InterAct Blog

Supply chains need buoyancy, not just resilience

Pre-pandemic, businesses were already working through the challenges of a VUCA world – where volatility, uncertainty, complexity, and ambiguity in general conditions and situations were often seen. Faster technological changes, digitization, shortening product life cycles, rapid changes in consumer preferences, and political changes all contribute to this view.

The events of the last three years have created even more instability in Supply Chains, and resilience is now a key topic of debate. We can define resilience as the “capacity to recover quickly from difficulties,” but this implies a return to how things were rather than a new, constantly changing paradigm. It is the challenge of an increasingly uncertain future that forces the question of Supply Chains’ purpose and how they should be designed, governed, and operated to continue running productively in the face of whatever challenges are thrown at them.

Just as a ball will float in a storm on the sea, so must our Supply Chains! They need to be buoyant.

Purposeful Supply Chain design

The purpose of a Supply Chain is to get products to people who need them, when they need them, and at an affordable price. This is the definition of a productive Supply Chain.

supply chain productivity model

This should be done sustainably and responsibly. Supply Chains often operate in a non-responsible way, presenting numerous examples of unfairness in the distribution of value along the chain. The control of data and information is a key enabler of negotiating power plays between parties – it is incredibly challenging to get two entities to collaboratively plan just for mutual benefit.

Large enterprises often optimize their operations to the cost of their SME suppliers. From a Supply Chain finance perspective, the bigger players have better credit terms but pass the risk and costs to their supply base – increasing their own cost and risk and leaving the Supply Chain sub-optimized.

Key supply chain design considerations

As part of a Business Model Design, product and marketing strategies should inform and drive Supply Chain strategy and ensure strategic alignment.

supply chain business model design

In a fast-moving consumer goods context, the Supply Chain design requirements for an everyday low-price (EDLP) pricing strategy with relatively stable demand differs from one with deep-dive Hi-Lo promotions and unpredictable demand. The challenge of the Supply Chain design is that within the life cycle of assets, a business may switch between EDLP and Hi-Lo many times. If the design is optimized for EDLP or has high predictability, there will be issues!

The design principles need to work through the infrastructure and operating model to deliver the necessary level of structural flexibility and dynamic flexibility.

Structural flexibility concerns the infrastructure and set-up of the physical Supply Chain and the assets. This includes:

  • in-house capacity
  • outsourced manufacture capability
  • multiple supplier capability
  • geographic location (in-country, near-shore, off-shore)
  • the option to extend or move nodes in the supply chain.

Dynamic flexibility focuses on the operating model – how the physical assets will be managed. The model covers the following:

  • business processes
  • governance and decision rights
  • organizational design
  • performance management processes (e.g. who determines the levels of stock, where it should be held, and the approval processes for those decisions).

Orchestration and synchronization of the Supply Chain are critical enablers for ensuring it is as productive as possible. This is achievable by maximizing flow through the Supply Chain and rightsizing the buffers for stock and spare capacity.

Actions are driven from the source

The signal from the head of the chain closest to the point of final demand should drive actions across the whole chain. Essentially, interactions between business entities within the Supply Chain should be principally taken from a planning perspective rather than a procurement perspective.

There is a need to understand the constituent elements of the buying demand behavior, such as surge and base volumes, to inform the decisions taken in the chain. For example, increased demand for mobile phone gifts may be seasonally driven by Christmas versus purchases for birthday presents or end-of-contract replacements, which are more likely to be spread throughout the year.

A segmentation approach to the demand signal is required to determine the right supply action – an example being the setting of production wheels within a factory or a runners/repeaters/strangers approach to planning.

supply chain flexibility model

Decisions on the required level of dynamic and structural flexibility are critical for businesses. There is a direct cost for resilience as businesses choose to move to lower-cost, more efficient Supply Chains from ones more sensitive to shocks. The positive financial impacts are facilitated by delivering a more responsive approach. An adaptable Supply Chain model, in short, brings new capabilities into the network.

We can consider this cost in a similar way to an insurance premium. Business cases for resilience will be needed – but how is that developed, measured, and articulated against traditional business cases optimized to ROI cash? A traditional business case based on a single number and set of assumptions is inadequate for the unknown storms which may lie ahead. They must incorporate tolerance for different assumptions to give range and richness to thinking.

A balanced response enabling flexibility

Business processes need to develop. One example would be the S&OP process. A traditional S&OP process focuses on dynamic flexibility – aligning Sales and Supply Chain plans to meet demand – often over a relatively short time frame. So, what is the trigger for a structural network design change? How would a review of structural flexibility sit alongside the S&OP process?

Supplier resilience strategies also need development. If one of the needs for structural flexibility is multi-sourcing – how will volume be allocated? Will businesses pay for suppliers to be ready to supply (just in case they are needed), even in a high-inflation economy? Supplier relationship management will need to develop longer-term, more collaborative processes rather than playing a zero-sum transactional game where the price is the key focus.

Top tips for improving Supply Chain flexibility and resilience

So, what are the actionable insights?

  • Commercial and Supply Chain Strategies need to work together over the lead time for structural flexibility.
  • Creating the capability to react to unknown future Supply Chain shocks will increase upfront costs. This needs to be reflected in business cases. Scenario evaluation tools provide insight into the decision-making process.
  • Design for uncertainty and segment the Supply Chain. Actively manage the inventory and capacity buffers to enable a stable beat.
  • Collaboration for network orchestration, both within and between enterprises, needs visibility of data across end-to-end Supply Chains. The use of advanced planning systems is an enabler for decision-making. Procurement’s role and behavior are likewise critical to supplier relationship management.
  • Businesses need to develop collaboration and governance processes for business process design and decision-making. Self-sufficient, empowered teams are enablers for dynamic flexibility.

One of the lessons from the last five years within Supply Chain management is that simply being resilient to recreate the previous conditions and Supply Chain set-up is no longer sufficient for future success. Teams constantly battle from one shock to another – and this is not sustainable. A reactive way of working creates burnout and costs businesses money.

Businesses must actively decide the right level of dynamic and structural flexibility they need. This creates the required capabilities, so they can bounce back from Supply chain Disruptions, use the next crisis to produce opportunities, and create competitive advantages.

Supply Chains need buoyancy, not just resilience.

Ready to learn more?

The insights in this blog are taken from our Innovating Profitable Manufacturing Supply Chains with Resilience webinar organised by
Board International

Watch it on-demand now to take a deeper dive!

InterAct Blog

Making investments into digitalisation – the manufacturer’s perspective

Digitalisation offers significant opportunities for manufacturers. By leveraging digital technologies and data, manufacturers can generate substantial efficiency gains in their own processes, create new forms of value for their customers, and develop innovative business models. These digitalisation opportunities are critical to address the productivity and sustainability demands the manufacturing industry is facing.

Although the range of opportunities digitalisation offers to the manufacturing industry is widely recognized it is of concern that only 35% of surveyed firms have adopted digitalisation solutions at scale[1]. One of the root causes of the lack of adoption in the UK is the lack of investment[2]. According to the Manufacturing Digital Productivity Report from iBASEt[3], 94% of UK manufacturers believe their industry has already fallen behind the US because of a lack of investment into digitalisation, and more than half of UK manufacturers are losing sales as a result. It is even more worrying that 93% of respondents expect that this lack of investment into digitalisation will lead to many UK manufacturers going out of business in the next decade.

To help manufacturers invest effectively in digitalisation, it is important to understand the range of challenges manufacturers commonly face. Only then can the appropriate solutions be identified and put in place. Aston University used a systematic review method to study the challenges for manufacturers and identify critical questions. The results are summarised in Table 1 and discussed below.

Digitalisation goalsThe lack of agreement on the goals of digitalisation encumbers the investment process.
The lack of ambitions in the goals of digitalisation limits the leaders’ ability to justify significant investments.
Investment processDigitalisation integrates a wide scope of investment domains which makes it difficult to apply established processes to assess and prioritise investments. 
The metrics used to evaluate business cases for investment do not relate to the opportunities that are particular to digitalisation.
Digital technology attributesThe high cost of digitalisation and the high uncertainty of return make it difficult to justify investments.
The rapid innovation (and obsolescence) of digital technology acts as a discouragement to making substantial investments.
People and their expertiseThe lack of expertise on acquiring external funding for digitalisation creates an investment barrier.
The lack of senior leaders with digitalisation expertise hampers investments into digitalisation.
Organisational cultureThe difficulty of accepting investment uncertainties inhibits investments into digitalisation.
The lack of openness and trust creates barriers to making effective investments into digitalisation.
Business networkThe lack of digital readiness of the wider network limits investments into digitalisation.
The lack of experienced or relevant finance partners reduces the opportunities for making investments into digitalisation.
Table 1. Challenges for manufacturers investing in digitalisation
Digitalisation goals

In manufacturing, digitalisation affects a wide range of stakeholders and they all feed into the development of the goals. The lack of a specific and widely agreed goal is a critical barrier to making investments into digitalisation.

Digitalisation offers manufacturers opportunities to significantly change how they operate, what kind of relationship they have with their customers, what products or services they offer and who they offer these to. However, many manufacturers restrict their goals to incremental changes and, therefore, struggle to justify making the necessary investments.

Investment process

Digitalisation cuts across established investment categories as it involves aspects of R&D, employee training, and education, as well as the acquisition and implementation of technology solutions. The multi-dimensional nature of digitalisation challenges the traditional investment processes of manufacturers.

Manufacturers traditionally rely on internal rates of return or net present values to justify their investment decisions, and these are not well suited to the possibility of dynamically adjusting an investment after it has been initiated. With digitalisation opening future and potentially unknown opportunities, metrics are required that reflect the flexibility to adjust an investment, change a technology or even abandon it.

Digital technology attributes

The research identified the high costs of required technologies as a major reason that manufacturers do not carry out investments into digitalisation. The cost of technology is particularly high to early adopters, before economies of scale are achieved. Furthermore, while digital solutions are highly scalable, the returns on investments are limited if scale is not achieved.

The pace at which digital technologies develop is unprecedented. Any technology manufacturers choose could become outdated rapidly and require updating, which increases costs. Manufacturers may, therefore, decide to wait for the next digital technology generation to become available or for further standards to emerge before making investments.

People and their expertise

To make significant investments requires manufacturers to raise external finance; but manufacturers often lack the expertise to raise external finance for investments into digitalisation, which significantly differs from raising finance for investments into capital equipment: it requires different funders, business case details and preparations.

Also, decisions on investments in production machinery are often made at the plant level, and are aligned with responsibilities for performance and quality. As digitalisation affects the direction of manufacturers, with implications for their customers and wider networks, identifying the right locus of decision-making is critical for making effective investments. It requires a senior leader with the authority and expertise to make such wide-reaching decisions.

Organisational culture

Creating value with digital technologies requires product and process experimentation following test-learn-tweak cycles. Organisations need to develop a ‘tolerance for uncertainty’ to make effective investment decisions within this context. For manufacturers with limited R&D activities, dealing with these uncertainties is particularly difficult.

Although digitalisation will require changes in organisational roles and processes, the creativity and imagination of staff members across the organisation need to be drawn on to capture the opportunities presented. It is critical to ensure that digitalisation is not perceived as a cost-cutting exercise aiming to create redundancies to ensure the widespread support and effectiveness of investments.

Business network

It is not only the manufacturer’s own investment into digitalisation but also that of their customer and wider network that is critical to making an effective business case. Ultimately, value is co-created by the customer and the wider network, and if these parties do not make investments into digitalisation themselves then the manufacturer’s chances of deriving a return from their investments are reduced.

Making investments into digitalisation also puts a focus on the external finance partner as a member of the network. Finance partners are often overlooked in industrial value networks, but in a digitalisation context their role is critical. This is because these partners are not just financing a machine but also a business process or business development, which requires a much closer relationship.

Making effective investments into digitalisation is a critical challenge for manufacturers. These investments not only determine the success of current digitalisation initiatives but also affect the viability of future digitalisation journeys. It is today’s investments into digitalisation that enable the future competitiveness of the manufacturing industry. Manufacturers need to rethink their established investment processes and organisational practices as many of them stand in the way of making effective investment decisions into digitalisation.





InterAct Blog

Actionable insights from the past: what can we learn from history in the new industrial transition?

Consider a company like Mueller Inc, an American manufacturer of steel buildings and metal roofing, among other things. Prior to their digital transformation, they were facing multiple issues. Their open-source management system lacked flexibility and their online presence was outdated. The buyer journey was far from clear, and customers needed to visit stores to complete purchases. In short, their future seemed increasingly uncertain. Could the answer to these dilemmas have lain in the past?


‘History is the teacher of life,’ goes the saying of the Roman statesman Cicero. But is that still true? More to the point, can it be true in this period of the Fourth Industrial Revolution when the rate of innovation far outstrips anything seen during previous industrial revolutions?

Our project for InterAct, undertaken by teams at Aston and Cranfield, is currently testing the hypothesis that historical examples provide actionable insights for contemporary manufacturers, and that manufacturers can leverage such histories as they adopt the next generation of industrial technologies. Our preference is not to talk about revolutions, but rather about transitions: periods of occasionally spectacular innovation, followed by a halting or gradual readjustment across industry, with occasional sallies back into earlier practices or technologies. Industrial transitions are less like sudden grand revolutions and more like the stop-start evolution of our own lives. As Melvin Kranzberg, one of the pioneers of the history of technology, said “Technology is a very human activity.”

Discovering actionable insights in history

For our project, the team at Cranfield set out to tackle a systematic search of literature about the challenges of digitalisation in industry, finding and analysing 278 articles. Most of the present-day challenges they identified concerned questions of technical innovation, marketisation, or the future of employment.

The Aston team (the authors of this blog post) set out to look at mechanization (18th and 19th centuries), electrification (late 19th and 20th centuries) and computerization (20th century) – the earlier processes of industrial transition.  What was clear from their review, however, was that the spectrum of industrial transition challenges is a lot broader than the perceived issues around technology and its monetisation. In this light, it is reasonable to argue that understanding digitalization needs a wider field of vision, one that is broadened by history, to tackle the challenges of the future and avoid the mistakes of the past.

By widening their field of vision through cases from history, we argue that today’s manufacturers have the chance during this digital transition to increase their appreciation of the potential risks and opportunities that lie ahead, and perhaps even stimulate creative solutions to them. Our historical case search reveals that there are dozens of issues that merit attention both within manufacturing operations (new safety questions, choices of innovation pathways, naivety about technical solutions) and outside of them (the power of location, globalization and culture, negative social consequences of innovation) which hardly figure on the lists of challenges for digitalization.


Returning to Mueller Inc’s dilemma, perhaps inspiration could have been found in historical cases such as the electrification of Zurich’s streetlighting. Over 100 years ago, the town council’s dilemma was whether to invest in AC, DC, or their alternatives. There was little room to manoeuvre, and the recently installed gas-powered streetlighting could have risked looking like an expensive mistake.

Zurich’s response, however, was to focus on stakeholders and to choose the technology that would be more affordable and scalable – AC as it happened – allowing the city to grow by serving surrounding populations more effectively. The solution was technically elegant, but above all politically savvy. Likewise, our friends at Mueller Inc did not focus on which technology was best in its class, but on which digital solution would help their customers achieve their needs. The company opted to move their business to a major digital platform that greatly improved the customer experience while providing big data and analytic tools for their management.

InterAct Blog

The Fourth Industrial Revolution and future of work

A host of publications in the grey and academic literatures herald the emergence of smart manufacturing and the digital transformations brought on by new waves of technological innovation. In manufacturing the Fourth Industrial Revolution (or 4IR) is the overarching socio-technical term, sometimes used to describe the changes arising from these emerging digital technologies and practices.

Smart manufacturing combines the automation of tasks, the digitisation of processes and co-ordinating platforms of digital networks alongside technologies like artificial intelligence (AI). Like the previous three Industrial Revolutions that used steam to mechanise production, electricity to power mass production, and electronic advances in information technology to automate production, smart manufacturing represents a systematic step change. This is because of the scale and complexity of integrating various advanced digital technologies (ADTs) and digitised data in manufacturing production and distribution systems.

Some of the most cited technologies include the Internet of Things (IoT), cyber-physical systems, big data analytics, cloud (and quantum) computing, additive manufacturing, 3-D printing, advanced robotics, augmented reality and blockchain technology: a landscape that is emerging and evolving through innovation, synergy and combination.

For manufacturers there are strong digitalisation incentives: longer product lifecycles, increased operational visibility, reduced costs, optimised production cycles and direct relationships with consumers. Digital servitization is the process of providing bundles of products, services and tools (e.g. big data) for greater customer value. Fuelled by cloud computing, IoT allows the multiple interconnections of (unique) ADTs, while sensors and rendering devices provide a digital intelligence to generate real-time data and actions. These along with big data analytics and platforming enable a shift to Business-to-Customer (B2C) models: greater market reach, faster product to market cycles, more brand control, opportunities to give added-value digital intelligence to products and the collection of customer usage data to inform design and product improvements interfaced with e-commerce platforming.

Digitalisation is depicted as an (yet) uncharted blue-sky horizon of technological development whose haze blurs the lines between the physical, digital and biological worlds: a fusion of technologies that will shape manufacturing sectors, workforces, jobs (their content, design, regulation and protection) and business models in the coming years. For manufacturers, the future script is one of opportunity and uncertainty: continuing and rapid product innovation as companies vie to integrate and develop their digital toy boxes of tools, products and markets.

Smart manufacturers will have to blend ADTs with the digital skills and unique attributes of people to lever their productivity gains. Typical of publications in the grey literatures, Deloitte offer an idealised vision of the types of high-skill, high-tech white-collar graduate-level jobs and roles that smart manufacturing will generate in the very near future. These stand in stark contrast to the often-stereotypical images of older, dirty, risky, and repetitive blue-collar factory jobs that can sometimes haunt images of the sector.

Deloitte outline six prototype jobs and three of these are described as examples: the Digital Twin Engineer who can ‘virtually’ look inside physical assets, systems and structures to optimise design, performance, predict maintenance and improve customer experience; the Robot Teaming Co-ordinator who trains people and bots to work collaboratively; and a popular example often cited in the literature, the Smart Factory Manager, with responsibilities for production, quality control, inventory, connectivity and analytics. Common to all these roles is the use of sophisticated co-ordinated ADT systems, AI and the support of co-bot teams working alongside people at different levels of production and distribution.

Against the backdrop of this digital toolbox meze there is no shortage of some very familiar challenges for work and employment. Automation is strongly associated with job polarisation and the decline in the share of mid-pay mid-skill jobs observed throughout leading western economies in recent decades. Digital production processes and platforming are usually negatively linked (especially in the retail and hospitality sectors) with job (and role) fragmentation and an increase in (the sometimes precarious) work that differs from the standard relationship of permanent, full-time and secure employment (i.e. ‘gig economies’).

Some of these issues may seem very distant from Deloitte’s clean, slick and precise white-collar smart manufacturing settings outlined above, in job design, smart manufacturers will still have to be savvy enough to address the issue of how to attract talent and create meaningful work: higher pay, access to employee benefits and work that is interesting. There are still several broad workforce challenges to be faced: work architecture, workforce skills and (re)training (attracting and retaining digital talent), and what this means for human resources, organisational and job/task design (and processes), strategic organisational leadership, capabilities and cultures. Working in smart manufacturing will also have the potential to raise concerns about greater data-driven employee monitoring and exposure to physical and psychosocial risks arising from constant connectivity and the overlap of work and non-work time.

A strong theme in the literature are the demands for high-skill smart manufacturing workforces with digital and ‘soft’ skills. A recent World Economic Forum study highlighted that the top 10 skills for the next decade include what we think of as essential human skills – critical thinking, creativity and people management – alongside technical digital skills. ‘Essential’ human skills are the things that cannot be automated (yet). This puts the emphasis on retraining existing manufacturing workforces, building ‘soft’ skilled workforce capacities and more widely, being able to attract and retain ‘digital people’ talent. To support the latter, there may be markedly better opportunities created in high-tech smart manufacturing settings for equality, diversity and inclusion initiatives around working time flexibility and the labour market integration of specific groups, such as women and those with more domestic care responsibilities and health issues. Also, as products, services, workforces and supply chains become increasingly connected, this results in new chains of value creation increasing the potential for more employee-led innovations, and distributed leadership to create more opportunities for change and building capacities for improvements to products and customer services.

A major workforce challenge in transitions to smart manufacturing will be fears about job substitution and the destruction of jobs (automageddon) by the rise of the bots (and their new co-bot allies). Automation has always been the harbinger of apprehension about its consequences for jobs and aggregate levels of employment: the jobs that people can do, the tasks they will perform and the new key skills that workers will have to acquire. This is a popular image of automation even though technology also creates many new jobs.

Historically, labour markets have always accommodated and absorbed automation. Technology complements workers skills and increases their task performance, while eliminating those manual and repetitive tasks that are easier to automate. Although technology has historically had little adverse impact on aggregate employment, this still masks some underlying processes of job destruction and creation in particular sectors and groups of workers. Initially, automation complemented low-skill work. Later, it substituted for it while complementing middle and high-skill work. Today it complements high-skill work but often substitutes for middle-skill work. It is reasonable to expect that these technology-related effects in smart manufacturing will rhythmically evolve, emerge and once again change in the future.

A significant limitation of current debates in automation and smart manufacturing is that it is very difficult to predict future levels of employment given the relative recency and quality of existing studies that are trying to map events that are still emerging in ‘real time’. There is still a great deal of speculation and uncertainty about what will happen as smart manufacturing sectors emerge, grow and develop. The Babbage Repot makes it clear that smart manufacturing is largely concentrated in larger sized companies in ten developed economies who tend to be those who make the greater share of new technology patents, investments, adoptions and implementations. Equally important but relatively understudied, are questions about how smart manufacturers influence the design of work and jobs, and which tasks/skills can be substituted, complemented or augmented. The mechanisms by which smart manufacturing technology complements/ arguments jobs and tasks are not well understood, nor the strategic decisions that companies’ make around technology investments. In this sense, there are interesting issues about workforce engagement and dialogue: and how smart manufacturers anticipate, plan and strategically balance decisions about technological investment alongside workforce issues.

InterAct Blog

Distributed leadership as a route to innovation and productivity in advanced manufacturing

New ways of working and leading in manufacturing

Advanced technologies such as robotics and AI, and other forms of digital innovation, open up important new opportunities for the transformation of work in UK manufacturing, with potential benefits for employees in terms of job quality and wellbeing, and for businesses in terms of improvements in productivity and innovation performance.

However, there are concerns that these benefits may not be fully realised if manufacturing businesses fail to innovate their leadership and people management practices to empower people to deploy technologies in an agile and effective way. Our research for the ESRC InterAct Network is working with manufacturing businesses to explore exactly these issues; what sort of changes in work organisation, people management and leadership are required if manufacturing employees across teams are to contribute to driving innovation and productivity?

One important clue as to what’s needed in leadership development might be provided by an emerging evidence base on the impact of ‘distributed leadership’ practices. 

Distributed leadership and empowering people to innovate

One potential constraint on innovation in organisations is the concentration of leadership roles and authority among a small cadre of senior managers. That’s why in a range of organisations, especially in public services such as education and healthcare, there is growing interest in the value of an alternative approach of distributed leadership: “an approach to leadership that endorses work practices that combine knowledge, abilities and skills of many individuals… creating opportunities for leadership to emerge from individuals at all grades and levels within a team or organisation”.  For example, Professor Graeme Currie and colleagues have argued that effective distributed leadership has been, and will continue to be, crucial to healthcare systems’ responses to the Covid-19 crisis.

It’s interesting that much of the current research on the challenges and opportunities of distributed leadership focuses on public services and other service sectors, with somewhat less interest from those studying manufacturing innovation. This is despite the fact that some of the seminal research on distributed leadership focused on its impact in manufacturing – more than thirty years ago, David Barry’s important research on so-called ‘bossless teams’ identified both opportunities in supporting team innovation performance and challenges where team members lacked the skills and resources to lead effectively. David Teece’s seminal work on dynamic capabilities – “the firm’s ability to integrate, build and reconfigure internal and external resources to address and shape rapidly changing business environments” – is another cornerstone for our research. It is notable that Teece and colleagues also cite distributed leadership as an important practice for dynamic and agile organisations in manufacturing and other sectors.

So, what sort of practices might be required for effective distributed leadership, and what are the potential benefits and risks for manufacturers?

Scoping the potential for distributed leadership as a route to innovation

InterAct Network researchers will be working with leading manufacturers in the coming months to explore what works in effective distributed leadership. But we already have some clues from existing research. Where distributed leadership has contributed to productivity and innovation, organisations have tended to make workplace investments to: develop leadership skills and identify succession pathways; re-design job roles to enhance autonomy; and create protected time and real or virtual spaces for leaders at different levels to collaborate and share ideas. The evidence suggests that these practices might be important, but also that context is crucial. Distributed leadership needs to be calibrated carefully to reflect the needs and capabilities of each organisation.

There are also potential challenges associated with promoting distributed leadership that need to be addressed, including: the risk of a fragmentation of accountability and unclear decision-making; gaps in leadership skills and capabilities; and limits to the time and resources available to people at different levels to participate in leadership activities.

A key theme for our InterAct research in the coming months will focus on how, and how effectively, some of our most innovative manufacturers adopt more distributed models of workplace and organisational leadership; the challenges and limits to such practices; and impacts in terms of job quality and innovation performance.

If you represent a manufacturing organisation and would like to share and learn from good practice in leadership and people management for innovation, join the InterAct Network today.

If you would like to access our free research on leadership and people management for innovation in manufacturing, contact:

InterAct Blog

The Future of the Economy

The Future of the Economy is one of the three substantive research streams of the InterAct programme.

Digitalisation is central to the new generation of manufacturing systems and processes. The diffusion of new digital technologies creates distinctive challenges to firms and organizations, in terms of the adoption of new technologies as well as the management of transition.

Digitalisation may disrupt existing firms while accelerating new venture creation and change the existing industrial structure. Eventually, this will affect the structure of the wider economy and it will be shaped according to the needs and benefits of digitilsation across industry.

It is the aim of our Future of the Economy workgroup to investigate these impacts and generate actionable insights that will allow businesses to prepare for major changes to the way the manufacturing sector operates.

Our focus is distributed between three key areas:

Digitalisation, diffusion, and high growth

Crucially, digital technologies can help reconfigure capabilities within companies and across industries. Eventually this may alter all aspects of the UK’s industrial fabric by reshaping the drivers of high growth. However, so far, there is limited understanding of how this will happen. There is an expectation that the digitalisation will alter the structure of the knowledge networks of the UK economy, and this will change the nature of linkages among sectors. If so, what new linkages will emerge and how can we map them? How does knowledge diffuse across industries? What are the new channels of diffusion?

Digitalisation, industrial structure, and social mobility

We know digital technologies may lead to the emergence of ‘superstar’ manufacturing firms. However, this not the only consequence of digital transformation. Crucially, the combination of new technologies and trade openness has led to rising job polarisation, wage dispersion, and regional divergence. It is argued that new digital technologies may have a similar negative impact, in particular for women and marginalised groups.

What is the impact of digitalisation on social mobility and how can the existing trends be offset? Importantly, what institutions need to be in place to maximise social mobility and inclusivity? In this respect education and training are key factors that can offset these trends.

Evidence from many countries suggests that dedicated centres of innovation linking industry stakeholders can help develop new programmes for re-skilling. The UK already has some of these types of facilities which could be better exploited to galvanise industry-wide change. This is essential so that digitalisation may lead to local technological diversification. As such, if marshalled within a broader coordinated national policy response involving all stakeholders, digital technologies have the potential to help society make significant progress on societal challenges such as inclusivity as well as social mobility. 

Digitalisation, the ‘Levelling Up’ agenda, and trade

Digital transformation creates tensions on the shape and the geography of the economy. Although often overlooked, these changes can be highly disruptive, as new generations of digital technologies replace and reshape industries, altering the geography of production as a result. Enhanced manufacturing performance can potentially help the ‘Levelling Up’ of many regions and indeed UK evidence already suggests that there are long-term local productivity advantages to the early adoption of digital technologies.

The fact that the levels of patenting activity, and particularly ICT-patenting activity, of the UK’s major manufacturing regions tends to be no more than ‘moderate’ by European standards further emphasises how important the rapid take-up of these digitalisation technologies is for the ‘Levelling Up’ Challenge.

SMEs are often at a financial as well as a technical disadvantage to deploy new capital-intensive technologies; at the same time, UK manufacturing is also more exposed to Brexit than other sectors, a trade shock which will impose significant costs to UK industry over those in other countries.

We want to address these two research questions:

  • How can the diffusion of digital technologies in UK manufacturing contribute to the ‘Levelling Up’ agenda?
  • How will the UK’s trade structures change in response to the manufacturing sector’s uptake of digital technologies?

The projects under the Future of the Economy workstream will examine the likely effects of digitalisation in manufacturing the context of the wider inter-industry, inter-regional, and international linkages evident in UK manufacturing. This will allow us to measure the impacts of digital transformations at the sectoral and regional scale and to consider the impacts of different digital-adoption scenarios across industries.

InterAct Blog

People management, dynamic capabilities, and workplace innovation

The COVID-19 crisis and its impacts have required organisations to demonstrate dynamism in innovating their business models, developing new product and service offers, and transforming methods of work organisation. Business stakeholders and researchers are accordingly interested in tools that can help them to understand why organisations have been more, or less able to demonstrate agility and innovation in the face of the crisis.

It seems to me that there is considerable value in revisiting the already highly influential ‘dynamic capabilities’ framework developed by US scholar David Teece and colleagues from the mid-1990s onwards. For David Teece:

“Dynamic capabilities are the firm’s ability to integrate, build and reconfigure internal and external resources to address and shape rapidly changing business environments.”

For Teece and colleagues, dynamic capabilities can be understood in terms of organisations’ capacity to sense and articulate opportunities and threats, seize opportunities, and dynamically reconfigure tangible and intangible assets to transform the organisation and its operations.

Sensing involves searching and exploring across networks, technologies and markets, identifying latent or emerging demand, spotting changes in sector and market structures and business models, and processing threats from competitors and insights from supply chain partners and customers.

Seizing involves responding through the development of new products or services and/or innovating the business model or ways of working (facilitated by investments in new technologies, systems, and capabilities). Reconfiguring and transforming requires the modification and re-alignment of product or service offerings in line with the organisation’s (renewed) systems, processes, ways of working and capabilities.

Examining dynamic capabilities is a helpful approach to understanding organisations’ handling of COVID-19 challenges, given the theory’s focus on responsiveness to change and crisis. Indeed, several reports have used the framework to assess the agility demonstrated by some organisations in pivoting and innovating in response to COVID-19. For example, Gloria Puliga and Linda Ponta’s recent research with Italian firms notes the importance of external networking to dynamic capabilities in organisations responding effectively to COVID-19 challenges.

However, perhaps a key weakness in much of the existing dynamic capabilities research is its relative failure to factor in the role of people management (or indeed just people at different levels and roles within organisations) in promoting dynamism and innovation. This isn’t to say that HRM and people management is completely absent from dynamic capabilities research. The original research by leading dynamic capabilities scholars makes some (albeit limited) reference to HR investments to promote a flexible workforce that is willing to buy-in to transformative change processes.

Recent work by Paula Apascaritei and Marta Elvira in Human Resource Management Review journal has been helpful in scoping out what ‘HRM dynamic capabilities’ might look like, focusing on:

  • Knowledge building capabilities (strategies to support workforce diversity to contribute to innovation; the valuing of relational ties brought to the organisation that can lead to knowledge, talent and/or customer acquisition).
  • Social integration capabilities (enabling relationship-building with customers and partners; building social capital within and across teams).
  • Reconfiguration-enhancing capabilities (a focus on upskilling employees for ‘functional flexibility’; but also practices helping employees to manage change and mitigate stressors associated with organisational transformation).   

There remains a need for further research on how these sorts of capabilities are made real by people managers in different organisational contexts. We also think that there may be important lessons for dynamic capabilities researchers that we can draw from the broader evidence base on how targeted HRM strategies can support ‘workplace innovation’.

Our previous research in this space warns against pursuing a single, de-contextualised best practice, but identifies a number of recurring themes around HR practices that have supported employees to innovate in different organisational contexts: job design that values high levels of autonomy; consistent and good quality feedback; strong communications and peer support networks within teams; and sufficiently challenging job content that nonetheless guards against employees becoming burnt out.

Manufacturing can be a challenging context within which to redesign work to maximise autonomy and innovation at the individual-level. However, even here there are examples where thinking creatively about people management has empowered employees at all levels to participate in innovation and drive change.

What more can we learn about the combination of workplace and people management practices that work well in tapping the innovative potential of employees to drive dynamic capabilities? What challenges do manufacturing employers face in aligning people management with their priorities for sensing and seizing opportunities and transforming their operations to build back better post-COVID-19?

These are some of the issues that our Strathclyde Business School InterAct team will be exploring with UK manufacturers in the coming months. If you are a manufacturing sector stakeholder or an employer interested in maximising the innovative potential of employees at all levels, we would be excited to hear your views and to discuss our research.

InterAct Blog

Will digital technology help Scotland’s manufacturers recruit and retain a more diverse workforce?

Earlier in the year I wrote a blog about the importance of diversity in the manufacturing sector. Diversity is about encouraging participation by people from different backgrounds, listening to different views and trying to understand others’ experiences. Inclusion (often talked about hand in hand with diversity) is about ensuring everyone feels welcome and valued.

In my earlier article I argued that diversity and inclusion can lead to clear business benefits including innovation and problem solving. A recent Make UK report suggests that manufacturers who embrace diversity and inclusion are 25% to 36% more likely to outperform their competitors in terms of profitability and performance. It is also a moral and ethical imperative that we are not excluding people.

Manufacturers in Scotland are dealing with significant change. The pandemic has changed many manufacturing businesses, and while some markets have been hit hard, many manufacturers are busier than ever. Meanwhile technology is also advancing apace, and during the past 18 months many companies have accelerated their digital journey. Recruiting staff is a major challenge for many manufacturers today, so more now than ever we need to be attracting a diverse population into the sector.

Diversity, inclusion, and wellbeing in the manufacturing sector are issues that the Scottish Government are taking very seriously, and I have recently been asked to join the Equalities and Wellbeing in Manufacturing short life working group. We know that we need to attract more people into manufacturing jobs in Scotland, we see the value of diversity and inclusion, and we also want to make sure that people are healthy and happy at work.

Wearing another of my hats, I am also involved in the UK government investment in digital technology in manufacturing through Made Smarter Innovation. This recognises the need for manufacturing firms in the UK to embrace new technologies and reap the rewards of the digital era of manufacturing.

One of the questions that I’ve been thinking about over the past few weeks is whether digital technologies will have a positive or negative effect on diversity in manufacturing.  I have been speaking with some inspirational people and asking this question. In this short article I hope to open this up for discussion.

The first thing I wanted to know is: do we have an issue with diversity in Scottish manufacturing? Often the conversation starts by focusing on under-represented groups or protected characteristics under the Equalities Act 2010 (age, disability, gender reassignment, marriage and civil partnerships, pregnancy and maternity, race, religion or belief, sex, and sexual orientation). But for me diversity of thought is also important for innovative and stimulating workplaces, people from different educational backgrounds, different social groups, different experiences. This is harder to unpick using statistics!  

Let’s look at what we can see from the statistics, according to the Office of National Statistics the Scottish manufacturing workforce is 76.6% male, 98% white, 10.4% are classed as disabled and just 1.9% identify as minority ethnic. In addition, 36.5% are aged over 50 and 25.6% have a long-term condition or illness. 8.8% work part-time. (Annual Population Survey 2019, Office for National Statistics). So, to be frank, there is work to do in tackling diversity, inclusion, and wellbeing.

We need more information before we can really tackle some of the problems. Statistics themselves don’t tell us is where the issues lie. Is it that manufacturing just isn’t attractive to certain people? Is it that we don’t talk enough about manufacturing in schools and in the media? Is it that we lack diverse role models? Is there discrimination in recruitment? Is it that environmental factors such as pay, hours, etc., do not work for some people? Is it an issue of leadership? Or maybe flexibility? There are many questions that we are seeking answers to. Understanding people’s perceptions of manufacturing is something I am committed to investigating as part of the ESRC Made Smarter InterAct Network.

Is digital technology likely to help or hinder diversity in manufacturing? And what will the impact be on wellbeing? Digital transformation will undoubtedly bring changes in the workplace and in the labour market. New jobs will be created, some occupations may disappear, but mainly we will see changes to jobs. Technology will assist people with tasks and change the way we recruit staff and the flexibility we can offer. Digital manufacturing should open new possibilities, as well as offering manufacturers the opportunity to become more sustainable and flexible.

New jobs will be created. Digital manufacturing requires a workforce with a broad range of skills. I have said before in earlier blogs that it frustrates me that in the media talk of manufacturing is often accompanied by images of heavy engineering. Manufacturing itself is diverse and there are so many jobs in manufacturing, particularly in a digital environment, that do not require engineering skills – manufacturing companies need people to manage the supply chain, analyse data, plan production, design products, run their social media, along with all the other administration that is needed to run a business.

If we can get the message out there, that manufacturing companies need a diverse range of skills, then perhaps we would appeal to a broader range of people. Digital technology also helps us to become more sustainable – both through becoming more efficient in our use of resources, as well as in more novel ways of working. Sustainability, we know is something that drives many people to choose who they work for, so the more manufacturers can show their sustainability credentials, the more people might be attracted to working in the sector.

But what of the jobs that might disappear? A recent report from Abi Hird at KTN warns us to be wary of the unintended effects of technology. She points out that females and ethnic minority groups occupy many of the lower paid administrative and operator positions in manufacturing. If digital technology displaces these jobs, then there could be negative consequences for workforce diversity. This is one area we do need to watch as it could be at odds with what we are hoping to achieve.

On a positive note, industrial digital technologies should offer us safer workplaces with less human exposure to harsh environments. It could be for example, technology is better suited to do certain tasks, and this could free up humans to focus on elements of the job where they are best suited or perhaps take on other roles, that are potentially more fulfilling. It also opens up the possibly be more inclusive.

I know an engineer of advancing years used to jump in and out of machines, climbing ladders and crawling under small spaces in manufacturing plants. Today this isn’t something he really wants to be doing with his creaking knees! With digital technology and the use of sensors, he needs to do these physical inspections much less, and can focus on the part of the job that he really enjoys, solving problems. Similarly, there are many instances where robots are taking the heavy lifting out of some manufacturing jobs, making it easier for people with less strength or mobility.

Finally, before leaving this topic we also need to design our industrial digital technologies with people in mind. In the Made Smarter report, Abi Hird makes a special plea to innovators to think about equality and diversity when designing digital technologies. She points to issues with virtual reality, largely developed with men in mind where not only are headsets often too large and heavy for women but also there are depth perception differences between men and women (largely ignored by tech developers) that cause more women to experience motion sickness.

I would be delighted to hear what you think about the impact of digital technologies on equality and inclusion in manufacturing. In particular, what you think we should be doing to make sure we build a more diverse manufacturing workforce going forward.