At the press of a button, modern software is capable of generating hundreds of insights that landscape contractors can use to monitor the health of their businesses.
It could be sales team data like closing percentage, cancellations, or discounts; it could be statistics tracking the call duration account managers have with clients; or it could be metrics on how efficiently the crews are out doing the jobs.
But all those numbers are completely worthless without being able to understand them. That’s why Caitlin Justice, the director of finance at Blades of Green Lawn Care and B.O.G. Pest Control, walked Lawn & Landscape Technology Conference attendees through data visualization best practices. The advice she offered could help a contractor communicate the story numbers tell and let data guide their decision-making process.
“It’s critical to be able to turn (numbers) into meaningful insight,” she said.
CHOOSING YOUR CHART. Though there’s plenty of variations of these charts, Justice offered five basic types of visualizations: line graphs, number/gauge charts, bar charts, maps and heat maps.
Line graphs are mostly used to show how numbers change over a period of time. Justice showed an example comparing Blades of Green’s cancellations year over year. Each colored line represented a different year, and the y-axis represented each month of the year. Visually, Justice could quickly show what years had the highest cancellation rates and when.
Number and gauge charts could help quite simply show how close a team is to its goal (i.e., we’ve sold this much, here’s the end goal). They’re often stylized to look like a gas gauge in a car, showing how much of the variable remains.
Bar charts, like line charts, are also used often to compare multiple variables, though they’re better served in comparing and contrasting data differences rather than a change over a set period (i.e., how many clients have cancelled in just one year and which month, rather than a year-over-year analysis). Maps are great for showing data that deal with geographic numbers (i.e., cancellations by zip codes), and heat maps can show data density (i.e., where on your website people are clicking most).
WORDS OF WISDOM. It’s not all about the numbers; Justice reminded attendees that once you’ve built a graphical analysis of data, it’s about figuring out what the story being told even means. For instance, they were able to effectively prove to their team that cancellations were a big problem. But they were able to solve the problem because they determined the root cause.
“You look at it and go, ‘What is going on?’” Justice said. “This is a great communication tool for our team.”
Justice recommends some basic judgment when deciding how to showcase the numbers. For example, green numbers are often associated with good data, while red numbers will often communicate that the numbers have a negative connotation.
Additionally, she warned attendees that not everything is a key performance indicator – in other words, don’t just send out a bunch of graphs and hope someone knows what to do with the numbers. Provide strong recommendations and divide up the work among your team to let each division handle the data most significant to them.
“You need to make sure that the data that you’re sharing is being shared with those that’s directly affecting those individuals,” Justice said. “If you share too much information, it’s going to be overwhelming.”
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