Data visualizations can be incredibly appealing. The prospect of having actionable data on key initiatives available at your fingertips is ideal for any industry, particularly in the Power Generation and Power Delivery sectors.
However, strategic decision making could be misguided if the data the report is built upon is incomplete, incorrect, or redundant. Instead of sorting through useful data, executives are forced to waste time debating whether the data can be trusted.
Even worse, they could end up making regrettable decisions based on bad or flawed data, which can be hugely expensive. IBM estimates it cost businesses more than $3.1 trillion annually. Utility and energy companies are no exception to this trend.
Getting the Data Right
Visualizations filled with inaccurate data or misleading information can trigger serious consequences ranging from schedule and cost overruns, to missed targets, to regulatory action.
The first order of business is ensuring the data being fed into your business intelligence platform is correct. Working with a consultant or third-party versed both in data science and the intricacies of the Power Generation and Power Delivery sectors can be a major benefit. Having data with a consistent high level of accuracy and processes in place for maintainability is critical.
Achieving data accuracy and consistency involves building an adaptable process that defines systems of record, accountability, unique identifiers, and attribute requirements. This may include inputs such as schedule, actual costs, cost forecasts, risk, safety, and other key items on a regular basis.
Establishing the right data sources and setting up a regular flow of information allows for the development of the right metrics. Key metrics and key performance indicators (KPIs) can be used to analyze progress.
Once the visualizations are created, a skilled consultant can be invaluable in helping spot inconsistencies in the data. These inconsistencies can range from duplicate entries, conflicting formatting from different sources, blank values, or errors in inputs such as the wrong date or incorrect values.
Let’s consider the following example from a PFES client where project phases are out of sequence:
- Tree trimming and vegetation removal near power lines is a task of critical importance for all utilities. An initial glance reveals the tree trimming activity is not yet complete along a specified power line. However, the post work verification activity has a reported actual finish date. That would indicate out of sequence work being performed and the need to investigate with the Vegetation Project Manager.
- Digging into the numbers, the consultant finds out that 97 percent of the tree trimming work has indeed been completed. But since every segment of the unified grid has not yet passed work verification, the unified grid should be listed as incomplete for the work verification phase. Knowing this, the work on the project, far from being stalled, is tracking closely to schedule. The project manager may have advanced tree trimming and work certification in other areas, even as work lagged in a few smaller segments. That finding, in turn, provides the information company executives need to assuage regulators, while preventing a hasty and potentially costly transfer of additional work crews to accelerate up the project. Of course, addressing vegetation strike potential clearances and undergrounding distribution lines in areas of dense vegetation are one small part of a much larger challenge ahead for utilities across the U.S. in the coming decades.
Solid Data is a Must Amid Historic Transition
Amid the historic transition towards a decarbonized utility, power and energy sector, the stakes are higher now than ever before for industry executives when it comes to data accuracy.
The price of decarbonizing the grid in the U.S., much of it to be shouldered by utilities and their rate payers, is expected to weigh in at $4.5 trillion according to a Forbes consulting group study.
The Electric Utility sector is ramping up its investments in solar farms, offshore wind and energy storage facilities, and the new transmission lines required to connect these green power sources to the existing grid. Furthermore, the Natural Gas sector is beginning to experiment with green sources such as hydrogen with help from the federal government.
However, as the Power Generation and Power Delivery sectors modernize their critical infrastructure, the importance of having reliable, accurate data available is at an all-time high. As companies move forward, the use of Excel tracking and manual compilation are being replaced with automation in the data collection processes. As utilities prepare to adapt to an increasing volume of projects of greater complexity and regulatory sensitivity, scalable and interactive business intelligence platforms have become a must.
Data visualization supports the critical importance of the foundational work needed to ensure accurate data is being fed into the system.
At the end of the day, it’s all about the quality of your data. Until the right measures are in place to ensure the accuracy, retrievability, and repeatability of the data, even a sophisticated looking dashboard will not be able to provide the actionable insights that are needed.
The Perfect Data Visualization Partner for the Power Generation and Power Delivery Sectors
Our team consists of industry heavyweights that bring substantial expertise to the table for our clients. We partner with you to reduce risk and uncertainty in your capital projects, delivering initiatives on time with significant cost savings while meeting industry and safety standards. Contact us today to find out how we can help.
by Kaylyn Mickelsen, VP of Project Controls and BI Services, PFES and Dana Jones-Harris, Business Intelligence Specialist, PFES
