ADDING VALUE TO PERFORMANCE MANAGEMENT WITH BUSINESS METRICS
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1 ADDING VALUE TO PERFORMANCE MANAGEMENT WITH BUSINESS METRICS Scott Chapman American Electric Power A great deal of system and human effort is expended to collect detailed technical measurements. These measurements are usually stored in some form of a Performance Database, or PDB. However, these data do little to help us understand the purpose of those systems: supporting our business. These basic performance measures tell us very little about the systems business value. To understand that business value we need to collect data about the work being performed in business terms. That data could be stored, along with selected technical measurements, in a Business Metrics Database, or BMDB. Introduction The disciplines of performance management and capacity planning are nearly as old as computer science itself. Most large organizations have staffs dedicated to both functions and even small to mid-size companies often have at least some processes in place. Typically, detailed technical measurements are collected, analyzed, summarized, stored and then dutifully reported to management. This allows us to proudly state that we did x million CICS (or database, web, etc.) transactions at an average response time of y milliseconds yesterday. We may then show how those numbers have trended over the past several days or weeks or even months. We can then show how our CPU utilization has increased with the additional transaction volume or that our database is now ntb. If we re sophisticated, we may even use modeling tools to predict future response times and utilization levels based on estimates of future workload increases. All of this is useful, but it misses a very essential point: it doesn t communicate what the systems are doing in business terms or why the workload is doing what it is doing. We certainly do need to understand how many CICS transactions or web hits we handled yesterday, but we also need to relate that to business terms. For example, how many time records were entered yesterday? How many employees used the system? How many time entries are stored in the database? Certainly most vendors understand that the speeds and feeds are not what drive the decision to purchase their products. Read any vendor press release and you ll find lots of verbiage about how their product will help your business; the technical details are secondary. Although not a prevalent practice, some vendors have even negotiated their payments to be based on their customers business volumes. The term business metrics can be used to describe the information that is related to business work that systems are performing. Just as we collect technical performance and capacity measures and store them in some form of performance database (PDB), I suggest that we need to start collecting and storing business metrics. Such a store of business metrics could be termed a business metrics database or BMDB. Once there is such a store of business metrics, it becomes possible to report those business metrics alongside more traditional technical measures of application performance and resource utilization. Indeed, storing high-level application performance and capacity measures in the BMDB simplifies consolidated reporting of all three dimensions of the application: business function, performance, and capacity utilization. 1 Only then, when we understand the relationships between the business work being performed, application performance and system resource utilization can we truly begin to understand the applications running on our systems. Why create a BMDB? The idea of creating and maintaining another database may seem daunting, especially if the performance management/capacity planning areas are understaffed. However, the design of the BMDB itself can be quite simple and new measurements can be added over a period of time. Because the goal of
2 Figure 1: Sample Consolidated Application Report the BMDB is to relate business measures to system performance and utilization, a BMDB has the potential to improve performance management, capacity planning, and management reporting. Additionally, the data from the BMDB might be published to help publicize what applications are running on what systems and how those applications relate to the business. In a fully developed ideal implementation, data from the BMDB might be used to validate charge back for the applications or even to negotiate vendor software contracts based on the value of the business work instead of the capacity of the system. The BMDB must be populated with information that is unique to each application. Therefore, the process of determining the metrics to capture requires someone to look at each application from a business perspective. This process may have its own benefits. Getting a performance analyst or capacity planner talking to the people that understand the business functionality may help build inter-departmental relationships that may have fallen by the wayside over the years and iterations of reorganizations. Additionally, the performance analyst will undoubtedly learn more about each application, which can be useful when performance issues arise in the future. The BMDB can be a useful resource when those performance issues arise. For example, if response time has suffered, the performance analyst may note from data in the PDB that there has been a small increase in transaction volume, which has increased contention for system resources. Typically at this point, a furious search is undertaken to answer the question what changed? However, if the BMDB can be examined and it can be shown that the amount of business work has increased, the search for a technical change can stop. Conversely, if the business workload does not seem to have increased, one then does need to look for either a technical change or perhaps an important new facet of the business that the BMDB is not currently capturing. Along similar lines, data from the BMDB can help drive capacity planning in business terms. Capturing both business metrics and high-level performance measurements in the BMDB allows the capacity planner to build expectations for technical measures based on business measurements. Capacity planners often do this today, usually based on a rough estimate along the lines of if we increase the number of
3 accounts by 10%, then transaction volume will increase by 10%. Developing a more formal relationship between business metrics and capacity requirements has been the subject of past CMG papers. 2 Having a historical data store of business metrics is a critical part of being able to use business metrics for capacity planning. Perhaps most importantly is the fact that a BMDB allows you to create that consolidated view of the applications showing the business functions, performance, and capacity utilization all on one screen. This single view of these three important dimensions of the application is something that is not often pursued. (See Figure 1 for an example of such a consolidated report.) However, such a consolidated view can facilitate communication between groups that previously focused only on their individual areas of expertise, such as server capacity, or application performance, or business functionality. Furthermore, it can be used to help communicate the real value the applications are providing to the business. This can help foster a sense of pride in one s work because one can see how supporting that system directly affects the business. Most people would agree that people that take pride in their work produce better work. This may seem like a far-reaching goal for a relatively small database, but not one that is out of reach. What should be stored in a BMDB? A PDB typically stores relatively similar things for all systems, such as CPU utilization, transaction volumes, response times, I/O rates, etc. A BMDB will likely have some common metrics for all applications (such as number of users, response time, etc.), but will also have some unique measurements for each application. Just as with a PDB, a BMDB could store numerous, very detailed metrics for an application, or it could store a few high-level metrics. While a few high-level metrics may be sufficient, in general it will probably be better to store as many detailed metrics as you can find. The BMDB should store metrics related to the three dimensions of the applications as mentioned earlier: business measurements, performance measures, and capacity measures. The performance and capacity measures are more technically oriented than business oriented, but storing them in the BMDB with the business metrics facilitates reporting on all three dimensions of the application. For example, if the BMDB includes a metric of number of calls received, then it is useful to also include the technical measures that those calls generate, such as the number of CICS transactions executed by the call center agents, the response time metrics for those transactions, and the CPU consumed by those transactions. This allows you to easily report that n calls resulted in t CICS transactions at an average response time of r and consumed z CPU time. Tracking that relationship over time is one of the key benefits of the BMDB. In general, the business metrics captured should represent the volume of the work performed as well as the volume of data that the application works on. For example, a BMDB might store the number of items sold each day as well as the number of sales in the historical database and the number of items in inventory. You would expect that these business metrics would relate to corresponding technical metrics such as number of CICS transactions, CPU utilization, disk utilization, and perhaps response time. PDBs often store performance measurements over relatively small intervals, such as an hour or 15 minutes. A BMDB would more appropriately store data at an interval that makes business sense. For many applications, this probably means a single day. While there may situations where having business metrics on less than a daily interval would be useful, most of the benefits of a BMDB can be realized with daily data, and the necessary business data is probably more readily available on a daily basis than on an hourly basis. Storing only a single value per metric per day also reduces the overall size of the BMDB. The business metrics for each application should minimally reflect the volume of the most significant aspects of the application. Ideally, the business metrics should be measurements that can be correlated to the technical measurements of the application s resource utilization. Having any metrics is better than having none, and it may not be necessary to capture all aspects of an application s business functionality to understand the primary behavior of the application. Aim to first capture the highest-volume or highest-value business functions and a measure of the business data that is stored by the application. Over time you can add additional metrics, but get the most important metrics into the capture process as soon as possible so you can start building their history. The most important business metrics to capture are those that are important to the business unit. But what metrics are important to the business? A good place to start would be to look at any service level agreements (SLAs) that are already established, as presumably the SLAs are related to measures that the business deemed important at one time. However, SLAs may not be updated to keep pace with business changes, so if the SLAs have not been recently reviewed, the creation of the BMDB is a good excuse to do so. For the SLAs that are valid, be sure to capture the necessary technical and business measures to report the SLAs and the business work that affects them. This allows you to show how the
4 business volumes affect your SLA attainment, or perhaps how your SLA attainment (or lack thereof) affects the business. Since the data in the BMDB lends itself well to being used for capacity planning, it might make sense to store high-level capacity planning data in the BMDB as well. While your business measures will probably be captured on a per-day basis, you may choose to capture technical capacity measures on a smaller interval that makes more sense for capacity planning. For example, it may be useful to capture peak loggedon users, peak transaction volumes, or peak CPU consumption per application. It may be useful to capture not just overall CPU utilization for an application, but how much of that CPU utilization came during the daytime and how much came overnight. These technical measures are probably already being captured in a PDB or a Capacity Planning database, and you may not wish to summarize or duplicate the data in the BMDB, but doing so may make some future reporting easier. As the BMDB will contain data from multiple applications, consider calculating and storing Apdex values for each application. Apdex is a measurement that purports to represent the users satisfaction with application performance in a manner that is directly comparable across applications with different response time measurements. See their website at for more information on this interesting idea. How to get started The heart of what the BMDB is trying to accomplish is to relate business processes with IT systems. This is not a new concept. Most formal frameworks that attempt to do this start at the business process and work towards the IT systems. This undoubtedly works well for fully documenting your business processes. However, because the BMDB is attempting to relate business processes to application performance and resource utilization, it doesn t need to document every single business process in grave detail. Therefore, it is easier to start at the IT systems and work towards the business metrics. This has the substantial benefit of being easier for the performance analyst or capacity planner who is already familiar with many of the technical aspects of the applications and systems. A high-level overview of the plan for developing a BMDB could be: 1) Identify and create the database structure 2) Identify the reporting tool(s) to be used and set up shell reports 3) Identify the initial applications to work with 4) Capture technical measures for the initial applications and the systems they reside on 5) For each application, start capturing metrics: a) Identify key application resources to talk to b) Identify the major technical aspects that drive capacity and performance c) Identify the business function of those technical drivers d) Determine how to measure those business functions e) Capture those measurements This is much less difficult than it may first appear! Creating the database structure and reporting architecture is a technical discussion beyond the scope of this paper. The structure can be very simple: the database only has to store a limited number of measurements per day per application. The overall size of the database will not be large, and can easily be implemented as a SAS database, but could also be implemented in whatever database tool you prefer. While any reporting tool may be used, it would be ideal to choose (or develop) one that can be easily extended to produce new reports for new applications. Ideally, these reports would be easily accessible to help facilitate communication across team boundaries. For a detailed description of my implementation of a BMDB, see An Implementation of a Business Metrics Database also published in this year s CMG Proceedings. Your existing capacity planning or performance database may already have the capability of storing the business metrics in it. If so, you may not need to create a separate database at all. One critical thing to consider when making these initial technical determinations is that you will need to automate the process of collecting the metrics and inserting them into the database. Therefore, choosing tools that will be difficult for you to automate will undoubtedly cause you eventual difficulties. An important consideration for choosing the initial applications is to choose ones for which you can successfully find metrics and are comfortable with. If the person setting up the BMDB has particularly good knowledge of an application or has a particularly good relationship with the application support team (or ideally both), then that would be a good application to start with. An alternative strategy might be to pursue an application that apparently nobody knows about. Almost anything you discover about such an application will probably be useful! Moreover, such an application is likely to be relatively small and lightly
5 used so relatively few business metrics should be required to capture the essence of the application. Once you have identified the initial applications (or set of applications), the next easy step is to capture the high level technical measures of performance and capacity utilization. At least some of this information probably already resides in your PDB and will merely need a simple process set up to extract it from the PDB and insert the data into the BMDB. Since these technical measures are already available in existing data stores and merely need to be broken down by application, it may make sense to set up the capture of related technical measures for all applications at once. For example, if you are going to capture batch job CPU time, it may make sense to read through all the batch job CPU records and assign the time from each job to an application. Assign resource utilization that you can t currently attribute to a special application called unknown. Although you probably already have some good methodologies in place to characterize workloads to applications, fully accounting for all utilization by application will be an iterative process. You can monitor the amount of utilization assigned to unknown over time to see how complete of a characterization you have achieved. Finding business metrics for applications Once you have accomplished the relatively minor technical concerns of establishing the database and have started capturing technical measures for a group of applications, it is time for the hard part: actually finding the business metrics. The first step is to identify what metrics should be captured that would reflect the significant business work being performed. In this context, significant means the work that tends to drive the application resource utilization or impacts the perceived performance or value of the application. There are a few different ways to approach this: 1) Look at the significant technical measures, then determine what business functions are driving them 2) Find an expert for the application, and ask him or her what the applications users do with the application 3) Find a representative of the application users (perhaps the owning manager) and ask him or her what the critical components and functions of the application are Attacking the problem with the first option is usually relatively straightforward and allows you to quickly get to the goal of capturing business metrics. For example, if you examine detailed transaction logs you will probably find that a relatively small number of transactions account for a significant portion of the application utilization. A quick call to an application support person should reveal the business functions that those transactions perform. From there, you can start to investigate how to measure that business function. If you are lucky, there will be a one-to-one relationship between transactions and business functions performed. This is not typical, but the application support person may still be able to suggest an easy transformation from the number of transactions to business functions. For example, to do function A, they perform x A transactions. Or maybe for function A they perform a variable number of transactions A and B, but they always perform one and only one transaction C for that function, which might not have been on your list of significant transactions. For disk capacity, it s usually simple to find the largest application tables or files and then determine what business objects those tables represent. However, these tables will probably be details for higher-level business objects that are more useful. For example, the table containing detail lines for purchase orders may be the largest table so you may want to capture the number of PO lines. You probably will also want to capture the number of POs as well since that may be a more readily understood metric, and it should drive the number of PO lines. Capturing both the detail count as well as the count of the high level objects lets you compare the ratio between the two measures, which may prove interesting in some situations. If you do not have a good transaction pattern that you can leverage to count the number of business functions performed, you may still have an easy method for finding the business metric relatively close at hand. Applications often keep logs or audit trails of significant processes; therefore, a simple database query may be all that is needed to capture the business metric. For example, if the creation of POs is an important business metric, then to calculate the number of POs created yesterday, a simple SQL statement selecting the count of the number of POs with a creation date of yesterday may suffice. You may even be able to calculate the business metric and insert it into the BMDB with a single SQL statement. These techniques of examining transaction logs and application logs probably will suffice for most metrics. However, there will likely be some business metrics that must come from elsewhere. For example, the transaction volume for a customer system may be driven by the calls into the company s call center. A critical success factor for those call centers might be the number of calls abandoned. So the number of customer calls per day and the number of calls abandoned are probably important business metrics
6 related to the customer system but probably can not be readily determined by examining the transaction or application details. Nevertheless, those values are almost certainly collected and reported on by the call center. Finding the person responsible may be a challenge, but when you explain how you re trying to relate their critical success factors to the application s performance, you ll probably find that they will be quite willing to help. Measures of Success At what point do you consider your BMDB efforts successful? Given the relatively low cost of entry, perhaps much sooner than you might think! The BMDB itself will be small enough (especially to start) that it probably can be hosted within an existing database system on existing server space. Indeed, if you store your PDB in SAS, then it would be entirely possible to store your BMDB in SAS as well no additional software needed. In addition, the physical database size is so small it almost certainly can be hosted on the same system that hosts your PDB. The only cost to get started should be the labor. Creating a BMDB requires you to critically examine your applications and devise methodologies to measure them. This is an ideal time to make sure that you are measuring the applications correctly; that you are attributing your system resource utilization to the appropriate applications. That critical examination of your applications and processes for measuring them will likely reveal important information about the applications. You may uncover minor issues with the application or measurements that no one had previously noticed. Certainly, if you find that your existing reporting is inaccurate or misleading in any way, then your BMDB efforts have already started to pay off. The second level of success will come when you start reporting the business metrics. This data will likely lead to insightful questions, such as: Why do we have three times the number of accounts that we think we should? Why does our call center efficiency not improve as response time improves? Why does this workload always appear around the second workday of the month? Why has our business workload decreased but our application transaction volume increased? Certainly those questions may be uncovered in the normal course of doing your application performance analysis and capacity planning, but frequent and consistent reporting from the BMDB increases the chances that those sorts of situations will be discovered. Reports from the BMDB showing the inter-relationship between application performance, system resource utilization, and business workload can also be used as the basis for discussions between departments. These discussions can increase everybody s awareness of both the business and technical issues facing the organization. The final level of success comes when you are able to mathematically correlate technical utilization measurements for the applications with the applications business workloads. Getting to this point may require quite some time and effort, but you do not have to achieve this ultimate goal to gain value from the BMDB. You may have noticed that the title of this paper refers to adding value to the performance management process, not capacity management. While a BMDB may ultimately greatly enhance to your capacity management process, I believe its more immediate benefits come in the area of performance management. If your BMDB has uncovered insightful questions or issues or sparked discussions, then the BMDB s cost/benefit ratio has already been very favorable. Further benefits, such as improving the visibility of the importance of the applications, can still be realized as you work towards the ultimate goal of correlating business and IT measurements. But the initial payback period for creating the BMDB is very short and the benefits continue indefinitely. It s hard to imagine how a BMDB implementation could not be successful! Conclusion As performance management and capacity planning professionals, we need to move beyond merely reporting the speeds and feeds of our systems to capturing, evaluating, and reporting on the business functions that our systems perform. Relating business metrics to performance and capacity metrics can help bridge the gap between those responsible for the technology and those responsible for the business. By starting at the technical measures and then finding the measures of business work that relate to the individual applications, one can start to build up a historical data store of the business metrics relatively easily. The process of building the BMDB will probably be useful by itself: the technicians will learn more about the applications and the business. The discussions between the different groups may even lead to the discovery of areas for improvement. Once created, the BMDB can then be used to improve management reporting, performance analysis, and capacity planning, and may lead to a new appreciation for just how valuable your IT systems really are.
7 References [BRO90] Browning, Tim, Forecasting Computer Resources Using Business Elements: A Pilot Study, CMG Proceedings 1990 [MOL05] Molloy, Chris, ITIL Capacity Management Deep Dive, CMG Proceedings 2005 [RAS93] Rashid, Teymoor, Hardware Projections Using Natural Forecasting Units, CMG Proceedings 1993 [REY87] Reyland, John, The Use of Natural Forecasting Units, CMG Proceedings This is very similar in concept to ITIL s subprocesses of business, service, and resource capacity management. See [MOL05]. 2 See for example [REY87], [RAS93], and [BRO90].
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