Data, data, data: Collection method is key to reliability
We live in a world with lots of data being collected. The digital revolution has allowed us to automatically collect and store a nearly infinite amount of information. Investors, writers, newscasters and entrepreneurs are seemingly constantly talking about data.
It is really exciting times that we live in with all that data. The only problem is good data goes uncollected and the data that is collected is often not used. Sometimes I feel so much is talked about with data with buzz terms like “big data” and “artificial intelligence,” which is based on data that have been talked about and hyped so much they have lost their meaning.
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The truth is, many small businesses or organizations don’t need to go crazy with data. But they need to be targeted and smart about the information they do collect and analyze.
First, let’s talk about a few reasons why data is valuable even to a small entity.
Understanding the behavior of your clientele, drivers of controllable costs such as overhead, and evaluating the performance of vendors and partners are common uses of data.
As managers we all want to make good and informed decisions. Data can give us the comfort and confidence to back our decisions. Now, the bad news - data can mislead.
As Mark Twain once pointed out there are “lies, damned lies, and statistics.” When we compile data together we often feel like these are the cold hard facts. But I believe all of us have had experiences in which we were presented with data we did not believe in or even data that was later proven to be unreliable.
Understand, evaluate and them make good decisions
Why does this contradiction seem to exist? We need to understand the context of data and why we are using it before we can make good decisions.
As human beings we tend to be biased. We think we are making independent conclusions when in reality we are looking for the data that supports our theories. We throw out the types of data that don't support what we want and drill down on the data that does.
Oftentimes “analysis” is involved, which takes the raw data and modifies it through calculations. Then we display it in nice charts and graphs that can create visual biases. So, we shouldn’t be spending all this time and attention on data then? No. What we need to do is understand the limitations of data and the context of said data.
Biggest issue can be how the data is collected
The biggest issue with data is often the collection of data. Understanding how the data was collected will often give you good insight into how to interpret it.
For example, I often dislike customer surveys. I typically don’t like them because they are extremely vulnerable to the self selection bias. Only those who want to take the survey, take it and those who want to take it may not necessarily represent all of your customers.
As a result, customer surveys typically only give you information about those that are"
Already respect you enough to take the time to fill out the survey
Those may be the type of people you really want to get information from, but it isn’t going to tell you enough about those wbho may have been disappointed or unaware of your services.
Another big problem is the volume of information. Small businesses do not have billions of data points. Walmart can be confident a product is trending based on point of sales data since they have millions of transactions every week. A small business may consider itself lucky if it has 100, and 100 data points is often not enough to have statistical relevance.
Trends rather than anomalies from outside events (maybe there was an event next door or really bad weather that week) are hard to suss out.
So what should you do? I suggest you still collect data. But you need to know what all the asterisks are with the data. Put it in context and consider alternate theories.
Targeted, deliberate and sober about reading the results
Understand what data you are collecting and just as important understand the data that isn’t being collected. As a small organization you should be very targeted, deliberate and sober about what types of data you are collecting and how you are analyzing it.
Know that charts and graphs are handpicked statistics modified for easy viewing. And at the end of the day, data can be informative, but you are ultimately the one that is responsible for the decision.