By Leslie Willcocks and John Hindle

For the past seven years, I have been working with John Hindle of Knowledge Capital Partners on automation and adoption of digital technologies, and we will produce a distillation of our work, in a book, this year. The book—provisionally entitled Optimising Automation—will cover robotic process automation, intelligent automation and digital transformation based on a 1,000+ database of cases, and a range of surveys from 2015 through into 2022. At the moment we are just finalising in-depth findings on digital transformation projects, and there are some very interesting conclusions emerging on why some organisations succeed and most underperform.

One of our core findings, whether looking at RPA, intelligent automation, or deployment of other emerging digital technologies—e.g., Cloud, Internet of Things, Blockchain—is how much value is being left on the table. These technologies have massive potential, which is being super under-optimised. In this article John and I look at the opportunity, and a more positive example, in the banking sector. The technology set on which we focus is intelligent automation.

Automation technologies could contribute an additional $US1 trillion annually in value across the global banking sector—through increased sales, cost reduction and new or unrealised opportunities. But this value is still largely being left on the table. Why? There are well documented challenges with automation, including lack of clear and strategic intent and senior executive support for automation, plus heavily siloed deployment within organisations, resulting in disconnects within and across digital transformation efforts. To be frank, operating models per se neither enable nor ask for strategic use of automation technologies. But a hidden key reason has become increasingly obvious—the failure to grasp the nature and size of the opportunity.

This is understandable. As a species we are not good at understanding the major engines of the opportunity for value creation—compound growth and combinatorial innovation. As our forthcoming book, Optimising Automation, highlights, if automation technology deployment produces small improvements each year, the compound results will be massive. If automation technologies can be recombined in new ways, not only can existing opportunities be seized, but new ones can be created, ad infinitum.

Prescient banking executives we are researching understand two things: the strategic opportunities offered by intelligent automation; and how automation can drive the twin engines of compound growth and combinatorial innovation.

They have also, for some time, been anticipating how automation can be deployed to address inescapable competitive pressures driven by rising customer expectations on digital banking. Financial institutions are aggressively deploying automation technologies. This has accelerated during the COVID-19 crisis. Moreover, digital ecosystems are dis-intermediating and re-shaping how financial services are discovered, assessed, purchased and delivered. Think, for example, of mobile devices, and multi-channel apps made available by fin-tech businesses such as Wise (formerly Transferwise) that have transformed the customer experience, beginning with foreign exchange and expanding into international banking. High-tech multinationals are also entering financial services, leveraging seamless multi-channel customer relationships, advanced scaled technology infrastructures, and immense real-time data lakes.

In all this, intelligent automation has become vital for future competitiveness and differentiation in financial services. Let’s look at a bank that has grasped both the problem and the opportunity.

North America | Human and Digital Workers Blend and Multiply Outcomes

In 2015, a major Canadian bank adopted a new value-oriented, purpose-driven management philosophy of increasing organisational agility and improving customer experiences. A key focus involved transforming disjointed operating processes on an end-to-end basis but from the customer’s perspective. This went far beyond simply tweaking existing systems and processes for incremental improvement and cost reduction.

Accordingly, the automation business case was based on increasing the value of the bank’s services as measured by customer metrics—retention rates, service expansion, and improved net promoter scores—rather than simply ‘doing (bad) things faster’. Taking an agile approach, aided by design thinking, the bank realised that a unified customer data structure was a critical requirement for improving service experience. They integrated front-end artificial intelligence and machine learning tools with their automation platform to capture, structure, and curate existing customer data in a shared repository supporting multiple service lines.

In addition to Efficiency savings estimated at more than 200 percent from the ability to access and use previously trapped data, the bank also estimated a 400 percent gain in enterprise Effectiveness—measured by increased customer retention and revenues from broader services integration. The technology platform, moreover, enabled a new organisational structure built on a blended human and digital workforce that could better match task times and volumes to appropriate resources. As the bank’s automation lead notes, “it changes how you think about ‘work’.” Taken in aggregate, the bank’s gains in Efficiency and Effectiveness feed and reinforce each other, exemplifying the dictum that innovations ‘do not merely add up, they multiply.’

The bank’s intelligent automation platform has also supported greater Enablement gains in terms of new products and services, enterprise resilience, and first-mover advantage. When the COVID-19 pandemic required major government response, for example, the bank was able to develop custom automations in just a few days to support massive government referral and aid programs. Without adding headcount, the bank was able to complete thousands of aid applications, attracting new customers and generating widespread public goodwill and reputational equity. The bank estimates the resulting gains in enterprise Enablement to be greater even than the combined Efficiency and Effectiveness gains.

Conclusions

In our wider research we have looked at a number of banks that lead in their use of intelligent automation. What are we learning?

• 1. Adopting a strategic executive mind-set in deploying intelligent automation is critical in capturing maximum value. Without a transformative view and an enterprise vision suffusing from the top, the strategic uses of automation for greater Effectiveness and Enablement are foregone by tactical local initiatives, focused narrowly on what can easily be measured: cost savings and cost avoidance.
• 2. Leaders in automation deployment start with an external focus on customers and competition, using that perspective to design an end-to-end business process architecture that accelerates digital innovation. By ‘seeing the business through the customer’s eyes’, they use automation to improve every aspect of the customer experience rather than ‘doing bad things faster’. Creating value is the primary objective; cost is important, but secondary.
• 3. Building a robust in-house automation capability creates flexibility and a knowledge base which, with strong governance and disciplined behaviours, forms part of the Enablement platform and accelerates strategic uses of automation technologies.
• 4. Longer term strategic Effectiveness and Enablement value from intelligent automation far outstrips near-term Efficiency gains in the leading deployments we have studied—by multiples ranging from 3x to as much as 7x— demonstrating the value of compound thinking.
• 5. In a rapidly evolving multi-vendor technology environment, choosing an open automation architecture is a critical decision factor.