C-SIGHTS

Secondly, distribute applications across public and private cloud so that all the traffic does not flow into your corporate network. Provide clear communication on which applications require VPN, so employees only use it when necessary. Using it for all online work means traffic routes to datacenters, rather than employees’ home offices, which will tank performance. Also, facilitate firmware upgrades and reboots of infrastructure equipment to provide better connection stability.

2. Reexamine your cyber security infrastructure

WFA requires separate risk assessment both from a cyber security and data privacy perspective. Unmanaged end points create additional risk of getting compromised from advance malware. Also many IT teams do not fully understood the architecture required for securing workloads in public cloud. Every company needs to start with standard security measures, including two-factor authentication, data encryption and secure transit, and advanced security settings on physical devices and virtual desktops, to help ensure that data stays safe, even when employees are accessing systems remotely. They should have well-documented RBAC policies. They also need to architect security for cloud infrastructure using

• data leak prevention technologies
• virtual next generation firewalls (north-south)
• microsegmentation across virtual machines (east-west)
• advanced malware protection
• network and end-point anomaly detection
• sand boxing
• tools and practices for thwarting advanced phishing attacks

3. Understand Data Privacy needs 

Concerns about data governance are ongoing, and specific requirements of the GDPR and country-specific data privacy acts need to be addressed on multiple levels and by various departments within an organization. These regulations carry stiff penalties for noncompliance. Enterprises need to design their architectures to address requirements like the ”right to be forgotten” and the “right to erasure.” This must be achieved across all data repositories and all environments, including private, public, and hybrid clouds.

C. Use Technolgy To Improve Business Productivity 

1. Focus on task automation, process augmentation, and job amplification 

Whether you’re using robotic process automation or machine learning (ML), or the hybrid of both that comprises intelligent automation (IA), you have a great opportunity to start scaling up investments in ML and other advanced automation technologies to augment a capacity constrained workforce.

With the advent of cognitive technologies and sophisticated products, as many as 50 percent of our traditional jobs are at risk as software bots take over automated tasks. But remember that using powerful BOTs is not simply about reducing the number of employees in companies. It’s about competitive efficiency and effectiveness. Only if we automate faster than our competitors and automate a broader number of tasks, will we have a competitive edge. Falling behind is bad enough when shifts in the market are linear; it becomes significantly more problematic when the shifts are exponential. Don’t forget that automation can mean freeing up employees for different work that brings greater value to customers.

2. Boost customer engagement with self-service

Companies should ramp up their digital strategies by investing in customer engagement, self-service, digital workplace and knowledge management tools. For those who haven’t built self-service capabilities, there’s no better time to start. Self-service channels and platforms will help employees, customers, and partners get what they need with little to no intervention from IT and the business. Transparency about service and prcess changes are critical to maintaining customer satisfaction. Collectively, these tactics will improve business resilience and create a path to future profitable growth.

3. Balancing between surveillance and trust - measuring productivity 

Organizations need to understand work-related activities so they can have a clearer picture of employee productivity; objectively measured productivity levels help keep the company running even without workers being physically present. Developing this framework during standard operations helps establish productivity benchmarks that are critical to implementing successful work-from-anywhere programs.

These benchmarks should include actual time spent completing work (including each team’s core responsibilities), attending meetings, etc. Once benchmarks are established, goals can be set as necessary to minimize distractions, eliminate unproductive habits, and increase actual productivity levels wherever needed. These benchmarks and goals hold constant no matter where any employee works from. They become the objective standards against which any employee’s efforts can be judged, instead of relying on ”the time put in at the office.“ Managers should have a built-in platform for determining the success of any project or team, as well as mentoring and managing employee efforts and output.

Organizations should have insights into the impact WFA has on productivity, efficiency, and employee engagement. They need a data-driven approach that illuminates work patterns and behavior within the organization. This allows them to automate the reporting of work patterns, time, and activity, and helps create baselines of expected work output as well as team goals. Tools need to be deployed to automatically gather and analyze the data to measure team engagement and productivity. CXOs can get a cross functional view of the efforts, while managers can see true capacity utilization, and employees can get insights into their own work routines.