The five biggest pitfalls of analyzing fuel data (and how to overcome them)
Today, as a fuel pricing analyst, you need to be informed, proactive, strategic, and most of all, certain. But do you ever feel like access to poor data means you’re playing a guessing game?
Unfortunately, a “gut feel” approach is minimally effective in the ever-changing world of fuel retail. You need access to clean, complete, and comprehensive market and fuel price data to make smart pricing decisions for your fuel network.
Unfortunately, aggregating and analyzing fuel price data is often challenging. The common pitfalls are:
- Collecting inaccurate data or being unable to fill gaps in that data
- Collecting too much data or collecting data from too many different sources and being unable to tease out what’s really important
- Aggregating, analyzing, and organizing the data inconsistently, leading to issues with data disparity
- Using different margin calculations and techniques, leading to inaccurate and inconsistent reports
- Failing to create the correct data structure and layers to guarantee data model flexibility
As a consequence, analysts are forced to make assumptions. They are often required to guestimate why a certain report shows a certain trend, without any real context, or to make concrete statements about the state of their pricing without relative comparisons to the rest of their market.
In either case, actionable insight is lacking. So, how can you create the seamless reports you need?
Define your goals and capabilities
Great reporting technology only works if you solidify your aim. Before embarking on a data-structuring, report-gathering adventure, pricing strategists and analysts must define their unique business needs and their capabilities today, and then create their data structuring and modeling plans.
In some cases, reporting requirements are requirements because they’re mandated, either by a regulating body or by your executives. In some cases, though, your reporting requirements will be informed by which types of strategic decisions you need to be enabled to make.
Are you hoping to study trends on a longer timeline to understand incremental margin? Do you want to be able to review snapshots of demand in your local market, in order to price differently based on the way your competition responds to shifts in demand?
Whatever your pricing strategy, many data points and external factors are likely to contribute to your decision-making process. Still, you need to understand your modeling and reporting capabilities to know whether you can interpret those data points well enough to accurately inform the decisions themselves.
Completely dependent on the strength of your data, data model, and processing technology, your reporting capabilities can either hinder strategic development or bolster it. You must understand the reporting power you wield today in order to improve it.
Understand all of the properties you collect, from brand influence to traffic counts. Draw out the structure of where your data is housed. Write lists of the tools you use to gather data, slice and dice it, present it back to your team or executives, and more. Create a full picture of your reporting processes and current technologies — and, as a result, avoid those pitfalls we mentioned.
Remove data silos
If your organization, like so many, operates in data silos, then gaining visibility is about more than just a narrow definition of your reporting needs and the technology to make those needs a reality. You need backing from all pieces of your operations and IT teams, and you need your other teams to share or segment data in a secure, reliable fashion. That means everyone has to be on board.
Start by taking an inventory of the tech each team currently uses. If you find massive disparities, it’s a perfect way to start the conversation about moving away from siloed, insightless information — toward something much more effective.
Find the right reporting technology
Once you have a clear understanding of your reporting requirements and your current capabilities, you can select a technology and fuel price data platform that will assist you in reaching your target: decision-making clarity.
Mapping your KPIs and standard informational needs is a first step. Using a report viewer allows you to see all of your tabular data. For example, if you wanted to sort sites by sensitivity and discover new opportunities based on price sensitivity, tabular data, shown through our report viewer, allows that discovery.
If your chosen platform has fuel price data exporting capabilities, you are able to pull competitor information out, in order to explain and present that information to your executives and stakeholders.
Additionally, a good platform will offer in-line reporting and what-if analysis, so you can make a “hypothetical” pricing decision within the tool and see the potential consequences on your volume and profit.
With just these three tools — standard filters/KPI charting, a report viewer, and in-line reporting/what-if analysis — you can successfully run the level of reporting necessary for a small fuel retail business to thrive in decision making. But what happens as your reporting needs change to be more enterprise-level?
The best-performing platforms, like Kalibrate Pricing, allow for direct data-access via in-product exports to common file formats such as CSV or via data APIs, giving you a pipe into the source. How you use that data is up to you. If you have the resources to report effectively and a strong reporting and data operations process, tapping directly into the source data can be an ideal option.
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