Connecting the SMART work design approach to sociotechnical design principles

Abstract

While sociologists have a strong interest in the division of labour, the labour process, and sociotechnical design aspects, in relation to job and work design, psychologists stress the importance of human needs and human satisfaction. Sociologists underline strategic and organisational choices as conditional to the quality of work, whereas psychologists focus on person-environment-fit approaches. Recently, we observe a rapprochement in the field, with regard to the development of the SMART work design model; individual, team, and organisational elements are integrated into an approach that links human needs, job characteristics and organisational conditions. In Europe (particularly in the Lowlands and Scandinavia) researchers have linked sociotechnical design thinking to organisational design principles for production layouts and quality of work criteria into a modern sociotechnical approach. The paper intends to stimulate discussion about how to integrate elements of the SMART work design approach and the 'modern sociotechnical' into an integral approach, in the sense that 'HR professionals meet the engineers'.

Full text

1
Connecting the SMART work design approach to sociotechnical design principles
Peter Oeij, Steven Dhondt & Fietje Vaas
Paper for “Work Design for Success: Innovative Research and Leading-Edge Practice”; The 2024
Centre for Transformative Work Design Conference, Perth, Western Australia | 13-14 February 2024
Abstract
While sociologists have a strong interest in the division of labour, the labour process, and
sociotechnical design aspects, in relation to job and work design, psychologists stress the importance
of human needs and human satisfaction. Sociologists underline strategic and organisational choices
as conditional to the quality of work, whereas psychologists focus on person-environment-fit
approaches.
Recently, we observe a rapprochement in the field, with regard to the development of the SMART
work design model; individual, team, and organisational elements are integrated into an approach
that links human needs, job characteristics and organisational conditions. In Europe (particularly in
the Lowlands and Scandinavia) researchers have linked sociotechnical design thinking to
organisational design principles for production lay-outs and quality of work criteria into a modern
sociotechnical approach. The paper intends to stimulate discussion about how to integrate elements
of the SMART work design approach and the ‘modern sociotechnical‘ into an integral approach, in
the sense that ‘HR professionals meet the engineers’.
Keywords: work design; sociotechnics; quality of work; organisational design; job design
1. Introduction
There has always been a diverging approach to the quality of work between sociological and
psychological disciplines with regard to job and work design. While sociologists -who identify
themselves with organisation designing engineers- seem to have a strong interest in the division of
labour, the labour process, and sociotechnical design aspects, psychologists -who identify
themselves with HR-to-the-business professionals- stress stronger the importance of human needs
and human satisfaction. Sociologists seem to underline strategic and organisational choices as
conditional to the quality of work, whereas psychologists seem to focus on person-environment-fit
approaches. Sometimes a controversy is framed between ‘objective’ and ‘subjective’ styles of doing
research and improving working conditions in practice. Unfortunately, this does not help much to
stress the commonalities and convergence between disciplines.
In recent years, however, we can observe an important rapprochement in the field. With the
development of the SMART work design model of Parker and colleagues it can be observed that
individual, team, and organisational elements are integrated into an approach that links human
needs, job characteristics and organisational conditions. We think that the SMART model is different
from the more usual person-environment fit models in the W&O psychology discipline. In Europe
(particularly in the Lowlands and Scandinavia) researchers have linked sociotechnical design thinking
to organisational design principles for production lay-outs and quality of work criteria into a modern
sociotechnical approach. Dutch researchers have started to seek to integrate elements of the SMART
work design approach and the ‘modern sociotechnical‘ into an integral approach (Oeij et al., 2021,
2023).

2
The purpose of our paper is to confront and connect the ‘psychological individual & team
approaches’ to work design with the ‘sociological organisation approaches’ to work design (Figure
1).
Figure 1: Connecting psychological and organisational approaches to work design
A reason to perform this exercise these days is the present debate to make industries and work
environments less technologically deterministic and more human-centric, as in the Industry 5.0
approach, compared to Industry 4.0 (Breque et al., 2021). To design human-centric jobs and
workplaces practical guidelines and principles are desired. The SMART work design approach is, for
example, related to a variety of streams in work and organisational psychology, such as the study of
human needs, job characteristics, job design requirements, job resources, and job / team crafting
(Bakker & Demerouti, 2017; Deci et al., 2017; Hackman & Oldham, 1975 and 1980; Oldham & Fried,
2016; Parker & Grote, 2020 and 2022; Parker et al, 2017; Tims et al., 2013; Van den Broeck et al.,
2021). The sociotechnical systems design approach is, amongst others, related to models of function
analysis (WEBA model), principles to design organisations and production systems (sociotechnical
principles, the job – demand / control model of Karasek, the ‘complete job’ model of Hacker (1986
and 2003), workplace innovation and skills approaches (De Sitter et al., 1997; Govers & Van
Amelsvoort, 2019; Karasek & Theorell, 1980; Kuipers et al., 2020; Pot et al., 1989 and 1994; Vaas et
al., 1995; Van Amelsvoort & Van Hootegem, 2017).
The sociotechnical researchers (i.e. mainly sociologists and management scientists) state that
organisational design is conditional to job design (‘primary prevention’, causal conditional
approach). The implication is that (subjective) job satisfaction of persons is subordinate to
(objective) job design criteria, because people differ in preferences but jobs should have quality
standards for everyone. HR-practitioners, however, are often trained as psychologists. Their point of
departure is more often to intervene in the skills and behaviours of persons (‘secondary prevention’,
combating symptoms approach) and to find an optimised ‘person-environment fit’. The sequence of
design interventions is therefore significant for their effects: the preference is first primary
prevention, then secondary prevention.
Our expectation is that this exercise can feed into constructive discussions among psychological,
sociological, management, and business scholars, and practitioners, in the field of jobs, work and
organisation design.
In this paper we shall first summarise the SMART work design model. Subsequently we identify the
organisational structural and cultural design criteria. And finally we connect these to integral system

3
requirements and the sociotechnical design rules. We close with conclusions and recommendations
with respect to the future of work and Industry5.0.
2. SMART work design model
Parker & Knight (2023) propose the SMART work design model, that identifies five higher order
categories of work characteristics, including stimulating work characteristics (task variety, skill
variety, information processing requirements, and problem solving requirements), mastery work
characteristics (job feedback, feedback from others, and role clarity), autonomous work
characteristics (decision-making autonomy, timing autonomy, and method autonomy), relational
work characteristics (social support, task significance, and beneficiary contact), and tolerable work
characteristics (low levels of: role overload, work–home conflict, and role conflict). They tested this
structure through higher order confirmatory factor analysis, followed by validity tests linking the
factors to the theoretically relevant outcomes of job satisfaction and performance.
Table 1. Higher-order work design factors, including their definition, theorized links to organizational
design and psychological processes, and their work characteristics (Parker & Knight, 2023).
By applying structural equation modelling Parker and Knight (2023) tested the relationships between
the five higher-order factors and psychological processes, i.e. psychological human needs, and the
outcome of job satisfaction. These relationships proved to be significant, and an additional positive

4
direct pathway was found between tolerable work characteristics and job satisfaction. Figure 2
displays the final model.
Figure 2. The final structural equation model showing the usefulness of the higher-order constructs
(Parker & Knight, 2023).
The third row of table 1 is concerned with a link to organising conditions of the mentioned SMART
higher-order factors and human needs. This is where sociotechnical thinking comes in. The Lowlands
variant of ‘modern sociotechnical systems design’ (MST) has developed rules to design
organisational conditions that can guarantee excellent organisational and job performance, and
holds the assumption that this will result in high job satisfaction (De Sitter et al., 1997), although
these sociotechnical researchers state that job design is more fundamental for meaningful work
than the job experience of persons, which is a merely a consequence of the quality of work and not a
cause of it.
3. Linking human needs to integral system requirements
Modern sociotechnical systems design theory (MST) is an open systems approach to design work
processes (the process of producing goods or services) (Kuipers et al., 2020)1. The design of work
processes of organisations follow from strategic choices that organisation members (often
management) make. These choices deal with matters such as markets, customers, products,
business models, finance. The mix of those matters results in decisions on how the product can be
produced to meet the needs of markets, customers, investors and so on. Thus, we have production
criteria for the lay out of the work process. The MST approach not only looks at economic values as
an input for the design. Human values play a significant role in the MST principle to minimise the
division of labour. In the end this principle contributes to the quality of work by the design of
‘complete jobs’ (Hacker, 1986 and 2003 )in which executive and managing tasks are not split up as in
Tayloristic and Bureaucratic organisation designs. This allows to take into account human-centric
values that lead to work criteria that enable the inclusion of well-being-at-work criteria, such as
reducing stress risks and enhancing learning and developmental opportunities. MST design rules
1 This sociotechnical variant of the Low countries is often overlooked, even in sociological overviews of the link
between sociotechnical systems thinking and quality of work (e.g. Guest et al., 2022). We think it is because it
is ‘too technical’, as it has a strong relation with operational management.

5
follow a certain sequence, namely to first design the production lay out top-down (called production
structure), and second, design the logic of dividing managing and operational tasks bottom-up
(called management structure). In line with minimising the division of labour the MST principle is to
locate decision latitude at the lowest organisational level where problems occur and where
autonomous decisions can be taken. Once these functional requirements of production and
management are determined, the design of supporting systems follow, such as technological
systems, information systems, management systems, human resources systems. The sequence of
the design is crucial. All too often, organisations choose the application of technologies and IT-
systems that create a division of labour omitting the quality of work criteria. Instead of a
complimentary technology to augment workers in their job (see figure 3; INSIGHTS_EU, a H-EUROPE
research proposal, to be submitted in 2024), technologies are steering and monitoring what workers
do. Both sociotechnical researchers and work and organisational, and occupational health
psychologists care about the well-being of people in their work, and that is the reason why
connecting the SMART work design model and sociotechnical design principles is a groundbreaking
opportunity to simultaneously improve organisational performance and the quality of work.
Figure 3: Complementary augmentation method
Table 2 shows the main features of the SMART work design model in column 1 to 4 as discussed in
section 2 (Table 1), and sociotechnical features in column 5 to 7: organisational structural design
criteria, organisational cultural design criteria and integral system requirements.

6
Table 2: SMART work design model features and sociotechnical design criteria and requirements
4. Connecting the SMART work design model to sociotechnical design rules
In this section we discuss the design rules that operationalise the sociotechnical design principles
and that can be connected to the SMART work design model. The issue we want to address first is
the question of why psychological researchers and HR professionals should have an interest in
sociotechnical design if all they have to focus on is the job satisfaction of workers. What’s in it for
them?
While ‘engineers’ usually design organisations and their production processes, ‘HR to the business’ is
responsible for ensuring the right personnel. While engineers concentrate on making the production
process and the products functionally more effective and cost-efficient, HR-professionals are
concerned with the person-environment fit. While engineers use their expertise to design and
implement (information) technology to enhance the productivity and the product’s competitiveness,
HR-professionals are improving the skills match between the present worker skills and new skills
requirements of technology. While engineers worry whether they meet the needs of management,
operational foremen, shareholders, clients and customers, HR-professionals worry about
occupational safety and health, psychosocial risks, musculoskeletal risks and job satisfaction. The
salient problem in such instances is that engineers have no expertise in people issues and HR-
professionals lack expertise in operational management issues. Consequently, certain options to
improve the quality of work are underused (Karanika-Murray & Oeij, 2017).
Can we change this? One option is to enhance the knowledge of engineers with the importance of a
good quality of work: better jobs enhance the commitment and involvement of people, which will
not only support their job satisfaction, but also their contribution to the quality of the output of the
production process and the process of innovation and organisational change in the form of
employee innovation adoption. But engineers may reason, why should I care about that as long as

7
people are replaceable by other people or technology through automatisation, robotisation and
digitalisation; as long as costs are controllable and customers are satisfied, who cares?
Another option may be to enhance the knowledge of HR-professionals with insights on operational
management. But HR-professionals may reason that this is not their cup of tea, and that their role is
‘HR to the business’. In this role HR-professionals have no position concerning strategy, business and
operations. Therefore, they have no direct influence on how engineers determine the quality of
work with their design of production processes and technology. But we can change this?
With the development of the SMART work design model by Parker and colleagues a bridge can be
laid with sociotechnical systems thinking. The SMART work design model captures the main
psychological human needs related to work, whereas the Lowlands variant of modern sociotechnical
systems design includes operational management design rules that align with good quality of work.
The SMART work design model has connected individual person-environment fit models with
concepts of team work and organisational design conditions. Modern sociotechnical systems design
related the strategic and operational demands of production systems with criteria for good quality
job design. While the SMART work design model focuses on human needs the modern sociotechnical
systems design stresses functional systems needs. This is where psychological job satisfaction and
operational job output requirements meet.
Figure 4: the integral design chain
Modern sociotechnical systems design (MST) offers design rules for organisations, based on strategic
choices with regard to markets, products and production methods. The principles behind the design
are to minimise the requirements for coordination (nodal points) that make organisations
unnecessarily complex and to maximise decision latitude to the level where decisions must be taken
and problems must be solved. Organisations become less bureaucratic, more resilient (flexible),
sustainable (efficient) and human-centric (quality of work) and in line with Industry 5.0 (Breque et al,
2021). The open systems approach of MST leads to principles for design. Such as: (1) design

8
integrally not partially; (2) apply the sequential order to first design according to the production
logic, followed by the design of the management structure, and finalised by designing the needed
information and technology; and (3) minimise the division of labour (Kuipers et al., 2020).
We superficially2 discuss this part or organisation level design rules (1 and 2 in Figure 4), but focus on
design rules that enhance the quality of work (3 to 6 in Figure 4); further we will address the design
of systems, like technology (7 in Figure 4). Below we summarise the 50 sociotechnical design rules
(Peeters & Mossink, 1995), and indicate the number of the steps of the integral design chain (i.e. the
seven steps in Figure 4).
Table 3. Sociotechnical design rules
Level
Sociotechnical design rules
Organisation
as a whole
General principles
1. Parallisation and segmentation of the organisation of production (crude design)
2. Units require a coherent set of management functions (preparing, supporting and controlling) to
enable control options into the functions of workers
3. Design production structure top-down from crude to fine
4. Design the management structure bottom-up from fine to crude (see Figure 4)
Production structure
5. Homogenize the production into parallel streams and segment these into independent,
separate units (parallelisation and segmentation fine design)
Parallelisation
6. Minimise organisational coordination between units by further division into subunits / teams;
7, 8, 9. Segmentation criteria are product variety, order predictability, order volume
Segmentation
10. Minimise organisational interdependence of units and maximise the interdependence of actions
within units
11,12,13,14, 15, 16. Dependency requirements can be sequence of activities, (interval) time, quality,
tooling (processing, manufacturing), space, skills; dependency conditions are a balanced flow rate,
clear demarcations, work pace sovereignty, communication options between units, skill
homogeneity to enable support and task take-over, option to affect product quality
Management structure
17. Grouping and coupling preparing, supporting and organising staff and operational tasks
(functions) at maximum decentralised level (decentralisation, deconcentration). Conditions are
independence of production processing, need for control options to deal with control problems,
geographical spreading, specialisation of staff, specific procedures, availability of staff expertise
18,19,20. Decentralise decision latitude, demarcate the central and decentralised staff tasks, ensure
independence between operational and decentral staff tasks
Teams /
units
21, 22. Analyse the option of integral design of a unit, its demarcation, and the need to adapt the
design of the production organisation (at higher level); assess the need of a structural design
(autonomous groups: team, task group, project-based group, project team), an organisational
2 Most publications about MST design are in Dutch, but a few good sources in the English language are Govers
& Van Amelsvoort (2019 and 2023), Kuipers et al (2020) and De Sitter et al (1997). See Annexe.

9
function design to include organising tasks, or a professional function design to divide executing,
preparing and supporting tasks.
Autonomous groups
23. Design a complete set of group tasks (preparatory, executing, supporting tasks) that is
demarcated and measurable
24. Allocate internal and external control options to make groups autonomous and independent
25. Group tasks must be mutually dependent and complementary, but allow individual space (loose
coupling)
26, 27. Group size (4-20 persons, ideally 8-12 persons) must enable significant organisational
contribution and ensure group flexibility
28, 29. Group members are multi skilled but do not differ too much in status; the group has a
(rotating) contact person
30, 31 Allocate management facilities (e.g. budgeting, HR-tasks) and information to allow for
autonomous task execution, and means of production (e.g. technology) to meet the requirements of
the group task
- Analyse the management structure and maximise the decision latitude for lower levels of the
organisation (‘whole task groups’, ‘complete jobs’), and minimise the need of decision latitude
at the highest organisational level concerning strategy and business decisions
Job & tasks
32. In the case of incidental control problems (e.g. stress risks) reduce the control problems by
adaptation and solving immediate, short-term problem causes (combat symptoms)
33. In the case of structural control problems enlarge the control options by improving and solving
long-term problem causes (combat causes) via first autonomy, second supporting tasks, third
organising task (enlarge learning and developmental opportunities)
34. In the case of incomplete functions allocate executing, preparatory, and supporting tasks
systematically
Adaptation – reduce control problems
35. Analyse control problems per control domain and improve control options. Control domains are:
information about the assignment, material (flow), means / resources, (planning of) operations,
information / feedback about results, reducing the complexity of the nodal network (interactions,
coordination), redefining / lowering the norms (output standards)
Improvement - enlarge control options
36. Enlarge autonomy of pace, method, sequence, and environment in executing tasks.
37, 38. Improve (functional and social) support by creating overlap between the tasks of workers
(internal / external control options) or the possibility of contacting non-team persons to solve
control problems
Making functions complete
39. Integrate executing tasks by task rotation and job enlargement (horizontal enlargement of
executive tasks)
40. Integrate preparatory and supportive tasks in the job by job enrichment (vertical enlargement of
non-executive tasks)
Design augmenting and complementary technology
41. Non-standard tasks and unpredictable events remain the responsibility of humans

10
42. Technology-implementation and the capacity of technological production means must take into
account the possibility of switching in the case of disturbances (modularity of technology, loose
coupling)
43. Technology and machines (including AI and ML) and their set-up and adjustment must be
possible by humans at the local, operating level
44. Technology design and implementation (automation, robotisation, digitalisation) should be such
that work with short cycle times is avoided
45. The work pace of teams should remain independent of other teams (buffering)
46. The work pace of transportation systems (conveyor belt, production line) must be uncoupled
wherever possible from executing the work
47. The unit / team disposes of their own means of production
48. Management and information systems must support the decentralised control options
49. Management and information systems must be available for operational users to provide
process information (feedback) and anticipatory information (feedforward)
50. Management and information systems must support inter-local communication between units /
teams
Having laid out the sociotechnical design rules and connected them to the design steps, we now
turn to the question of how these design rules and steps can be connected to the SMART work
design model (Table 4).

11
Table 4: SMART work design model features, sociotechnical design criteria and requirements, and the connection with sociotechnical design rules
SMART
model
Work
characteristics
Human
needs
Link to
organising
conditions
Organisational
structural
design criteria
Organisational
cultural
design criteria
Integral system requirements
Sociotechnical
design rules
Stimulating
work
characteristics
• Task variety
• Skill variety
• Problem-solving
requirements
• Information
processing
requirements
• Challenge
appraisals
•Work
meaningfulness
Horizontal
division of
labour
•Minimise
division of labour
•Maximise
learning new skills
/ job enrichment
•Technology to
augment work
•Opportunity of
learning (new
skills)
•Law of requite variety: external variety
must be met by internal variety, i.e.
internal control options / design active
jobs
1-20
33-36
39
44
Autonomous
work
characteristics
• Timing
autonomy
• Method
autonomy
• Decision-
making
autonomy
•Work
meaningfulness
Vertical
division of
labour
•Decentralisation
in division of
labour / limited
hierarchy / low
formalisation
•Autonomous
teamwork
•AI / ML as a
choice
•Presence of
leadership and
mentoring to
learn new roles /
growth in roles
•Shared
leadership
•Options for self-
management and
self-selection
•Reduction of structural complexity by
reduction of interfaces
•Parallelisation of order variety into
homogeneous sub-streams
•Combine executive, preparatory, and
managing tasks supporting of sub-
streams, and allocate such ‘whole tasks’
(self-regulation) to autonomous groups
(segmentation)
•Decentralisation of authority whenever
possible
•Minimize critical specification /
minimise monitoring and controlling AI
and ML
1-20
33-36
40-50
Mastery work
characteristics
• Job feedback
• Feedback from
others
• Role clarity
•Challenge
appraisals
•(Lower)
Activated
negative affect
Co-ordination
and
integration
via
information
•Maximise open
information
about company
results and
strategy
•Worker
participation in
organisational
change / renewal
•Contribute to
innovation
•Democratic
dialogue
•Teamwork implies control-capacity,
coordination, collaboration, social
support, uses of talents, enrichment,
learning opportunities
•Functional deconcentration of
information (grouping if required
information and data) /access to data /
augmenting function of (information)
systems
21-31
41-50

12
Relational
work
characteristics
• Task
significance
• Beneficiary
contact
• Social support
•Work
meaningfulness
•Fulfilment of
relatedness
needs
Co-ordination
and
integration
via
social
processes
•Maximise
external control
options
•Maximise
consultation at
work / discussion
of work progress
•Cooperation
based on
human(ist)
respect (equality
diversity and
inclusiveness) /
mature
employment
relationships /
labour relations /
commitment
driven HR system
•Integrate control-cycles to minimise
complexity in interactions (nodal
network)
37-38
Tolerable
work
characteristics
• Low role
overload
• Low role
conflict
• Low work–
home
conflict
•(Lower)
Activated
negative affect
Effort
required to
achieve
shared
organisational
goals
•Maximise
internal control
options / decision
latitude
•Workload self-
management
•Task /
assignments
based on
achievable (non-
exploitative)
production goals
and human well-
being
•Fair reward
system
•Taking into account the psychosocial
and physiological boundaries of human
functioning (in and outside work)
32-34

13
The foundational idea is how an organisation is designed as a work process that results in the design
of jobs with allocated tasks that will include or exclude well-being risks; and, that these risks are a
characteristic of the job, irrespective of the experience of a person. But the absence / presence of
risks will affect the experience of human needs being fulfilled or not. It is possible to assess control
problems at the level of tasks3. If a control problem is present, this means that there is a disturbance
or a disruption in carrying out a task. In order to solve the disturbance, control options (i.e. decision
latitude) are needed at the level of this task. This is a matter of applying a specific design rule. If the
control options are absent, and the disturbance cannot be solved at the level of that task, the
operator assigned to the task may experience the emotion of feeling incompetent or stressed. In
such instances, it can be said that the task is facing an unfavourable ‘well-being condition’ (Dhondt &
Vaas, 2001; Pot, 2017; Pot et al., 1989 and 1994; Vaas et al., 1995).
The diagram below (Figure 5) helps to understand how to identify control problems in relation to the
control cycle (Vaas, 1995; see also Oeij et al., 2017).
Figure 5: The control cycle, its tasks and domains
The control cycle is a systems element that contains inputs, throughputs and outputs. The inputs
must be processed by a task operator (i.e. the throughput) to achieve the output (e.g. a result like
making a product). A distinction can be made between tasks at the level of production (prepare,
execute, support) and the level of management (manage or ‘solve a problem’, ‘create a solution’)4.
The domains in the process of a task are operations, material, means and resources, information
3 A control problem is a disturbance in the work process that can be solved with control options (i.e. decision
latitude, regulatory power, autonomy); a control problem can occur at the level of job tasks, for which the
operator has or has not the control options to solve the disturbance (this is due to a choice in the job design).
4 Compare single-, double- and triple-loop learning in the reflective practitioner model and the organisational
learning model (Argyris and Schön, 1996; Oeij et al., 2017: pp. 5-6).

14
about the goal and the assignment (order), interactions with others, norms and feedback (on the
result). Each of these domains can be a source or cause for a disturbance or control problem. To be
able to deal effectively with control problems (and to learn from them), control options must be
allocated to a task. If control options are not present to a sufficient extent, the result can not be
achieved and unfavourable well-being conditions are indicators for that. We discuss seven of them,
derived from the method of Well-being at work (WAW) (Pot et al., 1989 and 1994; Vaas et al., 1995).
1. The completeness of a job - A ‘complete set of tasks’ implies the presence of all the grey
handling options (execute, prepare, support and manage). This means that the task allows
the operator to solve disturbances (i.e. the result / output is not met qualitatively of
quantitatively) with allocated control at both the level of the production structure and the
management structure.
2. Non-short cycle time tasks – Short cycle time tasks indicate work that is repetitive and
monotonous, and contains (physiological) risks. It lacks learning opportunities. Such tasks
should be limited.
3. Level of (cognitive) difficulty – Within a job there should be tasks that enable learning
opportunities. The combination of high task demands and high autonomy ensures a
combination of learning new things and the presence of control to deal with that (e.g.
solving a disturbance) without high-stress risks. A balanced mix of ‘complex’ tasks and
‘routine’ is desirable.
4. Autonomy – The tasks should allow for forms of autonomy in carrying out the task, with
regard to pace, method, (order) sequence and (work) place.
5. Interaction network – The tasks should enable functional and social contacts with other
persons and the job station should not be an isolated working environment.
6. Organising tasks - The tasks should allow organising functional contacts, peer review, etc. to
arrange assistance and consultancy (by colleagues, staff, and management).
7. Information - There should be sufficient information and data available about goals, the
assignment and feedback about the results.
If these well-being conditions are not met, and results cannot be achieved, this will also affect the
achievement of human needs. MST is however less concerned with human job satisfaction, but with
the absence of risks in tasks. The WAW method is a bridge between these two. Therefore, the
SMART work design model can benefit from the sociotechnical design rules to identify risks in the
design of the organisation and jobs in order to enhance the options to optimize human needs and
job satisfaction.
5. Example of a job: Operator production line
To show the connection between the SMART work design model and sociotechnical design rules we
present an example of a WAW-analysis of a concrete job, the operator on a production line (Oeij,
2023). This was part of a research into the health and safety risks of short cycle time labour. Based
on an expert-assessment of the seven well-being conditions a ‘well-being profile’ can be generated
(Table 5).
Table 5. Well-being profile of ‘operator production line’
Assessment
Unsatisfactory
Limited satisfactory
Satisfactory
1.Job completeness
2.Non-short cycle time tasks
3.Cognitive difficulty
4.Autonomy

15
5.Interaction network
6.Organising tasks
7.Information
Overall, the job profile of this operator does not look too bad, but can be improved by enhancing
cognitive difficulty to improve learning opportunities. To prevent, reduce and preferably structurally
eliminate the risks that lead to unsatisfactory scores the WAW method – based on sociotechnical
design rules- suggests adaptation measures, improvement measures and restructure measures (i.e.
redesign). Adaptation measures are mainly measures that solve the control problems, for example
by clearer work instructions, provision of more or better resources and materials. Note that this is
‘only’ an adaptation: it reduces the stress risks, but it also reduces the opportunities to learn from
solving the problem in case. Improvement measures are aimed at improving task composition and
introducing control opportunities as (social) contacts without requiring production-organisational
and/or production-technical measures (i.e. restructuring measure): task rotation, task expansion,
task enrichment (as examples of improving the horizontal division of labour), work consultation
(functional dialogue).
The machine operator in the studied plant rotates across various work stations on the production
line. At these work stations the operator has to carry out preparatory tasks and quality controlling
tasks. As a result, the job contains less short-cycle times as in the case of isolated work stations. This
contributes to the job ‘completeness’. Task enrichment here has little effect on cognitive difficulty
(i.e. learning opportunities) or functional contacts because most tasks on the line are of an equally
low cognitive level and the work stations are isolated (the operators do usually work there in pairs).
A useful task enrichment in this job would be to have the machine operators (in rotation) make the
daily schedule or introduce self-scheduling.
Introducing work meetings (functional consultation) for all operators on this production line would
enable the machine operators to jointly address control issues in areas such as material supply or
working conditions. A restructuring measure could be to make all operators on the production line
function as a 'task group' or 'autonomous team'. Such a team is responsible for the daily planning
and mutual distribution of work, does as much of the preparation, execution and support tasks in
the work process as possible, establishes contacts with colleagues inside and outside the
department independently when control problems arise, meets regularly for work consultations
involving planning and logistics, product and process specifications, materials (i.e. what is processed
by the machines), equipment, technology, working conditions, clean policy requirements, etc.
The formation of a task group /team requires a rearrangement of tasks and competences, i.e. a
change in the production structure and in the management structure of the work organisation.
In Table 6 we connect the SMART factors with the WAW conditions and the MST design rules from a
general perspective, not per se from the operator job that we just discussed. The point we want to
make is that the results of a job analysis with the WAW method (as in Table 5) lead to insights into
control problems. These problems can be combated by measurements based on MST design rules.
And, finally, these design rules can be related to the five factors of the SMART work design model.

16
Table 6: Connecting SMART factors, the WAW criteria and conditions, and MST design rules
SMART factors
WAW criteria and
conditions
MST design rules
Criterion:
Fulfill Human needs
Criteria:
1.No stress risks
2.Provide opportunities for
learning and development
General principles:
First: design the production structure (top-down);
Second: design the management structure (bottom-up);
Third: design ICT, technical and other systems.
1.Stimulating work
characteristics:
Task variety, skill variety,
problem-solving
requirements, information
processing
WAW conditions:
1.Job completeness
2.Reduction of short cyclic
work
3.Level of cognitive difficulty
A. Design the production structure:
1. Create divisions along the line of product groups or client groups or regions
2. Parallelilise within the divisions independent product streams (parallelisation)
3. Provide for segmentation within the parallelilised streams.
4. Create autonomous teams within the segments (dependency within a segment (i.e. team) must be strong,
between segments must be weak)
5. create jobs by combining executive tasks with the connected preparatory and supporting tasks (complete jobs).
B. Design the management structure
1. Allocate as much decision latitude as possible to lowest levels in the organization (i.e. to teams or jobs).
2. Allocate remaining decision latitude to the next higher level
3. Continue to the top level.
C. Design the information structure and system
1. To provide the workers and the teams at each level with information they need to do their job and respond to
their clients and responsibilities.
2. Make general information about results, plans future technologies etc. available.
2.Mastery work
characteristics: job
feedback, feedback from
others, role clarity
WAW conditions:
5. Interaction network
(opportunities to have
contact with colleagues and
supervisors)
7. Information supply
In the design of the production structure isolated jobs must be avoided.
Preferably the work should be done in teams where workers can support and help each other and share
information.
In the design of the management structure information supply contains clear information and data (e.g. on quantity
and quality requirements) at job and team level (AI and ML are amendable).
3.Autonomous work
characteristics
WAW conditions:
2.Reduction of short cyclic
work
4.Autonomy in method,
order, time and place
In the design of the management structure (bottom–up) add decision latitude on: time, method, order and place to
the job.
Create autonomous teams that can divide tasks among team members and can operate independently within the
boundaries of the result criteria.

17
4.Relational work
characteristics: task
significance, beneficiary
contact, social support
WAW conditions:
5.Interaction network
(Contact opportunities)
6.Organising tasks
In the design of the production structure isolated jobs must be avoided.
In the division of tasks on the shop floor there should be sufficient connection or overlap in tasks to enable help
from direct colleagues (and avoiding too many nodal
points).
5.Tolerable work
characteristics: Low role
overload; Low role conflict;
Low work–home
conflict
WAW conditions:
4. Autonomy
6. Organising tasks
In the design of jobs workers should be able to regulate the workload and eliminate ambiguous assignments .

18
6. Conclusions and recommendations
This paper investigated how the SMART work design model could be connected to sociotechnical
systems design in order to improve the quality of work from two angles: the design of jobs from
psychological human needs and from operational functional requirements of the organisational
business goals. The conclusion is that this is possible, at least in theory. The SMART work design
operationalised the human needs into five factors and into organisational conditions. The MST
approach translated production requirements into tasks that meet well-being conditions, for which
design rules were formulated.
Our contribution is in the first instance directed at supporting practitioners to develop organisations
and jobs that simultaneously enhance good organisational performance and good quality of work. In
doing so, the approach is in line with the concept of ‘workplace innovation’ (Oeij & Dhondt, 2017, p.
66; Parker & Boeing, 2023: 92). A next step is to translate our ideas into a concrete action plan with
concrete steps. This is foreseen to be undertaken in the INSIGHT_EU research, once its proposal is
granted.
A limitation of our contribution, therefore, is the lack of testing our approach empirically. That is to
say, the elements about human needs have been researched extensively and the SMART work
design model did stand its first tests (Parker & Knight, 2023). Concerning the MST design rules and
the WAW method there is quite some qualitative research carried out in the Lowlands (the
Netherlands and Flanders in Belgium) which supports the viewpoints, but a systematic, quantitative
evaluation has not been performed. Nonetheless, there are numerous qualitative case descriptions
available5. Moreover, there is serious concern that individual-level interventions (read psychological
interventions) do not engage with working conditions (read organisational redesign), and that such
interventions are not providing additional or appropriate resources in response to job demands
(Fleming, 2023).
We would like to express the importance of collaboration in the field to further develop this
approach, between different scientific disciplines (for the sake of science), and across different
countries and industries (for the sake of practice). The future of work is one with more digitalisation,
robotisation, artificial intelligence and machine learning. From Industry4.0 we learned that
technological progress and its application and implementation tended to neglect the human factor
too much. This has to change, according to the next policy initiative of Industry5.0, which intends to
make humans more central (Breque et al., 2021; Oeij et al., 2023). “Industry 5.0 is characterised by
going beyond producing goods and services for profit. It shifts the focus from the shareholder value
to stakeholder value and reinforces the role and the contribution of industry to society. It places the
wellbeing of the worker at the centre of the production process and uses new technologies to
provide prosperity beyond jobs and growth while respecting the production limits of the planet”
(European Commission, 2021).
5 See for example the Knowledge Bank Workplace Innovation (https://www.workplaceinnovation.org/).

19
References
Argyris, C., & Schön, D. A. (1996). Organizational learning II. Theory, method, and practice. Reading
(MA), etc.: Addison-Wesley (2nd ed., 1st ed. 1978).
Bakker, A. & Demerouti, E. (2017). Job Demands–Resources Theory: taking stock and looking
forward. Journal of Occupational Health Psychology, 22(3), 273–285.
Breque, M., De Nul, L., Petridis, A. (2021). Industry 5.0: towards a sustainable, human-centric and
resilient European industry. Luxemburg: Publications Office of the European
Union, https://data.europa.eu/doi/10.2777/308407
Deci, E.L., Olafsen, A.H., & Ryan, R.M. (2017). Self-determination theory in work organizations: The
state of a science. Annual Review of Organizational Psychology and Organizational Behavior,
2017(4), 19-43.
De Sitter, L. U., Den Hertog, J. F., & Dankbaar, B. (1997). From complex organisations with simple
jobs to simple organisations with complex jobs. Human Relations, 50(5), 497–534.
Dhondt, S. & Vaas, F. (2001). WEBA analysis. Manual. Leiden: TNO Work and Employment.
European Commission, Directorate-General for Research and Innovation (2021). Industry 5.0:
human-centric, sustainable and resilient. Luxemburg: Publications Office. Industry 5.0 - Publications
Office of the EU (europa.eu)
Fleming, W. J. (2023). Employee well-being outcomes from individual-level mental health
interventions: Cross-sectional evidence from the United Kingdom. Industrial Relations Journal, 1–21.
https://doi.org/10.1111/irj.12418
Govers, M., & Van Amelsvoort, P. (2019). A Sociotechnical Perspective on the Digital Era: The
Lowlands view. European Journal of Workplace Innovation, 4(2): Special issue: Sociotechnical
systems thinking in manufacturing. DOI: https://doi.org/10.46364/ejwi.v4i2.589
Govers, M. & Van Amelsvoort, P. (2023). A theoretical essay on socio-technical systems design
thinking in the era of digital transformation. Gruppe. Interaktion. Organisation. Zeitschrift für
Angewandte Organisationspsychologie (GIO). DOI: 10.1007/s11612-023-00675-8.
Guest, D., Knox, A., & Warhurst, C. (2022). Humanizing work in the digital age: Lessons from socio-
technical systems and quality of working life initiatives. Human Relations, 75(8), 1461-
1482. https://doi.org/10.1177/00187267221092674.
Hacker, W. (1986). Complete vs. incomplete working tasks: A concept and its verification. In G.
Debus, & H.-W. Schroiff (eds.), The psychology of work organization (pp. 23 – 36). Amsterdam:
Elsevier Science Publisers / North Holland Publishers.
Hacker, W. (2003). Action regulation theory: a practical tool for the design of modern work.
European Journal of Work and Organizational Psychology, 12(2), 105–130.
DOI: 10.1080/13594320344000075
Hackman, J. R. & Oldham, G. R. (1975). Development of the job diagnostic survey. Journal of Applied
Psychology, 60(2), 159–170.

20
Hackman, J. R. & Oldham, G. R. (1980). Work redesign. Reading, MA: Addison-Wesley.
Hay, G. J., Klonek, F.E. & Parker, S.K. (2020a). Diagnosing rare diseases: A sociotechnical approach to
the design of complex work systems. Applied Ergonomics, 86 (article 103095),
https://doi.org/10.1016/j.apergo.2020.103095.
Karanika-Murray, M. & Oeij, P.R.A. (2017). The role of work and organizational psychology for
workplace innovation practice: From short-sightedness to eagle view. EWOP in Practice, Special Issue
on Workplace Innovation, (1), 19-30.
Karasek, R A & Theorell, T G. T. (1990). Healthy Work: Stress, Productivity and the Reconstruction of
Working Life. New York: Basic Books
Kuipers, H., Van Amelsvoort, P., & Kramer, E.-H. (2020). New ways of organizing: Alternatives to
bureaucracy. Leuven, Den Haag: Acco.
Oeij, P. (ed.) (2023). Kortcyclisch werk. Quo vadis? Leiden: TNO Innovation for Life.
Oeij, P. & Dhondt, S. (2017), Theoretical approaches supporting workplace innovation. In: P.R.A. Oeij,
D. Rus, & F.D. Pot (eds), Workplace innovation: Theory, research and practice (pp. 63–78). Series
‘Aligning Perspectives on Health, Safety and Well-Being’. Cham (Switzerland): Springer.
Oeij, P.R.A., Gaspersz, J.B.R., Van Vuuren, T. & Dhondt, S. (2017). Leadership of innovation projects:
an illustration of the reflective practitioner and the relation to organisational learning. Journal of
Innovation and Entrepreneurship, 6(2), 1-20.
Oeij, P.R.A., Hulsegge, G., & Van der Torre, W. (2021). Technology Impact Methode 3.0: Een
kwalitatieve aanpak over de impact van technologie op werk. Leiden: TNO.
Oeij, P.R.A., Hulsegge, G. & Van der Torre, W. (2023), The impact of technology on work: enabling
workplace innovation by technological and organisational choice. In: Peter R.A. Oeij, Steven Dhondt,
Adela J. McMurray (eds.), A Research Agenda for Workplace Innovation: The Challenge of Disruptive
Transitions (pp. 67-89). Cheltenham, UK: Edward Elgar Publishing.
Oeij, P.R.A., Van Rhijn, G., Van Dijk, W. & Krause, F. et al. (2023). Conceptual framework of Industry
5.0 to study workforce skills (BRIDGES 5.0 deliverable D1.1, December 2023). Leiden: BRIDGES 5.0.
(Retrieved from: https://bridges5-0.eu/publications/).
Oldham, G. R., & Fried, Y. (2016). Job design research and theory: Past, present and future.
Organizational Behavior and Human Decision Processes, 136, 20–35.
https://doi.org/10.1016/j.obhdp.2016.05.002
Parker, S.K., & Boeing, A.A. (2023). Workplace innovation in the digital era: a role for SMART work
design. In: P.R.A. Oeij, S. Dhondt, A.J. McMurray (eds.), A Research Agenda for Workplace
Innovation: The Challenge of Disruptive Transitions (pp. 91-112). Cheltenham, UK: Edward Elgar
Publishing.
Parker, S.K. & Grote, G. (2020). Automation, algorithms, and beyond: why work design matters more
than ever in a digital world. Applied Psychology: An International Journal.
https://doi.org/10.1111/apps.12241
Parker, S. K., & Grote, G. (2022). More than ‘more than ever’: Revisiting a work design and
sociotechnical perspective on digital technologies. Applied Psychology, 71(4), 1215–1223.
https://doi.org/10.1111/apps.12425.

21
Parker, S. K., & Knight, C. (2023). The SMART model of work design: A higher order structure to help
see the wood from the trees. Human Resource Management, 1–27.
https://doi.org/10.1002/hrm.22200
Parker, S.K., Morgeson, F.P., & Johns, G. (2017). One hundred years of work design research: Looking
back and looking forward. Journal of Applied Psychology, 102(3), 403.
Peeters, M.H.H. & Mossink, J.C.M. (1995). The WEBA method. Part 2 Redesign. In: Vaas, S., Dhondt,
S., Peeters, M. H. H., & Middendorp, J. (1995). Method Well-being at Work: Manual Job Analysis.
Alphen aan den Rijn/Zaventem (Netherlands/Belgium): Samsom (in Dutch).
Pot, F.D. (2017). Workplace innovation and wellbeing at work. In Oeij, P.R.A., Rus, D., & Pot, F.D.
(eds.) Workplace Innovation: Theory, Research and Practice (pp. 95 – 110). Cham (Switzerland):
Springer.
Pot, F. D., Christis, J. H. P., Fruytier, B. G. M., Kommers, H., Middendorp, J., Peeters, M. H. H., Vaas, F.
(April 1990). Outlines of the WEBA-instrument: A conditional approach for the assessment of the
quality of work. Leiden: NIPG.
Pot, F.D., Peeters, M.H.H., Vaas, F. & Dhondt, S. (1994). Assessment of stress risks and learning
opportunities in the work organization. European Work and Organizational Psychologist, 4(1), 21-37.
Tims, M., Bakker, A. B., Derks, D., & van Rhenen, W. (2013). Job Crafting at the Team and Individual
Level: Implications for Work Engagement and Performance. Group & Organization Management,
38(4), 427–454. https://doi.org/10.1177/1059601113492421
Vaas, S., Dhondt, S., Peeters, M. H. H., & Middendorp, J. (1995). Method Well-being at Work: Manual
Job Analysis. Alphen aan den Rijn/Zaventem (Netherlands/Belgium): Samsom (in Dutch).
Van Amelsvoort, P. & Van Hootegem, G. (2017). Towards a Total Workplace Innovation Concept
Based on Sociotechnical Systems Design. In: P. Oeij, D. Rus, and F.D. Pot (eds), Workplace
Innovation. Aligning Perspectives on Health, Safety and Well-being (pp. 281-299). Springer, Cham.
Van den Broeck, A., Howard, J. L., Van Vaerenbergh, Y., Leroy, H., & Gagné, M. (2021). Beyond
intrinsic and extrinsic motivation: A meta-analysis on self-determination theory’s multidimensional
conceptualization of work motivation. Organizational Psychology Review. Advance online
publication.

22
Annexe: Basic MST design rules
Acknowledgement
Funded by the European Union under grant agreement No 101069651. The contents of this publication are however the sole responsibility
of the BRIDGES 5.0 project consortium only and do not necessarily reflect those of the European Union or HADEA. Neither the European
Union nor HADEA can be held responsible for them.
Funded by the European Union under grant agreement No 101135884. The contents of this publication are however the sole responsibility
of the SEISMEC project consortium only and do not necessarily reflect those of the European Union or HADEA. Neither the European
Union nor HADEA can be held responsible for them.
Short bios of presenter(s) and/or author(s)
Presenter/Author: dr. Peter Oeij is senior researcher at TNO Innovation for Life (the Netherlands), and has been trained as
work & organisational psychologist and work & organisational sociologist. His field of research is workplace innovation,
quality of work, organisational design and Industry5.0. Contact: peter.oeij@tno.nl
Co-author: prof. Steven Dhondt is organisational sociologist and his field of research is new technology and work,
workplace innovation and Industry5.0. He is affiliated as senior researcher at TNO Innovation for Life (the Netherlands) and
professor at KU Leuven (Belgium).
Contact: steven.dhondt@tno.nl
Co-author: dr. Fietje Vaas is researcher at TNO Innovation for Life (the Netherlands), and has been trained as work &
organisational psychologist. She was involved in the development of the WAW method in the late eighties and the
beginning of the nineties and is now manager of the knowledge bank on workplace innovation:
www.workplaceorganisation.org.
Contact: fietje.vaas@tno.nl
Paper to be found on ResearchGate (https://www.researchgate.net/profile/Peter-Oeij)
Powerpoint presentation to be found on Slideshare (https://www.slideshare.net/PeterOeij)