Step #6 towards an orchestrated datacenter: use data to tell IT's story

By Muneer Mubashir, Senior Marketing Manager, Cloud and Automation

 

Note: This is the sixth of a seven-part blog series exploring what steps you can take toward an orchestrated datacenter. Catch up on the other posts:

  

Okay, so it appears that you’re making great strides toward an orchestrated data center.

 

You’ve established your automation center of excellence (COE), with key IT department leaders working together to coordinate initiatives and share best practices — check.

 

You’re automating the manual, repeatable tasks that take up the bulk of IT admins’ time — check.

 

You’ve got teams focused on end-to-end IT service delivery by integrating people, tools and environments across traditional silo... — check.

 

You’ve even taken steps to begin adapting application architecture for greater agility — check — and are embracing a model-driven approach to DevOps for accelerating app development — check.

 

But before you start high-fiving and slapping each other on the back, think for a moment: How do you know if your orchestrated datacenter is succeeding? How do you track progress and encourage teams to continue expanding their efforts? How do you convince the bean counters and business executives that it’s working?

 

Tell your story through connected intelligence

11362547-bi-business-intelligence.jpgAs with any major IT initiative, you need to measure the impact your organization makes with its orchestrated datacenter transformation.

 

The good news is that with the remarkable volume of operational data that IT can now have access to, there are many ways to acquire and combine metrics across systems/environments through big data — what HP calls “connected intelligence” — to help tell your story. 

  

 

There are really three purposes for collecting data on automation across IT environments and departments: 

  1. Set standard benchmarks across functional areas
  2. Establish incentives for teams
  3. Report to the business on resource usage and cost structure

 

Within a cross-functional automation COE, each IT department will need to be accountable for its own metrics. They can start with what they know, using existing, standard measures of activity in their functional area, and then adding the amount of automation as a percentage of completing those tasks.

 

For example, in monitoring, they should track and report the percentage of alerts that triggered automated remediation processes. Similarly, service desks should know how many service tickets or change implementations are automated. Infrastructure should know the number of maintenance tasks it automates.

 

Such data becomes an important tool for informing what still needs to be automated. ITSM systems ought to provide the ability to categorize different types of service requests, incidents and change records, for example, so you can identify what occurs at a high volume and then systematically work to automate those.

 

As a department automates, however, it will become clear just what percentage of processes it is unable to fully automate because they rely on other areas of IT — and therefore what requires deeper orchestration.

 

Set your targets

As a COE, set benchmarks and agree upon across-the-board objectives — say, 15% more tasks or processes automated in each functional area year over year. Over time, that percentage of tasks or processes automated should progressively rise.

 

It’s important to bake those objectives into the operational targets for each department, so they have the proper incentives to continue to identify opportunities to automate and orchestrate these initiatives across IT services. Even automating standard operating procedures such as log files or maintenance checks makes a lot of progress.

 

And just to offer you some perspective, I typically see organizations with 10-15% of tasks automated. Although that can still make a big difference in cost savings and efficiency, imagine the impact of automating 80% of service requests!

 

The bottom line

Of course, as with anything in business, gathering these metrics also comes back to how budgets and resources are allocated. How does this initiative get funded, and how does it change how IT can use its budgets?

 

Automation data needs to be tied back to objectives and how it impacts the time and utilization of personnel resources — how many people were moved to more innovative projects, for example, or how many personnel hours are saved each quarter? With the right metrics acquired through connected intelligence, you can tell quite a compelling story about the value that IT delivers through orchestrated datacenter.

 

Watch this video on why Cloud Analytics for the hybrid cloud will help you get started for connected intellignce. Register to attend this webinar and gain insights on how cloud analystics addresses topics such as costing and pricing of services, evaluation of vendor performance, cloud implementation ROI. Gain better insights for deciding which resources to use to deliver a service and how businesses are consuming your services.

 

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Lending 20 years of IT market expertise across 5 continents, for defining moments as an innovation adoption change agent.
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