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7 Signs You’re Relying on Poor Quality Data

Energy and real estate professionals are well aware that they can’t move initiatives forward without the data to back them up. While most know that they need data and likely have procedures in place to access data, they may not be powering their programs with the most accurate and timely information at hand, leaving themselves at a disadvantage.

Here are seven signs that you’re relying on poor quality data:

You’re missing information

If you’re not using the right tools to collect your energy, water, waste, and carbon data, you’re most likely not getting the level of detail that you need. Access channels for consumption data like electronic data interchange (EDI) often leave out important data points from the original bill. Or, if you’re sourcing your data from the accounts payable department, you’re able to get information on bill totals, but you don’t have the granular data on consumption and cost for each site or facility that you need in order to make effective recommendations.

You’re waiting on costly delays

Let’s see if this situation sounds familiar: Your boss tells you they need the latest report done by the end of the day. You, on the other hand, are missing several pieces of information about specific sites that won’t be delivered until the end of the month, or whenever the utility decides to deliver the bill. Utility data is often made available on the provider’s website before you receive the actual bill, but you don’t have the time to go searching on every site. You need instant access to data in a centralized place so you can build your reports quickly and easily.

You spend too much time on menial tasks

Do you feel like you’re spending the majority of your time on manual tasks? Without effective data management in place, you could be manually organizing data from various paper and digital sources, calling up individual providers to fill in missing gaps, and keying in that data into spreadsheets, dashboards, or ENERGY STAR Portfolio ManagerⓇ. You may have become accustomed to it as part of your daily life, but it doesn’t have to be that way. Automating this process will free up your time to do the job you signed up for: planning efficiency projects, making recommendations, and driving innovation.

You don’t have enough actionable insights

You don’t just need detailed data to do your job effectively; you also need consistent access to it. Looking at a couple months’ worth of consumption data is all well and good, but you’ll need at least a year’s worth of historical data to even begin to see a clear pattern in your organization’s energy, water, waste, or carbon impact. Nor will you be able to make confident predictions around future consumption or prove ROI on your projects without granular data and clear visualizations.

You’re seeing too many errors

Nobody’s perfect, and that’s why you can’t expect yourself or your team to be perfect at manually entering data into your system. There are bound to be errors that arise, and data that hasn’t been audited by an external platform won’t make it clear whether those errors are coming from human mistakes or from the utility providers.

You struggle to analyze your data

With over 3,000 electric utilities and more than 150,000 public water utilities in the United States alone, managing data analysis for every disparate provider on your own is a nightmare. Each provider comes with its own formats, fields, and labels, and there’s little standardization in the industry. If you don’t have access to normalized data, it’s no wonder if you’re feeling the struggle when it comes to data analysis.

You’re missing opportunities

Unless you’re using a data management system that you trust, you’ll always be wondering whether you’re getting the most out of the data you have. Relying on poor quality data will expose you to unnecessary risk, leave you unprepared for sudden changes in rates and prices, and hold your sustainability program back from reaching its full potential.

If these signs sound familiar to you, it’s time for a change. Better quality data is out there.