One business and analytics expert explains the three most common mistakes employers make when handling big data.
Big data may be one of the most important developments to hit HR in the last 10 years but a number of common mistakes prevent employers from making the most of it, warns one analytics expert.
“There are several popular mistakes companies make as they enter the world of big data,” says Tracy Smith, president of Numerical Insights.
“First, many companies purchase an analysis or business intelligence tool before they’ve even determined what they need the tool to do.”
Smith – who has been formally identified as one of the “Top 50 Global Influencers in HR Analytics” – says companies often waste resources tracking data which they don’t really have any need for.
“For a company with a very low termination rate, there is little to be gained by using analytics resources to study turnover,” she explains. “The company with low turnover should focus their analytical efforts on a different business problem.”
The second major mistake, according to Smith, is that some companies believe their analytics journey is complete as soon as they’ve purchased a data visualization tool which provides them with actionable insights.
“This is incorrect because you still need someone to interpret what the data results mean inside your company,” she stresses. “The software tool won’t do that for you since it doesn’t know your business and its history.”
US-based Smith says the final common mistake is when employers put analytics projects on hold while conducting a company-wide data clean-up project.
“Data is a living set of information,” she says. “It is constantly changing and growing. It will never be perfect.”
Smith – who has over 25 years of experience in mathematics, statistics and data visualization – will be holding a session on big data at the upcoming HR Tech Summit.
There, Smith will offer practical advice on how HR professionals can use big data and analytics in a truly strategic way while discussing how employers can also use data to gain a better understanding of their workforce.
More information on the event, which will take place in Toronto later this year, can be found online.
“There are several popular mistakes companies make as they enter the world of big data,” says Tracy Smith, president of Numerical Insights.
“First, many companies purchase an analysis or business intelligence tool before they’ve even determined what they need the tool to do.”
Smith – who has been formally identified as one of the “Top 50 Global Influencers in HR Analytics” – says companies often waste resources tracking data which they don’t really have any need for.
“For a company with a very low termination rate, there is little to be gained by using analytics resources to study turnover,” she explains. “The company with low turnover should focus their analytical efforts on a different business problem.”
The second major mistake, according to Smith, is that some companies believe their analytics journey is complete as soon as they’ve purchased a data visualization tool which provides them with actionable insights.
“This is incorrect because you still need someone to interpret what the data results mean inside your company,” she stresses. “The software tool won’t do that for you since it doesn’t know your business and its history.”
US-based Smith says the final common mistake is when employers put analytics projects on hold while conducting a company-wide data clean-up project.
“Data is a living set of information,” she says. “It is constantly changing and growing. It will never be perfect.”
Smith – who has over 25 years of experience in mathematics, statistics and data visualization – will be holding a session on big data at the upcoming HR Tech Summit.
There, Smith will offer practical advice on how HR professionals can use big data and analytics in a truly strategic way while discussing how employers can also use data to gain a better understanding of their workforce.
More information on the event, which will take place in Toronto later this year, can be found online.
