How Artificial Intelligence (AI) And Analytics Are Shaping Digital Workplace Services In A Post-Covid World
Read blog 1 of this series to discover Digital Workplace Transformation Drivers in the Post Covid World
The COVID-19 crisis forced many organizations to reconsider traditional ways of working and adopt remote working models overnight. In a global survey by Gartner, Inc., 88 percent of organizations from across the world encouraged their employees to work from home during the peak of the pandemic. To enable this change at break-neck speed, new tools, rules, and norms were established by most organizations, aimed at better collaboration and automation of time-consuming processes to meet workforce shortages.
Today, after a year into the pandemic, organizations are continuing to evolve, with many opening their doors to employees again or following revolving shifts. Simultaneously, the pandemic has also changed customer expectations, which requires organizations to rethink their resource utilization to achieve operational goals. It is, therefore, imperative to invest in digital solutions catered to meet changing customer demands to stay relevant. At the same time, there’s pressure to create flexible workplace solutions to elevate employee experience for a safe and productive work environment.
In our last post, we discussed digital workplace solutions (DWS) to meet these critical goals. We also detailed how DWS can fulfil the demands of users, employees, and IT seamlessly. However, not all digital solutions are cut to meet the requirements of every business. Therefore, it is pertinent to identify digital workplace solutions based on user experience and long-term business objectives to create a future-ready workplace that’s crisis-proof to a large extent.
Top Technology Trends in DWS
It is a fact that all digital workplace solutions are not created equal. However, the following two technologies have had a profound impact on the development of DWS and continue to impact the way modern workplaces are evolving.
1. Artificial Intelligence (AI)
According to a KPMG report on workplace transformation in the post-COVID era, it is pertinent for organizations to have the right skills at the right time and right place to adapt to uncertain external trends, agile operating models, and rapidly changing trends. The report also points out that Gen Z demands agile working environments and personalized ways of working, making employee experience a key focus area for organizations in the post-COVID era. One of the critical areas in which AI can facilitate a digital workplace is creating personalized experiences through predictive analysis.
Enterprises can use AI-powered predictive algorithms to understand employee behavior and identify what their workforce needs to fine-tune the workplace model accordingly. Thus, using a DWS powered by AI can help organizations:
- Extract the maximum potential out of the workforce.
- Generate skill maps for reorganizing the workforce to drive efficiencies.
- Make employees aware of the available resources and content. This saves time and also helps in uncovering new business opportunities.
- Improve employee experience through personalization based on user preferences and behavior, enhancing employee satisfaction and engagement.
- Make use of data from the increasing number of connected devices used within an enterprise for business purposes, such as smartphones and social media.
- Introduce a high degree of automation to save time, costs, and effort. For example, many firms have introduced chatbots in customer service to automate query resolution, which can help them save up to 30 percent of customer service costs.
2. Predictive Analytics
A McKinsey report states that organizations have been using analytics to respond to challenges arising from the pandemic in four critical areas – protecting and supporting employees, informing strategic and financial decisions, managing supply chains, and engaging customers. A DWS with integrated tools and resources for collecting, consolidating, and analyzing data from various touchpoints is, therefore, quintessential for driving strategic business decisions. Predictive analytics can also be used for modeling employee behavior to identify churn, performance management, and develop policies for enhanced employee experience.
Another exciting application is predictive content generation to identify and eliminate potential bottlenecks from various work functions. Overall, organizations can use predictive analytics to measure the evolving workforce experience and fine-tune it as per user behavior and demand.
AI-powered DWS is essential for hyper-personalizing the employee experience to maximize productivity and fine-tune the future workplace. Additionally, other technological components like Internet-of-Things, cloud computing, and immersive media can further expand the scope and utility of DWS. However, as always, identifying the right solution for workplace transformation isn’t enough unless an organization is prepared for it. In the next blog, we will identify critical success factors for effective DWS implementation for enterprises to ensure productivity and revenue.