT CORP.: FORECASTING

THE COMPANY

A-CAT was one of the leading producers of electrical appliances in India. It competed with and belonged to the category of medium scale industry, which produced and distributed domestic electrical appliances to the rural population in and around the Vidarbha region. The company owned and operated two medium-sized manufacturing units in a sleepy town called Gondia, in one of the remote districts in Vidarbha, ironically a backward region in the most progressive state of India, Maharashtra. A-CAT had an alliance partnership with Jupiter Inc. for the production of cabinets and had a collaborative venture with Global Electricals for manufacturing TV signal boosters and battery chargers.

A-CAT's manufacturing units had been in operation since 1986. The budget year 2010-2011 showed annual sales of Rs. 9,800,000, and the company employed about 40 employees. The primary functional departments of A-CAT were its purchasing department, design department, manufacturing department and sales and service department.

A-CAT's primary flagship product was a voltage regulator of 500 kilovolt amps (KVA) that was branded and sold under the tag of VR-500. These voltage regulators were used for varied purposes but were most commonly used in households as a protective device for refrigerators and television sets, so as to protect the latter from the vagaries of load fluctuations and/or frequent power failures, which were a very common phenomenon in Vidarbha.

Instead of competing with the large-scale operations prevalent in a similar type of industry, A-CAT preferred to focus on the rural segment. The company offered nearly 100 different models of various electrical appliances for household use, including TV signal boosters, FM radio kits, electronic ballasts, battery chargers and voltage regulators. The broad range of products catered to the rural population in and around the district and Gondia, which comprised a large population. At the low end of the market were customers who were quite sensitive towards pricing. In the opinion of top level management, there was more scope in this segment of the market. They had been proved right but were worried that this situation was not going to last long and that the downward trend in sales was getting worse.

THE ISSUE

During the past few months, the sales of voltage regulators had fallen off. In reaction, A-CAT recently started deliberating on its policy of purchasing and stocking spares and components in the system, especially with regard to schedule and stock-in-hand inventory. The firm stored all its spares and components, including the transformers, in its factory store.

A few of the functional department heads were questioning the nature of keeping a big stock of transformers on hand. Since a large number of products manufactured and sold by A-CAT, such as the voltage regulator, had a transformer as one of their principal or primary components, the store managers always tried to keep a good quantity of spares as a buffer for this vital part.

Orders for the main product of A-CAT - that is, voltage regulators - came in throughout the year. Most of the time, these orders were categorized as "rush orders," and the store managers knew that the supplier of the transformers required for the product needed at least one week, if not more, for delivery.

On top of this, it was likely that the transformer supplier would raise prices if uniformity and continuity in placing of orders for transformers was not guaranteed. Placing orders beyond a certain limit also stretched the system - whereas A-CAT had previously had access to four suppliers, now there was only one.1 Thus, ordering too many transformers not only exposed the capacity constraints at the supplier's end but also led to a substantial tie-up of the company's cash reserves. Moreover, the blocking of capital had a domino effect on the purchase and inventories of other products' spares and components. Considering the prevailing market scenario and the economic outlook, A-CAT could not afford to fight problems on different fronts.

An increased cost of its primary spare component was the last thing A-CAT needed. Although the revenue and profits for the whole organization had steadily grown over the years of its existence, sales of voltage regulators had been quite volatile. They were already showing a sluggish year-on-year growth rate in comparison to their closest competitors.

The sales division was supposed to forecast the demand for voltage regulators as a measure for determining the right amount of transformers to keep in inventory. Though transformers were used in other A-CAT products, the company decided to consider only the issue of the number of transformers required for voltage regulators.

TVs, refrigerators, washing machines and other white goods used voltage regulators as a guard against potential voltage fluctuations and hence the resulting forecast of voltage regulators had an effect on the supply chain. It also had an impact on the number of workers called in for shifts, resulting in scheduling issues.

THE BRIEF

Vice-president Arun Mittra carried out several rounds of discussion at different levels in this regard, but they failed to completely resolve the issue. So he decided to take the matter in his own hands and called for a comprehensive data report of sales figures for the last several years.

Mittra deliberated on this for a while and asked his secretary to contact his operations head for an urgent meeting. He said,

We have always estimated how many transformers will be needed to meet demand for our final products, especially for voltage regulators. The usual method is to look at the sales figure of the last two to three months and also the sales figure of the last two years in the same month and make a guess as to how many transformers will be needed to sell this many voltage regulators. With this method, we were able to manage quite well until now; however, the general complaint is that either we have too many transformers in stock or there are times when there are not enough to even meet our normal production levels. It's a classic case of both under-stocking and over- stocking. In either case, we are facing troubles at the final product delivery front and also our supplier is raising a lot of objections about our haphazard manner of placing orders.

As operations head, Ratnaparkhi was asked by Mittra to have a closer look at the data report and to offer his understanding and analysis of the issue within a fortnight, when the next order for the transformers would have to be placed. The size and timing of the order was the bone of contention between various functional departments. Refer to Exhibits 1 and 2 for the data summary.

Mittra also emphasized that Ratnaparkhi's recommendations were to be very crystal clear and precise and accompanied by justification for the decision taken. He said, "We should be able to plan our transformer purchasing better. I would like you to not only understand, analyze and propose your projections but would also like you to come up with a report that even a lower grade clerk in stores should be able to fathom and follow."

You nicely performed regression analysis. However, you focus your analysis only to regression analysis. Please note that it should be more extensive in order to satisfy the requirements of the project.

For this purpose, you are expected to:

i. Develop descriptive statistics for years 2007-2010 that are to be submitted to the quality control department.

ii. Test the belief that the mean number of transformers that are required exceed 1000 transformers using the most recent (2010) data..... Hypothesis tests for Means (Chapter 11).

iii. Provide an analysis that supports or disproves that mean number of transformers that are required has changed over the period 2006-2010..... ANOVA (Chapter 20)

iv. Develop a linear model for forecasting transformer requirements based on sales of refrigerators... Correlation and Regression Analysis (Chapter 4)

This extensive set of analysis will allow you the opportunity to utilize the various statistical tools learned in the class. More explicitly:

You should explain which information can be obtained from descriptive statistics.

To test the belief that the mean number of transformers that are required exceed 1000 transformers, please follow a formal hypothesis-testing procedure and interpret the results carefully:

Step 1: State null and alternate hypotheses.

Step 2: Select a level of significance.

Step 3: Identify the test statistic.

Step 4: Arrive at a decision based on the sample data.

Step 5: Interpret the results.

In hypothesis testing, the claim or statement made about a population parameter is placed in the alternative hypothesis HA. The null hypothesis (Ho) is a statement of no effect or no difference. It is typically expressed as an equality statement. There are some resources that express the null hypothesis as a complementary statement of the alternative hypothesis. All the analysis is made under the assumption that the null hypothesis is true. Based on whether the sample data supports the null hypothesis, a decision of whether ‘reject' or ‘fail to reject' the null hypothesis is made. Based on this, a conclusion is made regarding the alternative hypothesis, the main claim that we are trying to test. Please see the examples in Chapter 11 (in particular, page 349.)

For this part, please make sure that you only make use of 2010 data for transformer requirements.

The p value should be calculated in accordance with a right-tailed alternative hypothesis.

Please note that ANOVA is an analysis method for testing equality of means across groups. In our case, this refers to testing if the mean number of transformers required is equal across years 2006-2010. A decision is made based on the value of the test statistic and the p value of the resulting analysis.

Overall, to ensure the reliability of the results, make sure that the underlying assumptions and conditions are tested for hypothesis testing, regression analysis, and ANOVA.

Make sure that you include all the tables and figures in your final report, label them, and properly refer to them within the main body of the text.

As stated in the rubric, include at least six sources cited in APA format.