Re - Engineering IT Service Management in Changing Times By Anand Vaitheeswaran, Director Global Business Services & Geetha Ganapathy, Service Improvement Manager, Philips Lighting

Re - Engineering IT Service Management in Changing Times

Anand Vaitheeswaran, Director Global Business Services & Geetha Ganapathy, Service Improvement Manager, Philips Lighting | Wednesday, 20 June 2018, 05:10 IST

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Application Management is not just about ‘Keeping The Lights On’. With vision and innovation, IT Operations can evolve into a strategic capability that provides competitive advantage to the organization.

Introduction

We all remember the epic lines of Robert Frost “Two roads diverged in a wood, and I-I took the one less traveled by, And that has made all the difference” from his poem “The Road Not Taken”. In today’s fast changing times, these are not mere lines of inspiration, but the mantra for organizations to live by. In the world of Application Management Services (AMS) it is more pertinent than ever.

AMS had traditionally been looked upon as a ‘Keep the Lights On’ function. The aim of AMS teams in many organizations was to ensure uninterrupted provision of IT servic­es to the Business by supporting the underlying Applications throughout their lifecycle. But to define it thus would be an over simplification. Ap­plications are no longer mere plat­forms but enablers of business out­comes. The potential for Innovation is immense in this area. In this article we will highlight some of the key en­ablers that can drive this transforma­tion to elevate AMS from an internal function into a strategic capability that provides competitive advantage for the Enterprise.

Step 1 – Tapping into the power of Data

The first step in the metamorphosis is to adopt a data-driven, results-orient­ed approach.  Organizations should tap into their existing data sources like IT Service Management tools(incident management databases, problem management databases) documenta­tion repositories, output from moni­toring tools and so on, to analyze and arrive at current performance base­lines. Some probable outputs of this exercise are –

     • Efficiency of change and problem management processes

     • Timeorgeography-basedissuedis­tribution

(This point especially can help optimize team structure and leverage teams better)

• Service performance indica­tors - availability, turnaround time for resolution

The most crucial insight to emerge should be- are services driven in silos or is there an integrated approach? As long as services are managed in silos, these metrics would remain pseudo business-performance indicators. The immediate need would be to look be­yond the immediate ecosystem and approach service management in an integrated manner with end-to-end flavor. This also would set the ball rolling for structural changes to drive longer term results.

 Step 2 –Left Shift

Among the various elements driving effectiveness of service management, one important department is the Ap­plication Helpdesk or the First Line Support (FLS)

"Applications are no longer mere platforms but enablers of business outcomes"

Based on data analysis, identify the percentage resolution of tickets by FLS. Any resolution figure close to or above 70 percent is a good start. If the numbers are lower, im­provement of FLS resolution levels should be the immediate area of fo­cus. This can happen in multiple ways - through effective knowledge crea­tion and retention and close collabo­ration between FLS and Application support teams. Once the underlying processes and knowledge repositories are established, cognitive solutions to identify and address frequently asked questions can also be deployed (more on that in Step 4)

                                                  

                                                      Geetha Ganapathy

Step 3 – End-to-End Management

To further break silos of Service Man­agement, and move away from Sys­tem-Based support model to Value Driven Ownership model, the next step is an End-to-End view. A com­prehensive end to end flow of Enter­prise data needs to be drawn. Critical points along the path have to be iden­tified and proactive monitoring needs to be implemented wher­ever needed to discover potential issues before they cascade and impact the Business. The data analysis done previously will once again come to the aid, to help discover these critical check­points. Detail-oriented, standardized guidelines (or Standard Operating Procedures, in other words) contain­ing precise remediation and commu­nication steps in the event of failure need to be established. This will not only ensure predictability of actions but also 100 percent automation-readiness, for future steps to come.

It is at this stage that the organiza­tion gets ready for true IT-managed Business KPIs. The effectiveness of this step has to be directly measured at the business level and unless busi­ness critical incidents are reduced by 70 percent, we cannot claim success. Other means of measuring effective­ness could also be certification from internal audits, NPS surveys done with direct business stakeholders etc.

Having brought in stabil­ity and predictability in operations, the next logical step is to optimize and automate.

Step4 – Optimize and Automation

The emphasis so far has been on or­ganizing the teams in optimal ways, bringing in predictability and work­ing better across ecosystems. The cost and capacity thus freed up can get invested in efforts such as auto­mation of repetitive and time-consuming tasks through Robotic Process Automation(RPA) and Artificial Intelligence(AI) platforms. Chatbots can be introduced to enable self-help for users, to get application information and perform simple tasks on applications, wher­ever possible, without re­lying on manual support from teams, thus driving further optimization.

Automation, in fact, need not stop with IT Application Manage­ment. Implementation of chatbots and other solutions can spread to customer service, marketing and other areas for direct Business (and end-consumer) benefit

What next - The future Intelligent AMS

The evolution needs to continue. With a firm and strong foundation already in place, the next milestone in the AMS journey is already chalked out. As machines become part of the reimagined workforce, the time for AI-driven Service Management is ripe. The power of Machine Learn­ing can be deployed to ensure stable systems that can detect anomalies and heal themselves without explicit programming. These very same al­gorithms can also help in correlating different factors that can impact Ser­vice performance and drive predic­tion and intelligent process execution based on findings.

Conclusion

Driven by this strategy, any AMS team can unlock its potential through agility and quick adoption of path breaking technologies. As Services run better and more value is de­livered, IT can strongly and surely become the strategic arm of any or­ganization and not a mere cost con­suming function.

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