6.7 The Data and Decision-Making Cycle

Making good decisions relies on knowledge. Knowledge comes from data but is not equal to it. A utility can have a lot of data and very little knowledge if the data is incomplete, of poor quality, inaccessible, or of the wrong type. For example, a utility may have 2,000 repair records for their main line pipes for the past 10 years. The records are scattered around an office and many of them are incomplete. There is no consistency between the records, so it isn't easy to tell what work was done. Information such as pipe type and size is missing from the records. Clearly, the utility has a lot of data. What it doesn't have is knowledge. This utility would not be able to determine which type of pipe was breaking nor could it comfortably rely on the data due to the poor quality. It would also be hard to use the data because it is in paper form and scattered throughout the office.

When they reach a point where it's breaking at twice our average break rate...is when we would start to proactively replace that pipe. --Kevin Campanella, Columbus, OH

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Instead, utilities need to determine what data they need to collect to gain the knowledge to make good, sound decisions about the management of the assets. Once this determination is made, the need to ensure good quality and thorough record keeping must be passed on to all of the staff.

At the beginning of an Asset Management program, it is highly unlikely that a utility collects all of the data it needs at a sufficient quality, organized in an accessible manner. Most likely, the utility will need to figure out what data it wants in order to improve decision-making. It will also have to establish parameters for the data quality and determine the best method to store the data.

The utility should consider data gathering and decision-making to be a cyclical process. Data will be collected and analyzed to gain knowledge and inform the decision-making process. This analysis will also point out weaknesses in the data, data quality, or data storage system. These weaknesses can be addressed and the process can be repeated. For the first several years of the cycle, considerable gains will be made in the ability to make decisions about the right way to manage the assets each time through the cycle. After that, the utility will still make gains, but the increments will be smaller.

Just as there may be data that is needed and is not collected, there may be data that is collected but not needed. If data is not useful for operations, maintenance, or capital decision-making and there is no other compelling reason to obtain the data, it should no longer be collected. Data should not be collected for data's sake; the collection of data takes time and resources and should only be done if there is a need for it.

...for our highly critical assets, we'll do frequent condition monitoring.... --Scott Maring, Cincinnati, OH

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An example of the data and decision-making cycle is the following. A wastewater utility wishes to determine if something can be done to address sewer back ups. The initial data available is the number, but not location, of customer complaints. The utility doesn't have enough information to proceed, so it can decide to start collecting more An example of the data and decision-making cycle is the following. A wastewater utility wishes to determine if something can be done to address sewer back ups. The initial data available is the number, but not location, of customer complaints. The utility doesn't have enough information to proceed, so it can decide to start collecting more information on each sewer back up. It develops a process to collect data on each back-up on a written form that is filled out in the field. The field data is then input into a simple computer spreadsheet. The data includes date, time, location, pipe type and size, and nature of the problem. Using this data, the utility begins a sewer cleaning program. The utility examines data for sewer back-ups for a year after the cleaning program is initiated to determine the effect. The utility notices that in one part of the utility, there was a significant improvement in the number of back-ups, but in another part of the utility, there was no improvement. Now the utility needs additional data on the sewer lines that are still experiencing back-ups. The utility decides to televise these sewer lines. The televised data show that several lines have severe root intrusion in the sewer. The utility begins a program to remove the roots. Data on sewer back-ups is analyzed for a year following the root removal to determine the impact. The utility determines that the cleaning program and root removal efforts have made a significant decrease in the number of sewer back-ups.

A data decision-making cycle that includes data collection, data analysis, decision-making, and action followed by data collection, data analysis, revised decision, and action can be used to address many operational and managerial concerns within a utility.

The business case showed that this was the way to go. --Eric Saylor, Cincinnati, OH

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