Instinctive Response vs Analysis
Today’s post is from our SafeSourcing Archives
When first seeing a complex problem our intuition is to try to take it all in at once, but this often leads to feeling overwhelmed by the size and complexity of the information and not knowing where to begin. It’s easy to get so focused on the substance of a problem, that we pay inadequate attention to the analytical process. The instinctive reaction to problem solving is to start going in a direction, any direction because we just want to get started, and see what turns up.
Starting an analysis without an appropriate analytical structure in mind can lead to a critical failure in your conclusions by:
• Using processes where data is corrupted by incorrect manipulation
• Allowing bias into your analysis by looking for data that supports your assumed conclusion
• Answering questions that were the wrong questions to begin with
• Missing clues in the information that could have informed your process early on
Below we offer a basic outline to approaching a problem that involves a large data set. Keep in mind, this is just a starting point, but one that may help prevent you from going too far down a wrong path:
1. Identify the goal: This helps us identify our angle of attack, our strategy for how to break down the data. Not to be confused with identifying the answer. The goal may be “to identify the spend in X category”, but cannot assume what the results will be until the data speaks for itself.
2. Identify the constraints: Not all data sets will contain the information required to perform an analysis. Some problems require some back and forth from your source before you will have all of the variables needed to solve. Does the data contain relevant information to our goal?
3. Identify the correct method for attacking the problem: The methodology chosen must be appropriate to the puzzle you are trying to solve. Do transactions need to be re-categorized? Do we need to prove the data is inclusive of all fees attached to each PO? Does it need consolidated and normalized?
4. Break down the problem into its constituent parts: The more complex the problem, the smaller “chunks” you will want to break the problem into and solve individually before regrouping and piecing any broad conclusions.
5. Tell the story: Once you have problem broken down into manageable chunks, establish patterns that tell the story behind the data with as specific of information and numbers as possible.
For more information on how SafeSourcing can assist your team this process or on our “Risk Free” trial program, please contact a SafeSourcing Customer Service Representative. We have an entire customer services team waiting to assist you today.
We look forward to your comments.
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