Creating a Culture of Data-Driven Decision Making at Your Facility

Creating a Culture of Data-Driven Decision Making at Your Facility

If you have been to a major water or wastewater conference in the last five years, you’ve undoubtably come across the phrase ‘intelligent water systems’. At first glance, this may seem like concept reserved for academic theory or large, sophisticated systems, but recent technological advancements have given utilities of all sizes the power to adopt data-driven decision making at their facilities. The two major drivers behind this change have been the rise of data integration and visualization technologies. Integration technologies bring together historically siloed datasets, and visualization technologies bring the data to life. 

While these technological advancements are creating new opportunities, having the right technology is only half the equation.  To be successful, you need to be deliberate about making sure you are using data to solve core business objectives.  Creating a Data Management Plan that defines the value of the data (the why), the needed data quality, and a data governance system, will position you to maximize the benefit of the data you are collecting.  While this may sound daunting, there are easy steps you can take to start down the road of creating a culture of data-driven decision making at your organization:   

1. Define the Value Behind the Data

Successful data-driven organizations begin with the question they want to answer. This question should broadly define the value you wish to extract from your data and will frame decisions around how and what data should be collected and analyzed. A great example comes from the Wastewater Resources Recovery Facility (WRRF) in Tavares, Florida. The Utility Director sought a way to reduce the facility’s monthly electric bills. The challenge was that the facility had already completed the traditional energy saving hacks, such as aeration and pumping upgrades, in a recent upgrade.  However, by looking creatively at their solids handling processes, the WRRF was able to modify the operation of the three aerobic digestion tanks from parallel to series.  The WRRF tracked the impact of this change and found that dewatering processing time, chemical use, aerobic digestion air flowrates, and filtrate pumping times were all reduced, resulting in a 30% saving in their monthly electric bill.  The process changes not only saved money on electricity but also chemicals, labor related to solids processing, and solids disposal. This focus on solids handling defined the data collection and analysis effort and allowed the WRRF to quantify the savings.  

2. Collect Accurate Data

Understanding the question you are trying to answer frames your data analysis, but facilities must be diligent to ensure they are collecting accurate data in a sustainable way.  The wastewater collection system in Tavares, FL has over 90 pump stations in the system.  In 2008, they did not have a timely means to track pumping rates and energy use.  Over the next decade, the utility invested in technology to collect pumping data, evolving from manual readings to SCADA.  They benchmarked the stations for a year and have used this baseline to identify performance issues and prioritize upgrades.  For example, this baseline data allowed them to quickly identify and pinpoint the location of a water main break when pumping rates at the nearby pump station increased for a sustained period. 

3. Empower the People

Perhaps the most powerful aspect of a successful data management plan is the opportunity it creates for employee engagement. By focusing the entire utility around the central goal and giving employees the skills and background the understand and interpret the data, you empower all staff to take a deeper interest into your operational efficiency.  The partnership of the Utility Director and the WRRF team led to the successful solids handing process changes that resulted in energy reductions and operational benefits.

No data management plan is established overnight. Utilities like Tavares, FL have been successful in transforming to data-driven decision making by taking a gradual, step-by-step approach and has been deepening their data collection, integration, and analysis ever since: linking the energy use data from the power company with their SCADA system, using DoForms mobile app to collect data, and implementing a CMMS system.  What started with a simple question of how to pay less for electricity at the WRRF has evolved into a data-driven decision-making culture at the utility.

Author

Senior Technical Manager
Municipal Wastewater

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