Cost Management - Part 3
Data Collection and Analysis

By Allen C. Hamilton, PMP, CCE

The first two articles in this series introduced the subject of cost management on capital projects, identified its key steps, and discussed cost estimating and cost control. This article discusses data collection and analysis.

Data collection and analysis is one of the most neglected areas of cost management. Data collection and analysis is the process for collecting, analyzing, and applying project historical information to benefit projects. At its best it is logical and methodical in gathering and using this information. All companies and organizations can benefit from this process. Lack of this effort will burden organizations with repeating past mistakes.

It is widely noted that organizations spend a lot of resources to estimate and control but when it comes to collecting and using this experience, the effort falls short. Some efforts to collect data depend on the availability of resources. These resources are frequently hard pressed and are usually busy with current problems and deadlines. It is too easy to neglect data collection until mistakes or inefficiencies are shown after the fact. It has been noted that data collection and analysis link and support the other steps in both the cost management cycle and the project process. The data collection and analysis function can be summarized by the following cycle.

Historical information can be utilized in a variety of ways on projects. The range can be from simple collection to an integrated strategic tool. The collection and use should have a specific benefit to the organization. Potential benefits include more accurate estimates, faster and cheaper bidding, and more profitable projects. Efficient storage can make retrieval quicker and easier. All projects should have a proper close out where the information is collected and handled by prescribed procedures.

A key to data analysis is the input to a system that reflects the specific needs of the organization. These information needs should be established in a plan which should also anticipate information needs based on history, current issues, and forecasts. The
collection and input of data will require resources to be applied over a period of time. Inadequate collection and support of the input system will only serve to generate poor information and waste resources.

The first step in the input process is to collect all available data, both historical and current. This information should include cost, time, and technical documents. One should insure that the collection of documents is as comprehensive as is feasible in cost and time. Many projects collect data when the project is finished, and this can be a problem as the resources may be shifted to other projects. Some organizations solve this problem by collecting and inputting as the project progresses.

The selection of what data to collect may present many challenges. The identification of parameters for each primary account and sub-account is necessary. Parameter selection is important to achieving successful use of the information and establishing a system that can be supported and maintained. Selecting too few parameters will restrict and limit the usefulness of the analysis. Selecting too many parameters will burden staff with gathering unused details, hard to populate database, hamper retrieval and restrict analysis.

To be useful, data input requires judgment regarding what actually goes into the system. The data may need to be authenticated from its source to ensure accuracy. Authentication and audit trails also assist in correcting errors if they should occur. In addition there are also examples of projects and organizations misusing the coding structure. The misuse may be simple errors or attempts to mislead the true source of costs. Whatever the reason, if a coding structure is inaccurate, it will require adjustment prior to inputting to adjust for omissions, errors, and misuse. Finally, old and obsolete data should be deleted from the database to present distortions.

The following illustrates a typical data collection summary table.



In this series of three articles, we have identified and outlined the basic steps in cost management: estimating, control, and data collection and analysis. Organizations will need to identify the best opportunities with the resources they can deploy to each of the key steps in cost management. Many organizations have expertise in one or both of the first two areas of cost management, estimating, and control. We have noted some weaknesses in the ability of organizations to effectively manage data collection and analysis consistent with the effort expended in the other areas. The planning and successful implementation of all of these steps in the project process will ensure efficient and effective management of costs.