For Ali Hussain, it’s the smallest details that can provide the biggest results.

His career journey from coding into data processing has given him the ability to derive rich insights from MR data points.

“Based on small differences in syntax, I can interpret what the data is saying in several different ways, to reveal unique perspectives,” Ali says.

Since becoming a Senior Data Processor with Logit in 2016, Ali has leveraged weighted data to take this approach to the next level, resulting in more nuanced and varied perspectives and interpretations.

“Weighted data tools are more complex in their usage,” he says, “but our team has identified that they are gaining wider adoption in the industry.”

A good example of this phenomenon occurred in the aftermath of the 2016 American presidential election. When polls were criticized for being inaccurate in predicting the election outcome, Ali saw an opportunity.

He noticed the trend that clients who weighted data based on respondents’ level of education — instead of the standard age, gender and region demographics —observed more accurate results.

Ali and his team applied these innovative strategies to the most recent Canadian federal election, and again saw improved polling accuracy.

“It’s exciting to see how new trends and topics are gaining importance in ways we never would have thought of previously.”

For more on Ali’s work, contact us today.