In the future, the success of workplace analytics will be determined by its ability to impact the humans running the business and employee productivity, rather than real estate or its footprint.
In the last decade, many forward-looking companies, mainly in the technology sector, have created iconic workplaces unlike others.
These innovative offices not only provide a competitive edge in the talent game but also offer a significantly improved experience to help their workforce excel. This paradigm is now shifting.
The more structured and centralised financial organisations, which have been relatively slower to embrace these changes, are now partaking in this rising trend.
Once seen as late to the game, these financial institutions now have the potential to leapfrog into the future of work. The keyword? A human-centric approach.
In the future, the success of workplace analytics will be determined by its ability to impact the humans running the business and employee productivity, rather than real estate or its footprint. After all, costs related to salaries and employee benefits make up 90% of total operating costs, while real estate costs account for less than 10%.
With the outbreak of COVID-19, organisations have had to send their workforce home. Globally, 70% of Standard Chartered’s employees are now working from home, while in Singapore the number is as high as 85%.
In the Asian city-state, remote working was already in high demand in pre-COVID times by the younger generation seeking improved work-life balance. This recent change of conditions may have just tipped the balance in their favour.
As demonstrated by the smooth continuity of operations and the positive sentiment from employees, most everyday tasks have proved performable away from the office. Close to 90% of Standard Chartered’s employees worldwide feel that they can support the needs of customers while working remotely.
For Big Data Analytics, the challenges faced by businesses are unique and so will be the solution required to help access the full potential of Big Data.
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Disclaimer: Many points made in this post have been derived from discussions with various parties, but do not represent any individuals or organisations.
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