Real time, aggregated analytics help organizations save dollars

Analytics is redefining IT organizations to gather actionable business intelligence. Harbinger Systems is a global company providing software technology services for independent software vendors and enterprises. Since its inception in 1990, Harbinger has developed a strong customer base of organizations worldwide that includes high-tech start-ups in Silicon Valley, multi-national product companies, and in-house IT teams of large organizations.

Here, Shrikant Pattathil, President at Harbinger Systems, tells us more. Excerpts:

DQ: What are the business plans of Harbinger Systems?

Shrikant Pattathil: Harbinger Systems leverages the latest digital technologies to build software solutions in HR Tech, Health Tech, and Learn Tech domains, and helps solve complex business problems in these areas for organizations across industries.

The future of the enterprise workforce is rapidly changing. The key factors that are contributing to this change are the technology advancements, gig economy and expectations of the future Gen Z employee. Harbinger’s goal is to help vendors and enterprises, successfully go through this rapid digital transformation and maintain their business leadership by maintaining a razor-sharp focus on their human capital. Harbinger is involved in creating solutions using latest technologies like AI, Blockchain, AR etc. that enables a seamless employee and HR operations workflow, and improves the employee experience and engagement.

DQ: What are the trending technologies for the year 2020?

Shrikant Pattathil: Based on our experience, we feel the following technologies will have a major impact in 2020 and beyond.

AI and ML: These days, most applications are embedding AI and ML in their systems, either from a perspective of workflow automation or analytics. The cloud service providers have made it easy for incorporating basic AI- and ML-based functionality in products. However, it’s important that application developers think of good use cases to harness the true power of AI in their applications.

Blockchain: The core problem that Blockchain addresses is the issue of trust. Today, no application or process works in isolation, therefore there are many use cases where blockchain would be a good solution. In some cases, like background screening it may require multiple parties to come together to create a blockchain, which may a blocker. However, in smaller groups where information is being exchanged and needs to be trusted, blockchain is a very viable solution.

Edge Computing: Newer systems and applications are using edge computing principles to address the issue of latency. By using edge computing, one needs to take the computation closer to the user, so that there is less data transfer and the computational capabilities of the edge device or network gets leveraged to the fullest. This trend will make applications and integrations more complex for developers, but at the same time it will improve user experience.

Augmented and Virtual Reality (AR & VR): In addition to gaming, we are experiencing that AR & VR tech is steadily gaining adoption in learning and development domain, across various industries like manufacturing and healthcare. We are also seeing it being used in retail B2C applications to improve user experience and influence online buying decisions.

Cybersecurity: The adoption of cloud has further increased the need for security. Of course, the cloud providers are doing their best to ensure application and data security in their environments, however, the onus is also on the users and developers. One needs to constantly evaluate new threats and make the necessary configuration or programming choices to protect themselves.

DQ: How has data engineering become a key-focused area for companies?

Shrikant Pattathil: Today, most of the analytics that we have seen focuses on improving efficiency. The reason for that is because we are getting analytics only from one or two systems. For example, if you take the HR domain, it would be reports like time to hire, resumes per job etc. As the number of software applications are growing, vendors and corporates are collecting huge amounts of data, from their customers, employees and partners in their respective applications.

Companies need to setup a dedicated data engineering practice, which can help them aggregate the data across multiple sources to help derive analytics that influence business outcomes, e.g. cost of hire, whether a hired employee was a good, bad or average performer etc. Real time and aggregated analytics can help organizations continuously improve their processes, save dollars and stay ahead of competition.

DQ: How has technology been a driving force for talent acquisition?

Shrikant Pattathil: Most organizations acknowledge that having the right talent is key to success and it helps in maintaining the competitive advantage. However, today’s talent is very transient, and technology is continuously changing, so talent acquisition teams in organizations cannot afford to relax anytime. The only way to keep pace with this 24/7 demand for talent is to leverage technology effectively. Using the right platforms and tools like domain specific ATSs, background screening software, onboarding apps, recruitment marketing and interviewing solutions will help talent acquisition teams to stay lean and support the growing needs of an organization.