Handy Hydraulics Industries and the BMP Enterprises - Dissertation Example

Handy Hydraulics (HH) Industries SUMMARY The statistical study of an organization named HH Industries is taken up in this report. After completing some successful years the company is now experiencing a steady but smooth sailing. The management being aware of the competition in the market wants to revive an inclined growth once again. The edge that the company feels it has is past data which was carefully preserved over the last few years. This report is all about the statistical analysis of that data. The aim is to figure out and highlight the problems through using statistical procedures and to produces recommendations for solutions though appropriate analysis of the given data. In this report the problems related to the following areas are indicated and the recommendations are made accordingly. The areas are as follows, Sales Utilization of resources Human resource Clientele It is found out that the management overlooked some highly important information regarding sales and it is recommended that the future strategies be made with this issue taken into account properly. There existed a need to cut down unnecessary expenses of the company due to malfunction of resources. Appropriate recommendations have been made after careful analysis in this area too. The company was facing a shortage of human resource in one of its department of central importance. The statistical analysis done on the data for this reports suggests the solution of this problem as well. Moreover the purchase volumes of the customers are also analyzed and some important conclusions have also been drawn. INTRODUCTION A renowned Data Analyst Laurel has just joined her new job at the Handy Hydraulics Industry. The nearly two decades old company had changed a lot since its inception. The most drastic change being that of the ownership. Its original creators were the Doughlas Family. They were substituted by the current owners the BMP Enterprises. When the new owners of the industry took charge they realized a number of problems the company was undergoing then. The problems involved inappropriate handling of the company’s outlets other than the main headquarters that were stationed in Florida. Since its inception the company had exhibited a steady growth ratio. The Handy Hydraulics were not manufacturers but were mainly distributors and repairers. They would deal in all kind of hydraulic parts. For example, hydraulic seals, gauges, pump cylinders and all other related spare parts etc. Initially there weren’t many marketing strategies that would propagate the company’s products. Later on a marketing strategy called Brute Force was introduced. This resulted in an increase in demand of the company’s products but unfortunately the inexperienced family run business could not stand the increase in number of orders and their system collapsed. . The headquarters in Florida was not the company’s only outlet. By the early decades two new outlets at Arizona (1985) and Ohio (1986) had also become operational. However, the lack of proper maintenance and handling of inventory in all the outlets resulted in havoc. Poor maintenance and absence of a far sighted approach led to the closing down of the Ohio warehouse by the new management. For three years the new management applied expense cutting and profit making strategies which resulted in a stable situation and the business started breathing again. Nearly 2 years later another warehouse was reopened in Pennsylvania. This was a streamlined and carefully worked out version. Some other cost cutting strategies like the shrinking of the payroll and substitution of hefty catalogues with flyers were employed. The growth of the company had reached a steady pace. This called for a something new. At this stage the management thought of utilizing the past data for assessment of the growth of the company and for betterment in future planning. For this purpose the management hired a data analyst/statistician. The data that was very carefully recorded proved to be an asset for the company as its correct analysis led to some very important recommendations. The following report is a depiction of the data analysis processes. METHODS Q1a. The histograms of daily average order size for quarter 1 and 2. Avg Order Size 10 30 50 70 90 110 130 150 170 190 210 Frequency 0 0 0 0 4 16 16 17 5 3 1 Avg Order Size 10 30 50 70 90 110 130 150 170 190 210 Frequency 0 0 0 0 6 17 26 7 5 2 1 Q1b. Quarterly charts for the company’s total number of orders per day are as follows. Total Orders per day 105 115 125 135 145 155 165 175 185 195 205 Frequency 0 1 3 4 5 17 15 11 5 1 0 Total Orders per day 105 115 125 135 145 155 165 175 185 195 205 Frequency 0 0 0 2 3 11 13 12 4 10 9 Total Orders per day 105 115 125 135 145 155 165 175 185 195 205 Frequency 0 1 2 2 1 8 9 13 9 7 10 Total Orders per day 105 115 125 135 145 155 165 175 185 195 205 Frequency 0 1 0 0 0 4 9 16 13 12 9 Q1c. Analysis: The histograms presented above in part (a) and part (b) clearly exhibit that the although the number of orders increased over the time but average order size declines and does not show a proportional increase. 2. (a) Number of Orders/day Quarters 3 4 1 2 Mean 155.52 171.67 171.26 177.81 Median 156 168.5 171.5 177 Mode 150 163 177 191 Average Order Size Quarters 3 4 1 2 Mean 133.96 121.00 126.01 119.93 Median 132.35 120.09 125.74 116.71 Mode 130 119 124 113 As per the tables presented above the mode seems most appropriate. The data supports Laurel’s findings that are, Customers are increasing but they are placing short orders. Customers want to maintain short inventories. Small workshops place small orders. The weather factor. Company’s total Sales dollars Quarters 3 4 1 2 Total Quarterly Sales 1287906 1327508 1346084 1368181 Stan’s assumption that the sales figures are increasing seems correct as there is an increasing trend in sales. 2. (b) Figures of Profit Center 3 Quarters 3 4 1 2 Mean number of daily orders 28.17 30.69 31.18 35.06 Mean of daily sales 2731.63 3144.11 3121.19 3328.94 Average order size 96.96 102.46 100.11 94.94 The trend seems to be a little divergent from an overall trend. The surges and spikes in the values ask for individual investigation of each profit center as per Laurel’s recommendation. 3(a). Inter-Quartile Ranges of average order size in each quarter IQR Total Range IQR Quarter3 IQR Quarter4 IQR Quarter1 IQR Quarter2 32.83 37.77 26.83 33.08 20.2 The average order size values are more consistent in quarter 2. The same trend towards consistency seems to appear in the overall range. 3(b). Number of Orders Quarters 3 4 2 1 Standard Dev 16.73 21.63 23.42 18.36 Variance 279.83 467.72 548.39 336.95 CV 10.76 12.60 13.67 10.33 Average Order Size Quarters 3 4 2 1 Standard Dev 28.05 24.13 26.51 24.44 Variance 786.64 582.41 702.68 597.08 CV 20.94 20.00 21.04 20.37 The data seems to get more consistent towards last quarter. 3(c). CV and SD for Number of Orders for All Profit Centers Quarters Q3 Q4 Q1 Q2 Profit Center 1 SD 20.12 14.22 13.73 10.86 CV 19.57 15.54 14.70 11.62 Profit Center 2 SD 7.73 8.93 8.74 8.83 CV 20.99 18.03 18.72 17.91 Profit Center 3 SD 5.89 5.24 7.74 6.70 CV 20.90 17.08 24.83 19.12 CV and SD for Average Order Size for All Profit Centers Quarters Q3 Q4 Q1 Q2 Profit Center 1 St Dev 42.99 43.27 46.66 42.00 CV 27.87 28.85 29.59 29.46 Profit Center 2 St Dev 42.58 25.06 27.39 29.71 CV 41.70 31.91 35.25 31.39 Profit Center 3 St Dev 23.11 32.58 40.98 26.44 CV 23.58 32.07 40.67 27.74 The differences observed seem significant between the relative dispersions. 3(b) The staff should get aware of the true picture of sales as increase in the number of orders without proportional growth in average order size is an alarming situation. The staff should come up with customized suggestions regarding the profit centers individually. Proper measures should be taken to boost the confidence of new customers by improving the after sales services. The discount promotions for larger sale volumes seem appropriate. To verify the findings of Laurel’s the real data regarding small business and small workshops should be acquired. 4(a) and 4(b). The probabilities concluded from the given data is as follows, The probability that a machine will be down on any given day is 20.8% i.e. The individual probability of each machine is 10.4% With 250 working days per year, (i) The expected number of days for which one machine would be down is 52 days. (ii) The expected number of days for which both the two machines would be down is one day. 5. Expected yearly cost. Average service call cost for a machine = $68 Average service call cost for 2 machines = $100 Cost of copies lost = $150 per copier per day. The expected number of days for which one machine would be down is 52 days. The expected number of days for which both the two machines would be down is one day. The service call cost for 52 days = $68 x 52 = $3536 The service call cost for both the machines for 1 day = $100 The cost of copies lost for 52 days = $150 x 52 = $7800. The cost of copies lost for both the machines for 1 day = $15 x 2 = $300 Hence the total yearly expenditure becomes = $3536 + $100 + $7800 + $300 = $11,736. 6. As per the given data the year duration assumed for this analysis is 10 months. Evaluation of proposal 1: Per month rent of 2 copiers = $350. Yearly rent = $350x10 = $3500/- Considering the given probability of a machine being down on any given day the value in terms of number of days would be = (0.05 x 250) = 12.5 i.e. approximately 13 days. This becomes 26 days for both the machines. Per year cost of copies lost = 2x ($150 x 13) = $3900. The service call cost is covered. The yearly cost = $3500 + $3900 = $7400 per year. Cost of 3 years = 3 x $7400 = $22,200. Evaluation of Proposal 2: Purchase cost of new machine = $8750. Considering the given probability of a machine being down on any given day the value in terms of number of days would be = (0.017 x 250) = 4.5 i.e. approximately 5 days. The new machine would replace both the machines, so the cost of copies lost for first year = 5 x ($150 x 2) = $1500. The service cost is covered for the first year by the seller. The total cost of first year = $8750 + $1500 = $10,250. The service call cost for the next year = $175 x 5 = $875. The cost of copies lost is assumed to be the same as previous year. So the total cost for 2nd year = $875 + $1500 = $2375. This cost is assumed to be replicated for the 3rd year as well. So the total cost of 3 years = $10,250 + $2375 + $2375 = $15,000. Proposal 2 of buying a new machine appears to be feasible. 7(a). The average number of calls per hour calculated from the data given = 27.48. 7(b). For 28 calls/hour the operators needed would be at least 4. 7(c). There would be the need of 4 more operators if the current scenario is considered i.e. It would amount to 5 operators in all including Stan. 8(a). 8(a) The histogram presented above shows that the distribution of purchases done by the customers appears to be ‘Normal’. The mean of purchases = $13706 Thus it is a skewed Normal distribution.. 8(b) The Mean, Median and Standard Deviation of the given data are as follows. Mean= $13705.89 Median= $13291.5 Standard Deviation = $4396.791 8(c) P(a ≤ X ≤ b) = P(X ≤ b) – P (X < a), The values are calculated through MS Excel. (i) Calculations show that 7.6% customers would be expected to have accounts greater than $20,000. (ii) Whereas 20% are expected to have accounts below $10,000. (iii) 72.4% customers fall in these ranges. Analysis and Conclusions: This report comprises of four main parts. The by part analysis is as follows, The order and sales data of four quarters when analyzed with the help of histograms showed with particular class intervals revealed an asynchronous trend between the number of orders and average order size. The last quarter exhibited an inclination in the number of orders but decline in the average order size. The reason was assumed to be a large number of orders with low sales volumes OR LARGE number of SMALL orders. To confirm this suspicion the central tendencies that are mean, median and modes were observed. The mode being the representative of the majority found out to be the most appropriate as the position it acquired during the analysis of Number of Orders and Average Order size confirmed the above finding. To observe the consistency of data and to confirm the results measures of dispersion like Inter-quartile ranges, standard deviation and CVs of respective quarters were analyzed. The last quarter was found to be the most consistent with low mean. This finally concluded that the average order size is not increasing proportionally with the number of orders. Certain recommendation like new promotions and further data collection strategies are proposed. Another problem for which the statistical analysis was conducted is related to the photocopier machines. Company’s two photocopiers were reported be down most of the time resulting in additional expense of repairs and cost of the copies. The analysis of the yearly data produced specifically the probabilities of down time on the basis of which current expenses were calculated. The figures found out to be considerably high and were not taken into consideration before this analysis. With a probability of expected high down time in future the expense value was taken as a threshold and two proposals were evaluated. The proposal of replacing both the machines with a new advanced machine was found suitable. The number of phone operators dealing with the customers for incoming business was a question mark. The data in this regard was analyzed and on the basis of a hypothetical value of 8 calls/hour/operator the number of appropriate phone operators was recommended. Finally to analyze the purchase volume of the customers the distribution of data was figured out to be normal. With a threshold of $20,000 on high side and $10,000 on the low side, it was concluded that approximately 7% customers hold purchase volumes on high side, 20% on low side and 73% lie between these ranges. The information can be considered as very useful for future strategies. REFERENCES: LearnShop Tutorial on Using Excel 2007 with Business Statistics, < http://www2.estrellamountain.edu/ctl/ls_tuts/excelbusinessstats07.htm>, [Accessed 15 May 2011]. Winston, Wayne L.. Microsoft Excel Data Analysis and Business Modeling. Microsoft Press. © 2004. Books24x7. (accessed May 19, 2011) Read More