This is part one of a ten-part series leading up to the inaugural Australian release of the Digital IQ report.
By far, one of the most popular picks among futurists and career researchers for the ‘best jobs’ of the new decade is data science. Last year, Harvard Business Review called the profession one of the “sexiest jobs of the 21st century”, while research from McKinsey suggests a need for 190,00 more workers with analytics expertise by 2018.
Technology allows digital enterprises to capture more data than ever before. From high-end data centres supporting popular retail websites to tablets that allow a manufacturing business to track activity on a warehouse floor, more data is being concentrated in readable formats.
Clearly, the appetite is here for business analytics – the Digital IQ report shows that globally 44% of business owners intend to spend more in this area, than any other category.
This is already happening across various industries in both the private and public sectors – and you’ve probably already heard of them.
During the 2012 United States presidential election, the Barack Obama campaign hired several data scientists in order to crunch figures on who was responding to marketing and in what ways.
The campaigns’ top data official, Rayid Ghani, made sure that every decision was based on analytics, integrating analytics in processes across the entire campaign. A major use for analytics was in emarketing, through which the campaign was able to target users with specific subject lines and headings based on the likelihood of their responses.
Using data analytics doesn’t always necessarily translate to a digital marketing effort. In the United States, department store Target started tracking what purchases their customers were making – those who bought higher quantities of vitamins containing magnesium and zinc were assumed to be expecting a pregnancy.
Although these signs are accurate, a customer complained when her 16-year-old daughter received a brochure for baby products. A few days later, she discovered her daughter actually was pregnant – and apologised to the local store manager.
The usage represents a good lesson for businesses – although the move was technically accurate and beneficial, it can still run the risk of offending customers if information they consider too personal is being used to predict their next moves.
So what does this mean?
For businesses of all sizes the difficulty in capturing and using this data differs. For small enterprises, the first hurdle will be to introduce methods into the business of accurately capturing that data. There is an ecosystem of businesses designed to do this and thriving by focusing on the SME market. For many, they can get away with doing this themselves – and many will.
Larger enterprises, however, will face a more difficult hiring challenge. The popularity of data scientists will continue to be a major theme during the second half of the decade. Those businesses with so much data they cannot sift through it all will be almost forced to hire data analysts by necessity – finding those with sufficient business training will be another challenge. The younger generation of analysts will be ripe for training.
Furthermore, the ongoing problems of privacy and private information will continue to play a significant part in the ways businesses gather analytics.
By investing in new technology, distributing it throughout all the channels of a business and then capturing the data – no matter the industry – businesses will no longer be making guesses about how to best manage themselves. Instead, they will be making calculated, informed and precise moves with predictable outcomes.
Stay tuned for the second in our Digital IQ series, which will explore the intersection of the social world with corporate operations and how businesses are using these tools to improve efficiency.