Companies spend millions of dollars generating or purchasing insights every year. In 2012, a report by McKinsey and IDC found that an employee spent an average of 8.8 hours searching for information and an additional 8.1 hours analysing it during a workweek. That equates to around 60 days per year of people spending time generating insights rather than executing on them. In dollar terms, those days are worth at least $12,500 per employee per year.
While the availability of collaboration and information management technologies has increased in the decade that followed, the rate at which we are producing information has also been accelerating. IBM estimated that humanity is doubling the amount of information it generates every 12 hours by 2020. The amount of information we have in 2020 is already 40 times more than what we have in 2010. Are we still able to keep up – even when we are augmented by technology?
Artificial intelligence technology has automated the processing of much of this data and yet the demand for knowledge workers is still increasing. Knowledge workers are people who conduct non-repetitive cognitive tasks. While technology is great at producing generic analytics, knowledge workers excel at generating customised insights that are relevant to businesses’ specific needs.
This is why knowledge workers represent around 35% of the American productive demographics right now and the demand for them is growing at 2.5 times faster than other jobs. While the need for knowledge workers will continue to rise, there is already significant gap between supply and demand. It is estimated that 13% of knowledge work jobs will not be filled due to a lack of talent in the market. As competition for talent intensifies, so will the cost of hiring these people.
In addition to the talent gap in the market, the complexity and diversity of knowledge work make it even harder for organisations to find the right people. Most knowledge work is unique, industry-specific, and task-specific. That means organisations often need different knowledge workers for different projects and situations. Furthermore, the seasonality of projects and demand for specific talents makes it financially challenging to justify hiring these individuals on a full time basis.
Consulting firms, for instance, work across a diverse range of industries and often need input from industry veterans in crafting solutions and recommendations. However, keeping all these experts on their payroll is expensive, and the seasonality of projects makes it hard to fully utilise these individuals. This conundrum repeats itself in creative industries that require copywriters or designers with unique perspectives. Having access to a pool of on-demand knowledge workers makes it possible for these companies to circumvent cost and expert discovery issues, while giving them access to the right people at the right time.
These challenges make on-demand talent solutions appealing to organisations. While the rise of on-demand work started with repetitive task-based roles such as food delivery and driving, technology has made it easy for knowledge work to be delivered on-demand. Collaboration, communication, and document sharing tools facilitate remote working and information exchange. Companies in consulting, engineering, and creative industries are already working with many on-demand knowledge workers as they often rely on experts with unique backgrounds and capabilities to deliver customised insights.
As such, the popularity of on-demand knowledge workers will continue to rise. Organisations benefit from having access to a global network of expertise and at the same time enjoy the flexibility of deploying them only when needed. At the same time, these knowledge workers have the optionality of working across a diverse range of projects and organisations on their own terms, making the on-demand model even more appealing.