The collection method is the key to reliability
We live in a world where a lot of data is collected. The digital revolution has enabled us to automatically collect and store an almost infinite amount of information. Investors, writers, news anchors, and entrepreneurs seemingly constantly talk about data.
It’s a really exciting time that we’re living with all of this data. The only problem is that the right data is not collected and the data collected is often not used. Sometimes I feel like we talk so much about data with buzz words like “big data” and “artificial intelligence”, which are based on data that has been talked about so much and that has been talked about so much. of them that they have lost their meaning.
The truth is, many small businesses or organizations don’t need to go crazy with data. But they need to be focused and smart about the information they collect and analyze.
First, let’s talk about a few reasons why data is valuable even for a small entity.
Understanding your customer’s behavior, controllable cost factors such as overhead, and evaluating the performance of suppliers and partners are common uses for data.
As managers, we all want to make good, informed decisions. Data can give us the comfort and confidence to support our decisions. Now the bad news – data can be misleading.
As Mark Twain once pointed out, there are “lies, cursed lies and statistics”. When we compile data together, we often get the impression that it is hard and cold facts. But I believe we’ve all had experiences in which we’ve been presented with data that we don’t believe in or even data that later turned out to be unreliable.
Understand, evaluate and make the right decisions
Why does this contradiction seem to exist? We need to understand the context of the data and why we are using it before we can make good decisions.
As humans, we tend to be biased. We think we are drawing independent conclusions when in reality we are looking for the data that supports our theories. We throw away the data types that don’t support what we want and explore the data that does.
Often an “analysis” is involved, which takes the raw data and modifies it through calculations. Then we display it in nice tables and charts that can create visual bias. So, shouldn’t we be devoting all this time and attention to data? No. What we need to do is understand the limitations of the data and the context of that data.
The biggest problem may be the way the data is collected
The biggest problem with data is often data collection. Understanding how the data was collected will often give you a good idea of how to interpret it.
For example, I often hate customer surveys. I generally don’t like them because they are extremely vulnerable to self-selection bias. Only those who want to take the survey do so and those who want to take it don’t necessarily represent all of your customers.
Therefore, customer surveys usually only give you information about those who are “
- Already customers
- You already respect enough to take the time to complete the survey
They might be the type of people you really want information from, but that won’t tell you enough about those who may have been disappointed or were unfamiliar with your services.
Another big problem is the sheer volume of information. Small businesses don’t have billions of data points. Walmart can be confident that a product evolves based on point-of-sale data, as it performs millions of transactions every week. A small business can consider itself lucky if it has 100, and 100 data points are often not enough to be statistically relevant.
Trends rather than anomalies from external events (there may have been an event next door or really bad weather that week) are hard to spot.
So what should you do? I suggest you continue to collect data. But you need to know what all the asterisks are with the data. Put it in context and consider alternative theories.
Targeted, deliberate and sober in reading the results
Understand what data you are collecting and just as importantly understand what data is not collected. As a small organization, you need to be very focused, deliberate, and sober about the types of data you collect and how you analyze it.
Be aware that tables and graphs are handpicked statistics and edited for easy viewing. And at the end of the day, the data can be informative, but ultimately you are the one responsible for the decision.