The Promise of Platforms – Joined up outcomes and better value

One of the often-quoted benefits of digital transformation is the improvement in the ways government departments interact with citizens and business. Departments aim to use the same systems and shared data to avoid time consuming and repetitive tasks. But the reality often falls short of expectations. So, in this blog I take a look at why cross-cutting activity is rare and how digital platforms might help.

Why are public services so siloed?

The current departmental structure brings together and manages most areas of government business through a top down, vertical management structure. This approach is highly effective in delivering many of the government’s key priorities. It provides a single, clear line of accountability and keeps tight control over resources.

However, vertical structures also have many disadvantages:

First, issues or problems which straddle departmental boundaries are neglected. Budgets tend to be allocated on a departmental basis rather to policies that cross boundaries. And mechanisms for reconciling conflicting priorities are weak.

The result is that policy makers can take too narrow a view of the issues. They fail to look at problems from the perspective of the user. And they focus on what is easiest for government to supply, not what makes sense to the service user.

Second, departments also fail to recognise that local authorities have separate lines of accountability to local voters and may not share their priorities. So, departments tend to be overly prescriptive, in specifying the means of delivery as well as the ends.

And third, there are real obstacles to effective cross cutting working on the ground. It involves complex relationships and lines of accountability. Costs tend to fall on one budget while the benefits accrue to another. If appraisal systems are incapable of identifying and rewarding a contribution to a successful cross cutting project, the risks are one way.

So how do we join up government?

My experience is that cross cutting interventions work best when government makes clear their priorities and when champions at Ministerial and Permanent Secretary level (and / or chief executive and senior management team in local government) have a lasting effect on behaviour.

Also, with these supportive conditions, the adoption of digital technologies will enable cross-cutting work. For example, emphasis in UK government is now quite rightly focussed on how digital can support business transformation through, for example, the creation of shared components (such as Verify, Pay and Notify) and common workplace tools . The common link is, of course, information technology: co-ordination involving multiple providers that both depend on compatible IT systems and common data collection and architectures.

But perhaps just as significantly, digital approaches can promote dialogue with citizens and service users.

There are two aspects to this dialogue. First government needs to provide digital channels for information and views to reach them, which are not constrained to departmental silos – people and organisations should not have to tailor their views to fit Whitehall’s structure. People often want to be involved in shaping services, particularly at a local level, not just choosing between them. Open source methods that involve users in designing services have become commonplace in business and have always been common in civil society.

And second, government needs to shift the quality of the relationship between citizens and the state, so services are shaped around the individual’s needs rather than being too standardised. The commitment to make services more personal can mean little more than having someone – a teacher or a doctor – to talk to face to face. But it can mean a different curriculum and programme for every pupil. Or a different pattern or modular options of care for every patient.

Where are we see the benefits of joined-up government?

The harbingers of the future can be found where governments face the most intense pressures. This includes the increasing incidence of chronic conditions, as an ageing population and changes in societal behaviour are contributing to a steady increase in common and costly long-term health problems. Mental illness is equally significant, accounting for over 30% of all GP consultations and 50% of follow up consultations.

As a result, in the UK we now spend over £24 billion on disability and incapacity benefits for over 3.5 million working age people.

Chronic and other complex conditions are not easily administered or treated either through a traditional clinical lens or prescriptions. Much of the care is provided by families and friends and is too expensive to be provided by formal structures and by highly paid doctors. Most of the most important knowledge about how to handle these long-term conditions resides with other patients rather than just doctors.

So, part of the answer lies with giving people control over how money is spent and support structured to meet their needs. This means giving service users direct power over money and new structures of advice, often through simple but powerful online platforms/

At its best, these approaches bridge the bottom-up and top-down, paying attention to the worlds of daily experience rather than seeing people as abstract categories. Networks and platforms can help the state track behaviours, highlighting ‘what works’, and make it easier for people to band together and take control of their care.

Reframing Digital Inclusion: going beyond basic

Basic digital skills and access to the internet are essential for living well in today’s world, issues of too much screen time and the like aside. People with even basic digital skills earn more money, save on household expenses, have access to better employment opportunities and can stay in touch with distant friends and family. For the last decade, digital inclusion initiatives in this country have been focused on ensuring all people have the skills, confidence, and access to technology to get online.

While we must continue to get as many people to that basic level of digital aptitude, it’s time for those of us working on digital inclusion to think bigger. We are facing a perfect storm: an increased need for advanced technology skills as digital permeates everything (and the business understanding that will be needed to take advantage of sophisticated, disruptive new digital technologies), and a growing skills shortage.  Add to this a serious diversity problem and the growing understanding of the knock-on effect of unconscious bias in programming (e.g. of AI), and it’s clear we have a problem. But these challenges also present brilliant opportunities for the industry.

With this in mind, digital inclusion itself must become more inclusive; we must think bigger. I offer a new definition of digital inclusion that also acts as a mission statement in our sustainability work:

Digital inclusion means ensuring all people have basic digital skills and access to technology and the internet now, while expanding opportunity for gainful employment through more advanced digital skills attainment now and in the future.

To achieve this vision, we must start:

  • Investing in the next generation of tech talent now, and not just with coding education
  • Finding and training non-tech workers wherever they are now
  • Transforming our industry’s culture and image so different kinds of people can see themselves in it

Investing in the next generation of tech talent now

Already many of us in the industry, including Sopra Steria, are working with schools, colleges and other organisations to supplement curricula with various STEM learning initiatives.  But, as a society, we need to go further and think more broadly.  Coding clubs are hot right now, and have contributed to changing perceptions of our industry for the better.  However, we have fallen behind in investments in core education: a large proportion of schools report that their teachers do not feel prepared to teach using digital tools, and even computer science tutors aren’t confident when it comes to teaching coding.  Furthermore, connectivity is still a problem.  As of 2014, two-thirds of primary schools and half of secondary schools said they didn’t have adequate WiFi provision.

We also need to continue to reposition STEM (Science, Technology, Engineering, and Maths) subjects, ensuring they are part of core curriculum throughout schooling, not spinning off computer science modules as elective subjects.  The level of technology education today’s students will need tomorrow is much greater than it ever has been, and so related subjects should be treated as sacred as English and Maths are.

I would argue the same is true for arts education…or at least creative education.  The STEM acronym is emerging in a revised version: STEAM (A for Arts), and for good reason.  As computers evolve to become more self-sufficient (i.e. more programming being undertaken by computers themselves), some coding careers will become obsolete.  The more advanced jobs in this space will be for not just the cleverest programmers, but the most creative minds among them.   (Recall the Albert Einstein quote “Imagination is more important than knowledge…” for a reminder that creativity has always been a part of brilliance in science).  But creativity and imagination won’t just be important for the techies of the future: the promise of many of the technologies on the horizon is that we will all be able to use them for better outcomes of all kinds.  We are told doctors shouldn’t fear being replaced by robots, because they will have their work enhanced by AI and big data.  The same goes for lawyers, scientists, social workers, and so many other kinds of workers.  We will become (even more) augmented humans, and augmented humans will only reach their potential if they know what questions to ask their computers.  That takes imagination and creativity.  Likewise, these skills will continue to play an outsized role in dreaming up how technology can be applied to solve current and emerging challenges, be it business challenges that lead to the creation of the next Uber, or societal challenges like solving plastic waste.

Finding and training non-tech workers wherever they are

There is still too much reliance on people finding their way to us in tech.  That is, people who benefitted from the education system and recruitment pipeline that is still plagued by unconscious bias, and an industry culture that, although cooler than it used to be, is still not welcoming to all potential talented people.  We can’t afford to wait for those who are in school now to join us, so we must transform our talent search and employment offer.  There is much to be done – and, to be fair, a lot being done, including offering more flexible working and setting objectives for diversity in recruitment and performance management – but I see two main hurdles not getting enough attention: reliance on traditional talent pipelines (including elite universities), and stubborn insistence on non-essential skills.

Elite universities produce many talented people, to be sure, and they should be in the recruitment mix.  But they shouldn’t be the only avenue, or even the most significant one.  First of all, we will never get enough candidates if we only target students coming out of top universities.  Second, these univiersities won’t help fix our diversity issues.  People from ethnic minority backgrounds and of lower socio-economic status are severely underrpresented here.  This in itself will perpetuate the lack of racial and socio-economic diversity in our sector, if we rely on these universities for our candidates too heavily.  But the problem goes deeper: the pervasive homogeneity within these institutions could mean that organisations that rely on them too heavily for talent will not only have diversity problems as described above, but they will also have a lack of diversity of thought and experience.

Drawing up a job description for a recruitment advertisement is not fun, and if you can reuse one you’ve already got, you’re probably going to do that.  The problem is, the one you’ve got is probably a wish list instead of a job description.  It’s much easier to just list everything you can think of that your ideal candidate might be able to, than to take the time to seriously challenge yourself to identify and prioritise a few skills and qualifications that you absolutely cannot do without.  (The old quote “I’m sorry I wrote such a long letter, I didn’t have time to make it shorter” springs to mind).  But we absolutely must start to do this.  For one, we know that women are likely to rule themselves out for a position if they feel they don’t meet 100% of the criteria, whereas men will tend to apply for the role if they feel they meet a third of them.  Going beyond gender, I believe we could also find untapped talent pools if we took up the practice of examining our real needs and priorities, and considering training and reskilling options.   Could a construction worker become a project manager?  Could an artist become a UX designer?  Could a stay-at-home mum who worked in tech 10 years ago jump into a sales role?  The answer is maybe, but not if we weigh down our adverts for roles with too many non-core criteria.

Being imaginative about where we’re going to find talent now and in the short-term is also crucial to preparing for any displacement that emerges from greater automation.  We will have to be better at seeing skills and competences that are transferrable, and spotting potential for non-technical people to become more technical.  And we have to commit to real retraining programmes.  Done right, retraining should be a better option than letting people go and trying to find talent in this tight market.

Transforming our industry’s culture and image

Despite progress, our industry’s culture and image continue to be barriers to addressing the skills gap.  If people don’t want to come to work in the industry because they don’t see others like themselves, or because some actors are contirbuting to a bad reputation, we will struggle to get the people we need.  The transformation will take place in our workplaces and in our work with schools and colleges, with new recruitment and talent management practices and culture change initiatives, and school outreach with a focus on diversity.  Again, though, we must think more creatively about the kinds of skills we want the future workforce to have.  We can’t train the kids of today for jobs that will be obsolete by they time they enter the jobs market; we have to help them develop problem solving skills, creativity, critical thinking skills.  If we do this, it will have a knock-on effect on our culture and image, because we won’t just be bringing in the old school geeky types from the same backgrounds.

Finally, we can do more to inspire the people we want to attract.  Technology is playing a huge role in addressing some of the world’s greatest challenges, such as climate change, social isolation, and access to healthcare.  I’ve seen firsthand in our work with schools and colleges how talking about technology as a force for social and environmental good captures imaginations and gets kids’ interest.  People of all ages want to make a positive difference in their work, and ensuring we offer those opportunities to our workers now and in the future is the right thing to do and a good way of attracting people.

It’s a lot of work.  Is it worth it?

The benefits to us in business should be clear enough: we can solve our skills shortage over time and address our diversity issues, and improving diversity brings with it its own business benefits. But this is also important on a people level: almost all jobs will require tech skills of a level higher than is required today, and the best jobs will continue to be in tech (yes, I’m biased). Enabling more people to work effectively in the most rewarding jobs could help to turn around the trend towards growing economic disparity in developed countries, and will foster stronger, fairer economic growth.  It will also make those of us in the industry better at what we do: right now we are at risk of creating flawed products because we don’t have enough people from different backgrounds contributing to their creation.

So, yes, the challenge of becoming truly digitally inclusive in the terms described above is a big one.  But we don’t really have a choice if our industry is going to continue to be the engine of economic growth and innovation that it has been.  Let’s get to work, and more importantly, let’s get others to work with us who aren’t yet!

AI – The control problem

When designing a system to be more intelligent, faster or even responsible for activities which we would traditionally give to a human, we need to establish rules and control mechanisms to ensure that the AI is safe and does what we intend for it to do.

Even systems which we wouldn’t typically regard as AI, like Amazon’s recommendations engine, can have profound effects if not properly controlled.  This system looks at items you have bought or are looking to buy. It then suggests other items it thinks you are likely to additionally purchase which can result in some pretty surprising things – like this:

amazon.png

Looking to buy a length of cotton rope?  Amazon might just recommend that you buy a wooden stool alongside it.  As a human, we would not suggest these two items alongside each other.  However Amazon’s algorithm has seen a correlation between people who bought cotton rope and those that also bought wooden stools. It’s suggesting to someone buying the rope that they might want a stool too with the hope of raking in an extra £17.42.  At best, this seems like an unfortunate mistake.  At worst, it’s prompting extremely vulnerable people and saying ‘why not?  This happens all the time?  Why don’t you add the stool to your basket?’.

If this can happen with a recommendation algorithm, designed to upsell products to us, clearly the problem is profound.  We need to find a reliable means to guarantee that the actions taken by AI or an automated system achieve a positive outcome.

Solutions?

Terminal value loading

So, why don’t we just tell an AI to protect human life?  That’s what Isaac Asimov proposed in ‘I Robot’.  Here are the three laws;

  1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.
  2. A robot must obey orders given it by human beings except where such orders would conflict with the First Law.
  3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

They sound pretty watertight.  Adding in no injury through action or inaction seems to avoid a dystopia where AI takes over and lets the human race finish itself off.

Despite how good these laws sound, they don’t work.  Asimov wrote these laws for use in novels, and the novels were much more interesting when things went wrong.  Otherwise we might have ended up with a book of ‘Once upon a time, the end’.

There’s a 4th law, the ‘Zeroth Law’ added by Asimov . This extra rule was supposed to fix the flaws of the other three, the ones that gave Will Smith a bad day. I confess, I’ve not read the book, but I understand that one didn’t go so well either.

The rules don’t even have to refer to people to be a risk.  They could be about something really mundane.  Take the idea of a paperclip maximiser, an idea put forth by Nick Bostrom. This would be a machine made by a hypothetical future human race to manage paperclip creation. Paperclips are just a simple resource and seemingly don’t need a ton of consideration to make them safe, if we tell the AI that it’s purpose is to make paperclips, and that’s just what it does.

But what if we end up with a super intelligent system, beyond our control, with the power to rally the resources of the universe making paperclips? If this system, whose priority is turning everything it around it into paperclips, sees its creators attempts to prevent it reaching this goal, the best bet is to eradicate them.  Even if it doesn’t decide to eradicate them, those humans are still made out of valuable matter which would look much nicer if it was turned into a few paperclips, so turn them into paperclips it shall.

How do we change that terminal value?  Tell the machine to make 1,000 paperclips instead of turning the entire universe into paperclips? Unfortunately, it’s not much better.  That same AI could make 1,000 paperclips, then proceed to use all the resources in the observable universe (our cosmic endowment) to make sure that it’s made exactly 1,000 paperclips, not 999 or 1,001, and that those paperclips are what its creator intended for it to make, and all of the perfect quality to satisfy their desire.

It might not even be fair to give a super intelligent machine such a mundane terminal value– assuming we find a way to make its value remain constant despite becoming extremely intelligent.

Here I am with a brain the size of a planet and they ask me to pick up a piece of paper. Call that job satisfaction? I don’t.

Marvin – Hitchhiker’s Guide to the Galaxy, by Douglas Adam

 

TL;DR – Terminal values don’t seem to work well.

Indirect normativity

Instead of giving a machine a terminal value, could we instead indirectly hint towards what we want it to do?

If we managed to perfectly sum up in terminal value what morality meant to the human race in Viking times, we might have an AI which prizes physical strength very highly.  We might think we’ve reached a higher ethical standard today but that’s not to say 1,000 years from now we will not look back on the actions we are taking were ignorant.  Past atrocities happened on human timescales, with only human level intelligence to make them happen.  Doing it orders of magnitude faster with a machine may well be worse and irreversible.

With indirect normativity we don’t even try to sum up that terminal value; instead we ask a machine to figure out what we want it to do.  Using something like Eliezer Yudkowski’s ‘Coherent Extrapolated Volition’ which asks that an AI predict what we would want it to do if “if we knew more, thought faster, were more the people we wished we were, had grown up farther together”

Rather than following whatever ethical code we have at the time of releasing the AI, we create something which grows and changes as we do, and creates the future which we’re likely to want rather than a far more extreme version of what we have today.

There’s perhaps still some overlap between this system and terminal value loading, and contradictions that the systems would find.  If a machine is asked to do whatever is most valuable to us, and prizes making that correct decision over anything else, perhaps its decision will be to take our brains out, put them on a petri dish and figure out exactly what we meant for it to do.  A clause like ‘do the intended meaning of this statement’ would seem to lessen the concern, but again, to know what we intend the machine needs to be able to predict out behaviour.

A perfect prediction system would look a lot like a ‘Black Mirror’ episode.  Using an application without a second thought to manage your home automation or to find your next date. Not knowing that the machine is simulating thousands of thinking and feeling human minds to make an accurate prediction of your desires and behaviours, including all the pain that those sentient simulations feel when being torn apart from one another on thousands of simulated dates to gauge how likely you are to stay together against all odds.

The control problem is extremely tricky, and looks for answers to questions which philosophers have failed to reach a consensus on over thousands of years of research.  It is imperative  that we find answers to these questions, not just before creating as Super Intelligent AI, but in any system that we automate.  Currently the vast majority of our resources and effort is put into making these systems faster and more intelligent, with just a fraction focused towards the control problem or the societal impact of AI and automation.

Let’s redress the balance.

 

Bridging the gap: how Fintechs and ‘big business’ can work together

by Colin Carmichael, UK Fintech Director

Everyone’s talking about Fintechs – but what does ‘Fintech’ really mean?  It’s a generic term that loosely groups a number of innovative technical organisations within Financial Services.

As the Fintech director for Sopra Steria, I believe I know all about Fintech. To me, Fintech is all about change – introducing new, fresh ideas and ways of working – and making them happen. I’ve worked in financial services across the UK, Europe and further afield for many years – and organisations of all sizes find it hard to change; the bigger the organisation – the greater the challenge. Change means that organisations have to think and act differently to introduce brand new ways of working to deliver desirable services to their customers.  The customer really is king and new products and services need to be built to their wishes (rather than the ‘old fashioned’ way of creating a product and selling it hard). What’s more, new, faster technology and access to huge amounts of data have made this issue more acute as it’s raised customer expectations. Put simply – there’s so much to think about and to do to get ahead and stay ahead.

Organisations need to keep up with the very latest ideas – and still deliver a reliable and robust service. And it’s a fact that incorporating new technology is how they will do it. So why is it so challenging for Fintechs and big players to work together? All too often, Fintechs struggle to get their ideas to the right decision makers – and established businesses are nervous of too much change.

The biggest hurdles are often company politics, internal structures, old processes and course – the difficulty of incorporating brand new ideas into ‘old’ systems. For Fintech’s, it’s tricky to get the right contacts at the right level – and to also ensure their ideas are brought to life safely and securely.  For banks and insurers, introducing new, untried and tested ideas is hugely risky and it can take a long time – as well as effort and money to get it right.

What’s needed is a bridge between the Fintechs and the more traditional organisations – to help them to work productively together. Organisations like Sopra Steria have platforms that are at the heart of many of today’s large businesses – and they also understand existing processes, procurement and politics which often stand in the way of getting things done. By working together, Fintechs, established players and platform organisations can listen to and learn from each other, in order to fast track innovation and get the results they need – quickly and cost effectively.

So, my advice to banks and insurance companies as well as the Fintechs is to work and collaborate with a platform provider from the start. Fintechs can safely test and prove their worth in ‘virtual factories’ using real systems and data – and financial organisations can be confident about bringing the best and brightest ideas to market without huge risk. It puts new Fintechs in touch with established players – and accelerates change. And that’s what we all want.

So, maybe, we shouldn’t be using the term ‘fintech’ to refer to just new and upcoming technology companies. After all – aren’t we all Fintechs? Perhaps instead we should be focusing on partnerships and collaborations between new technology companies, established organisations and the role platform players have to accelerate change.

It really is true. It’s not what you know but who you know that makes all the difference.

Google Dupe-lex

Google unveiled an interesting new feature at their I/O conference last week – Duplex.  The concept is this: want to use your Google assistant to make bookings for you but the retailer doesn’t have an online booking system?  Looks like your going to be stuck making a phone call yourself.

Google wants to save you from that little interaction.  Ask the Google assistant to make a booking for you and Duplex will make a call to the place, let them know when you’re free, what you want to book, when, and talk the retailer through it…. With a SUPER convincing voice.

It’s incredibly convincing, and nothing like the Google assistant voice that we’re use to.  It uses seemingly perfect human intonations, pauses, umms and ahs at the right moments.  Knowing that it’s a machine, you feel like you can spot the moments where it sounds a little bit robotic, but if I’m being honest, if I didn’t know in advance I’d be hard pressed to notice anything out of the ordinary, and wouldn’t for a moment suspect it was anything but a human.

I think what they’re using here is likely a branch of the Tacotron 2 speech generation AI that was demoed last year.  It was a big leap up from the Google assistant voice we are used to, and it was difficult to tell the difference between it and a human voice.  If you want to see if you can tell the difference follow this link;

https://ai.googleblog.com/2017/12/tacotron-2-generating-human-like-speech.html

googledual

So, what’s the problem?

The big problem is that people are going to feel tricked (or ‘duped’ as me and likely 100 other people will like to joke).  Google addressed this a little bit, saying that Duplex will introduce itself and tell the person on the other end of the phone is a robot, but I’m still not sure it’s right.

I can absolutely see the utility in making this voice seem more human.  If you receive a call from a robotic sounding voice, you put the phone down.  We expect the robot is going to try to be polite for just long enough to ask us for our credit card details for some obscure reason.  By making the voice sound like a person our behaviour changes to give that person time to speak – To give them the respect that we expect to receive from another person, rather than the bluntness that we will tend to address our digital assistants with.  After all – Alexa doesn’t really care if you ask her to turn the lights off ‘please’, or just angrily bark at her to turn the lights off.

Making the booking could be just a little bit of a painful interaction. The second example that Google shows has a person trying to make a booking for 4 at a restaurant.  It turns out that the restaurant doesn’t make bookings for groups less than 5, and that it’s in fact fine just to turn up as there will most likely be tables available.  Imagine this same interaction with a machine.  Imagine that conversation with one of those annoying digital IVR systems when you call a company and try to get through to the right person – Saying ‘I want to book a table’…. ‘I want to book a table’…. ‘TABLE BOOKING’…. ‘DINNER’.   Our patience will run thin much faster if we’re waiting for a machine than if we’re waiting for a robot.

Just because there is utility, doesn’t mean this deception is fair.  I can see three issues with this.

  1. Even if the assistant introduces it as a machine, the person won’t believe it

It might just seem like a completely left of field comment and make people think they’ve just mis-heard something.  They’ll either laugh it off for a second and continue to believe it’s a person, or think they just couldn’t quite make the word our right – Especially as this conversation is happening over the phone.

  1. They know it’s a robot, but they still behave like it’s a human

Maybe we have people who hear it’s a robot, know that robots are now able to speak like a human, but still react as though it’s a person.  This is a bit like the uncanny valley.  They know it’s a machine, and the rational part of their mind is telling them it’s a machine, but the emotional or more instinctive part of their mind hears it as a human, and they still offer much the same kind of emotion and time to it that they would a human.

  1. They know it’s a machine and treat it like a machine.

This is interesting, because I think it’s exactly not what Google want people to do.  If there wasn’t some additional utility in making this system sound ‘human like’, they wouldn’t have spent the time or money on the new voice model and would have shipped the feature out with the old voice model long ago.  If people treat it like a machine, we may assume that the chance of making a booking, or the right kind of booking would be reduced.

If you believe the argument I’ve made here, then Duplex introducing itself as a machine is irrelevant.  Google’s intention is still for it to be treated like a human – And is this OK?

I’m not entirely sure it is.  When people make these conversations, they’re putting a bit of themselves into the relationship.  It reminds me of Jean-Paul Sartre talking about his trip to the café.  He was expecting to meet his friend Pierre, and left his house with all the expectations of the conversation he would have with Pierre, but when he arrives Pierre is not there.  Despite the café being full, it feels empty to Sartre.  I imagine a lot of people will feel the same when they realize that they’ve been speaking to a machine.  As superficial as the relationships might be when you are making a booking over the phone, they are still relationships.  When the person arrives for their meal, or their haircut, and they realise that person they spoke to before doesn’t really exist – that it has no conscious experience –  and they’ll feel empty.

They’ll feel kinda… duped…

Light at the end of the financial tunnel?

In March 2018 the government reached a significant economic milestone. It eliminated the deficit on its day-to-day budget. Tax revenues will exceed public spending. Public sector net debt will fall for the first time since 2001-02. It took eight years rather than five. But the primary target set by government in 2010, as the UK struggled to recover from the financial crisis, had finally been met.

The chancellor declared the nation was at a turning point in its recovery. He could see ‘light at the end of the tunnel’. Some commentators suggested the light might be an oncoming train, pointing out that economic forecasts rely on the government following through on ambitious plans for further spending cuts.

What does the economic evidence tell us?

We recently asked the National Institute for Economic and Social Research (NIESR) to help us understand if the upbeat economic message was justified.

They told us that if government is to achieve its ambitious target of a balanced budget by the middle of the next decade, public spending as a share of Gross Domestic Product (GDP) would need to fall to 36.6% in 2022-23. The post-war average is 39.3% of GDP.

Since 2010, significant savings have been made by transforming how government works, through commercial reforms and reducing the costs of major projects. However, the evidence is that public sector pay restraint and relatively low levels of public spending, rather than widespread productivity gains, explain the vast majority of deficit reduction.

What future do public services face?

We then asked NIESR to suggest how sustainable these savings might be. They told us government faces a daunting challenge. Why?

First, continued pay restraint is unlikely to have the same impact. The across-the-board 1% pay cap has already been lifted. And there are signs in health and education of recruitment and retention problems. Second, there are signs that low levels of public spending might be affecting the quality of public services. For example, the Institute for Government have noted a marked deterioration in key government targets for health and public safety. And third, most significantly, the pressure from further ageing of the population is gradually building. Significant extra resources will be needed to cover raising health and care costs and serve a larger number of pensioners.

NIESR used a series of scenarios to reveal the economic strain that government might experience over the next seven years. They warned that a public spending gap of up to £300bn could emerge, created by the cumulative impact of an ageing population and the cost of easing austerity.

Of course, it is possible that the economy will improve significantly, lifting tax revenues and providing an opportunity to increase public spending and reduce debt (the government still owe more than £1.6 trillion). But this cannot be counted on and it would be better to consider other options.

What options are open to government?

To meet this challenge, the government will need to embark on a transformation programme on a scale unprecedented in the post-war era. The combination of fiscal consolidation and rising expectations for service delivery represents both an opportunity and an imperative to radically redesign the services government provides to the public.

Government have already started digitising front-end interfaces, processes and workflows to improve cost efficiency and user experience. The next step is to reduce duplication of structures and resources between and within levels of government. And this requires a change of mindset – from government and industry. Rather than simply implementing bits and pieces of technologies on their own, there is a need for equally necessary organisational and service design changes. And this means joining up and trying to de-silo processes, creating new processes that do things once rather than many times.

In launching a new strategy for the government business last week, Sopra Steria commits to using our understanding of the public sector and emerging technologies to introduce a series of platforms for government, focussed on core government activities, which are standardised and repeatable. They will enable government to re-engineer, streamline and automate policy processes (including those enabling the UK’s exit from the EU).

Further information on the strategy launch and the NIESR research can be found on the Sopra Steria website. As always, I would be grateful for your thoughts and suggestions on how public services should be reformed.

Going waste-free

This weekend is Earth Day – a time to highlight global support for improving environmental sustainability and bring together millions of people, cities, and organisations across the world.  As part of the sustainability committee at Sopra Steria, part of my role is to raise awareness of initiatives amongst our employees, I am also thinking about the importance of individual action, including my own.

Going into 2018, the images I saw in Blue Planet 2 such as the albatross parents unwittingly feeding their chicks plastic, and the proliferation of media stories about the impact of plastics on the environment prompted me to think more about the waste that arises from my own lifestyle choices.

What does Zero Waste mean?
Zero Waste is as simple as it sounds: it’s all about trying to live without waste.  Everything we use should be reused or recycled or composted; nothing should go to landfill; ideally more and more of what we use will contain materials that have already been used before. Everything that we produced or consumed should be returned back to society or nature – so products are either reused, recycled or biodegrade.

In reality it’s not so simple.  Look around your supermarket and you’ll see thousands of products in packaging that cannot be recycled, everything from our food and drink, to cosmectics, to cleaning products comes in single use plastic and the challenge is how can we elimate this. .

How to get started

Arming myself with a list of all the places that stock zero packing products. I was ready for the challenge and started to plan how to adjust my lifestyle. I planned to reuse first, using my newly acquired home composting bin second, then recycling and finally sending non-recyclables to charity.

The first step was to eliminate all single use plastic. From the morning cup of coffee in the plastic-coated, non-recyclable cardboard cup, to the disposable cutlery used at lunch and the unnecessary food packing at supper, most of us have a lot of waste in our day-to-day life.  For instance buying a coffee daily is 30 cups and lids a month, all which end up in landfill,  and may take hundreds of years to decompose.  More importantly, it is 30 cups worth of materials that had to be mined, shipped to factories, manufactured,  and then shipped to my local Starbucks.  Thinking about the life of a coffee cup, from origin to where it ends up, its environmental impacts become clear and throwing a cup away every day seems unconscionable.  Suddenly, using a reusable mug seems like no-brainer.

Secondly, was composting all my food scraps.  I found that this step alone eliminated about 50% of my waste. Living in a second floor flat with no garden made this more of a challenge, I found a friend willing to take my scraps in their home compost heap which has made things much easier. But there are plenty of local councils who have composting services and there are lots of alternative options such as indoor womeries here.

The final stage was to address the longer use plastic items, buying cosmetics that come unpackaged (such as solid shampoo from Lush) and finding suppliers who will refill your cleaning product, eco companies such as Ecover are more than happy to refill existing bottles – find a local one here.

The results

By making a concerted effort to eliminate waste from my life, I have been able to reduce my waste footprint by about 90%.  The remaining 10% was made up of parcels covered in plastic, make up where there isn’t alternative packaging and longer use items such as headphones, tupparware that do break down eventually. The best result of this month-long experiment is the simply way it has enabled me to change my habits and make a difference.  It showed me that I can reduce my waste by a huge proportion, without requiring me to spend more money or make much more effort, and I have continued to live a low-waste life.

It is debatable whether it is possible to be truly zero-waste in modern society due to the complexity of our supply chains, but there are very easy ways to reduce the sheer amount that we as individuals get through.  What’s more, in the process, by changing the way we consume products – choosing products  with no packaging or recyclable packaging – we can have an influence the companies who sell them to us.

In any case, in sustainable living, it’s far more important to ensure we don’t make the perfect the enemy of the good.   I have put time into changing my routines to make how I live as sustainable as possible and have no intention of going back.   While I’m not going to stress if someone accidently puts a straw in a drink I order, I will continue to search for no-waste solutions to my everyday decisions.   If we all take small steps in our personal lives, and continue to campaign for companies and governments to affect larger change, we can make a difference.