The Data Consumption Dilemma: 4 Pitfalls to Avoid
Data is as critical to your business as ingredients are to cooking. For example, it’s almost impossible to find food that doesn’t contain wheat, because it’s a critical component in so many of the things we eat. But flour is good for nothing on its own—it doesn’t burn or give you heat, you don’t eat it, and you can’t build a shelter with it.
Your data is exactly the same. Everything in your company runs off of data, but the numbers can’t stand alone—they need to be combined for specific purposes before they help you put food on the table. Below are the pitfalls to data consumption and the remedies to turn your data into the “secret ingredient” for your business:
1. Like Ingredients, Data Can’t—And Shouldn’t—Stand Alone
Having a data source or a metric is like having a bottle of cinnamon: super critical for dozens of uses, but pretty awful when you take it on its own.
And business professionals understand that a single point of data can’t stand on its own; that’s why we all have dozens of data sources spitting out numbers, metrics, ad KPIs for departments throughout the company. Unfortunately, having all of these numbers residing strictly in their respective departments is much like keeping your spices in their bottles and never using them to season a meal.
You see where I’m going here?
Let’s follow a typical data consumption scenario: revenue is up 12% from last month and 22% from the month before—hurray! So what caused the lift? You increased your call center by 10%, your web traffic was up by 25%, and your brick-and-mortar saw 14% more foot traffic. Which was the cause? What do you need to invest in to give consumers what they’re look for? How can you know without the guesswork?
If you’re not looking at all your KPIs together in real time on an executive management platform, you’re flying blind.
2. Great Data/Ingredients Don’t Always Equal a Great Outcome
Remember that time you tried to make dinner and the fire department ended up outside your house? There’s no doubt that you bought the highest quality meat, but things can go south quickly if it’s not put together right.
When you’re using your data, the context and interpretation is everything. With very little effort, an employee can use a very expensive data source to give you doctored, late, or just plain incorrect data. You start using that data to put together objectives, and poof! Time to bring in the fire brigade.
3. Timing Is Everything
You pay a pretty penny for your data analytics, but without an executive management platform, you’re probably getting delayed information and reacting to outdated issues. It’s like paying for a nice restaurant and getting whipped cream on your salad and creamy Italian dressing on your gelato—good stuff, wrong place.
4. The Recipe Matters
If you’re comparing numbers from different platforms that are not set up to measure the right metrics, you may be trying to reconcile apples and oranges. Do you know what an apple pie tastes like when apples are switched out for oranges? If you can picture what that would do to your next dinner party, then you’re starting to get the idea of what the wrong numbers can do to your business.
Have you had any data pitfalls you can share? What are some of your best practices for getting accurate info? Share it in the comments!
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