botsWe were very interested to read KPMG’s recent survey on investment in intelligent automation – highlighted in the Wall Street Journal’s CIO Journal blog. KPMG’s team summarized discussions with senior technology and service delivery leaders at 80 large enterprises, highlighting the same conclusion that we’ve reached with our own customers: The real barrier to scaling intelligent automation comes from business, not technology, limitations.

The KPMG survey found that 37% of respondents are looking closely at intelligent automation, with 24% currently testing proof-of-concept or pilot projects. And within only 3 years, 49% of respondents say they plan to be operating intelligent automation tools at scale – “the transformative value lies in fundamentally disrupting the business model,” as Todd Lohr of KPMG observed.

But KPMG also confirms just how hard it will be to meet these ambitious goals. “Despite such high expectations, researchers found little readiness to deploy smart automation at scale. Nearly two-thirds of businesses surveyed cited a lack of expertise on IT teams to oversee smart automation efforts, while more than half said they have yet to formulate clear goals and objectives to gauge the success of smart automation deployments.”

Given the challenge, it’s no surprise that we see a growing focus from our partners – including KPMG – on helping enterprises move from initial RPA pilots to enterprise-scale programs. These businesses see the tangible impact of automation pilots, and they recognize longer-term potential that is orders of magnitude higher. But they also recognize that simply deploying more technology isn’t enough to break the barrier to large-scale intelligent automation.

Enterprises also need to:

• Efficiently ramp up a pipeline of prioritized opportunities
• Manage the complex cross-functional dependencies created by large-scale automation
• Focus limited resources on the highest impact areas
• Connect RPA technical design decisions to business impact
• Build reliable budgets that account for both RPA investment and cost savings

So what’s the path forward? Scaling from initial RPA pilots to 1,000 (or 10,000) production bots requires a fundamental mindset shift: From a focus on validating RPA technology to a focus on building a sustainable enterprise capability. As a result, successful enterprise-scale intelligent automation starts with bringing together fragmented RPA efforts into an integrated, program with clear, quantified business objectives. From there, successful programs establish a structured process to capture opportunities, build a prioritized pipeline, manage delivery for maximum business impact, and credibly measure post-deployment ROI – all at large scale.

And it’s no surprise that breaching the scale automation barrier also requires different enabling technology than deploying individual pilots. If you’d like to learn more about how Shibumi supports enterprise-scale automation, please check out our web site or contact us to schedule a discussion and demo.