Term Paper: Budgets

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¶ … Budgets

There are a number of different strategies that are used to manage budgets and try to keep them within forecast. It is important to have cost analysis because this is the bedrock of sound accounting in any organization, in particular in a health care organization. There are several strategies for managing budgets. These include the investigation of variances and variance analysis calculations (Cleverley, Song & Cleverley, 2011).

The first step is to understand costs. As Finkler, Kovner and Jones (2007) note, there are a number of types of costs, including average costs, fixed costs and variable costs. All of these are useful in setting and managing the budgets, which highlights the importance of training. Managers in the health care setting need to have a firm grasp of both financial and managerial accounting concepts in order to work with these numbers. It is also worth noting that the budget variance analysis and other techniques are GIGO -- garbage in, garbage out. Thus, the first step in having a great cost control system is to have a budget that makes sense. If the budget bears no relation to reality, then having variances does not mean anything either. There are a few different techniques that are utilized to create great budgets.

The first technique is to start with the prior year's budget and adjust for inflation. This is a natural first step, as rates of inflation are often known are easy to estimate within a range. The manager needs to record what rate of inflation was assumed, because later the variance will be tested for a number of factors, among them the real vs. The projected inflation rate. Another budgeting technique is high-low cost estimation, wherein the high and low costs over the past five years are taken into consideration. This technique to some degree ignores inflation and it ignores projected changes in demand. Regression analysis is a more mathematically-sophisticated version of the high-low technique, for those who are so inclined and want more accurate results. In business, demand forecasts are usually taken into account -- so for example of a certain type of surgery has been growing rapidly of late that trend will be extrapolated into the budget, something that regression analysis does a good job with.

When the actual results start to come in, they can be compared with the budget This is why the budget needs to be good, because this comparison only works when the budget was based on careful analysis. The variance analysis measures the variance of each item of the budget, noting the amount of the variance and perhaps the percentage as well. This variance analysis is the "detection" part of the detection-correction technique that emphasizes finding the variances, then understand the cause of the variance and where necessary taking corrective action. There are times when the variance relates to the assumptions, such as inflation assumptions, but there are other times when something in the business changes. The objective is to find the situations where it was not simply a change in the business that changed the budget but a problem in the company that can be remedied.

As Cleverley (2011) notes, variance analysis aims to find the abnormal variances. Because of the imprecise nature of the budgeting process, there will always be variances, but it is necessary to identify those that represent the largest outliers either on an absolute or percentage basis, and then investigate the causes of those variances. It is the strong variances where the company is going to have the most problems -- with cash flow, costs or inventory accumulation -- so it is with the outliers that the bulk of the energy needs to be focused.

There are two methods of investigating variances that are identified in Cleverley (2011). The first is classical statistical theory, which uses a control chart. This tool looks at the actual results to see which of those are outside of the prescribed variance limits that were set in the original budget. These are the outliers, and they must be investigated.. The other tool is decision theory focuses on the payoff table. The manager will make a rational decision about a variance based on two factors -- is the problem likely to be under control or out of control, and then weighing the costs of an investigation with the costs of letting the problem continue out of control (Cleverley, 2011). This technique is not as attractive because it involves guesswork and essentially accepts that sometimes out of control problems should be let to fester -- this is not a great way to run a business. However, such an approach can be cost effective in the short run, even if it is unlikely to be cost effective in the long run.

2. Appendix A contains the variance chart. The largest variance here in real dollar terms is the salaries, but this is not the largest variance. However, since the budget is written in real dollars it is important to take into consideration the real dollar values. Salaries were substantially more than expected. In this case, the salaries really should not vary this much. An increase in salaries due to an increase in staff members is something that can and should have been predicted. To go 49% over is incredible. Overtime is one way to go over budget, but this figure of 49% organization-wide indicates that there is a tremendous amount of overtime in this organization. Moreover, the level of overtime was apparently not expected, and was not something that the organization faced last year.

This is important to consider because that much extra payout in salaries that was unexpected is crazy. The business actually did much less on the other measures, which begins to paint a picture. For example, the company did not sell any medical supplies. It expected to sell $757 in medical supplies but only sold $14. Reagents were also well down, and medical supplies were, and so was floor stock. How it is that the company could use far fewer supplies than expected by so much more in salary. There should, if things make sense, be a correlation between salaries, supply costs and how many patients there are.

We can see that there were 4.3 extra patients in a day, which tells us that salaries probably should have been higher. Patient figures were 35.8% higher, and if everybody got time and a half for their overtime, in addition to the fact that they worked overtime, it is not hard to see how salaries were 49% higher than expected. What is interesting is that the supply expenses were much lower, because with higher than expected patient volumes they should not have been. Individually, these difference variances are more likely to occur if there were far fewer patients. There a couple of unconventional explanations.

The first is that there was a natural disaster. The salaries were paid overtime for the all the hard work that the staff had to put in, but sales were not conducted -- the medical supplies were given away. Conventional business was down and the medical staff were doing other duties, like helping with first air or other activities. This is the sort of explanation that starts to explain the disconnect between the demand for medical staff but not medical equipment -- maybe they also used donated equipment. I would not be surprised if these figures were from a clinic in New Orleans after Katrina.

3. There are three different benchmarking techniques that seek to improve budget accuracy. The first is with internally developed standards, the second is with engineered standards and the third is with comparative group standards. Internally developed standards are typically based on historical performance, with adjustments such as for expected changes in demand or cost, and for… [END OF PREVIEW]

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