Overcoming common failure points for Intelligent Automation

Intelligent Automation is nearing mass adoption in enterprise corporations. Now is a perfect time for us to reflect back on the lessons learned from the trailblazers that have come before us.
Over the next few weeks, I’m going to address a few of the most common sources of failure for organizations adopting intelligent automation both to start your journey, and to scale it within the organization. Today we are starting with one that often catches people by surprise: Infrastructure.
Let me give you fair warning. If you are reading this and are getting excited at the prospect of casting blame on your IT Infrastructure team, you are not going to like what I have to say. While a project failure may be linked to your organizational infrastructure, it is not to say that your infrastructure team is at fault.

IA DEMANDS A DIFFERENT KIND OF IT STACK

All too often Intelligent Automation (IA) is considered as another software stack for IT to set up and the business to operate. Unfortunately, this approach creates a spiral of activities that adds significant friction for the proper implementation and management of IA, and can lead the entire program grinding to a halt. The IA stack by its very nature is a very different beast than traditional solutions. It doesn’t store transactional data, users don’t operate on it and it completely changes the ongoing business operating model. Yes, this is strange but intentional.
Take the example of RPA. When systems are deployed in support of RPA, the systems (the infrastructure) become the resources used by the business. They are not the supporting tools the business uses, they ARE the resources.
As such, the business needs to have far more control over how their resources (virtual machines) are managed. The business needs to decide:

• When the machines are up or down
• When to add or remove machines
• When changes to the software happen
• How often the changes can happen
• When to change all the above

Not only is such a request unconventional, but it’s also very hard to implement in a traditional IT infrastructure environment.
Just consider that a typical infrastructure environment has specialized skills and teams for:

• Network access
• Application access
• Software licenses
• Security
• Virtualization
• Backup and resiliency
• IT compliance

And that’s not an exhaustive list, either.

THE CHALLENGE DOESN’T STOP THERE

For those programs that do make it through the first round, we often find ourselves right back at addressing similar challenges as soon as we introduce a second or third IA technology solution.
In short, organizations have optimized infrastructure for a large set of technology solutions that support enterprises and give the ability to scale while managing the rapidly increasing demanding compliance requirements.
Intelligent Automation introduces a different set of business requirements that don’t fit into this model and requires a different approach altogether.

A LACK OF COMMITMENT

Most IA journeys today are not part of a larger transformation program as is common with complex IT-related initiatives like implementing ERP solutions. Instead, they are incubated as a small pilot program either; within IT or one line of business.
While I am the first to applaud such efforts to incubate change, they do compound the infrastructure challenge laid out above. These programs are not big enough to involve all the stakeholders, demand a change in procedure, properly educate the staff, or even warrant sufficient resource dedication for implementation and ongoing support.

HOW TO AVOID THE INFRASTRUCTURE CHALLENGE

Your approach will change based on how you start your journey. Here are a few suggestions

• Consider to embed IA into your digital transformation journey: This would be the preferred approach. IA is a significant accelerator and enabler for digital transformation and should logically be embedded as part of the overall strategy.
• Take a Cloud-first approach: Finding a fully managed turn-key solution in the Cloud removes significant heavy lifting early on in your journey. You still need alignment and sign off from Infrastructure and security but nearly all responsibilities are now offloaded in a dedicated and experienced environment.
• Self-contained: Can’t go the Cloud route? Can’t go big? The next best thing is a fully self-contained environment that is managed within the initiative itself, not within the enterprise infrastructure organization. I am not advocating shadow IT here. Get proper support for this. And to some degree, you are kicking the can down the road but it does allow you to start quickly and build a proper plan for what you need to take the initiative further. When done with the infrastructure team, you get the added benefit of joint learning from the pilot.

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