Information technology professionals add value to their business by ensuring that its technological systems support organizational goals. At present, the IT management industry is the most applicable through its use in almost every sector. ManageEngine is such an IT company and Rakesh Jayaprakash is its product manager. Analytics Insight has engaged in an exclusive interview with him.

Kindly brief us about the company, its specialization and the services that your company offers.

ManageEngine is the enterprise IT management division of Zoho Corporation. Established and emerging enterprises—including 9 of every 10 Fortune 100 organizations—rely on our real-time IT management tools to ensure optimal performance of their IT infrastructure, including networks, servers, applications, and desktops.

Our tools help IT teams with service management, operations management, endpoint management, IT security, and data analytics. They are available both on-premises and in the cloud. Our solutions also help our customers effectively manage their on-premises and their private and public cloud infrastructures. We cover the entire spectrum of IT management, allowing our customers to be nimble as they navigate their digital transformation.

Kindly share your point of view on the current scenario of the big data analytics in India and its future?

Analytics and big data initiatives were originally considered nice to have, especially in Asian countries like India, mainly due to the cost associated with procuring analytics tools and training employees to build expertise in this area. The onset of the pandemic accelerated analytics initiatives that complement remote work and allowed business leaders to make crucial decisions irrespective of their physical location. Big data analytics has filled the void created by the lack of direct supervision over daily activities.

As business leaders taste the initial success of big data initiatives, they are expected to support and continue to employ data for business decisions well after the pandemic is behind us.

In what ways is analytics helping organizations with business continuity?

Maintaining a line of communication and the ability to oversee operations is one of the first hurdles organizations face during a natural calamity. A well-designed operations dashboard is imperative when the normal course of business operations is disrupted. This helps top management and mid-level managers monitor organization- and team-level performance irrespective of where they are located. With hybrid work becoming the norm, organizations will see less of a need for close physical proximity to oversee operations.

Many different types of companies have turned to analytics applications since remote work took precedence following the pandemic. Success stories such as Morgan-Keller Construction's use of analytics to support remote workers during the pandemic can inspire other companies to kick-start analytics initiatives.

What have been the most significant challenges that companies have faced at the forefront of analytics?

Organizations that have adopted a data-driven culture use data analytics at the forefront to make strategic decisions. They do not limit themselves to using data in business decisions but also apply it to intra-organizational decisions that help improve operational efficiencies across departments. Organizations that are slow to comprehend these trends risk falling behind their competition.

The biggest problem we see today is not the lack of understanding the benefits of analytics but the speed of adoption by businesses. While larger organizations have started to reap the benefits of utilising analytics, SMBs have been slow to do so, especially in India. This problem is fueled by a lack of initial capital investment and technical expertise. However, this is changing as more businesses realize the importance of deploying an analytics system early and as they recognize, from reviewing success stories, that benefits can be obtained.

How can business analytics help Indian enterprises avoid security threats?

One of the biggest challenges faced by enterprises is detecting a security breach before it inflicts damage on them. This requires detection of anomalies in user and network behavior, which involves analyzing large volumes of machine-generated data and finding actions that don't conform with normal behavior.

Analytics solutions use machine learning algorithms to perceive user and network behavior over a period of time, establish a baseline, and look for deviations from that baseline. They can highlight abnormal patterns in the form of visualizations or trigger alerts via email or SMS. Some analytics applications also offer compliance reporting out of the box, allowing security analysts to keep an eye on the degree of compliance with industry and ISO regulations.

What are the barriers to data democratization?

A recent global study by ManageEngine found that manufacturing, customer support, and HR departments were the least likely to increase their usage of analytics, indicating its adoption is still not widely embraced within organizations.

The two biggest barriers to data democratization are concerns about the misinterpretation of data and the lack of trust fueled by the absence of strict enforcement of data security and privacy policies within a company. Organizations today worry about the possibility of non-technical users arriving at incorrect conclusions from their self-analysis of data. While it is not uncommon for non-technical users to overlook important considerations while deriving actionable insights, they often attain better insights over time as their understanding of the data in relation to the business improves.

An important step in democratizing data is having a robust privacy framework across the organization and educating employees periodically regarding both its importance and the financial implication of non-compliance with privacy laws. The cost associated with educating employees and the fear associated with the risk of a data breach makes companies shy away from democratizing data for wider use. With the introduction of the GDPR and similar privacy regulations around the world, organizations have all the more reason to keep employees informed and make sure they internalize data handling best practices.

Please  brief  us on the recent enhancements to ManageEngine's IT analytics solution – Analytics Plus, which addresses the need for faster actionable insights?

Analytics Plus uses AI coupled with natural language processing to quickly interpret business questions such as, "What is our SLA compliance percentage this week?" or "Which business service has the highest downtime?" and provides answers in the form of vibrant visualizations. This means business users don't have to understand the business logic or data sets required to build analytics—they can get actionable insights directly. Since this doesn't require administrators to expose the underlying data, organizations can turn data democratization into a reality with minimal effort.

Analytics Plus provides out-of-the-box analytics for popular IT and business applications. By performing all the heavy lifting without the need for manual intervention, this solution enables people to spend more time on decision-making instead of dedicating time and effort to figuring out ways to use the data available to their organization.

Analytics Plus also offers a robust forecasting engine that allows organizations to predict future trends with a higher level of accuracy, so they can anticipate and tackle business problems before they cause harm. Additionally, users can set up alerts for critical business metrics, such as service availability and ROI, and only be notified when they breach preset thresholds. Notifications can be sent to collaboration apps, such as Slack or Microsoft Teams, enabling users to concentrate on business-critical functions rather than spend hours sifting through reports every day.

What does your technology and business roadmap look for the rest of the year?

Our main focus in the near future is to strengthen our augmented analytics capabilities, which truly opens up analytics to non-technical users. This will build on the major update that we released in July this year with the following set of capabilities:

AI-driven insights: Our built-in analytics assistant, Zia, now offers narrative insights from reports with zero human effort. These insights help highlight facts that are not obvious to the human eye. Zia allows users to ask follow-up questions, helping them perform deeper analysis with the least amount of effort.

What-if analysis: This allows users to run simulations of possible outcomes by factoring in dependent variables. For example, help desk managers can make hiring decisions by visualizing improvements in SLA compliance as a result of including additional technicians to share the workload.

Blended analytics: This enables organizations to break data silos and build unified operational dashboards. In addition to offering blended analytics for popular IT applications, Analytics Plus auto-suggests data blending options for other data sources, such as databases and non-IT applications.

Lastly, can you throw light on the latest employment trends in big data and analytics industry?

As businesses generate more data, the need for cleansing, organizing, and analyzing data has increased. This has given rise to an increased demand for data analysts. Thanks to online courses, working professionals are able to quickly improve their skills to meet this demand.

The real challenge for data analysts in the long run is to continually build expertise to perform complex analysis. The real competition for data analysts will not come from those with more experience but from analytics solutions themselves, because analytics vendors are in a perpetual race to simplify and automate data analysis with the help of AI, ML, and natural language processing.