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The Future of Work in Health – Part 3

April 4, 2017

This is the last of three blogs leading up to a forum on the future of work in health. In this one, David Lye, Director and Fellow of SAMI, and a former Senior NHS Manager and Department of Health official, identifies a few key questions posed by changes in society, technology and other dynamics.

The story so far…

In his blog, David Smith, CEO of Global Futures and Foresight, highlighted the rapid and accelerating changes taking place in the world of work and technology. In the second blog, I identified a number of the key factors that will drive change in health care – social, technological environmental, economic and political.

The Overriding Question … “So What?”

We know that the world of work is changing, and we know that there are currents of change that will affect the worlds of health and social care. These factors lead us inevitably to the question of how they will change the world we know.

What We know

We can probably be sure of some things. The ageing population will drive up demand for health care. More people living with comorbidities; more people living alone; more people living with dementia.

The march of technology will drive up the number of new treatments some will be incremental improvements on current options, whilst some – genetech, biotech and nanotech, for example, will seem like miracle cures. This flood of innovation will add a further cost pressure to the pressure of the ageing population.

There is no immediate prospect of a windfall of extra funding to help the NHS to absorb these pressures, although no doubt battles will be fought in the trenches of UK politics. NHS England’s publication, “Next Steps on the NHS Five Year Forward View”, published last week, recognises the need for the NHS to change, and to look again at its priorities.

So we face the likelihood of a world of rising demand, new opportunities (at a cost) and little prospect of a financial windfall.

What We Don’t Know

The future health of our health system will therefore depend on how it can adapt to these challenges, making use of the opportunities of new technology to provide services in ways that are better and more efficient. Here are some of the questions to which we don’t know the answer, but which will determine how successful we are in the future.

The Patient of the Future

The market is awash with apps and wearables that claim to help us to keep a closer watch on our vital signs, diet, exercise, sleep patterns etc. How far will this lead to a change in lifestyles? And what proportion of the population will refuse to engage in proactive management of their health? How can health services best encourage and support the willing, and try to convert the unwilling?

The Clinician of the Future

Given the ability of artificial intelligence to absorb entire libraries of information and to diagnose more quickly and accurately than humans, what will change in terms of what clinicians need to do, and need to know? Will significant areas of the current professional training curricula become redundant? What new skills will be needed? How will boundaries between different professions change?

Will the current boundaries between primary, secondary, tertiary and social care need to shift? For example, will primary care become accessible from the patient’s home – or wherever they happen to be? Will traditional secondary care services, such as diagnostics, be centralised? Will advances in AI and robotics mean that some services will become less labour-intensive (the NHS paybill is over £45 billion)?

Research in the Future

How to ensure that different technologies and strands of research can join up and allow cross-fertilisation? And how to ensure a safe and efficacious transfer from the laboratory to the clinic. How will funding streams and licensing/regulatory systems need to change? How do undergraduate and graduate syllabuses need to adapt to produce the researchers of the future?

Managing for the Future

The NHS and social care have been very resistant to radical change. How to ensure that change can be adopted more quickly, without compromising safety and efficacy? How to persuade the public and the staff who work in health and social care to support changes to the status quo? How to prioritise the massive change agenda facing services?

As John Maynard Keynes exclaimed:

“The difficulty lies not so much in developing new ideas as in escaping from old ones’

The workshop on 6 April will begin to address how we can distance ourselves from the bondage of established dogma and start to explore the questions posed above. We will report on the outcome in a future blog. But undoubtedly there will need to be a lot more concentrated and continuing thought, and we will be looking for ways to foster and contribute to that debate.

Written by David Lye, SAMI Fellow.

The views expressed are those of the author and not necessarily of SAMI Consulting.

If you enjoyed this blog from SAMI Consulting, the home of scenario planning, please sign up for our monthly newsletter at and/or browse our website at

The Future of Work in Health – Part 2

March 29, 2017

This is the second of three blogs leading up to a forum on the future of work in health. In this one, David Lye, Director and Fellow of SAMI, and a former Senior NHS Manager and Department of Health official, looks at the trends and factors that will drive change in the way that health and social care will need to work.

The story so far…

In his blog, David Smith, CEO of Global Futures and Foresight, put the world of health into the wider context of applied technology across the wider corporate world. He highlighted the rapid and accelerating changes taking place – noting the prediction that in ten years’ time, 75% of companies in the S&P 500 in will be ones that are not there now. More specifically to health, he noted the observation by Professor Nick Jennings of Imperial College that the rate at which medical knowledge is being generated is doubling every 18 months.

The STEEP Drivers of Change

Looking forward over the next 15-20 years, it is clear that rapid technological advances will drive significant change in the way that health and care services need to operate – and therefore the way that people work within those services, but there is more than technology at play here. Taking the STEEP (social, technological, environmental, economic and political) headings as a primer, we can see key drivers of change across all the headings.


According to the Office for National Statistics, the population of the UK will grow from 64.6m in 2014 to 73.9m in 2039. The median age will rise from 40 to 43. One in 12 of the population will be aged 80 or over.

By 2040 we should be well on the way to being a “post-smoking” society, but there is rising incidence of obesity and its associated illnesses, such as diabetes. An aging population will have a range of different conditions (comorbidities). The over-80s will have a rising demand for social care among the ageing baby-boomers (of whom this author is one). Baby-boomers will be more vocal and demanding service users than their parents’ generation have been.

If there is great instability in the world of work, and greater job insecurity, we can expect a rise in the incidence of mental illness.

Generations X and Y will become the leaders of health care. Last year’s junior doctors’ strikes indicated they may bring a different attitude to their employment. And if Brexit leads to reductions in immigration, this will potentially affect the available pool of NHS and social care staffing. Currently the UK is neither self-sufficient in doctors or nurses. The UK needs 11,000 new doctors each year. UK medical schools train just 7,500.


Technological change is accelerating. In modern health care the pharmaceutical industry, and the suppliers of medical devices and equipment are joined by Google, whose Deep Mind is being piloted at Moorfields Eye Hospital in London and elsewhere, IBM, whose Watson is being piloted in healthcare around the world, including Alder Hey Children’s Hospital, and many other smaller innovators in IT and artificial intelligence.

Technology will allow quicker and more accurate diagnoses, more thorough scanning for potential drug interactions – important in a population with more comorbidities – and do the routine work of trawling through medical records and test results, quickly and effectively. In the private sector, Babylon is offering AI-based online consultations.

Alongside artificial intelligence, big data is getting bigger – the digital universe is doubling every two years. The ability to hold more data adds to the need for AI machines to mine it.

Robots are being deployed as care and nursing assistants in Japan, as porters in hospitals, and have been piloted within UK hospital pharmacies as far back as 2010.

These technologies empower the patient too. Implants and wearables – such as 24/7 blood sugar screening for people with diabetes, allow people to become partners in their own health care, rather than passive recipients of care. Not all will choose to do so, but the uptake of apps, fitbits etc suggests that most will.

Genetic advances have allowed personalised medicine, pre-diagnosis, targeted treatments for cancer, and gene splicing to address hereditary conditions. Nanotech will allow micro-invasive techniques for screening, diagnosis and treatment. Biotech is opening up the possibility of much-needed new anti-microbial treatments. And 3-D printing and robotics together are beginning to open up the prospect of exoskeletons. There is a constant wow factor on medical websites today as we look forward to a world in which the blind will see and the lame will walk.


Advances in technology will change the way in which services can be delivered. People will welcome the chance to access services digitally.

More generally, the change in the infrastructure of urban and rural Britain will impact on health care. If drones can deliver pizzas and shoes, then why can’t they also deliver prescriptions? Will advances in renewable energy lead to better air quality – and thus improve the health of children and other vulnerable people?

On a global scale, might there be major effects of climate change that trigger major migrations? The continent with the fastest population growth in this century will be Africa. Mass-migrations are likely to be towards Europe. This would change the UK’s population figures, add to the pool of younger working-age people, and change the health profile of the population.


Aside from the economic news of today – Brexit, Trump, a growing sentiment against globalisation – the wider impact of the so-called 4th Industrial Revolution will be felt more and more. We have seen a shift in the balance between capital and labour, favouring “the few” relative to “the many”.

Whilst the changing demography of the UK will drive up demand for health and social care, the availability of public funding lies with the politicians. In this they will be influenced by tax revenues, which are in part, down to the state of the national economy, but also to the ability of the government to collect taxes.

The pressures are real, but the economic outlook is uncertain.


Many of the pressures and drivers above will depend in part on political responses. For example the post-Brexit policy on immigration will affect the availability of staff, or force an increased investment in recruitment and education & training among UK citizens. Government will determine how much money it can afford to invest in health and social care, and the relative priority against other demands for public spending.

Government will use its influence to drive the pace of investment in new technologies and determine the legal framework in which new technologies, such as genetic sciences, are able to operate.

The Government should also recognise the potential strength of the UK as a clinical science and research base, which will be enhanced by the application of AI and big data to the national hospital episode statistical data – which is a unique global resource.

This very brief and high-level overview illustrates how much change is going to have an impact on the health care services that we know. In the final blog, we will start to identify some possible areas in which the world of work will change.

Written by David Lye, SAMI Fellow.

The views expressed are those of the author and not necessarily of SAMI Consulting.

If you enjoyed this blog from SAMI Consulting, the home of scenario planning, please sign up for our monthly newsletter at and/or browse our website at

Roadmapping the future of mobility

March 22, 2017

I was delighted to work with Cambridge University’s Institute for Manufacturing (IfM) to facilitate a pilot event to be called ALFI. This stands for Alternative Futures Insights. The Round Table was initiated by Anna-Marie Greenaway, Director of International University and the topic chosen for the first UK pilot was on the future of mobility – for people and freight.

The Round Table was at the end of February at the Møller Centre, at Churchill College Cambridge: I had not been there before – it is really well organized for our sort of event, with very helpful staff used to providing for the range of people that we gathered together. These included academics from Anna’s network and Dr Nicky Athanassopoulou’s network at IfM, experts on transport from the European Commission, and futurists. From BP, Mike Muskett, Distinguished Advisor Downstream Technology and Dr Dan Walker, Head of Emerging Technology and members of his team joined the lively discussions.

After introductions over a sociable dinner at St Johns College, the next day we tackled an agenda integrating two different methodologies – scenario planning and road-mapping on the topic of “what mobility in Europe might look like by 2040 for both people and goods”.

Scenario planning traces its history back to just after the Second World War, when Hermann Kahn pioneered the technique of “future-now” thinking, aiming through the use of detailed analysis plus imagination to produce a report as it might be written by people living in the future, to promote debate on nuclear weapons. Since then the method has been used extensively for creating future mental models to improve the quality of decision-making.

Roadmapping is a powerful technique regularly used by companies, government organisations and academic institutions to establish and support strategy and innovation. Roadmapping explores, manages and communicates the linkages between technology, research and product development to commercial objectives and market opportunities through a structured visual framework.

Roadmapping blog

We started by emphasizing that scenarios are not forecasts and went on to use Three Horizons to capture drivers of change important for the future of mobility to 2040. The Third Horizon social and economic drivers were used to form the scenario axes. In principle, the technology-based drivers from all Three Horizons would be then examined in all the scenarios, using the road-mapping process. In practice, due to time pressure, we used the scenarios to highlight technologies implicit in their development and did not get time to examine those generated through the drivers discussion. These were however captured for the write-up.

The workshop used the Strategic-Plan (S-Plan) framework developed by the IfM over a period of several years [[1], [2]]. The framework was configured to elicit the emerging technology implications from each scenario developed and evaluate which technologies maybe important for several scenarios.

If you are interested in finding out more, please contact either Nicky Athanassopoulou ( or Gill Ringland (


[1] Phaal, R., Farrukh, C.J.P. and Probert, D.R. (2004), “Customizing Roadmapping”, Research Technology Management, 47 (2), pp. 26–37.

[2] Phaal, R., Farrukh, C.J.P. and Probert, D.R. (2007), “Strategic Roadmapping: A workshop-based approach for identifying and exploring innovation issues and opportunities”, Engineering Management Journal, 19 (1), pp. 16–24.

Written by Gill Ringland, SAMI Fellow and CEO.

The views expressed are those of the author and not necessarily of SAMI Consulting.

If you enjoyed this blog from SAMI Consulting, the home of scenario planning, please sign up for our monthly newsletter at and/or browse our website at

Work Automation

March 15, 2017

This is the first of three blogs leading up to a forum on the future of work in health. IN this first blog, David Smith, Chief Executive of Global Futures and Foresight, looks at the wider context of automation in the workplace and its impact

DS blog

The rate of change is such that by 2027, 75 percent of the companies in the S&P 500 are predicted to be companies that are not in the index today. Adapting to the underlying economic, technological and social changes that are reshaping the world of work will be critical for incumbents wishing to survive and thrive.

One major area of change obviously lies with technology; not so much with the technology per se but in what it enables organisations to do. Many of the technologies underpinning digital transformation are relatively prosaic yet nine in ten organisations in 2016 still reported the implementation of digital transformation as a significant challenge, with 70 percent of these citing internal complexity as an inhibiting factor . In addition, a wide range of ostensibly differing industries and professions possess a common set of characteristics that are open to codification and thus automation. How such organisations can successfully merge artificial intelligence (AI) and humans to work together remains an infinitely bigger task than the digital changes made thus far, and one that few seem prepared for.

The organisational and leadership implications of artificial intelligence are enormous. Jobs, processes, the relationship with consumers, patients, citizens and organisational models will all be reworked by artificial intelligence. Indeed, PwC says 64 percent of CEOs believe that robotics will bring new innovations to their business models. Crafting models that enable a given organisation to frame these challenges as opportunities – and then to capitalise on them – will be a huge task, requiring multidisciplinary thought and genuine innovation.

Such changes may in fact be necessary for the organisation to evolve at the same rate as its wider environment. The rate at which medical knowledge is being generated is estimated to be doubling every 18 months. This gives practitioners little chance to stay abreast of all developments, even within their field of expertise. Even medical students stand little chance in the current educational set-up, since the time from acceptance in a program to graduation is likely to see a doubling of medical knowledge twice over. The ability of algorithms to help deliver the most relevant details and updates to doctors (as well as for students), on-demand and on a case-by-case basis holds great potential.

There is also the possibility, that, along with other trends, emerging AI will open new possibilities in future medical business and organisational models. AI capability is advancing at such a rate that as many as 47 percent of jobs (or at least the tasks within them) will be highly susceptible to automation over the next two decades. In 2016, an autonomous robot surgeon bested human doctors in stitching up pig intestine. In addition, haptically enabled robots, able to touch and feel, have enabled remote diagnosis and abdominal ultrasound imaging. Alone these developments are not enough to constitute an immediate threat to the current model. It is, however, worth recounting that in their seminal study, Osbourne and Frey suggested surgeons and physicians were amongst the least likely of all professions to be automated, at 0.42 percent. This clearly suggests that even within those jobs unlikely to be fully automated, automation is likely to feature alongside the human worker.

Automation is likely to contribute to a quickening ‘skills turnover’ in the coming years. A Deloitte survey found that 75 percent of executives believe that automation will require new skills over the next several years. The ability for the organisation at large to change successfully is questionable however, much as it is with the related digital transformation process. Only 13 percent of executives believe their organisation’s capabilities to redesign work done by computers to complement talent are excellent. By contrast, 34 percent see them as weak. The friction, between what is needed and what is organisationally possible will account for much turbulence.

As a result, ‘…in the Next Economy, companies (will) use technology to augment workers, not just to replace them, so that they can do things that were previously impossible,’ says Tim O’Reilly. Given that flatter and even decentralized work structures are better equipped to cope with ambiguity, speed and evolving digital norms, it is quite likely that much work will occur within team units. Bain predicts that ‘…by 2027, most work will be project-based, with agile teams (internal and external) the dominant unit.’ Designing for this will be key, with GE Healthcare’s Chief Patent Officer Greg Petroff, noting that design thinking should be used ‘…to have multidisciplinary teams frame the problem space more accurately. It’s a great process for stakeholder alignment,’ he suggests. Healthcare is set for radical change, and carefully planned and implemented AI solutions may be key to a successful transformation.

In the next two blogs we will look at the social, technological and environmental changes that will drive change in health care; and then look at specific potential impacts on the work that professionals and others do in health and social care.

Written by David Smith, Chief Executive, Global Futures and Foresight.

The views expressed are those of the author and not necessarily of SAMI Consulting.

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Re-using scenarios in strategy

March 10, 2017

Scenarios are the most powerful vehicles I know for challenging our mental models about the world and lifting he blinkers that limit our creativity and resourcefulness” Peter Schwartz

The Strategic Foresight method that is most widely taught in Business and Management Schools is scenario planning or scenario thinking. In this module we explore when and how to build and use scenarios as part of a Strategic Foresight toolkit. It is largely self contained but assumes a knowledge of environmental/horizon scanning. It covers some of the well known examples of scenario thinking in action as well as many other examples. It is an extensively updated and extended version of a brief that appeared in “Business: the ultimate resource”, ISBN 978-1-4081-2811-4.

What is scenario thinking? Scenarios as models of future worlds

Scenario thinking creates possible future outcomes (scenarios) to improve the quality of decision-making. One of the best definitions of scenarios is by Michael Porter:

an internally consistent view of what the future might be, not a forecast but one possible future outcome”.

At a time of volatility and change, managers need to be able to step out of their current framework and imagine future worlds – which may arrive sooner than expected.

But some organisations feel that they do not have the capability to develop scenarios, for instance because they are not sure what questions to ask, or because they do not feel confident of their expertise outside their operational domain. In these cases, using existing scenarios is really useful.

Why use existing scenarios?

Using pre-existing scenarios as a basis for work in an organisation makes a lot of sense under some circumstances. For example

  • Where the external environment is a dominant factor, e.g. the economy, then using scenarios based on economic futures to frame a discussion of implications for different parts of the organisation can be helpful
  • Where the intention is to introduce scenario thinking to a group of people for the first time, it is often useful to use external “reputable” scenarios to allay suspicion of the provenance
  • Where an organisation has developed scenarios already – for instance with an internal task force – and business units or functions need to explore the implications for their functions and roles.

quoteSources of scenarios

There are many well-established global and national organisations that undertake scenario studies on a regular basis, for instance

The scenarios below have been used across industry sectors and geographies:

An up-to-date list and links are maintained on the Unlocking Foresight Know How web site,

How to use existing scenarios

Existing scenarios are best explored in workshop mode. They need to be briefed as “fairy stories” which have been useful to other groups in developing their thinking. It is important that these workshops are held off-site to signal “different”, and that the participants have the opportunity to think themselves into the scenarios through sharing among the group members. A two-day format is good to allow reflection and absorption time; so residential workshops work better than non-residential.

More can be found in our scenario primer,

Written by Gill Ringland, SAMI Fellow and CEO.

The views expressed are those of the author and not necessarily of SAMI Consulting.

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Melding machine learning and participatory foresight

March 1, 2017

Last year SAMI colleagues assisted in beta-testing a workshop process design which was used in a project looking at the skills that may be required in the future and is the subject of the following article.

Occupations, Tasks, Skills: what might we need most in the future?


What do you want to be when you grow up? Are you thinking about choosing a new career? Worried about the jobs available for your children, and what skills they might need to succeed in the future? Pearson, the world’s largest education company, has sponsored Nesta UK and the University of Oxford in forecasting future jobs availability and skills requirements.

The resulting project, “Employment in 2030: Skills, Competencies, and the Implications for Learning,” explored which occupations may disappear in the future, and which may be in greater demand. Robots and smart things everywhere are supplanting human labour —how many occupations are actually in jeopardy?

Official government occupational lists from the UK and the USA provided the starting point for the project. Each occupation’s description includes a list of typical tasks and the skills they require. Consequently, forecasting the potential for growth or decline of a specific occupation also indicated the potential for growth or decline in demand for specific skills: will we still need chefs in the future?

Or will nimble robots assemble raw ingredients into gourmet meals in gleaming restaurant kitchens? Does that only mean that restaurants no longer require line cooks, and that the chef’s key tasks—of designing the dishes and curating the meals, calculating the ingredients required and their most efficient use—and related skills will still be in high demand?

Understanding what skills future occupations will require helps educators understand what the critical educational needs of the future might be. What do people really need to know to thrive in the transformed economy of the future?

How can experts work together to help train an algorithm about occupational futures?

Pearson, Nesta and the University of Oxford set out to explore these questions with a unique futures approach: a dialogue between human experts and an active learning algorithm. The array of methods available to foresight researchers and forecasters splits across Snow’s two cultures: the highly data-driven and quantitative vs the data-informed, intuitive and qualitative. This project sought consciously to bridge the two.

It’s a tricky bridge to build. Nesta invited world class thinkers to discuss emerging changes and their potential effects on occupations to one workshop in Boston, and another in London. I should also declare an interest at this point: I was commissioned to design and facilitate the workshops that elicited the expert opinion that informed the algorithms.

The workshop attendees were looking forward to a stimulating conversation and discussion about transformations in jobs and labour. The active learning algorithm that we needed to feed, on the other hand, simply wanted those experts to rate possible growth or decline in 30 occupations—not a very interactive task. Our goal was to design a process that supported wide-ranging thinking about change, stimulated discussions across the expert perspectives in the room—and paused periodically to inform the algorithm, via a simple web-based input form.

How did we do it? The most critical part of the process design was explaining clearly what we were asking participants to do, and why: the introductions to the project goals (understanding what skills the future will require), the overview of machine learning (introducing them to the algorithm they’d be training), and their role in sharing data and contributing insights. Second, while many of the experts had deep understanding of one sector of change, we wanted everyone to have a shared baseline of changes across multiple sectors of changes that might affect the future of occupations. Thus a key component of the project was extensive research into critical trends, and summarising them as a trends deck for discussion.

The workshop live

What, then, did we actually do on the day? Each workshop began with a round of introductions that included—as an icebreaker and a way to frame discussions —the question, “When you were ten, what did you want to be when you grew up?” It turns out that even economists, social scientists, and technology experts wanted to be astronauts or soccer stars when they were ten!

The project team then galloped rather rapidly through the extensive map of trends and emerging issues affecting economic activity and potentially transforming occupations over the next twenty years. After listening to a data-dense presentation for thirty minutes, participants deserved an opportunity to process the information and its implications, and to discuss the trends amongst themselves. We wanted them to think about how those impacts might affect all the different activities in the economic landscape. We also wanted to switch thinking modes from listening (verbal) to mapping impacts and interconnections (visual).

To spur that conversation and encourage that thinking mode, we printed out a table-sized cartoon of a city landscape (office buildings, retail space, government buildings, arts and leisure, manufacturing facilities, transport infrastructure, agriculture, suburbs, etc.), and a deck featuring each of the key trends and emerging changes, summarized in a phrase. Participants worked in pairs to cluster the trends they thought reinforced and amplified each other, and then placed each change or change cluster on the map where they thought it would have the greatest impacts.

If they thought the change affected more than one economic activity, they could use coloured tape to connect their chosen change to other activities. We then asked them to summarise by suggesting two occupations that, as a result, would increase in future, and two that would decrease.

After stretching their mental muscles with that exercise, we moved on to labelling specific occupations with directional forecasts—“will this occupation increase or decrease in the next twenty years?”—an activity that was assisted by fact sheets that included a definition of the occupation, its specified tasks and required skills, and historical trend data summarizing its growth in the economy. We instantly displayed the forecast output to the group, so they could discuss the range of answers, explore the different assumptions each of them used to arrive at their forecasts, and potentially amend their initial judgments. Participants could refer to the trend deck for change ‘evidence’ to support their assumptions and forecasts. To provide the algorithm with its required base of thirty occupation evaluations, we repeated this process two more times.

Giving the participants discussion space during the occupation forecast labelling gave them an opportunity for unconstrained and exploratory thinking, in contrast to the very constrained mental process of assigning ‘increase or decrease’ labels to 30 different occupations. But it didn’t provide space for another obvious potential output from combining emerging changes, forecasts of impacts on current occupations, and human creativity: brainstorming entirely novel occupations, or radical transformations in current occupations. To capture those creative insights, participants ended the day by pairing up again and scrawling their wild and divergent extrapolations of the occupations of the future on a wall mural with the key change clusters already posted.

Emergent forecasting… watch this space

The research team has mapped the interesting changes, the experts have discussed the possible impacts, and the algorithm is computing. We are looking forward to the output: forecasts of potential future growth—and decline—in specific occupations in the UK and the USA and, more importantly, in the range of critical tasks and skills that may be required of the next generation of workers.

Web pundits trumpet the erosion of employment due to increasing roboticisation and the emerging ecology of ‘smart everything’ (cities, factories, cars, toasters, you name it). Nesta has just demonstrated at least one instance where human intuition and machine learning can work hand in hand. Maybe that’s the best future we could hope for.

Written by Wendy Schultz, SAMI Principal. A version of this article  was previously published in the January 2017 edition of Compass, the newsletter of the Association of Professional Futurists, and is republished with their permission under a Creative Commons licence. There is more information, and project reports, at Nesta UK.

The views expressed are those of the author and not necessarily of SAMI Consulting.

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How should families protect themselves under the new Bereavement Benefits system?

February 23, 2017

From April 2017 the Government is changing the rules on bereavement support for new claimants. 

Existing ones will carry on under the previous regime. Under the old system there were three benefits. These are now combined into one “bereavement support payment”.

First there was a lump sum of £2,000 provided that you were under pension age and your spouse, or civil partner, had paid NI contributions on earnings equal to 25 times the lower earnings limit in any one year.

Although if they died as a result of an industrial accident then that was not required. Under the new system a family without children will get £2,500 and one with children will get £3,500.

This is a significant improvement although it is still below the cost of many funerals. And of course, it does not contribute towards any debts, such as paying off a mortgage. Life and critical illness insurance remains essential cover for such circumstances. It may however reduce the amount of basic cover needed under low-cost funeral plans.

Second there was bereavement allowance for those with no children. It was only payable if you were 45 years old, or older and was payable for 52 weeks.

The amount you got was dependent on the amount your partner had paid into the state pension and also on your age. It was taxable and offset against any contributory benefits you might be entitled to, for example contributory based JSA. At 45 you could get up to £33.77 a week but you would then have your JSA reduced by that amount.

Under the new system you would get £100 per month payable for 18 months and it is not taxable or offset against contributory benefits. So overall, another improvement on the current situation.

Finally we move to the sting in the tail, widowed parents allowance (for those with children).

This was payable if you had dependent children or your partner was pregnant until children ceased to be dependent. The amount was based on your partner’s contributions to the state pension up to an amount of £112.55 a week. It was taxable but you would be entitled to child tax credits.

As with bereavement allowance it would be offset against other contributory benefits. Under the new system, it is £350 per month and is payable in full if your partner has paid NI contributions for a full year. It is not taxed and not offset against other benefits. However it is only payable for 18 months. For families with children this is a very significant reduction in state support.

So what should families do to protect themselves under the new arrangements? The solution is family income benefit insurance.

This insurance currently has a tiny market. It pays out for the term of the policy based on the income of the deceased partner. For two income households it is essential to purchase a policy that covers each life individually.

The interactions with universal credit mean that, assuming the surviving partner continues to work, such a family will have little or no entitlement to benefit after the 18 month period.

I think the changes offer an opportunity for increased sales and innovation in the family income benefit market.

The abolition of support for families after 18 months means that serious consideration should be given to making FIB a rider to life/CI insurance sold as a standard part of protecting your family, rather than as a stand- alone niche product. Costs should also be low.

Even as a stand-alone product is it usually cheaper than term life.

Written by Richard Walsh, SAMI Fellow and first published in Cover magazine, January 2017

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