In today’s business landscape, making smart decisions is both harder, and more important than ever. You’re constantly bombarded with an avalanche of data from seemingly every angle, and gut decision-making can only take you so far. This is where data-driven decision-making can change your business – and all it takes is a few changes and some good old sweat!
Today I’ll be going over a few small steps you can take – without hiring a dedicated data scientist – to improve your business decision-making and get the results you want.
Begin With a Goal
This might sound like a no-brainer to anyone who’s ever had a strategy meeting (all of us), but it’s mission critical to start your campaigns and projects with a goal, and most importantly, a way to benchmark and measure that goal.
I’m sure you’ve heard of it before, but your goals should be smart, and when I say smart, I mean specific, measurable, attainable, relevant, and time-based! This will set you up to be responsible for your own success, with a framework for success and benchmarks so you can see what is and isn’t working.
Organize Your Data
You can’t implement a data strategy if you don’t know where your data is, and in what condition it’s in. Take time to understand where your data is stored in your organization, how it’s organized, and what tools you need to work with it.
For example, imagine that you’re looking to decrease freight spend by 10% this month – where is all your transportation data? How accessible is this data? Is it stored in a centralized cloud location? On paper? On excel spreadsheets? Figure it out so you can begin a plan to clean it up.
Visualize Your Data
This is one of the most under-appreciated aspects of running a data-driven business. Oftentimes, the trends you need to see and analyze can be understood instantaneously with a good graph, oftentimes with very little statistics work required.
As a decision-maker, sometimes it’s more important to recognize the overall trend than specific numbers – a graph can tell you instantly and intuitively that sales dropped exponentially, in a way that a table of numbers just can’t. This doesn’t have to be expensive or complicated either – FreightPath has great built in analytics support for a variety of logistics KPIs, for example, and Excel has a great built-in graphing platform if your data is still in CSV’s.
Like any science, good data science relies on the scientific process – making a hypothesis, testing a small change, and observing the results. This is key! Just because you notice a trend, you shouldn’t jump to change your entire strategy overnight.
Decide based on your data, insights, and trends a single change you can make in your strategy to impact your benchmarks or KPIs (Key Performance Indicators), then follow through and look at the results! Be honest with yourself – did the change work? How much did it change? What could you have done better? After doing this, come up with a better change; rinse and repeat. This is the essence of good data-driven decisions – test, observe, evaluate, repeat.
With these small tips in place, your organization should be well on its way towards becoming more data-oriented and making better-informed decisions. Remember, the first step is always the hardest one, so don’t be afraid to make mistakes!