Scale now

Embedding intelligent automation across the enterprise

How do you scale your intelligent automation efforts fast and effectively? According to a joint KPMG/HFS Research study, having the top-down leadership courage and vision to charge ahead and upskilling and reskilling in-house IA talent are key pillars. This revolution is not just about technology; it’s really about a monumental transformation of human beings. It’s about change – and, therefore, change management. The true leaders will be the ones who succeed in doing business in wholly different ways, with human and machines complementing each other.

Key research findings

  • The inability to scale is the largest perceived inhibitor to achieving goals. Two-thirds of organizations are piloting, moving to production or scaling their IA, but only 17% of organizations have fully scaled intelligent automation technologies across their organizations. The most-scaled technology is smart analytics (23%).
  • IA solutions are siloed. Although 60% of respondents are using multiple technologies, the implementation is piecemeal. Only 11% have integrated automation, analytics, and AI as a ‘trifecta solution.’
  • Investment in intelligent automation technologies is strong. More than half (52%) of organizations surveyed have invested more than $10 million, and nearly a third (30%) have dedicated over $50 million.
  • The top strategic goals: driving revenue growth and making better use of data; the top operational goals are centered on the customer experience. Thirty percent aim to improve customer service quality and interactions; 23% want to streamline the customer service delivery model. Almost a quarter (24%) are motivated by topline growth; 18% by accelerating data and analytics and improving insights.

Scale smart

The clear path forward for any business is scaling automation technologies across the entire expanse of the enterprise – and the only way to get there is by building a digital-first culture where IT and business work together.

This report will give you guidance on how to lay the foundation for business and operating model transformation built on data and new technologies supported by people.

How to transform business and operating models

A portfolio approach that prioritizes and balances needs and goals is the best path. However, nothing will advance without two basic realizations:

  • The C-suite needs to lead the way and make bold decisions on scaling functions across business units – and organizations must have the right-in-house talent to develop and benefit from the transformation.
  • Automation is not simply about deployment – it’s about business and operating model transformation built on data and new technologies supported by people.

60% of decision-makers at firms adopting AI technologies cite data quality as either challenging or very challenging. It was the No. 1 challenge facing firms trying to deliver AI capabilities.

How to build enterprise-level intelligent automation

  • Build culture: The prevailing approach to automation is IT-led: The KPMG/HFS Research survey shows that just one-fifth have created integrated IT and business leadership teams to grapple with IA strategy and deployment.
  • Mind your data: 18% see accelerating the ability to leverage data analysis as a key strategic goal.
  • Go to the cloud: In 2019, cloud computing will firmly establish itself as the foundation of tomorrow’s enterprise application platforms. It’s the best way to create the compelling software experiences that your customers demand and your competitors fear.
  • Blend technologies: The most notable trend in the KPMG/HFS Research study is that the majority of enterprises are investing in myriad automation technologies.

New way of working: how to build the culture for scale

Top-down leadership and in-house talent are the fuel of transformation and success.

People make and mold IA — and they will be the guiding hand in its evolution. IA in turn will supercharge human capability. A strong culture must be ethical in its design and deployment of IA. Only then can it breed trust and reinforce the brand.

The golden ticket: change management

The biggest hurdle facing leaders as the ground shifts under their feet is how to effectively manage the change. It’s such a deep and difficult issue – and it doesn’t get the coverage it deserves amid all the talk about tech and outcomes. Consider the depth of the challenge: jobs are changing as AI technologies pick up some of the tasks, functions are being automated, and the workplace itself is just coming to grips with a whole new way of working. Leaders have to engineer a massive, unprecedented cultural shift to get everyone ready, willing and able for transformation.

Future scale: holistic integration

Embedding intelligent automation across the enterprise requires more than technology. To scale smart and stay ahead of the competition, you need leadership and in-house talent to transform business models and mold solutions.

Executives know they can’t achieve their goals for IA without more scale. The ambition is there, but they’re struggling to embed and enable IA technologies as deeply as they want across the organizations. Among the reasons according to our research: They’re too cautious in terms of pushing IA beyond pilots or deployments at the functional level; they lack the financial commitment; and they’re fighting to secure the talent they need to become truly digital-first organizations. In many ways, the age of automation boils down to people—and leadership.

Every business needs to be a tech company in its mindset and actions. In essence, leadership must approach automation boldly and intelligently to redefine core processes and the roles of people in the full range of functions—how they work, what they can do and the intelligent interactions they have with customers.

KPMG's 4th Annual Executive Symposium on Intelligent Automation