Easing the pressure points: The state of intelligent automation, a new report by KPMG International and HFS Research, provides the data and research needed to help properly assess an organization’s progress on the intelligent automation (IA) journey.
Based on a survey of nearly 600 business leaders across 13 countries, this report paints a clear picture of current IA implementation around the world – from the aspirations and strategies at play through to the barriers and challenges being faced along the road to enterprise value.
The report finds that the vast majority of organizations are struggling to secure value from their IA activities. In particular, the survey shows:
- Most organizations are actively pursuing IA initiatives but are hindered by a lack of coordination, integration and prioritization.
- Even with RPA – arguably the most mature of the IA technologies – organizations are struggling to achieve scale.
Skills shortages – particularly in machine learning and artificial intelligence capabilities – are inhibiting IA growth.
- While everyone recognizes IA will change the way people work, few have determined how best to address the impacts.
- However, the report also finds that executives are keenly aware of the need to press forward with their IA investments and activities. They recognize their peers are moving ahead. And they know they need to take action.
Featuring lessons from some of the world’s leading organizations as well as KPMG insights on how to tackle the issues, this report helps explain how the leaders of tomorrow are capturing value from their IA investments today.
Intelligent automation (IA) and data and analytics (D&Al are at the top of every organization’s strategic and tactical agendas. And rightfully so: the technologies don’t just promise to improve operational efficiency and effectiveness; they also provide the basis for a broad range of new or enhanced products and services. In fact , more than a third of today’s business leaders say they view IA as a way to drive future revenue growth. Many also see it as an opportunity to improve customer service quality.
While there is much concern around IA (for instance it will lead to massive job losses, marauding bots, privacy invasions), the reality is that it will have a huge impact on how organizations operate and on the nature of what constitutes work in the future. In fact, it already seems clear that IA will be key in addressing skills shortages in aging workforces, enhancing worker skills and automating the mundane to free up worker time to focus on value-added services such as analyzing data instead of just processing. The key for organizations is to parse hype from reality by better prioritizing IA investment areas and also by realizing that all pilots are not equal in terms of benefits returned. The onus is on enterprises to determine how best to integrate and coordinate cross-organizational efforts, and ensure adequate change management programs and practices are in place to address the disruption IA adoption will entail.
While advanced D&A adoption is more mature, IA adoption is much more nascent in most organizations, with less than 20 percent of firms surveyed at scale saying they are beyond pilot stage and ‘up and running’ with their IA efforts. This is due to many factors, including immaturity of the technologies and cost of deployment but more so due to organizational uncertainty on where to start, how to coordinate and integrate (or not) disparate efforts, and how to address the impact these technologies will have on their operations and workforces. Robot process automation (RPA), for example, could partially or fully eliminate many work roles in an organization. In addition to managing the disruption this will cause, organizations must determine how to address the future of their workforces: will you retrain, reskill, or retire employees affected? And if you choose to retrain or reskill, in what exactly?
Ironically, at the same time as organizations are struggling with what to do with workers whose jobs are eliminated, they also recognize that their intelligent automation efforts, especially in the areas of machine learning and artificial intelligence, are hampered by a lack of skilled resources needed to design, build, deploy and manage these systems and initiatives. There is a gulf emerging among the have and have-not companies -a gap that ‘s only widened as less than 10 percent of companies held more than 30 percent of the job postings among the largest 100 US companies’. So where do organizations find the talent and skills they need to support their IA ambitions?
Regardless of these challenges, organizations must press ahead with their IA efforts or seriously risk longer-term marginalization against competitive peers that are forging forward. The evolution and adoption of IA technologies is proceeding at such a rapid pace that, while executives recognize its game changing potential, many struggle to understand what that means to their own organization and its operations, and what it means in terms of where they should place their own IA bets and investments. While it is relatively straightforward, for example, to save some money via an RPA deployment, even RPA is proving more complicated and time consuming to successfully enable what was often initially estimated. If all an organization gains through IA is incremental cost savings, it is missing out on its full potential.
To get the most from IA efforts beyond cost savings, broad-ranging transformation is needed, not just in a piecemeal way. This holds true even to achieve benefits from lower-level RPA.
It takes a corporate culture that is ready and capable of embracing fundamental changes in how it operates. It requires tangible and active top-level executive commitment and strategic leadership. It takes an understanding of the impact of IA on the workforce and the change management capabilities to address it. And it requires practical knowledge of the various IA technologies, judicious use of third-party expertise and, finally, a recognition of the amount of time, money and resources it will take to exploit its potential.
Our study found that the organizations that are having the most success in overcoming IA challenges and taking advantage of its opportunities are often those already in agile, fast-moving markets and industries. This is not surprising. These firms strive to proactively get ahead of the IA curve even if it means pivoting from traditional existing businesses. They are the leaders or ‘frontier firms’ ‘ (investors in new technologies and process that yield gains that compound over time to pull them ahead of laggards). not just fast followers. These frontier firms also tend to have much less legacy baggage in terms of mindset, operating models and IT systems.
“Feeding the core business while retooling is a really big challenge,” sums up Cliff Justice , Principal, Intelligent Automation, KPMG in the US.
It takes patience when pushing forward with IA efforts, especially given the whole transition may face resistance from managers and staff who may naturally resist and feel threatened by change, especially when it might lead to job loss and changes to roles and operating models.
Despite these challenges, organizations must press ahead with their IA efforts. They must also pay keen attention to how to address not only the technological challenges they will face, but also those more operational and cultural in nature.
Intelligent automation will span quickly across all industries and will disrupt businesses at an accelerated pace. The competitive businesses of the future will be far along the IA curve of development.