While most routine physical tasks have been mechanised over the past 150 years, many routine and arduous mental jobs continue to be carried out by people. In the legal sector, employees plough through vast numbers of cases, check the ﬁne print of contracts for loopholes, for example; and in healthcare there’s the need to work through a mass of medical evidence reports, patient records and clinical trials to make diagnoses. It can be slow, expensive work; as well as being dull and unrewarding for employees themselves.
Artiﬁcial Intelligence technology and algorithms that can replace many routinised tasks are already available, and have the potential to improve the productivity of professional services. AI essentially separates the roles of making predictions from a mass of data on one hand, and informed judgment on the other. As well as reducing costs and eliminating the potential for human error, AI releases professionals to focus more of their time on making better judgments, management and strategic thinking. Automation of data processing and delivery also opens up opportunities for new streams of service oﬀerings.
But for the moment AI is adopted much more by bigger professional services organisations, with the resources to invest in experiments, than by smaller ﬁrms. There are also layers of cultural and institutional norms that need to be understood and possibly challenged: ﬁxed ideas about the roles of professionals; the types of people they want to recruit (what’s a data scientist and how are they going to ﬁt into the traditional oﬃce environment?); and how are new entrants going to learn about the profession without ﬁrst being involved in routine tasks?
The principal issue, learnt from many years of problems with technology adoption in organisations, is about understanding how adoption takes place and what the role of management is in that process. This requires people with the understanding, motivation and support from the top, to implement unfamiliar and challenging technologies.
We’re part of a major new research project to help mid-sized law and accountancy ﬁrms do just this. The Innovating Next Generation Services through Collaborative Design project will help professional service ﬁrms that are cautious or uncertain over how to implement technological change, and exploring what AI and machine learning can and can’t do. The project will explore enablers and barriers to adoption and run design ‘sprints’ to try out possible technological and organisational changes with collaborating ﬁrms, so as to understand better how to overcome obstacles to greater AI adoption.
Our Productivity Connections event with The Work Foundation and the North West Business Leadership Team, bringing together a mix of senior people from business and unions, academia and policy, highlighted the importance of management skills and attitudes to beginning the engagement with Industry 4.0 technologies.
Lesley Giles, Director of The Work Foundation, pointed to how the rise of technology is making ‘human’ skills – management, leadership, emotional intelligence, and innovation –more important and valuable. While well-run businesses use and develop their people well, she argued, the UK has few companies adopting high performance working practices; less than half of employers invest in external training for their people.
Participants agreed that there needed to be a new awareness and understanding among managers of the importance of more training and development for building skills, and of where the ﬁnancial support for this could come from. Data shows UK ﬁrms are lagging behind their G7 counterparts in terms of skills development; which could be related to the perceived high cost of training (both direct costs and opportunity costs) particularly among owner/managers of SMEs. Digital skills aren’t being seen as a core part of business strategy, only as a supplementary add-on, a token nod to the future.
A core challenge was identiﬁed as being the need for more ‘hybrid’ staﬀ; people with a blend of business, ethical, and technical skills. The shortage of schoolleavers and graduates with STEM skills mean only a small proportion are available to smaller ﬁrms once larger employers in ﬁnancial services and technology have had their pick. There aren’t the numbers of digitally-savvy workers needed to help turn small enterprises into medium-sized ﬁrms.
Naturally, smaller businesses are more focused on day-to-day operations and survival than strategic development for the long-term. That means a ﬁxation with cheaper, low-risk and short-term solutions, including when it comes to productivity and skills issues. Investing in training and new technology keeps drifting down the list of priorities. The biggest challenge, then, is in gathering powerful evidence of beneﬁts for SMEs.
Proof of what Industry 4.0 looks like and how it works in practice is everything. A Made Smarter pilot is running from March 2019 across the north west of England, led by Siemens CEO Juergen Maier. The £20 million project includes a package of leadership development for manufacturing SME ownermanagers delivered by Lancaster’s Management School on how to accelerate their adoption of Industry 4.0 technologies. A peer network will be created to encourage sharing and support for digitisation ideas and initiatives. Firms will have the opportunity to experiment with digital technologies and ideas for improving productivity, sustainability and services for customers, working together with their stakeholders –suppliers, customers and employees –to test the practicalities of implementation.
The pilot will lead to the creation of ‘lighthouse’ examples of digitisation, the impact it’s had on productivity, performance and proﬁtability; the kinds of evidence and bottom-line successes that will spur many more manufacturers and members of their supply chains to commit to being part of the revolution.
Lancaster’s expertise is being drawn on by international partners. A developing relationship with the University of South Australia includes input into research looking at the transition from advanced to intelligent manufacturing, including the use of an ‘adoption barometer’ to keep track of how manufacturing SMEs in the state are digitising operations.
Martin Spring is Professor of Operations Management and Director of the cross-disciplinary Centre for Productivity and Eﬃciency. More information on the Made Smarter programme and participation can be found at madesmarter.uk
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