As the Covid-19 crisis has deepened relations between politicians and their scientific advisers have become increasingly frayed. Politicians want to hear we are making progress and that the actions they are taking are being effective. They may want to highlight statistics that point in this direction. The scientists however must stay true to their data and if that says the infection rate is still too high to support some lockdown measures that is what they must advise.
Anyone who has practiced action research will recognise this dilemma. The people responsible for action want to hear that it is working and they may find it uncomfortable to hear from those responsible for the research what is actually happening on the ground. And if they don’t like the message the next step may be to ‘shoot the messenger’; perhaps to ignore what they are told, to question the competence of their researchers or even get rid of them. It is a very human characteristic. As Paul Simon wrote, ‘Still a man hears what he wants to hear and disregards the rest’ (The Boxer). And it may not just be a question of information about an action that is not working: it is even more difficult if the information challenges fundamental beliefs and ideologies.
But if we are to deal effectively with a very dangerous and unfamiliar opponent like the virus we have to deal with reality not with our own favoured construction of it. If we don’t, we run the risk of having to deal with a much worse situation later.
So how can we help people take on-board information that may be difficult for them? What we don’t want is pressure on the advisers to hold back from presenting evidence for fear of their own future. They need to be given a kind of immunity, a license declared at the beginning of the process to report things as they find them. Another necessary requirement is that the people responsible for the action plans do not receive research information in any kind of public forum in which they may feel they have to defend their actions. They need a private space in which they can consider and reflect on the new information, question it as appropriate and explore its implications. The process also needs trust between colleagues and confidence in their judgement.
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The Government process for dealing with the Covid-19 crisis has revealed many of the issues at the heart of creating an effective action research strategy. The Government is responsible for policy making and they have SAGE (the Scientific Advisory Group for Emergencies) to provide scientific and technical advice.SAGE assesses the data on the progress of the virus, models the impact of possible actions and collates all the relevant information. The Government says it ‘follows the science’ but that is not the same as ‘we do what the scientists say’. Scientists advise but ministers decide: weighing up the trade-offs between the health risks and the economic consequences of different ways of coming out of lockdown is a burden politicians must bear.
The structure we have at Government level mirrors the separation between the research phase and the action phase in action research. This is a necessary separation so we get evidence that is as objective as possible.
Any organisation seeking to use an action research strategy to find their way out of lockdown will need to separate the responsibilities for planning and action (the policy making) from the responsibilities for research (the gathering and processing of the evidence). In a large organisation this separation of function may be relatively straightforward: the senior management may determine the action steps and staff from functions such as information analysis, business analysis, Human Resources and Health and Safety may undertake the research. It is also possible that a separate organisation, such as ourselves, takes responsibility for the research and evaluation functions in the action research cycle.
But in a small organisation there may be no pre-existing separations of role to make use of. If this is the case it can be useful to give somebody a specific responsibility for gathering the evidence to underpin the debate about the next action steps.
How well this separation will work in practice will depend upon the level of trust between members of the organisation and the degree of openness that people display to the evidence that is gathered. This is a topic we will attend to in the next post.
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The Government mantra is ‘our actions follow the science’. The scientists collect evidence of how the virus is spreading in order to give the politicians the advice they seek. But what evidence to collect? And how long is the lag before you know whether actions taken are being effective?
Problems about gathering the evidence have bedeviled our national response to Covid-19, so much so that our strategy has been likened to ‘driving blind’. These same issues will confront every organisation that is trying to find its way out of lockdown, albeit on a more local scale. If careful steps are being taken to get going again, how can we avoid ‘ driving blind’? If the aim is to scale up business activity without endangering staff and customers, what evidence can be collected to show the plans are working? The obvious hard data includes the number of staff, customers etc who test positive and the number of customers prepared to come through the doors. The Government test and trace system is gradually providing more local data but there have been lags in getting information that is sufficiently detailed to be useful.
There are, however, lots of other indicators that may provide more immediate and useful feedback. In action research every new action phase has specific aims and we need ways of measuring whether these aims are being achieved. If the aim is to create safe workplaces for staff, regular surveys are needed to assess how staff are feeling. Ideally there should also be opportunities to discuss specific problems and these can be addressed in the next action phase. Similarly, as shops, pubs and restaurants re-open there will be a crude measure of how many customers arrive but, if the response in slow, more effort needs to be put into discovering why and what can be done to give people more confidence that they will be safe. As schools re-open ways are needed to assess whether children and their parents feel confident about the measures taken and opportunities need to be created to discuss any concerns they may have.
The basic message is that if you are going to take ‘baby steps’ into the unknown you have to have measures in place to warn you if you are about to fall down the stairs.
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We live in a blizzard of regulations, requirements, guidance and advice that changes regularly as the Government tries to find ways of guiding us out of lockdown. People crave clarity so they know exactly what to do but in reality there are so many different circumstances that we must all to some extent find our own way forward. For companies, how we solve the riddle of getting back to viable business activity whilst at the same time protecting staff, customers and everybody else, is going to be largely a matter of making local decisions.We will all have to take our own ‘baby steps’, review the implications and gradually in an iterative way find our own ‘new normal’. Government may be treating getting us out of lockdown as a top-down decision making process but there will be a lot of bottom-up decisions to be taken as well.
So how can we prepare for the bottom-up process?Here are four action research suggestions:
Set up a task force to ‘design’ the new way of working and monitor how well it is achieving its purpose
Work out what is a regulation that is enforceable by law and what is advice or guidance. This will define the discretion the task force has to create ways of working that meet local needs. Schools may have to abide by the social distancing regulations, for example, but they may be able to decide for themselves whether children come back full time or part-time, what spaces they can press into service for teaching, how to manage lunchtimes and playtimes and so on.
Be clear what the new system is expected to achieve and measure whether it is being achieved. Are people able to work following the social-distancing rules and face-mask wearing or do further adjustments need to be made? Above all are customers confident they are safe and are they willing to follow the procedures that have been set up?
Make regular reviews and be ready to change. The results of internal ‘research’ may suggest changes but there may also be outside changes. Government may change the regulations and create new restrictions or opportunities. Mandatory face-masks today: who knows what tomorrow.
Agility and invention will be needed.There are plenty of examples of how organisations are adapting that can be our inspiration.
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Across the world nations are struggling to find their way back to some kind of ‘new normal’. But they cannot do it by announcing a grand plan and then implementing it. They are dealing with an unpredictable opponent: they don’t know how we the public or the virus will respond as they lift restrictions. So from the UK Government we hear that the ‘road map’ is to take ‘baby steps’, review what happens and move forward when we can without causing a new ‘spike’.
We are told we are in uncharted territory and we are not used to planning this way. And yet we have had a well-developed methodology for managing change in this way for nearly 100 years. Action Research was developed by Kurt Lewin in the 1920s as a way of dealing with change in circumstances where the complex system being changed is unpredictable. Over the past century many forms of action research have been developed but at their heart is a four-stage action research cycle: plan, act, research (observe, study the results) and reflect.
First you create a plan to achieve a goal and then you take the first actions to implement the plan. Then, before taking the next step, you undertake research to see what the results of your actions have been. You then reflect on what has been achieved and plan the next actions accordingly. This becomes an iterative process, moving through a series of action research cycles so that over time a flexible plan is implemented that deals with the complexities of the real world as they become apparent.
For the past 30 years the Bayswater Institute has been helping clients of all kinds manage change processes by using action research. This is particularly pertinent now because as the UK government adopts its own version of action research, knowingly or not, so organisations of all kinds are going to have to adopt some form of action research as they try to come out of lockdown and resume a form of normal activity.
Our aim it to use our experience of action research to help organisations adopt this approach to planning. The next posts will be on different aspects of following an action research approach. If you want help with any aspect of the approach please let us know and we will build it into future posts.
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This report by the King’s Fund, presented at the Digital Health and Care Congress 2018, usefully draws out some of the challenges in adopting and scaling digital health and care interventions through consideration of five significant case studies. It begins by recognising some of the unique challenges of digital change and goes on to identify some key themes. The report is a practical and timely contribution to the practical understanding of digital change and not only references some of the work that The Bayswater Institute (BI) members have been involved in for many years but raises many of the issues that the BI come into contact with on a daily basis.
The report recognises several challenges around large-scale digital change. The negative memories around the National Programme for IT (The Implications of e-health System Delivery Strategies for Integrated Healthcare) and the inability to undertake such change whilst under pressures of current demand on resources being key issues.
The Evidence About Managing Digital Change
The report references the Wachter review (Making IT Work) which identifies the need for change processes using digital technology to be ‘adaptive’ and ‘technical.’ That “Adaptive change is change that relies on human behaviour for its success.” At the heart of this challenge lies approaches that are central to the BI way – action research and sociotechnical systems. Action research involves iterating towards a solution and sociotechnical systems thinking recognises that the solution is a collaboration of people working with technology. This recognition represents a significant departure from the “big-bang” approach to system change where it is assumed everything is known up-front. It signifies a shift to more “test and learn” thinking that underpins so much successful innovation in other industries and endeavours.
The report goes on to recognise the productivity paradox identified by Brynjolfsson (Beyond the Productivity Paradox.) That efficiency gains accompanying widespread digitisation is often absent in the traditional indicators. Our work indicates that it is often necessary to expand the range of indicators and evidence to understand how new practice is being enabled and what that means. This means that the evaluation approach must evolve with the intervention.
In considering the barriers to successful digital change the work of Greenhalgh is cited (Beyond Adoption: A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies ) which distinguishes between complicated and complex interventions. Complexity in this sense arises from systems that are interconnected and dynamic and produce emergent behaviour. Too often solutions are assumed to be complicated and fail because they do not address the complexity. In discussing the use of telephone triage in primary care the report refers to the absence of clear evidence of benefits but that some practices improved their ability to cope with demand. The same intervention in a different sociotechnical implementation could yield completely different results. Further, the originally identified benefit may not always be the useful benefit found in practice. This complexity again goes back to the need for a “test and learn” approach. This situational complexity and lack of a one-size-fits all approach underlies the challenges of the Whole System Demonstrator which saw the intervention as fixed and tried to generate an economic value (or QALY) for the intervention. Although the value of telehealth in reducing emergency admissions and better managing patients is generally recognised (Reduced Cost and Mortality Using Home Telehealth to Promote Self-Management of Complex Chronic Conditions: A Retrospective Matched Cohort Study of 4,999 Veteran Patients) it is highly situationally dependent and cannot be implemented as a black box approach as it is a sociotechnical intervention. The report reiterates that digital change is adaptive and does not lead to static states for testing – it evolves.
The report goes on to explore five different digital interventions across very different sites and applications. It identifies five key themes that are highly correlated to themes we see recurring in our BI work.
Leadership and Management
A key theme here was that personalities count. Often, selecting the right person to lead on a particular aspect was central to success. This is reinforced by the observation in the report that technology implementations should not be seen as IT projects but as a cultural change that is highly dependent upon good leadership. This leadership is most effective when clinically driven. At the BI our experience shows that many digital projects are approached as linear implementations that do not seek to learn or understand what is working and what is not. The need to build collaborations, often across organisational boundaries, is underestimated. In our work we regularly see digital projects pigeonholed as IT and lacking in the attention to culture change and leadership identified in the report.
User Engagement
The report recognised that a common approach across the case study sites was to recognise user engagement not as a single event but as a continual collaborative process involving users of the technology. The work we did at the BI in the BOLD-TC (Better Outcomes for People with Learning Disabilities – Transforming Care) project was based on just such an ethos involving not just the front-line practitioners across health and social care but also people with learning disabilities and their families. The move to a more collaborative, ongoing engagement with users is essential if services are going to evolve.
Information Governance
The case study sites focused on cultural rather than the technical aspects of information governance. By creating the right environment for partners to come together and solve the problems of sharing data it was found that collaboration, in general, was increased. Leadership and approaching information governance as a framework rather than trying to solve each problem as it occurred led to sustainable approaches.
Partnerships
It was identified that the right supplier could act as a facilitator for change by coordinating actors and change processes. Our experience at the BI is very similar. The ability of a supplier to see all of the challenges being addressed by the organisations coming together in pursuit of a common digital solution puts them in a key coordinating role. By providing each of the stakeholders in the intervention with valuable reporting and evidence specific to their needs they can act as the glue that binds the intervention. However, this requires an open supplier that sees the long-term benefits in building trust and collaboration. As the report points out choosing suppliers is a significant contribution to the success of the approach.
Resourcing and Skills
For the project to succeed the resources and skills need to be there, over and above what is required to keep the engine of delivery going. For large-scale digital interventions this is challenging in the current environment. Recognition was given to starting small and evolving solutions in a phased way. This was particularly important when crossing organisational boundaries. Trying to do too much at once absorbed resources and slowed progress. Our experience reflects this. Developing solutions that can have an impact on day-one but evolve over time to cross boundaries is essential and, again, part of the ongoing “test and learn” approach.
Evaluation
Although not a separate heading the importance of evaluation was noted. Significantly, the importance of evaluating success and failure was recognised. One of the quotes equated randomised control trials with a lack of rigour recognising that iterating understanding and learning was essential. At the BI we are committed to evaluation that engages with complexity and evolves with the intervention to develop learning and understanding. This requires formative evaluation and an understanding of the challenges the collaboration partners are facing.
Conclusion
The report is a significant contribution to understanding the challenges of implementing digital change. The use of case studies that demonstrate both the barriers and how they were overcome is the most useful way to share learning and understanding. At the BI we hope to see more of this kind of sharing and a move to learning “what works for who and under what circumstances.”
In my work with Airedale NHS Foundation Trust we addressed the issues of one-size-fits-all, the black box view of technology and the need to embrace complexity. Beginning in 2008 as part of the Assisted Living Innovation Platform (ALIP) we worked with Airedale NHS Foundation Trust and partners to use video in the home to address a range of care scenarios. Over a period of eight years Red Embedded Systems Ltd. developed the v-connect service. We developed a communication platform that could facilitate a range of care scenarios including video calls through the TV and delivery of educational content. We implemented interventions for long-term conditions, social care interventions such as virtual visiting, support for people with renal failure and remote support for people with learning disabilities. We integrated ambient monitoring, remote physical measurements, evidence collection and reporting (A Socio-technical Approach to Evidence Generation in the use of Video-conferencing in Care Delivery and Factors Affecting the Move to an eSystems Approach to remote Care delivery.) Many of the challenges discussed here were addressed in working with a broad range of partners in care delivery. We overcame barriers in all of the key themes identified but failed to make the commissioning case in every situation. Digital interventions have the potential to prevent and reduce current activity in the care system. Better educated and managed patients are more independent, and this reduces the need for care. For people with learning disabilities, remote support enables them to live more independent and confident lives. Prevention reduces need for care, independence and confidence all reduce the amount that the current providers are paid. This raises significant issues for leaders and for culture change. Often the right thing to do for the patient or client is the wrong thing for the financial standing of the organisations involved. This requires leadership at the policy and Governmental level. The focus of this report is on how successful digital interventions can be against the resource and skills challenges in the current climate. Imagine how successful they could be if there was a strategy and funding to facilitate a market in solutions.
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In 2017 the Local Government Association in collaboration with NHS Digital introduced the Local Investment Programme. The programme recognised that the imperative for local care services to transform has never been greater due to rising needs, citizen demands and expectations alongside sustained pressure on resources. Although technology will never be a replacement for the delivery of care it can, if used appropriately, support people to live at home for longer, enable professionals to work more effectively together and help commissioners target services where they have the greatest impact. The Local Investment Programme (LIP) supported transformation through one-off local investment funding of up to £50,000 for projects that seek to use information and technology to improve adult social care and health outcomes and deliver financial savings as well as supporting more resilient care services and in improving outcomes, including people’s experience of care.
The programme was underpinned by a number of key principles:
encouraging open and replicable approaches which enable other LAs to adopt digital ways of working
supporting innovation and new thinking within adult social care and health, assisting its digital maturity within a challenging financial environment
assisting cross-council or multi-agency use of information and technology
developing an evidence-base and tools to support ongoing local digital investment in adult social care and health.
It was expected that the outputs and learning from these projects would be reusable and replicable, enabling them to be shared and implemented widely across the sector.
Councils who were successful in their bids for funding received support from an external partner organisation to help evaluate benefits, capture learning and support dissemination to assist other local areas. Participating local authorities were required to actively support this work, over the course of the programme, including in the development of guidance and tools for the sector.
The Bayswater Institute and OPM Group (now Traverse) were successful in winning the opportunity to evaluate the 19 technology interventions funded by the programme. In April 2018 an interim report was produced capturing the learning on the ground as well as considering the programme itself.
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Christmas saw the publication of another forecast of the number of jobs that are at risk because of the march of robotics and artificial intelligence. This time it was the IPPR (Institute of Public Policy Research) forecasting that up to 44% of UK jobs are at risk across wide sectors of the economy.
There are now many forecasts of massive job losses and attention is being focused on a world where a small proportion of people (the highly skilled ones) will be employed and the rest will be out of work and poor.
But there is also another common theme in the debate about the future of work. It is that we exist in a complex, ever changing, interconnected, global economy and that to survive organisations have to be flexible, resilient and adaptive. The cry is that:
The Only Constant is Change
Who will manage the change?
How do we reconcile these two different perspectives on the future of work? Our clever technology may be very good at doing the operational work but it cannot help us make sense of the messy world of international trade, market forces, competitiveness, social change, government action and technical innovation. And it cannot determine what we should do to take advantage of new opportunities and defend against threats. AI may be smart but it is a narrow intelligence with a clever understanding of a specific work domain. Indeed, such narrow AI is also known as weak AI because it cannot replace the breadth of capabilities of a human. However imperfect they may be, human beings are currently the only general purpose intelligent resource we have that can make sense of a confusing, changing world – sentience is known as strong AI.
How is a work organisation to manage in a changing world with a small labour force and a large and sophisticated technological base that may be difficult and expensive to change? The small labour force may have a big agenda: to manage the technology and make sure nothing goes wrong, to monitor the outside world and spot opportunities and threats and to design and implement new ways of working to meet changing requirements. And to keep doing all of these things all of the time. There are many reasons to predict that this model of future work organisations will be ineffective and could be dangerous. One of the reasons for this prediction is what we know about how work actually gets done.
People as the adaptive, coping agents in work systems
Every study of how work actually gets done shows that it is rarely done strictly according to the formal processes specified that may be embedded in the technology. The people in the work system embellish the formal processes with their own knowledge, often tacit and undeclared, in order to give work delivery the flexibility to meet varied and emergent requirements. They are the ‘oil in the system’ that ‘keeps the show on the road’. They recognize what is new and different, learn how to adapt, and add new, often unspecified, procedures to the repertoire of the organisation. In doing so they often have to ‘work around’ inflexibilities in the formal system to get work done and meet customer requirements.
As a result in any well-established work system there are people who have a deep but often implicit understanding of how the system actually works and a learning capability that means there is a bottom-up process of adaptation and evolution in place that responds to local changes.
The danger of the current narrative about robotics and artificial intelligence is that it implies the replacement of this human resource with technologies that will produce the work on their own. If that is the case not only will work systems become less resilient and adaptive but all the collective tacit knowledge will be lost. And as the saying goes ‘you don’t know what you have lost ‘til it has gone’.
There is always ‘Organisational Choice’: changing the balance of task 1 and task 2
To their credit, the IPPR recognize that it is only some of the tasks that can be automated and there are many other parts of jobs that are best done by people. So instead of just assuming technology will replace people we have to ask how the new technological capabilities and the very different capabilities of human resources can be harnessed together for the long-term resilience and adaptability of work organisations. The solution has to be sociotechnical change not just technical change. There will be significant organisational choices to be made to find the right solutions and we need some principles to guide this process. Here are a few to consider:
Immediate cost-effectiveness may be a dangerous objective. The key argument for automation may be economic – you get greater and more reliable productivity from robots and they are cheaper than human resources. That may be so, but you also have to consider what you might lose….
Knowledgeable and skillful human resources provide a sense making resource that can cope with the unforeseen. We need to keep a general sense making capability at all levels within the organisation; to keep a watchful eye on our technology and to provide flexibility and adaptability wherever it is needed. But to be effective people need to keep their knowledge and skills up-to-date and that means actually doing the operational tasks some of the time. So, enabling them to ‘keep their hand in’ is an important design criteria for future systems design.
Having people who understand the task domain means there is a double-task resource to add significant knowledge to planning future developments. Task 1– getting today’s work done – has dominated.
People also have Task 2 abilities – to step back and reflect, to review their performance, to see what can be improved etc. The more they can do this, the better chance the organisation has of coping with the need for continuous change.
Helping people and organisations develop their Task 2 capabilities is an important part of the Bayswater Institute mission. It could be that one of the consequences of robotics and AI will be that people need to spend less time on Task 1 and they can spend more time on Task 2 – in particular thinking about how the work system may be changed to meet new challenges and opportunities. Exploring the potential impacts up-front would seem a good investment in that this is a global challenge and will generate new requirements of the work force that could benefit from planning rather than reacting.
https://www.bayswaterinst.org/wp-content/uploads/2017/10/header-logo-white-blend-deeper-top.png00Adam Hoarehttps://www.bayswaterinst.org/wp-content/uploads/2017/10/header-logo-white-blend-deeper-top.pngAdam Hoare2018-01-09 10:36:182018-11-21 18:23:12The Future of Work: Automation and Continuous Change?
Comparison of the Hospital Internal Communications (HIC) project of the 1960s with the Better Outcomes for People with Learning Disabilities (BOLDTC) project in 2016 and their use of action learning approaches
Purpose – The purpose of this paper is to explore how action learning concepts were used in two healthcare projects undertaken many decades apart. The specific purpose in both cases was to examine how action learning can contribute to shared learning across key stakeholders in a complex socio-technical system. In each case study, action learning supported joint design programmes and the sharing of perspectives about the complex system under investigation.
Design/methodology/approach – Two action learning projects are described: first, the Hospital Internal Communications (HIC) project led by Reg Revans in the 1960s. Senior staff in ten London hospitals formed action learning teams to address communication issues. Second, in the Better Outcomes for People with Learning Disabilities: Transforming Care (BOLDTC) project, videoconferencing equipment enabled people with learning disabilities to increase their opportunities to communicate. A mutual learning process was established to enable stakeholders to explore the potential of the technical system to improve individual care.
Findings – The HIC project demonstrated the importance of evidence being shared between team members and that action had to engage the larger healthcare system outside the hospital. The BOLDTC project concerned the continuing relevance of action learning to healthcare today. Mutual learning was achieved between health and social care specialists and technologists.
Originality/value – This work draws together the socio-technical systems tradition (considering both social and technical issues in organisations) and action learning to demonstrate that complex systems development needs to be undertaken as a learning process in which action provides the fuel for learning and design.
Eason K. D.Action learning across the decades: case studies in health and social care settings 1966 and 2016 Leadership in the Health Services, 30(2) 118-128 https://doi.org/10.1108/LHS-11-2016-0057
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The Organisation for Economic Co-operation and Development has downgraded its 2017 growth forecast for the UK to 1.5% from a 1.6% estimate made in September, making Britain the weakest economy in the G7. The office for budget responsibility had taken the rosy view that after 2008 UK productivity growth would return to previous levels of around 2% It has now admitted, after years of getting it wrong, that it is likely to sit around 1.3-1.5% until 2020. Last week’s budget reverberated with the recurring issue of low productivity growth. The solution presented was an industrial strategy. Something that had fallen out of favour as Government interference.
The announcements based on borrowing came thick and fast:
Digital skills and startup funding to reinvigorate the UK’s waning productivity.
£3 billion to cushion the landing of a potential hard Brexit, the chancellor said: “This Budget is about much more than Brexit. For the first time in decades Britain is genuinely at the forefront of this technological revolution. Not just in our universities and research institutes, but this time in the commercial development labs of our great companies, and on factory floors and business parks across this land. But we must invest to secure that bright future for Britain.”
Last year’s £23 billion National Productivity Investment Fund was to provide £31 billion in funding over six years, compared to the originally planned five. R&D to receive another £2.3 billion investment, under the government’s Industrial Strategy aim to ramp up R&D spending to 2.4% of GDP.
To double the number of tech startups founded in Britain with the goal to see one created every half an hour.
A £10 million Regulators’ Pioneers Fund to help regulators find new ways to bring emerging tech – AI and 5G – to market.
Tech City UK, to be rebranded as Tech Nation, a body with a remit to spend £21 million on developing the UK’s various startup hubs.
In a bid to tackle the UK’s stark digital skills gap, the chancellor also outlined fresh cash to retrain people and provide a greater focus on maths and computing for children and teenagers.
The idea of a strategy and a long list of funding opportunities for new technology seems to overlook some very important evidence. Figures for various IT projects (some of the figures originating from the National Audit Office no less) demonstrate a persistent gap between the projected benefits and the reality:
Magistrates Court LIBRA – £232 million estimated loss;
HM Prison Service C-NOMIS – £690 million estimated loss;
Fire and Rescue FiReControl – £469 million estimated loss;
NHS NPfIT – £20 billion estimated loss.
As we borrow money to fuel a technological “hail Mary pass,” it would seem a good time to think about why we fail to convert so many such passes to a touchdown. The Bayswater Institute has been extensively involved in embedding and evaluating digital technologies in health and social care over several decades. Over the last decade alone there have been hundreds of initiatives to improve productivity in care provision by elevating the use of technology to 21st century standards. Although there has not been an overall assessment of the impact of these initiatives the experience of care provision points to low impact from these initiatives. From seeing these projects from the inside, we have developed a level of understanding of why they struggle – and it is not the technology. Two things work against the use of technology in many of these scenarios:
The technology does not exist in isolation it is part of a system that involves the people using it and the people receiving services. If it does not work for them it is not productive.
Where there is an increase in productivity it usually means a single person can handle more work or the workforce can be reduced. This inevitably generates resistance.
Both of these challenges are rooted in social science and the interface between people and technology. Understanding these sociotechnical systems is essential in successfully capturing the benefits the technology can bring. Looking back over the announcements we cannot see where this is mentioned. Throwing money at the technology and expecting social transformation is an interesting approach but the evidence is – it has been done before and it will fail.
A third issue that recurs in productivity considerations. To know a system is more productive than it was before it must be measured in a meaningful way. This links back to point 1 above. If it works for the professional but not the citizen – it does not work. Hence, the outcomes of productivity must include social value and social impact otherwise public money is spent on making the system happy and the service recipient unhappy.
We spend much of our time providing summative evaluations of where the barriers and challenges are in technology projects that are trying to embed into practice. We have a special interest in formative evaluations of interventions where we can draw on our experience and anticipate some of the problems ahead of the development and have the opportunity to have an impact on the NAO estimated loss. If the focus remains on the technology and not the combined scoiotechnical system the return on investment is likely to be negative. The last thing that Phil wants.
https://www.bayswaterinst.org/wp-content/uploads/2017/10/header-logo-white-blend-deeper-top.png00FiDeeEdit1https://www.bayswaterinst.org/wp-content/uploads/2017/10/header-logo-white-blend-deeper-top.pngFiDeeEdit12017-11-29 14:10:202018-11-28 17:11:32Productivity? – Don’t Just Fund the Technology Phil! A response to the budget of the 22nd November 2017.
The Government mantra is ‘our actions follow the science’. The scientists collect evidence of how the virus is spreading in order to give the politicians the advice they seek. But what evidence to collect? And how long is the lag before you know whether actions taken are being effective? 
