At MacKenzie, we are constantly interacting with people of varied levels of appreciation and understanding of data analytics. Both clients and staff commonly have differing perceptions of what the numbers mean, or what the data is saying. One of the great things about data is that it can become a language, open for interpretation. But that’s also one of the difficult things about data, it is open for interpretation.
The current state of technology allows virtually anyone to collect primary research data, sift through outside sources for secondary research data, or review internal sales data with hopes of better understanding a specific market. In theory it’s a good thing to empower the every-day business person to leverage data analytics. However as easy as the data collection process might be, it’s an uphill battle from there.
One example, highlighted in the article linked below, is determining between “causation” and “correlation.” Causation suggests two things are directly linked, and the movement of one impacts the other. Whereas correlation is when two things can be seen moving together but are doing so independently; they are not directly influencing each other. Mistaking one for the other can lead to negative results, and through no fault of its own the data will be blamed for misguiding a team or project.
This is why it’s so important to fully understand the depths of knowledge and skill needed to effectively decipher what data sets are saying. Furthermore, the simple act of combining multiple data sources is in itself a detailed practice; one that can make-or-break the validity of any conclusions moving forward.
To avoid being led down the wrong path, it’s best to leave data analytics to the professionals. MacKenzie has over 30 years of experience collecting, analyzing, and reporting data. Over the years, we’ve helped our clients overcome many obstacles the first time around by listening to what the data says and creating a strategic plan of action around those findings.
Are you in danger of misusing data analytics? Might you be misinterpreting what the numbers are saying? This article from the Harvard Business Review covers some common mistakes being made by marketing managers when dealing with data. If you relate to anything in this article, give us a call. We can help.
READ THE ARTICLE HERE
(Source: Harvard Business Review)
