Many organizations think collecting their own data is too expensive or time-consuming so they often rely on secondary data for decision-making. Secondary data may be purchased or offered free and found online or offline. Governments, for-profit companies, research institutes, universities, professional associations, and non-profit organizations often produce secondary data.
There are many advantages to using someone else’s data including:
- Cost may be lower than collecting your own data;
- Time to access findings is generally shorter;
- A specific problem is identified, a specific approach is used, and specific answers are given; and
- Key factors affecting the problem are defined.
However, can you really trust someone else’s data?
Using low quality data, even if it is free, will lead to bad decisions and cost you more money in the end.
Here are 4 things to ask yourself when you are tempted to use someone else’s data to make decisions in your organization.
1. What was their method? This question may be the most important one of all.
- What was the size of their sample? Did they ask 5 people or 500 people? Do you know what size of sample is adequate?
- Who were the people they asked? Did they ask new mothers about diaper rash cream or 30-something bachelors?
- How did they collect the data? Did they stand out on the street corner to ask people about their recent visit to their doctor or did they get a list of recent patients from the doctor’s office?
- Did they define and measure the key factors in ways that are aligned with your organization? Did they define “high-income households” as over $90,000 annual gross and while you define “high-income households” as those with more than $150,000 annual gross income?
2. When were the data collected? If you are using the data to make decisions in a market that is rapidly changing, someone else’s data may not be current enough for your decisions.
3. Why were the data collected in the first place? Your objective in using the data might not match their objective in collecting the data. You will never find a perfect match between the two but there needs to be enough overlap.
4. Is the source credible? Check the credentials, reputation, and expertise of the authors. Be skeptical of data collected to promote sales, advance specific interests, or studies that do not include details answering the three questions above.
Do you have secondary data project that is giving you second thoughts? Send us an email at FixIt@SaquiResearch.com and include your data source and a short description of your project. We will pick a few submissions to review and give recommendations in one of our next posts.