In a hurry to virtualize its desktops, Glenmark Generics banked heavily on its system integrator—a mistake that led to an IT meltdown. Here’s how they cleaned up that mess. Summary:“The company had three months to centralize apps, encrypt access to data and apps, and deliver them to globally distributed users,” says Mahendra Sekharan, GM-IT, Glenmark Generics, who joined the company four months after it decided to go for virtualization. “There was no time to evaluate technologies or develop best practices. The company had no choice but to rely on the SI’s expertise and the vendor’s assurances.” In retrospect, that would be a mistake.Highlights: SUBSCRIBE TO OUR NEWSLETTER From our editors straight to your inbox Get started by entering your email address below. Please enter a valid email address Subscribe “You can’t implement a new technology just because your neighbor did,” says Sekharan.The Organization: In April 2008, the Generics and API division of the Rs 3000-crore Glenmark Pharma was hived off to form Glenmark Generics. The Business Case: As a first order of business, Glenmark Generics’ management issued a diktat to centralize the data on a common server to reduce cost. And it needed to be done fast. “The company had three months to centralized apps, encrypt access to data and apps, and deliver them to globally distributed users,” says Mahendra Sekharan, GM-IT, Glenmark Generics, who joined the company four months after the order came from the top. “There was no time to evaluate technologies or develop best practices. The company had no choice but to rely on the SI’s expertise and the vendor’s assurances.” In retrospect, that would be a mistake. “Implementing anything new without best practices requires careful scrutiny and a thorough understanding of business priorities.”The Project: Glenmark Generics system integrator deployed Citrix XenApp and things started to go south very quickly. Although the SI had configured the system to support 600 users simultaneously, it slowed to a sloth-like pace if 300 users logged on. E-mails, for example, took as much as 20 minutes to download. “Things got so bad that people would click on their mails, go for a cup of coffee and return to their mail still downloading,” says Sekharan. That’s when the bad advice started. “We increased the RAM on the desktops and even changed the printers which, according to the SI, weren’t compatible with Citrix. But the problem persisted,” says Sekharan. By this time, the problem was already forcing users to work over time and, stall the business, “causing the company to bleed revenue.” The Lesson: When multiple rounds with the SI, and the consultant didn’t bear any fruit, Sekharan decided to quit the polite talk. “The problem with consultants is that they just fine-tune existing configurations. They don’t look at root causes and make design changes,” he says. Sekharan demanded that Citrix do an investigation. Over three weeks, a top executive from the vendor prepared a detailed report—and the results were shocking. The probe revealed the inexperience of the implementation team. The problem was that each request from a user was being sent to different servers. So if a user opened three apps, mail, a word document, and an Excel sheet, for example, his system would create three sessions at the server level, creating a latency problem. Glenmark Generics asked the vendor to re-implement the app. Once bitten twice shy, the company ordered an intense 45-day trial period during which it tested the new environment on two servers. “Today, applications that took 30 minutes to open, do so in less than 20 seconds,” says Sekharan. “You can’t implement a new technology just because your neighbor did,” says Sekharan. “Implementing anything new without best practices requires careful scrutiny and a thorough understanding of business priorities.” “Implementing anything new without best practices requires careful scrutiny and a through understanding of business priorities.” Related content brandpost Should finance organizations bank on Generative AI? Finance and banking organizations are looking at generative AI to support employees and customers across a range of text and numerically-based use cases. 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