Municipal water/wastewater utilities today face a multitude of issues, including ever-changing treatment requirements, higher labor costs, aging infrastructure and aging workforce.
Treatment processes are partially automated with some manual aspects, made possible by individuals in the workforce with decades of hard-won institutional knowledge — people who can enter a process area and within moments identify that something is amiss, where the problem lies, and how to address it. Unfortunately, these individuals are most often those closest to retirement age, and will take with them a wealth of institutional knowledge when they exit the workforce.
The higher cost of labor might dictate that the funding that would support a new staff member is allocated to improving the control system tasked with automating the process. From this standpoint, the industry is moving to a paradigm of more fully automated processes with decisions driven by information.
The question then comes down to this: How does the superintendent or director of a utility adapt to this shift to data-driven management, where instead of relying on operators who knew the plant back to front, they are presented with a mountain of data collected by sensors, instruments and equipment, processed in multiple disparate systems, such as SCADA, automated metering, customer information, financial data, GIS and more?
With so many digital and manual systems collecting information, the problem is rarely the availability of data. Cycling through multiple paper reports or electronic spreadsheets to find the numbers, however, doesn’t lend to informed decision making. It is imperative that data be transformed into information (defined as “data with context”), then collected and formatted in a way that facilitates timely and accurate decisions.
The solution is business intelligence, a term which refers to technologies, applications and practices for the collection, integration, analysis, and presentation of business information.1 Business intelligence is meant to take in all the data generated by a business and present easy-to-digest performance measures and trends that will inform management decisions.2 For utility administrators and superintendents, this means finding ways to get more out of the resources at their disposal: extending the life of existing equipment in an informed manner and deploying staff to perform tasks that ensure equipment uptime instead of responding to emergency calls.
Imagine a dashboard that, with a few simple clicks, displays the equipment that cost the most to maintain over the past six months. It assembles the number of incidents involving a piece of equipment, the cost of tools and materials purchased for repairs, and the cost of labor to make those repairs. By having the actual cost of maintenance for equipment, the justification for upgrading or replacing the equipment may become easier. This advantageous technology is more and more becoming an achievable reality.
In the next entry in the series, we’ll discuss some of the underlying systems that contribute to effective business intelligence and some of the potential pitfalls in deployment.