News & Events
Illuminate Your Environmental Data
01 February 2017
The New Year has begun, and annual reporting deadlines are approaching—mounting pressure and a tremendous amount of work on the desks of those responsible for collecting, crunching and compiling environmental data for 2016. If that’s you, how much confidence do you have in your data?
Do you ever feel like measurements and figures are fed into a black box that spits out results for you to collect and report? Without transparent data collection and processing, is it enough to just cross your fingers and hope the data is processed correctly?
The good news is that you can illuminate that process and gain full confidence in the environmental data you report to management, standard holders, auditors and authorities. It’s not about working harder, being more efficient or running additional data quality processes. Rather, it means putting the right tools in place to bring your environmental data into the light.
The Black Boxes
Widely used tools and software may constitute black boxes for environmental data and reporting.
Still in widespread use for collecting, processing and managing environmental data, Excel is a great tool for single users but highly challenging if multiple users need to collaborate. Calculations formulas are hidden in the cells, and references are easily lost in multiple connections.
Legacy understanding of how the spreadsheets work can be lost with a colleague’s retirement. The biggest challenge of Excel, however, is the lack of an audit trail. Data and formulas can be changed intentionally or by mistake, without a trace or record.
Some companies have built their own customised, internal databases with processing capabilities, or use data historians to process environmental data. While a custom environmental database may work for collecting and maintaining large amounts of data, if calculations are made inmultiple systems or databases, you can’t be sure of how the data has been processed, unless you have full access and a good, well-maintained audit trail throughout the different systems.
Even some enterprise-level EHS or EMIS software can act like a black box if the underlying architecture is not built with transparency in mind. Some systems use calculations, factors and data processing actions that are hard-coded into the system and happen behind the open window. To understand the processing, you need to either read the software documentation or try to calculate your way backwards. These systems have potential for systemic errors, which are difficult to spot.
Properties of Transparency
If visibility and understanding of environmental data processing is important to you and your organisation, there are systems designed to include both transparency and traceability. Here’s what to look for in your system’s data handling.
Unit System Conversions
Sometimes a poor unit system can cause problems, where the software is built on one base unit system and data collected in other units is converted back and forth. Depending on the robustness of the conversion, the unit system itself can cause errors in the data. Lack of flexibility can also be a factor, as many systems are unable to cater to users in other parts of the world where metric units are in use instead of imperial ones (or vice versa).
Data Collection Source
For the best data quality and transparency, it’s important to collect data at the lowest possible level, preferably automatically. If your environmental data system receives aggregated calculated values that are processed somewhere else, you don’t have the means to follow the trail and verify your data. If automatic data entry is not facilitated, relying on purely manually entered data introduces the most common error of all: human error.
Factor and Property Handling
Transparent classification, structuring and calculation of data requires proper handling of factors. The best systems equip skilled managers with the functionality to add, edit and change how properties and factors are assigned to different processes within transparent matrices.
The validity of factors can be set for specific periods of time to ensure factors can be outdated and replaced without losing the history. Incorporating public factor libraries further aids this process.
Calculations in environmental management software could range from simple multiplications to complex algorithms with multiple arrays and dependencies. Regardless of how complex the calculations are, data should be processed in a transparent and understandable way. With Emisoft, the calculation formula and factors used are stored together with the calculated data, providing full visibility of how the data was processed.
A complete, detailed audit trail will show how the data has changed over time. This can enable users to generate reports based on historic data to answer questions about which factors have changed, how and why. Such understanding can support your data assurance and build confidence in the data.
Trustworthy, high-quality data is fundamental to effective environmental reporting. Unless the entire data collection, calculation and compilation process is transparent, you cannot have full confidence in your data.
Are there dark areas in your process that you want to illuminate? Bringing your environmental data into the light will not only help you manage your data better, it can provide you with the confidence you deserve and need to do your best work.Return to News & Events