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by: Robert.hillard
26  Sep  2017

Three things every project needs

It’s wrong to think that all a project needs is a scope, budget and timeframe. The three things that separate the best projects from the rest are: insight (into the future), simplification (of the business today) and inspiration (through new capabilities).

Even a cursory glance at the news shows how fast things are changing. The rate of change for business and government is greater than at any time in the working lives of the current generation of leaders. Disruption in some form is hitting everything from retail through to healthcare and it doesn’t seem to matter whether it is the private or public sector.

The improvement over recent decades in project and programme management capabilities mean that scope, budget and timeframes are now ingrained into almost every team. Most organisations have a portfolio of these projects from which you can deduce their ambitions for the year or few years ahead. Unfortunately in many cases, the sum of the parts isn’t as transformational as the changing times we live in really requires.

Organisations need to look again at their projects and make sure they move beyond scope, budget and timeframe to insight, simplification and inspiration.

1. Insight into the future
Any project that assumes that the context in which it is operating at commencement is the same as at implementation is doomed to be behind before it ever sees the light of day. Even three months in today’s business world is enough time for fundamental changes in the relationship with suppliers, competitive landscape, customer expectations and the working environment.

Too many project teams make the assumption that what is true now, or even in the immediate future, is true forever. They also underestimate their project’s ongoing impact on the organisation way into the future.

It is hard to make predictions for the business and technology environment a decade or more out. Projects should, however, at least identify different scenarios, some of which will be uncomfortable. Scenarios, and their impacts, allow those that follow to make sense of the portfolio of projects and better build out a transformation narrative.

For example: urban infrastructure projects can describe a smart cities future; retail fitout projects should navigate the plethora of predictions on changing customer behaviour and supply chain system projects need to anticipate radical new business platforms that remove whole layers from the business architecture.

Some changes are nearly universally anticipated and should form part of every scenario such as greater workforce automation, improved technology infrastructure and greater government regulation of digital markets.

2. Simplification of the business today
Complexity is the enemy of agility and in times of change, agility is critical. It is amazing that so many executives and boards lament the opportunity of their lean, startup, competitors who don’t have the legacy that they have to deal with. This is not just technology but also long-defunct products, outdated business processes and expensive infrastructure.

Established businesses should have an advantage over their startup rivals, they have market knowledge, infrastructure and large amounts of data. To be ready to adapt they also need to have a constant focus on simplification.

It would be great to do a one-off spring clean of our organisations, the reality is that this is too hard and unlikely to get the sustained focus that it needs except in a crisis and by then it’s too late. The best approach is to make simplification the goal of every project.

Where today we usually measure a project’s success by time, budget and scope, we should add the total enterprise complexity as well. Of course many projects will have to add to the complexity of the part of the business where they operate, but that doesn’t mean that a completely different part of the organisation can’t be the target of offsetting simplification.

3. Inspiration through new capabilities
Finally, every project needs to be delivering something new. Business is increasingly looking to somehow change their relationship with customers, find new ways of connecting suppliers and customers and engage better with their staff. Understanding the strategic goal of the new and how it fits with a wider business goal is critical.

Projects that seek to simply adapt to the future (such as future of work, future of cities or future of transport) lack the focus to motivate teams. Projects that only streamline and simplify the organisation (such as a new enterprise operational system) lack the inspiration to excite and maintain the motivation of teams. People often gravitate to projects that have something completely new as part of their scope, even when it may not be a major component.

Every project is an opportunity to experiment, whether it be with new business platforms, new technology or new ways of working. While not every project is a transformation, many transformations are incomplete through a lack of a something that makes stakeholders go “wow”. It is a good idea to include an element in every project that gets the heart racing in the midst of even the most benign of changes.

There is much to be done
The years in front of us require organisations to take on huge amounts of change. It is oft quoted that organisational lifespans are getting shorter. I don’t accept this, I think that mergers and acquisitions account for many of the movements as the best businesses find alignments and synergies that add value to shareholders, customers and suppliers. However, there is no doubt that those organisations that don’t take ownership of transformation find themselves a victim of it.

There is so much that every organisation can do to create value through transformation for their stakeholders. Just delivering a vision of the future, improving today’s business process or adding new functionality over the top of existing processes is incomplete. It is only by harmonising all three that genuine and sustainable change is possible.

Category: Enterprise2.0
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by: Robert.hillard
27  Aug  2017

Your desk is a guide to the future of work

The future of work is the topic on everyone’s lips. The talk of automation and artificial intelligence can seem really abstract and alien, making the future seem scarier than really needs to be the case. A good way for white collar workers to think about what lies ahead is by looking at their office surroundings and how those might change in the coming years.

Anyone worried about what work might look like in the coming decades should remember a worker of the 1970s would feel like a fish out of water if they were magically transported to today. The desk of a white collar, clerical, worker would likely have had “in” and “out” trays, stationary and a phone (an extension of a central number). By the 1980s, they may have had their own direct phone number and possibly, depending on their job, access to a computer terminal for very basic tasks. Reports were manually typed, with large offices and senior staff having access to typists who would convert their handwritten notes into neat reports. Rows of those typists were exacting workers who had to mix speed with accuracy and were the ultimate slaves to their desks.

The desk of the turn of the century was very different. The trays were rapidly disappearing. Every desk had a personal computer with a graphical interface and the tethered phone was giving way to IP telephony allowing hot desking to make an appearance. The basic mobile phones and dial-up networking that most workers had at home meant that working remotely was becoming possible, if not practical, for many tasks. Working from home was still called “teleworking” referring to the use of the telephone as the predominant infrastructure.

Ten years later, the desk didn’t look very different, just a little more efficient. Internet connections were faster but the equipment was fundamentally the same. Although smart phones were starting to appear, they weren’t ubiquitous and the functions to which they were applied were basic.

Today the desk is starting to change in much more fundamental ways, but the transformation is no more dramatic than the changes that we’ve gone through in the relatively recent past.

Our desk is finally less bound by paper with some evidence that the US, at least, is seeing a reduction in its use as the form factor of tablets is encouraging less paper (having said that, at about 10,000 sheets of paper per worker per year it is still very high). Our technology is also moving from being a passive tool of efficiency to an active driver of activity.

The balance of power may also have turned. Equipment on our desks are starting to monitor the work being done and the worker themselves. Testing whether the white-collar worker is being productive or, when working remotely, whether they are being active at their desk. This is a form of working for the machine rather than the machines working for us and is likely to be the subject of debate in years to come.

Even more dramatic than simply detecting whether the worker is active, the equipment of our desk is increasingly able to allocate tasks between workers. While every good leader argues that we should measure outcomes and outputs rather than effort, a world where workers can be remote and be paid by output can lead to problems.

When there is a break between the supervisor and the supervised, the nature of competition means the rate individuals get paid often gets pushed down. We are already seeing this effect in the so-called “gig economy”. It is likely that governments will need to step in to protect workers, particularly in fields where there is substantial competition.

If understanding the desk of the future is important, what will be surrounding our workspace in the coming decade? For the first time in a long time, the form factor of the devices on that desk are far from “one size fits all”. The single hinge notebook has given way to all forms of tablets. The desk phone is gone and the fax is long gone. It even seems that voice control is finally finding form in technology dubbed “beyond glass” but also challenging the fully open plan office.

Electronic communications are also rapidly changing. Social networks are merging with messaging services and we are just starting to move past email. It is very likely that more structure will be added to the interactions we have through our work activities, probably driven by our artificial intelligence co-workers.

The future of work is uncertain, but not such a radical shift from what we do today. There are risks that we need to navigate but using history as a guide we should be able to manage the transition without a single change on its own tipping over too many desks at once.

Category: Enterprise2.0
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by: Robert.hillard
30  Jul  2017

Defence as the best form of attack

The global economy is powered by business innovation with small and large organisations alike inventing the future for us all. The rapid rate of change brings both opportunities and threats with recent cyber events acting as a wake-up call. Far from being afraid, we should be reminded that we need to design businesses to operate and even thrive in unexpected circumstances.

In the 1970s, companies like Toyota revolutionised manufacturing with “just in time” supply chains. Nothing ever comes for free, for every dollar of stock taken out of the system there is a dollar of contingency and slack also removed. When everything works well, there isn’t a problem, when it doesn’t the flow-on effects can create a supply chain whiplash or bullwhip effect. The best manufacturers in the world solved this by putting enormous pressure on quality to avoid exactly these sort of disruptions.

These are lessons we need to learn as we look to roll out more sophisticated systems in our society such as connected infrastructure and transport and even make the move to autonomous systems. Our society in a few short years is likely to be orders of magnitude more connected through complex networks and supply chains.

Computing generally follows real world models in its first iterations, and its mirroring of best practice supply chains is no exception. Moving from a world where each system was independent to one where they are tightly coupled across corporate boundaries has seen a data supply chain that lends heavily from manufacturers. The addition of cloud computing means that almost every process involves at least two and often more players linked together through a multitude of interdependencies.

This trend is as prevalent in our digitally enabled infrastructure (such as support for our rail networks and energy grids) as it is in digital-only systems (such as banking, telecommunications and government systems). The tighter those linkages the more functions that can be added and the lower the overall cost.

As amazing as the capabilities of our world of technology is, the integration leaves us with almost no room for error or ability to flex in an environment of disruption. For example, our energy grids seem to be becoming more brittle with the rise of interconnections and regular travellers know the impact of airlines operating without slack when something goes wrong.

Like the manufacturing supply chains of the last half century, the key to keeping this technology running is quality with CIOs aiming to keep systems up 24/7. Even small outages, though, have a flow-on effect that is harder to predict and further reaching than the equivalent disruption in a manufacturing process. That’s because the complexity of these system interdependencies has grown exponentially.

The brittle and inflexible nature of complex systems have been one of the reasons that retail has struggled to adjust to the juggernaut of online shopping and manufacturers are still trying to get control of their supply chains back. Recent cyber-attacks, leaving major companies offline, have brought this into stark focus. The attacks have typically encrypted or hijacked one or two systems in the network and brought a brittle environment to breaking point.

The architects of systems and processes tend to design for today’s business. Defensive computing is a paradigm for boxing components in such a way that they work regardless of what happens. This is a mindset that goes beyond testing for the scenarios outlined by stakeholders and moves to safe failovers in the event of anything unexpected.

Defensive measures include having systems work while offline or while counterpart systems are unavailable and when reference data is corrupted or hijacked. If technologists adopt a more defensive mindset, the testing burden is dramatically reduced and the uses of their systems can be extended far beyond the context of their initial design.

Where tightly-coupled systems are brittle, those that have been defensively architected are like flexible buildings that can withstand the buffeting winds of cyber-attacks and the shifting sands of changing business models.

Defensive design requires more expansive thinking about the worst-case scenario for every module. Data should backed-up incrementally and then be thoroughly validated. Connected systems should be assumed to provide completely unexpected and illegitimate responses. Users can be expected to approach every interaction with an almost destructive mindset.

Every part of a system should be independently robust and proactively test that every interaction is valid, rather than only checking for known invalid responses. The more modular and API-driven such a solution is, the more likely it is to be flexible and robust enough to survive cyber-attack as well as business disruption through combination with new applications.

Our infrastructure is never going to be impregnable. Even the strongest perimeter barriers can be breached by one innocent user clicking on the wrong link. Similarly, our business models aren’t invulnerable. The answer is to have each component of the information supply chain designed in a defensive way such that it assumes the worst of even trusted systems, users and competitors.

Businesses building for the worst case, planning to run even when seriously compromised, will find that they more easily weather cyber issues and competitive disruption. Neither should ever come as a surprise.

Category: Enterprise2.0, Web2.0
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by: Robert.hillard
24  Jun  2017

More but not better jobs

The future of work is the topic on everyone’s lips. We’ve gone from worrying about whether our children will have jobs to worrying about our own place in the workforce. The rise of artificial intelligence and robotics has been at the upper end of twenty first century predictions.

Everyone wants to know whether automation will trigger a massive cut in jobs. This is not academic. Previous predictions that automation would hit employment in the 1970s and 1980s led some countries such as France to move to shorter working weeks and effectively ration available work. The consequences have been large with lost productivity and languishing economic performance which, in turn, has created the very unemployment they were trying to avoid.

The automation of human labour is not new. The development of cotton mills in the industrial revolution and Henry Ford’s production line of the early twentieth century are perfect examples. Both reduced the labour required per unit of production but increased demand caused a net increase in jobs.

The Luddites in the early days of the nineteenth century worried about the impact of automaton and showed their opposition by smashing machines. No lesser technologist than Bill Gates recently said “Right now if a human worker does, you know, $50,000 worth of work in a factory, that income is taxed. If a robot comes in to do the same thing, you’d think that we’d tax the robot at a similar level”. We can interpret his comments as a proposed brake on machines through taxation, a modern equivalent to the machine smashing of the Luddites.

The rise of artificial intelligence is just a continuation of computer-driven automation since the 1970s. We have seen many jobs displaced in that time, yet more work has been created. Word processing has displaced the typing pool. Workflow processing has all but eliminated traditional clerical roles. Yet there are more jobs today than ever before. At about this point many people say “more and better” jobs. It is the latter half, “better” that needs closer examination.

Our jobs can increasingly be described in terms of whether we’re working “on”, “with” or “for” machines.

Those of us who work “on” machines are shaping what they do, we are defining the problems they solve and identifying the questions that need answers. Examples of working “on” the machines include programming, design and data science. These are activities that require an insight that is not within the scope of this second generation of artificial intelligence (see Your insight might protect your job). I would argue that there are the same or slightly more of these jobs than in the past and that the jobs are, largely, as good as ever.

The jobs that work “with” the machines are giving many of their day-to-day repetitive activities to artificial intelligence and traditional technology. Teachers are increasingly handing over much of the content creation and learning interaction to technology and students are largely responding well. This is true at all levels of schooling, from pre-school to university. Teachers are, though, more important than ever, for example see Universities disrupted but not displaced.

Finally, the largest pool of increased employment is working “for” the machines. These are the jobs that are scheduled and managed by technology. At the extreme are the “Mechanical Turks” and other crowd workers who do piecework for a few cents a job. Also in this category are rideshare drivers, online retailing pickers and increasingly some of the more manual health roles. Done well, these jobs can fit into a flexible working arrangement that suits many lifestyles.

To put this third category of jobs into perspective, consider what actually happened with the early nineteenth century cotton mills and then again with the early twentieth century production lines. Far from destroying jobs, more labour than ever before was needed. But as anyone who has watched a period drama or read a Dickensian novel knows, these were not pleasant places to work. Workers were regularly injured or killed, rights were almost non-existent and worker was played-off against worker.

The future of work could see more of these jobs that work “for” machines created with the emphasis on dehumanising and optimising scheduling to suit the needs of technology and employers. Working remotely, or largely instructed by computer, it’s possible that we’ll repeat the mistakes of the past.

But history also gives us reason for optimism. Within a few decades the cotton mills and production lines became much more desirable places to spend a working day. In our far more competitive world, many companies are realising that there is a commercial advantage to eliminating the several decades gap between creating new job and making them desirable. Those companies are winning the war for talent.

At the end of the day, business production of goods and services is for the consumption of humans. The modern services economy means customers are interacting with workers more than ever, and want it to be a social and positive experience. Even the production of goods is increasingly social with the rise of shorter supply chains and a booming “craft” movement of artisan products ranging from food to furniture. Businesses that want to win in this world need employees who are going to portray their brand in a good light and for that their day-to-day work needs to be life affirming.

With a focus on the right things, there is an opportunity for the automation of the coming years to lead to both more and better jobs.

Category: Enterprise2.0, Web2.0
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by: Robert.hillard
27  May  2017

Information age delivers new space race

At the height of the race for the moon, everyone imagined that by now we would be living in a space age. Instead we got the information age which has given us access to unparalleled global connections and almost the sum of human knowledge at our fingertips. Stanley Kubrick’s “2001: A Space Odyssey” assumed the information revolution would happen alongside the move into space, in fact it seems they had to be sequential. Despite a many decade hiatus, space is back in vogue and the connections to the technology industry are intimate.

In the 1960s, the Cold War spurred the US to race to the moon in the largest peacetime project in history. The hangover from the massive drain on the budget (where up to 400,000 Americans were employed by the programme through NASA or its contractors and many times that indirectly) actually delayed space development through the next fifty years. Today, it is well recognised that the massive investment in technology had huge spinoff benefits, and being a peacetime project it didn’t come with the truly horrible consequences of wartime investments in technology.

As exciting as the robot explorers of the solar system are, the future of our species is inspired by our own travels. With the aging Russian Soyuz capsules as the main working space vehicles for human travel it is time for a new generation to enter the race. The increasingly sophisticated, autonomous, systems that have powered the exploration of the solar system have, however, been both beneficiaries of and contributors to our Earth-bound robotic technologies. Far from relying on manual intervention, it is now possible for unbelievably complex decisions to be made without human intervention by machines that are too far from home to get human help.

It isn’t a coincidence that big names such as Elon Musk and Jeff Bezos are behind the new space age. There are still quick riches to be made from connecting people on the Internet in new ways, but real wealth is created from fundamental shifts. Musk is betting on infrastructure and Bezos on supply chains. Both need new innovations and inventions to achieve their commercial aims and support Tesla and Amazon respectively. Both companies are priced by investors on potential rather than profit and risk a collapse of their value if future inventions don’t continue their apparently endless expansions.

In an era of digitisation of the physical world, it’s hard to say “it’s not rocket science”, because it is! To make our world work better, millions (and eventually billions) of devices have to be integrated. The technology required to safely launch humans and successfully reuse some of the equipment takes this requirement to extremes. Batteries, fuels, guidance systems and sensors are just the start of a tightly integrated network which has to operate together to take a vehicle into space and return it safely to Earth. With Earth’s orbit becoming increasingly crowded with active equipment, and inactive junk, smart traffic management is going to make the race for autonomous vehicles look like child’s play!

The beneficiaries of the technologies of the new space industry will include the energy grid, electric vehicles, autonomous transport, medical life support and propulsion for air travel, to name just a few that we can imagine today. The technologies that will spin out of investment in a new generation of space activity will be just as disruptive to today’s business models as the recent explosion of new, technology-fuelled, platforms.

The information age has removed many inefficiencies in the distribution of existing resources. The shift of many economies from production to services reflects the huge waste that was occurring in the use of infrastructure and goods. The ongoing focus on financial services, telecommunications and other services sectors, leveraging disruptive information technologies, suggests that there is still much further to go. However, no matter how you look at it, the information age is not adding to the sum of resources for humanity to draw on.

Turning our information age into a space revolution is different. Far from just reallocating what we have today, it promises access to minerals from extra-terrestrial ore bodies and super-efficient farm production to name just a couple of opportunities to add to the sum of resources available to humanity.

Just as investors have gotten their heads around the transformation of existing business models to disruptive platforms, we are all going to have to think about business and government differently all over again. The ability to think about every aspect of what we do through the use of disruptive technology will serve us well in the years ahead. Just when we thought we might see some stability in how we do business, it is clear that the changes have barely begun.

Category: Information Development
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by: Robert.hillard
28  Mar  2017

Post-truth surprises

Unexpected election results around the world have given the media the chance to talk about their favourite topic: themselves! With their experience running polls, the media are very good at predicting the winner out of two established parties or candidates but are periodically blindsided by outsiders or choices that break with convention. In most cases, there were plenty of warnings but it takes hindsight to make experts of us all.

Surprises are coming as thick and fast in business as they are in politics and similarly there are just as many who get them right with perfect hindsight! The same polling and data issues apply to navigating the economy as they do to predicting electoral trends.

The Oxford Dictionary picked “post-truth” as their 2016 word of the year. The term refers to the selective use of facts to support a particular view of the world or narrative. Many are arguing that the surprises we are seeing today are unique to the era we live in. The reality is that the selective use of data has long been a problem, but the information age makes it more common than ever before.

For evidence that poor use of data has led to past surprises, it worth going way back to 1936 when a prominent US publication called The Literary Digest invested in arguably the largest poll of the time. The Literary Digest used their huge sample of more than two million voters to predict the Republican challenger would easily beat the incumbent, President Roosevelt. After Roosevelt won convincingly, The Literary Digest’s demise came shortly thereafter.

As humans, we look for patterns, but are guilty of spotting patterns first in data that validates what we already know. This is “confirmation bias” where we overemphasise a select few facts. In the case of political polls, the individuals or questions picked often reinforces a set of assumptions by those who are doing the polling.

This is as true within organisations as it is in the public arena. Information overload means that we have to filter much more than ever before. With Big Data, we are filtering using algorithms that increasingly depend on Artificial Intelligence (AI).

AI needs to be trained (another word for programming without programmers) on datasets that are chosen by us, leaving open exactly the same confirmation bias issues that have led the media astray. AI can’t make a “cognitive leap” to look beyond the world that the data it was trained on describes (see Your insight might protect your job).

This is a huge business opportunity. Far from seeing an explosion of “earn while you sleep” business models, there is more demand than ever for services that include more human intervention. Amazon Mechanical Turk is one such example where tasks such as categorising photos are farmed out to an army of contractors. Of course, working for the machines in this sort of model is also a path to low paid work, hardly the future that we would hope for the next generation.

The real opportunity in Big Data, even with its automated filtering, is the training and development of a new breed of professionals who will curate the data used to train the AI. Only humans can identify the surprises as they emerge and challenge the choice of data used for analysis.

Information overload is tempting organisations to filter available data, only to be blindsided by sudden moves in sales, inventory or costs. With hindsight, most of these surprises should have been predicted. More and more organisations are challenging the post-truth habits that many professionals have fallen into, broadening the data they look at, changing the business narratives and creating new opportunities as a result.

At the time of writing, automated search engines are under threat of a ban by advertisers sick of their promotions sitting alongside objectionable content. At the turn of the century human curated search lost out in the battle with automation, but the war may not be over yet. As the might of advertising revenue finds voice, demanding something better than automated algorithms can provide, it may be that earlier models may emerge again.

It is possible that the future is more human curation and less automation.

Category: Business Intelligence, Enterprise2.0, Information Governance
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by: Robert.hillard
25  Feb  2017

Moonshots

In business, we tend to focus on the incremental changes we are dealing with every day. The big opportunities always seem too far away to build into our monthly, quarterly or even annual plans. These opportunities, though, are the “moonshots” that completely change the world and generate growth for years to come.

The big changes can come from unexpected places. There are, however, themes that help all of us to be ready to jump-to and lend a hand when we see answers to the biggest questions our generation needs to answer. At the right time, these changes are opportunities we need to be ready to grab.

Google coined the term “moonshots” to describe big, imaginative, investments that were of significant scale and potential impact. Most famously, perhaps, they took on autonomous vehicles before they were popularly regarded as seriously disruptive. I really like the term because it describes both ambition at a global level and tackling things at the edge of our abilities.

I would argue that the moonshots of our time tackle at least one, and often more, of the major challenges of the twenty-first century: environment, living space, energy, resources and health. The danger of the current focus on the information and digital economy is the tendency towards small incremental gains which just aren’t going to cut it in a world that is going to be dramatically different in forty years. That doesn’t mean that our view of innovation today is bad, but there is not enough focus on these major challenges as opposed to incremental gains on what we already do well today (see Where is the digital-fuelled growth?).

The twentieth century’s growth in population (nearly quadrupling to more than 6 billion) and industrialisation of the twentieth century has been both caused by and a cause of our huge lift in economic growth and living standards. At the same time, it has created an undeniable strain on our environment for which transformative technologies can make a huge difference. Technologies scrubbing carbon, cleaning particle pollution, protecting species are almost guaranteed to be developed but they won’t get mass appeal unless the information economy takes the lead to find pathways to market, profitable funding models and integration of what are likely to be disparate solutions.

The same growth in population and urbanisation has put an enormous strain on our cities. As governments struggle with affordable housing, there are few miraculous ways of creating more land near the city centres where a large portion of the population works. While working from home is now a viable part of many a commuter’s week, it is only a stop gap for the social activity of work. The real moonshot here will be to make commuting from a much wider geographic area possible through revolutionary transport technology. As Uber has shown, joining the dots on transport can accelerate the viability of different vehicle options.

Energy security and cost is at the forefront of the minds of many as the race for a low carbon future collides with disasters like Fukushima, gaps in renewable technologies and monumental spending requirements on grid infrastructure. Where there is a great need (cheap energy is a economic growth opportunity) and material friction (unaffordable and inadequate technology) there is a moonshot opportunity.

Even solving the energy gap will not solve the inevitable crunch on many of our planet’s resources. Global supply chains have enabled tremendous gains in economic efficiency, but at the cost of resources (with each stage often adding a layer of wastage). Advanced manufacturing, urban food production and other technologies that shorten supply chains are likely to be in high demand. While many of us who grew-up with the promise of space travel would love it to be a solution to living space constraints, it is far more likely that our century’s space moonshots will be geared towards mineral riches from our near solar neighbours.

Finally, most health moonshots concentrate on new technologies to solve the remaining killers. The opportunity that is often missed is to dramatically reduce the cost of maintaining our overall health. Societies around the world are dealing with healthcare costs that are blowing-out, while recognising the inherent inefficiencies of our current health bureaucracies. Digital solutions that turn the problem on its head could potentially save more lives worldwide than almost any new drug.

We’ve seen moonshots in past centuries bring us efficient transport, industrialisation, modern medicine and, of course, the first footsteps on the moon! While we face many challenges in this century, I believe there are more reasons to be an optimist than a pessimist as long as we are prepared to take-on exciting new moonshot opportunities.

Category: Enterprise2.0
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by: Robert.hillard
28  Jan  2017

Measuring transformation

We live in times of rapid change when businesses that assume they have a secure market are suddenly having their world turned upside down.  With the most substantive impact coming from technology, many have assumed that large investments in IT and digital would act as a protection.  In fact, many of the businesses who have made the largest investments, such as some retailers, are actually the ones experiencing the greatest disruption to their operations.

It is hard to describe disruption in a meaningful way, but I like Jack Welch’s famous quote “if the rate of change on the outside exceeds the rate of change on the inside, the end is near”.  A disruption index can be described in terms of the ratio of the external and internal rates of change.  But, how do you measure change and the transformation within your organisation (the numerator and denominator of this ratio)?

When I was putting the finishing touches on Information-Driven Business, I had the opportunity to share an editor with Douglas W. Hubbard who wrote How to measure anything.  This book is a wonderful reminder that the only limit to putting a numerical value on any business problem is our imagination!  Whenever someone argues that their change, driven by transformation, is too hard to measure, I’m reminded of this book.

Not only do I think that the change associated with any transformation can be measured, I also think that the first measure you think of is unlikely to be the best.  For example, customer-service focused transformations often default to net promoter score as the main measure while overhead-driven transformations frequently rely on measuring the cost or headcount taken out of the business.

These are good measures, and should play a role, but they aren’t great denominators for the disruption ratio.  What we really need to measure is sustainable strategic change in an environment where the very nature of corporate strategy is changing.  On the one hand, top-down one-off strategy work is making way for ongoing experimentation combined with a small number of “crossing the Rubicon” moments.  On the other hand, too little focus on the Rubicon leads to worrying about horse carcasses in growing cities, something I discussed when I wrote about the difficulty of seeing past today’s problems.

Customer transformations that rely too heavily, for example, on net promoter score, lend themselves to disruption by a better offer.  I’ve seen numerous organisations get customer feedback after each interaction only to find it a poor correlation to customer churn.  The issues are many, but can include a metric-driven incentive for customer service agents to provide exactly what the customer wants to hear but without any realism that it can actually be delivered.

When we talk about customer loyalty, that really means a build-up of value.  Really thinking about this could result in some form of balance sheet recognition.  Each time there is a genuine discount to the market, a real solution to a meaningful problem or a deeply insightful interaction there is value.  Similarly, the balance sheet value of employee-generated IP is as much a meaningful measure of employee satisfaction and inventiveness as any engagement score or innovation survey.

A great resource which combines employee and customer engagement is Zeynep Ton’s work on The Good Jobs Strategy.  Ton’s research very nicely identifies the relationship between the cost of staff, investment in their capability and the loyalty of customers.  From here can come an approach to measuring a sustainable transformation.

Like many researchers, Ton has identified that transformation is as much about what you take away as what you add.  Simply targeting the creation and launch of new products ultimately destroys organisational agility and adds complexity which stymies both customer service and future innovation.  Radical decommissioning is one approach, but another is to measure complexity and target its gradual reduction as I’ve previously suggested by Trading your way to IT simplicity.

Regardless of whether it is customer service, supply chain, human resources, costs or products that you are trying to transform, the challenges are similar.  While the strategic goals might be easy to describe, the real work happens when you try to design measures.  Rather than setting once and assuming the measure is right, constant experimentation and confirmation is essential.

The attribute of a great transformation measure is that it doesn’t just correlate with the outcome you want, it is intrinsic to it.  Given the complexity of changing a business, it is very likely that these outcomes will be complex and the measures you need equally sophisticated.

Category: Enterprise2.0, Web2.0
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by: Robert.hillard
23  Dec  2016

Who do you love?

An alien relying on TV for their knowledge of humanity might watch a few ads and assume our closest emotional relationships are with banks, utilities and retailers. After all, they all claim to be your best friend, look how many ads talk about “falling in love” with your service provider!

It is popular to talk about the relationship between customers and the businesses that serve them. Banks, airlines and utilities all seek to be best friends with their customers. This is probably understandable given that most of us are passionate about the businesses we work for and we want our customers to be as well.

In building such a relationship, marketers can point to great examples such as airline loyalty schemes, social media and even the account balance page of internet banking sites,. In each case, there are individuals who interact daily, even hourly, with these services and look forward to each touchpoint.

Such a strong relationship is hard for most businesses to maintain with the majority of their customers. After all, most people don’t get excited looking-up their electricity prices, mortgage rate or recent phone numbers they’ve called.

The common attribute of the businesses we care about seems to be the information they provide. Many people can’t imagine why they would care deeply about a bank, yet a small number of people check their bank account balances multiple times in a day. Anecdotally, those repeat checkers are dreaming of a saving goal which provides a halo effect for the bank.

Similarly, many travellers love to track their frequent flyer status which they see as a reward in its own right. The airlines create portals that engage their premium passengers and offer a regular sense of progress and engagement.

Uber has a fascinating screen on its app showing all the cars circling locally while eBay has nailed the search for a bargain. Some fintechs are attracting customers by creating a “fiddle factor”, letting them earn small rewards in different ways.

At the same time, it doesn’t seem that people care too much whether they love their basic services. Most people just want their savings to be safe, their lights to stay on and their phones to ring. The only problem is that in an environment where they can change providers easily, this lack of loyalty means that they are more likely to make a switch.

How can a brand that provides a capability that people need, but lacks passion, align with a brand that everyone cares about? This is the power of the API economy where it is easy for businesses to partner seamlessly.

Banks and airlines were pioneers in partnering, bringing together credit cards and air miles. Similarly, phone companies are partnering with music and movie streamers to dramatically increase engagement with their services. In coming years we can expect to see social media, fashion brands and travel businesses join with the everyday services that meet our basic needs.

To be successful, partners need to make sure they understand what elicits a strong affinity. To-date, brands have largely taken the same approach for all customers. For example, “daily-deal” style retailers are highly attractive to some customers and highly annoying to others. Basic services, such as insurance, who choose to partner with businesses like these need to be very targeted, otherwise they risk alienating as many customers as they delight. Too many marketers have made this mistake and have potentially damaged their brands.

The key to a meaningful relationship is tailoring the partnerships to offer the customer something they genuinely want to engage with. Talking to their customer community and offering them choice is a very good start, giving the winners in the race to pair more opportunities to generate genuine friendship, if not love!

Category: Enterprise Data Management, Enterprise2.0, Web2.0
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by: Robert.hillard
26  Nov  2016

Serendipity

Information overload is as much an overwhelming feeling as it is a measurable reality. We often feel an impossible obligation to be across everything, which leaves us wanting to give up and absorb nothing that hits our various screens. Despite all this, the good news is that the majority of the information we need seems to appear just in time.

Where does that leave those of us who are control freaks? I am not comfortable to know that the right information will find me the majority of the time. I want to know that the information I need is guaranteed to find me every time!

The trouble is, guarantees are expensive. This is related to the debate between search based big data solutions and enterprise data warehouses. Google provides a “near enough” search solution that, given the massive amount of data it trawls through, usually seems to find what we need. Knowledge and business intelligence solutions provide the predictable information flows but come at a huge cost.

Of course, the real sense of serendipity comes when information arrives unsought just when we need it. It can come through the right article being highlighted in a social media feed, a corporate policy being forwarded or the right coffee conversation with a colleague. Of course, serendipity isn’t random coincidence and there is much we can do to improve the odds of it happening when we need it most.

Before doing so, it is important to know what things have to be predictable and reliable. A list is likely to include financial reports, approvals and other controls. What’s more, a scan of any email inbox is likely to show a significant number of messages that need to be read and often actioned. Despite its tyranny on our working lives, email works too well!

Serendipity depends on the quality of our networks, both in terms of who we know and the amount of activity the passes between the nodes. A good way to understand the power of relationships in an information or social network is through the theory of “small worlds” (see chapter 5 of my book Information-Driven Business).

Ironically, in an era when people talk about electronic isolation, social networks, that is who we know, are more important than ever. Serendipity relies on people who we know, at least vaguely, promoting content in a way that we are likely to see.

Just as control freaks worry about relying on serendipity, those that are more relaxed run the risk of relying too much on information finding its way mysteriously to them at the right time. Those that don’t understand why it works, won’t understand when it won’t work.

Far from making experts and consultants redundant, this increasing trend towards having the right information available when it’s needed is making them more necessary than ever before. The skill experts bring is more than information synthesis, something that artificial intelligence is increasingly good at doing and will become even better at in the near future. The job of experts is to find connections that don’t exist on paper, the cognitive leaps that artificial intelligence can’t achieve (see Your insight might just save your job).

The first thing is to be active posting updates. Networks operate through quid quo pro, in the long-term we get back as much as we give. In the office, we call this gossip. Too much gossip and it just becomes noise but the right amount and you have an effective social network. Those people who only ever silently absorb information from their colleagues quickly become irrelevant to their social circle and gradually get excluded.

The second is to be constantly curious, like a bowerbird searching and collecting shiny pieces of information, without necessarily knowing how they will all fit together. The great thing about our modern systems is that massive amounts of tagged content is easy to search in weeks, months and years to come.

Finally, have some sort of framework or process for handling information exchange and picking a channel based on: criticality (in which case email is still likely to be the best medium), urgency (which favours various forms of messaging for brief exchanges), targeted broadcast (which favours posts explicitly highlighted/copied to individuals) or general information exchange (which favours general posts with curated social networks). Today, this is very much up to each individual to develop for themselves, but we can expect it to be part of the curriculum of future generations of children.

No matter how often it seems to happen, almost by magic, information serendipity is no accident and shouldn’t be left to chance.

Category: Enterprise Content Management, Enterprise Data Management, Enterprise Search, Enterprise2.0, Information Strategy, Information Value
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