MANAGEMENT DYNAMICS Merging Constraints Accounting to Drive Improvement phần 2.pdf (kỹ thuật PR)

10 Thinking Bridges Exhibit 1.11 Internal Rate of Return (Scenario 2) Cost savings (the presumed net cash inflow resulting from the investment, $6.31 * 4,992) Initial investment required $31,500 per year $5,000 Approximate value of, and upper limit on, the internal rate of return (cost savings / investment) (The payback* reciprocal) 6.3 ≈ 630 % * The payback period of this investment is about 2 months (5000 / 31,500 = 0.159 years). Scenario 2: Global Measurements Thinking Bridge Analysis Let’s ask the T, I, and OE global measurement questions about scenario 2 and see if anything has changed there. What prevents the ﬁrm from increasing throughput? The answer to this question has changed. The company is currently producing and selling at its capacity of 4,992 units, a limitation that is established by workstation 102. The engineer’s proposal increases the time required at workstation 102 to produce a widget from 25 minutes to 27 minutes. As previously shown, the number of widgets that now can be produced actually drops by 370 widgets from 4,992 to 4,622. In this case there are plenty of sales; the ability of the overall system to generate greater throughput is limited by the capability of workstation 102. Will the total amount of throughput (T) change? Yes, as shown in Exhibit 1.12, the throughput is actually reduced in the second scenario. Exhibit 1.12 Throughput Lost (Scenario 2) Lost Sales Volume: Original capacity Capacity if proposal is implemented Reduction in productive capability Throughput per unit: Price Variable Expense Throughput Throughput lost $400.00 – 80.00 $320.00 4,992 – 4,622 370 units per year units per year units per year per unit per unit per unit (The throughput per unit multiplied by the number of units lost) $320.00 x 370 $118,400.00 per unit units per year per year Thinking Bridges Example 11 The proposal reduces the available capacity below that which is currently being sold. This means that the organization will be late delivering (or not be able to ﬁll) about 370 of the existing orders (4,992 widgets) for which it has contracted. For each unit that is not delivered, the company will not receive the $400.00 sales price. However, for each unit not delivered the company will not need to incur its variable cost (raw materials costing $80.00). Hence, $320.00 throughput per unit ($400.00 − $80.00), when extended by the lost volume, provides a measure of the lost throughput. The current period throughput lost, as shown in Exhibit 1.12, is $118,400. This may be used as an estimate of future losses also, although there may be an additional adverse effect in the future resulting from the poor delivery performance. We just don’t know at this point. We also should recognize that as a result of such situations the organization’s employees, who have to answer for late shipments, feel the pressure of being trapped by policies outside their control. Will the operational expenses (OE) of the ﬁrm change? No, as in scenario 1, the operating expenses do not appear to change. Will the amount of inventory/investment (I) in the ﬁrm change? As in scenario 1, the inventory/investment increases by $5,000, the cost of the new ﬁxture. What is the real economic effect of this proposal? The real economic effect of the proposal in scenario 2, where the effect was to reduce the capacity available on an existing fully utilized resource, combines the $5,000 additional investment with the $118,400 throughput reduction for a total economic loss of $123,400 in the ﬁrst year and a continuing amount of $118,400 or more until something else changes. The measurements for scenario 2 are summarized in Exhibit 1.13. Scenario 3 In scenario 3 we start from the original case again. For this scenario we assume that the potential market is at least 6,000 widgets. The ﬁrm is currently operating at a level of 4,992 widgets. The plant engineer makes a Exhibit 1.13 Summary of Changes in Global Measurements (Scenario 2) Global Measurement T I OE Cash Flow (=T-I-OE ) - $118,400 +$5,000 no change Subsequent Years - $118,400 no change no change - $123,400 - $118,400 First Year 12 Thinking Bridges Exhibit 1.14 Proposed Change to Widget Manufacturing Process (Scenario 3) Workstation Original Processing Time 101 102 103 104 15 minutes 2 5 minutes 10 minutes 5 minutes Proposed Processing Time 20 minutes 23 minutes 10 minutes 5 minutes Total Time 55 minutes 58 minutes similar suggestion, but this time the effect is to increase the time required to produce the product by three minutes. In this case, as reﬂected in Exhibit 1.14, ﬁve minutes is added to workstation 101’s processing time. The processing time at workstation 102 is decreased by two minutes. Thus, if this proposal were to be implemented, there would be a net increase in processing time of three minutes. Scenario 3: Least Product Cost Thinking Bridge In this scenario, the standard cost of a widget increases by $6.31. The calculations for this are shown in Exhibits 1.15 and 1.16. The cash ﬂows that would be estimated for this proposal, based on the increased unit cost, are shown in Exhibit 1.17. It appears that this proposal will cost the organization $36,500 in the ﬁrst year and $31,500 annually thereafter. When analyzed using the least product cost method, this proposal does not appear to be a very good one. Scenario 3: Global Measurements Thinking Bridge Once again we ask our global measurements questions. What prevents the ﬁrm from increasing throughput? As with scenario 2, workstation 102 restricts our ability to serve all of those potential customers who would like to purchase our widgets. Exhibit 1.15 Revised Unit Cost after Implementing Proposal (Scenario 3) Cost Element Raw Materials Direct Labor (58 minutes @ $0.3000) Overhead (58 minutes @ $1.8029) Standard Unit Cost Unit Cost $ 80.00 17.40 104.57 $201.97 Thinking Bridges Example 13 Increase in Standard Cost (Scenario 3) Exhibit 1.16 Original standard unit cost New standard unit cost Cost increase per unit $ 195.66 201.97 $ 6.31 Will the total amount of throughput (T) change? The proposal, even though it increases the standard cost of the product, will increase the relative capability of workstation 102 as the time required for processing a widget at workstation 102 is reduced from 25 minutes to 23 minutes. Now 5,426 widgets per year may be processed through workstation 102 (124,800 minutes per year / 23 minutes per widget). Since the market potential is 6,000 units, the additional units can be sold. As shown in Exhibit 1.18, this is an increase of 434 widgets sold during the year. With a throughput of $320.00 per unit, the sales volume increase translates into a $138,880 increase in throughput. Will the operational expenses (OE) of the ﬁrm change? No. Once again there is no real impact on operational expense. The ﬁrm has the same number of employees and approximately the same other costs as it had before. What has changed is that it has the ability to produce more widgets than it did previously. Will the amount of inventory/investment (I) in the ﬁrm change? Yes, they will again spend the $5,000 for the ﬁxture. What is the real economic effect of this proposal? They gain $133,880 in the ﬁrst year and $138,880 in future years until something else changes. The measurements for the results of scenario 3 are summarized in Exhibit 1.19. Scenario 4 In scenario 4 we start from the original case again, but now we assume that the potential market is at least 6,000 widgets and that the ﬁrm is currently operating at a level of 4,992 widgets. The plant engineer again Exhibit 1.17 Annual Cost Increase (Scenario 3) Cost increase per unit Annual volume Annual cost increase Cost of fixture First year cost increase $ 6.31 x 4,992 $ 31,500 5,000 $ 36,500 units 14 Thinking Bridges Exhibit 1.18 Additional Throughput (Scenario 3) Additional Sales Volume: Capacity if proposal is implemented Original Capacity Increase in productive capability 5,426 – 4,992 4 34 Throughput per unit: Price Variable Expense Throughput Additional Throughput $400.00 – 80.00 $320.00 (The throughput per unit multiplied by the number of units gained) units per year units per year units per year per unit per unit per unit $320.00 x 434 $138,880.00 per unit units per year per year makes a similar suggestion. This time the effect is to decrease the time required to produce a widget by three minutes, as was the case in the ﬁrst two scenarios. In this case, however, as reﬂected in Exhibit 1.20, the processing time at workstation 103 is increased by two minutes, allowing the processing time at workstation 101 to be reduced by ﬁve minutes. Scenario 4: Least Product Cost Thinking Bridge As with scenarios 1 and 2, which also reduced the total time required to produce a widget by three minutes, the standard cost of a widget decreases from $195.66 to $189.35. The analyses shown in Exhibits 1.5, 1.6, 1.10, and 1.11 apply equally in this case. This, again, appears to be a desirable action when evaluated by the conventional least cost analysis. Scenario 4: Global Measurements Thinking Bridge We ask our global measurement questions a last time. What prevents the ﬁrm from increasing throughput? As with scenarios 2 and 3, Exhibit 1.19 Summary of Changes in Global Measurements (Scenario 3) Global Measurement T I OE Cash Flow (=T-I-OE ) + $138,880 +$5,000 no change Subsequent Years + $138,880 no change no change + $133,880 + $138,880 First Year Thinking Bridges Example 15 Exhibit 1.20 Proposed Change to Widget Manufacturing Process (Scenario 4) Workstation Original Processing Time Proposed Processing Time 101 102 103 104 15 minutes 25 minutes 10 minutes 5 minutes 10 minutes 25 minutes 12 minutes 5 minutes Total Time 55 minutes 52 minutes workstation 102 restricts our ability to serve additional customers who might like to purchase our widgets. Will the total amount of throughput (T) change? Unlike scenarios 2 and 3, scenario 4 does not involve, or touch, the limiting workstation 102. Therefore, the ﬁrm will neither gain additional capacity nor lose existing overall capability because of the proposal. Sales will still be 4,992 widgets, and throughput does not change. Will the operational expenses (OE) of the ﬁrm change? Operational expense also remains about the same. Will the amount of inventory/investment (I) in the ﬁrm change? As with all of the other scenarios, $5,000 is spent for the ﬁxture. What is the real economic effect of this proposal? There is a loss of the $5,000 investment in the ﬁxture. Exhibit 1.21 displays the summarized results of scenario 4. Example Summary The results of each analysis are summarized in Exhibit 1.22. There is also a column for you to write in your opinion as to which is the more correct analysis. Exhibit 1.21 Summary of Changes in Global Measurements (Scenario 4) Global Measurement T I OE Cash Flow (=T-I-OE ) no change +$5,000 no change Subsequent Years no change no change no change - $5,000 no change First Year 16 Thinking Bridges Exhibit 1.22 by Analyses Example Summary, First Year Dollar Gain or (Loss) Shown Least Product Cost (LPC) Global Measurements (T, I, & OE) Scenario 1 $17,085 ($ 5,000 ) Scenario 2 $ 26,500 ($ 123,400 ) Scenario 3 ($36,500) $133,880 Scenario 4 $ 26,500 ($ 5,000) Range of Estimates of Bottom-line Profit Effect $63,000 $257,280 Which analytical technique do you believe more correctly reflects reality? What we originally had thought was a nice but minor sort of enhancement with a cost of $5,000 and an annual beneﬁt of about $20,000 actually embraces a range of bottom-line proﬁtability effects of more than a quarter of a million dollars! SUMMARY What can we discover from the thinking bridges example? Three conclusions are evident. First, we need to think carefully about what we mean by improvement. Second, in each of the four scenarios, the limitations on the ability to produce or sell the product created an Archimedes point for the company. Finally, the least product cost thinking bridge appears to be ﬂawed. Improvement How do we determine whether an action is an improvement? We probably can agree that an improvement to a system makes the system better. However, this question leads immediately to a second question: “better relative to what?” In order to learn whether an action results in an improvement, we must ﬁrst know what to compare it against. In the thinking bridges example, the engineer set about to reduce the amount of time required to produce a widget. The engineer’s proposals in scenarios 1, 2, and 4 were successful in this effort, and—from that point of view—the proposals were improvements. But why did the engineer want to reduce the amount of Summary 17 processing time required? The intention was to increase proﬁts by reducing the resources, and hence the cost, required to produce the product. When examined from the point of view of the global organization, however, proﬁts did not increase. An improvement ultimately must be deﬁned in terms of an organization’s global goal. An action resulting in better performance relative to the global goal is an improvement. Actions resulting in worse performance, or in no change, relative to the global goal are not improvements. If the primary purpose of an organization is to pursue proﬁt, then improvement must be measured in terms of greater bottom-line proﬁtability. In scenarios 1, 2, and 4 of the example, the intention was good—to reduce the standard cost of the item—but the result was not an increase in profits. Therefore, the action, even though successfully reducing the total time required to make a widget, was not an improvement. Improvement is evident only in scenario 3. Archimedes Point Some locations within an organization are particularly sensitive to changes. Something very big happens when changes touch these locations. It may be good or it may be bad, but in any event it is very big. We call such a component of an organization an Archimedes point because it marks a place to focus attention in order to get dynamic results. It is apparent that workstation 102 plays a special role in scenarios 2 and 3. In these cases the quantity a company can sell is restricted not by the market demand but by its internal ability to produce the product. Workstation 102 represents an Archimedes point for the company in these two scenarios. In scenario 4, workstation 102 again plays an important, though less obvious, role. It is still an Archimedes point for the company. However, since the proposed change in scenario 4 involves only workstations 101 and 103, which are not Archimedes points, nothing much happens in terms of improvement. In scenario 4 an Archimedes point was not touched; therefore, no signiﬁcant system reaction occurred. Now consider scenario 1. The company has plenty of manufacturing capacity to provide the entire quantity of widgets demanded by the market. Therefore, there is no currently active production limitation as to how much can be sold. Neither workstation 102 nor any other production workstation is an Archimedes point in the ﬁrst scenario. Accordingly, there was no signiﬁcant effect on the bottom line, even though the proposed change in the ﬁrst scenario involved workstation 102. Is there any Archimedes point in the ﬁrst scenario at all? Every system has at least one Archimedes point. In scenario 1 it is just someplace other than in the manufacturing function. In fact, since the company has 18 Thinking Bridges the ability to produce considerably more than it is selling in scenario 1, it appears that the Archimedes point is likely to be somewhere in either the marketing or sales function. It might be in a physical resource such as the number of sales outlets or salespeople. Or it might be a management policy. However, an apparent Archimedes point in sales or marketing also might be the result of actions taken in other areas, for example, poor delivery performance or poor quality that results in a lack of sales. Least Product Cost What about using reduced product cost as a guide for management actions? As we have seen in the example, least product cost provides a deceptive beacon. If the least product cost technique were to lead us in the right direction, it would seem to be just a matter of good luck. One might suggest that if many companies are making decisions based on reducing the standard cost of products, then isn’t that evidence that it works? The answer is yes, and no. Yes, many companies do this, and many of those companies are both large and have enjoyed long corporate lives. And, no, the evidence does not support the usefulness of the least product cost methodology to guide actions leading to a robust process of ongoing improvement. Four things contribute to the resolution of this apparent contradiction: 1. 2. 3. 4. The intuition aspect The Archimedes point effect A different goal The meaning of success First, the intuition part of the least product cost thinking bridge represents what we often call management judgment. This intuition, perhaps unverbalized but based on solid experience, overrides strict adherence to the product-cost reduction tactic with sufﬁcient frequency to mitigate the misdirection provided by the least cost model. Second, although the more exciting aspect of an Archimedes point is dynamic results, the Archimedes point concept also has a converse attribute. When changes occur in areas of an organization that do not contain an Archimedes point, there is little bottom-line effect. Hence, even though many decisions are made in a manner that resulted in the relatively minor $5,000 loss portrayed in the thinking bridges example, occasionally powerfully correct decisions are also made.12 Even though the data that managers receive include many misleading signals, the data are sometimes likely to touch on the critical areas. These lucky hits provide enough sense of false hope and security to last until the next lucky break Notes 19 happens. The company in the example would be in good shape if it made one $133,880 “right” decision for every 10 or 20 $5,000 “wrong” decisions. But controlling destiny by the roll of the dice—and knowing it—produces fear and anxiety. Third, perhaps the effective goal of the organization is something other than increased shareholder proﬁtability. When we discuss cost-based pricing in a later chapter, we will see that an operating strategy based on product cost can be successful under certain conditions. One of these conditions is that the managers of the ﬁrm desire only some minimum level of proﬁts, as opposed to the open-ended goal of greater proﬁts. In this case, the company manipulates the pressure to perform, replacing the anxiety associated with the roll of the dice with the comfort of knowing that the costs will be covered with each sale. This strategy, of course, assumes that the sales will be made. Finally, maybe these organizations are not actually so great. We tend to perceive wealthy people and large organizations as being successful and having the ability to know the right thing to do. We then carry this reasoning one step further and feel that if they do something, it must be right, and so we attempt to imitate it. But are the operating results of these organizations really so good? Management of these organizations comes under tremendous pressure to show good results on a repetitive quarterly basis. If the roll of the dice is such that the reality of the results does not match the expectation for the quarter, there is pressure to manipulate the reported results. Many of these same companies are downsizing or rightsizing, which seems to be the ﬂavor of today’s explanations for massive layoffs, are taking extraordinary restructuring charges on their ﬁnancial statements on a recurring basis, and are reducing their dividends. Still, there is such a need for a thinking bridge to link actions with their bottom-line effects. If it is not to be the least-cost model, then what should it be? The global measurements T, I, and OE questions were the alternative method used to evaluate the proposals in the example. But note that the power of this method came not from the T, I, and OE metrics alone, but rather from understanding the impact of an Archimedes point on bottom-line improvement in each speciﬁc scenario and the ability of the T, I, and OE metrics to predict that impact. Understanding the impact of Archimedes points on the bottom line is a key to locking in a process of ongoing improvement. NOTES 1 H. Thomas Johnson and Robert S. Kaplan, Relevance Lost: The Rise and Fall of Management Accounting (Harvard Business School Press, 1987). 2 Eliyahu M. Goldratt, The Haystack Syndrome: Sifting Information Out of the Data Ocean (North River Press, 1990).

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