In my previous article, I used the most complex service I could imagine—a distributed Web-based application running in a virtualized environment—to illustrate that you cannot take a bottom-up approach to achieve fair cost apportionment in a cost-effective manner.

Instead, I recommend using a top-down approach; using the simplest method possible and then progressively drilling down until fair service costing can be achieved with a manageable level of effort. In this article, I will elaborate on that theme and provide some recommendations for drilling down. I will use a familiar example to illustrate how one industry has achieved optimization. Then I will apply the techniques to our use case.

Non-IT Use Case

The fast food industry provides us with an illustrative use-case: determining appropriate costing methods for a sandwich. First, note that they do not measure the exact time it takes to prepare and sell your sandwich (e.g., 35 seconds of cook time, 27 seconds at the register). Nor do they measure the exact amount of onions, pickles, and other condiments that comprise your sandwich.

Measuring onions and pickles for a single sandwich seems ridiculous, but this approach mirrors the naïve, bottom-up approach that many IT departments have pursued in costing their services. Instead, the fast food industry has used a number of techniques to “rightsize” their costing model. Those include determining which cost elements are best dealt with as being direct (e.g., number of sandwich patties, cheese) and which are best dealt with as being indirect (e.g., onions, pickle chips).

Next, they determine what cost elements are best dealt with as being unabsorbed. Many times a statistical proxy is used rather than actual measurements for apportioning absorbed and unabsorbed costs. For example, one might know that, on average, a 10-pound bag of onions with an estimated cost of $X will yield Y sandwiches. Thus, the cost of each sandwich includes an estimated unit cost of $X/Y for onions, whether the consumer want onions or not. The fast food industry has determined that providing a discount for not using onions adds cost and complexity while adding little benefit to customers.

Next, they take unabsorbed overhead (e.g., rent, salaries, electricity) and distributed those costs across all cost items as a percentage uplift. Finally, they apply business logic to modify user behavior and perform demand management. For example, knowing that the profit on French fries is huge, they formulate special meal packages which induce their customers to buy fries by providing an embedded discount on sandwiches. Let’s now apply similar techniques to our IT use case.

Direct Cost Elements

In the case of our IT scenario, we probably have services that utilize dedicated resources. These cost elements are simply assigned to the services they support. This might include dedicated physical servers, software, hardware and personnel.

Easily Measurable Indirect Cost Elements

This might include resources such as the mainframe. Since the mainframe was created to manage a shared resource, usage accounting mechanisms were built in and have bee used by most organizations for over 40 years. Although UNIX and other distributed environments are similar, applications have to be instrumented correctly so that usage by service is captured.

For example, if your applications all run under the super user ID, you will not have the metric data required for accurate apportionment. Network environments are similar, where DHCP is used and not configured in a manner to allow mapping of usage data to specific services. Cost elements that are not easily measurable can be left unabsorbed or absorbed using a proxy metric.

In my previous article, I used the most complex service I could imagine—a distributed Web-based application running in a virtualized environment—to illustrate that you cannot take a bottom-up approach to achieve fair cost apportionment in a cost-effective manner.

Instead, I recommend using a top-down approach; using the simplest method possible and then progressively drilling down until fair service costing can be achieved with a manageable level of effort. In this article, I will elaborate on that theme and provide some recommendations for drilling down. I will use a familiar example to illustrate how one industry has achieved optimization. Then I will apply the techniques to our use case.

Non-IT Use Case

The fast food industry provides us with an illustrative use-case: determining appropriate costing methods for a sandwich. First, note that they do not measure the exact time it takes to prepare and sell your sandwich (e.g., 35 seconds of cook time, 27 seconds at the register). Nor do they measure the exact amount of onions, pickles, and other condiments that comprise your sandwich.

Measuring onions and pickles for a single sandwich seems ridiculous, but this approach mirrors the naïve, bottom-up approach that many IT departments have pursued in costing their services. Instead, the fast food industry has used a number of techniques to “rightsize” their costing model. Those include determining which cost elements are best dealt with as being direct (e.g., number of sandwich patties, cheese) and which are best dealt with as being indirect (e.g., onions, pickle chips).

Next, they determine what cost elements are best dealt with as being unabsorbed. Many times a statistical proxy is used rather than actual measurements for apportioning absorbed and unabsorbed costs. For example, one might know that, on average, a 10-pound bag of onions with an estimated cost of $X will yield Y sandwiches. Thus, the cost of each sandwich includes an estimated unit cost of $X/Y for onions, whether the consumer want onions or not. The fast food industry has determined that providing a discount for not using onions adds cost and complexity while adding little benefit to customers.

Next, they take unabsorbed overhead (e.g., rent, salaries, electricity) and distributed those costs across all cost items as a percentage uplift. Finally, they apply business logic to modify user behavior and perform demand management. For example, knowing that the profit on French fries is huge, they formulate special meal packages which induce their customers to buy fries by providing an embedded discount on sandwiches. Let’s now apply similar techniques to our IT use case.

Direct Cost Elements

In the case of our IT scenario, we probably have services that utilize dedicated resources. These cost elements are simply assigned to the services they support. This might include dedicated physical servers, software, hardware and personnel.

Easily Measurable Indirect Cost Elements

This might include resources such as the mainframe. Since the mainframe was created to manage a shared resource, usage accounting mechanisms were built in and have bee used by most organizations for over 40 years. Although UNIX and other distributed environments are similar, applications have to be instrumented correctly so that usage by service is captured.

For example, if your applications all run under the super user ID, you will not have the metric data required for accurate apportionment. Network environments are similar, where DHCP is used and not configured in a manner to allow mapping of usage data to specific services. Cost elements that are not easily measurable can be left unabsorbed or absorbed using a proxy metric.

In my previous article, I used the most complex service I could imagine—a distributed Web-based application running in a virtualized environment—to illustrate that you cannot take a bottom-up approach to achieve fair cost apportionment in a cost-effective manner.

Instead, I recommend using a top-down approach; using the simplest method possible and then progressively drilling down until fair service costing can be achieved with a manageable level of effort. In this article, I will elaborate on that theme and provide some recommendations for drilling down. I will use a familiar example to illustrate how one industry has achieved optimization. Then I will apply the techniques to our use case.

Non-IT Use Case

The fast food industry provides us with an illustrative use-case: determining appropriate costing methods for a sandwich. First, note that they do not measure the exact time it takes to prepare and sell your sandwich (e.g., 35 seconds of cook time, 27 seconds at the register). Nor do they measure the exact amount of onions, pickles, and other condiments that comprise your sandwich.

Measuring onions and pickles for a single sandwich seems ridiculous, but this approach mirrors the naïve, bottom-up approach that many IT departments have pursued in costing their services. Instead, the fast food industry has used a number of techniques to “rightsize” their costing model. Those include determining which cost elements are best dealt with as being direct (e.g., number of sandwich patties, cheese) and which are best dealt with as being indirect (e.g., onions, pickle chips).

Next, they determine what cost elements are best dealt with as being unabsorbed. Many times a statistical proxy is used rather than actual measurements for apportioning absorbed and unabsorbed costs. For example, one might know that, on average, a 10-pound bag of onions with an estimated cost of $X will yield Y sandwiches. Thus, the cost of each sandwich includes an estimated unit cost of $X/Y for onions, whether the consumer want onions or not. The fast food industry has determined that providing a discount for not using onions adds cost and complexity while adding little benefit to customers.

Next, they take unabsorbed overhead (e.g., rent, salaries, electricity) and distributed those costs across all cost items as a percentage uplift. Finally, they apply business logic to modify user behavior and perform demand management. For example, knowing that the profit on French fries is huge, they formulate special meal packages which induce their customers to buy fries by providing an embedded discount on sandwiches. Let’s now apply similar techniques to our IT use case.

Direct Cost Elements

In the case of our IT scenario, we probably have services that utilize dedicated resources. These cost elements are simply assigned to the services they support. This might include dedicated physical servers, software, hardware and personnel.

Easily Measurable Indirect Cost Elements

This might include resources such as the mainframe. Since the mainframe was created to manage a shared resource, usage accounting mechanisms were built in and have bee used by most organizations for over 40 years. Although UNIX and other distributed environments are similar, applications have to be instrumented correctly so that usage by service is captured.

For example, if your applications all run under the super user ID, you will not have the metric data required for accurate apportionment. Network environments are similar, where DHCP is used and not configured in a manner to allow mapping of usage data to specific services. Cost elements that are not easily measurable can be left unabsorbed or absorbed using a proxy metric.

Unabsorbed Cost Elements

Determine which cost elements remain unabsorbed and identify potential proxy metrics for their apportionment. Proxy metrics can be derived any number of ways. The above example uses a statistical proxy—average cost of onions per sandwich. An IT-based metric might be the average number of database transactions per HTTP request. In this case, HTTP requests can act as a proxy to represent the number of database transactions, network usage, and application server usage.

This would eliminate the need for real-time monitoring across those components of the distributed environment. Another example would be to use transactions against the virtual environment (e.g. the same HTTP request) as a proxy for usage of the physical environment, thus eliminating another level of real-time monitoring.

Allocate Remaining Unabsorbed Costs

Remaining unabsorbed costs might include accommodation and supervisory salaries. Metrics to allocate these costs can include the number of services, or the number of users of the service or even a proportion derived from the apportionment of all direct and absorbed costs.

Apply Business Logic

Having formulated a hypothetical cost model, you will want to rationalize the model against the objectives of your business. For example, it might seem wise to allocate resource costs for a service desk application running on a virtual environment with an actual usage metric.

But when you consider that the service desk was added to increase user productivity, you might decide  it is in your company’s best interest to treat usage as an unabsorbed cost. Otherwise, as those costs turn into charges, you might dissuade users from utilizing the service desk, thus reducing their productivity.

Another example would be to determine that the benefit of measurement does not warrant the cost. Again, in this case you might elect to treat and indirect absorbed cost as an unabsorbed cost, using some high level metric as a proxy. In order to ensure you are aligned with the business, you need to discuss the model with the appropriate business managers.

Summary

There are a number of techniques to allocate costs to services. Each has its merits. Start as simply as possible. Take a top-down, business-driven approach. Add complexity only when it provides proportional benefit. This will lead to cost models that are simple and manageable. In our next articles we will turn our attention to service level management and how service level compliance measurement can be rightsized.

Frank Bucalo is a senior architect at CA. Frank has more than 20 years of experience implementing business applications for the Wall Street community. Over the last five years, Frank has a track record of successfully delivering ITIL implementations – from business analysis, through intelligent design, and technical implementation.