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 protect 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.

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Framing new ideas

It often feels like every idea has its time. Be it workplace trends, new technologies or social changes. With the benefit of hindsight, we can’t imagine why these things took so long. Yet, when a good idea’s time hasn’t yet come, it is incredibly hard to get innovations off the ground in business or government anywhere in the world.

Equality for everyone in the workplace seems so obvious it is outrageous that it took so long (and unacceptable that it is still an issue in so many areas, but that is a separate topic). Workplace safety was once almost ignored but is now simply the norm. The idea of telecommuting was controversial but now most professionals take it granted for at least some of their job. Yet before all three of these changes became mainstream they seemed just as compelling but too hard to make into reality.

Humans are social animals and we like to move in a herd. As much as we laud pioneers, we are seldom comfortable being too far out in front. So where does that leave all of us who are trying to create change and enable transformation in business?

That change is necessary must be obvious to anyone who looks at the poor rate of productivity growth over many years and the graveyard of businesses that just haven’t spotted disruption in their sectors. How do we bring forward the “time” for every idea rather than wait?

New ideas don’t just happen because they are logical. The herd has to provide leaders with a sense of protection and the people who follow have to be more than vocally supportive, they have to move with them. Leveraging our social instincts we can give people confidence to try new things, such as new technologies, by either moving the herd or creating a paddock where it feels like the herd is already headed.

The latter requires a level of creativity. The sense that the herd is moving when they may only be just starting to break. This requires those who seek to introduce something new to “frame the market”. It creates certainty (continuing the paddock metaphor, it is describing to the herd where the fences are).

Many proponents of new technologies and solutions are amazed that their proposals aren’t immediately adopted. This is as true today with technologies such as robotic process automation and social media at work as it was with email and graphical user interfaces in the 1980s and early 1990s. I remember having a debate in one organisation I worked with about whether staff should have access to the internet at all, a laughable proposition now but a very real concern to the leaders at the time. What swayed them was when their peers in comparable organisations allowed their staff access (they could take comfort in being part of the herd).

Business transformation, combining technology and organisational change is about as big as any change that we need to tackle and brings in new organisational models. Anyone seeking to introduce automation, streamlining and simplification needs to make the case that these are mainstream concepts. Vendors looking to sell these capabilities should consider moving away from claiming their wares are unique to putting them in the context of a wider market that is already there.

It is the dream of everyone who operates in a competitive marketplace to be the owner of a monopoly franchise. Putting aside the fact that a lack of competition makes us lazy, the evidence is that buyers avoid buying at all if they don’t have some sort of choice.

Even the solutions who appear for a time to be in a category of one (such as Windows or Facebook) have grown as a result of being part of a market. Uber needs Lyft, Windows needed the Mac and Facebook was possible because of Myspace.

We see this today in a range of technologies that could accelerate productivity but are struggling to gain traction. Each has vendors who claim to have a monopoly on a specific component and a market that is very hard to frame. Gartner talk in terms of their “hype cycle” where, at the peak of the hype, the innovations has been shown to have some sort of value. However, at that peak it is hard for users to make a comparison and the market is left to a few early adopters.

What this means for those of us trying to create change is that if we want organisations to adopt new ways of working, new technologies and new approaches to skills we need to frame the market and collaborate with our competitors to create a larger opportunity.

Collaboration between competitors can take the form of common standards, methods or even just the adoption of similar language to enable organisations to make meaningful comparisons. After all, we now expect to go into supermarkets and see the price per unit of weight and nutritional information in a form where we can make a reasonable comparison between competing products. The same should be true of more complex products and services used by organisations.

When ideas are new, collaboration can create larger and more competitive markets which benefits everyone.

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Robots will make better negotiators

Negotiation is one of the oldest human activities and is an important part of our economy.  It is essential for sharing resources between people and groups.  However, as our organisations have become more complex, the outcomes that we are achieving are getting worse not better.

The usual objective of negotiation is to match the needs of two parties.  In business, this is often bringing together the provider of goods or services with someone who is in need of the resource or to get the holder of budget to release it for a given initiative.

Negotiations have three potential outcomes: win-win, win-lose or lose-lose.  Amazingly, talking to many businesses over many years, I’ve come to the conclusion that lose-lose is increasingly the most common outcome.  That is because in the absence of confidence, people opt to avoid loss and choose not to act.  But in choosing not to act, they are adding friction into their businesses and missing out on the return on risk they should be taking.

As business has become more complex, so it has become much harder for buyers to know what a good outcome is.  Worse, this is becoming a major cause of stress in business as both buyers and sellers have a huge amount at stake and lessening ability to navigate to a good result.

Consumer example

To illustrate the problem, consider this case we can all relate to.  You are in the market for a car, but have limited time and need to buy now.  You know the car make and model you want and know the recommended retail price.  You walk into a dealer who makes an on-the-spot offer for the car that matches your requirement at 10% less than the listed price.  Do you sign?

The dealer could be offering you a great deal, or they could be holding out and most customers could be getting 15% off.  You just don’t know.  Meanwhile, if it is the former the dealer is frustrated and has less incentive to offer a good starting price for future customers.

Independent brokers are sometimes a solution for this dilemma, having knowledge of the market and knowing which price is actually a fair one.

In business

Few executives have any more time available than our hypothetical car buyer.  Also like the car buyer, most things they are seeking to acquire are outside of their day-to-day experience.

It’s relatively easy when commodity items (like replacement parts for machinery) are needed, procurement experts can negotiate against a pricelist.  However, when it’s a complex product, such as a computer system or an internal budget allocation for a new service, then there are few points of reference within the organisation.

I lamented in a past post about the lack of productivity growth resulting from our transition to a digital economy (see Where is the digital-fuelled growth?).  Where new approaches to sharing knowledge takes friction out of the systems, there is a boost to productivity and this is where much of our effort should go.  Negotiations are a prime candidate for this focus.

Increasingly digital solutions are allowing for the creation of anonymous or semi-anonymous benchmarks.  But complex procurement and negotiations require more than simply finding a fair price.  Factors at play often include risk, time, quality, the competitive landscape and so many more.

Artificial Intelligence and Robotics

The two technologies that could make a material change here are Artificial Intelligence and Robotic Process Automation.

Artificial Intelligence, or Cognitive Computing, is a form of very advanced analytics.  In negotiations between parties, the primary objective is for the person who wants to acquire the resource to work out what a fair trade would look like.  Even when it is just the allocation of internal budget for a new capability, there is still a need to know whether the return is commensurate.

Where these technologies come in is their capability to find things that are similar based on a wide range of criteria.  For example, anyone who has seen how well search engines can group similar questions, worded completely differently, has some idea of how Cognitive Computing can bring together the right answers from disparate sources.

Where Robotic Process Automation (RPA) can be most effective is in taking the emotion out of negotiation and pushing to get the best outcome based on relative criteria.  There is an argument that the political and emotional process is an important part of getting to the best possible outcome.  The problem with this is that as the environment has become more complex, negotiations have become simplified on a subset of dimensions meaning that it isn’t the best argument that wins but, all too often, no argument that wins.

Most negotiations are a manual process with lots of spreadsheets and lists of points to push on and others to give on when pushed.  This is exactly the sort of complex process that RPA is ideal at and makes it an ideal target for the technology.

Win-win

Our robots can be programmed to provide a win for us all.  While some negotiators are happiest with a win-lose, win-win puts the right incentives in the system for the long-term.  If we program our robots that way we can be freed-up for the creative task of getting the right job done with the right resources.

In a future economy, where robots act on our behalf to find winning combinations, everyone could win.

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Playful business

Business is both complicated and structured. Our education, training and professional lives all teach us to think inside the box. Before rampant automation, and when problems sat inside the same box, this was ideal. The business world we are dealing with today needs a new approach.

It is increasingly popular to approach strategic questions using the power of games which encourage people to leave their assumptions behind. I’ve talked before about the role of games more broadly (see Turning decision making into a game).

While games are great, they still keep decision making within a frame. Games are a competitive activity within the confines of a set of rules. Every lunchtime kids launch into all manner of ball games in schoolyards around the world. Most games follow structure, build teamwork and have a win/lose outcome.

Sometimes, though, rather than play a defined game, children feel free to make up their own rules and migrate to free play.

To test this, give a group of kids a ball of any shape or size and tell them to make up a game. Watch what happens as they play and explore different approaches. Free play is really important for children to learn about the world around them. For children the world is far more full of mystery than known boundaries and rules-based learning doesn’t work until they have a better handle on their surroundings.

Many parents would know about the Reggio Emilia approach to preschool teaching. The idea of learning through exploring the world around you. Watch a child and they explore everything with an open mind.

It is interesting that modern sports went through an intense period of development in the eighteenth and nineteenth centuries with free play exploring different sets of rules that might make for great games. Largely (and there are, of course, exceptions) today’s most popular games have had stable rules for many decades.

In our world of disruption, we can argue that in many business settings the world around us is full of more mystery than known parameters. The sport of business that seemed so well defined is now up for grabs. No wonder a structured approach seems to limit us to thinking inside the box.

It is hard to find a consistent definition of play, but it does seem to be an activity conducted for pleasure, with the journey being the goal rather than any end and it is self-directed with minimal rules. It seems that play is far more important to our wellbeing than we ever realised, as described by psychiatrist Dr Stuart Brown in his TED talk.

When we’re looking for new employees, it makes sense to interview for the skills of the job they will tasked with. The trouble is that the return on the investment is unlikely to come with the first task that they complete but rather the job they will do over a number of years. Increasingly, that job hasn’t even been invented yet!

My personal view is that the characteristic that really matters in future employees is a curiosity about the world around them and a willingness to play for its own sake. In my own field of management consulting, I regard this as the renaissance consultant.

Elon Musk gets a lot of press around his intensity, but he does embody the idea of the renaissance with his wide range of interests (rockets, electric vehicles, batteries et cetera). Like Leonardo da Vinci, the best of our next generation will be interested in everything from science to music and much that goes in between.

There is a lot of discussion at the moment on the role of STEM (Science, Technology, Engineering and Maths) in education and our future workforce. Some are arguing that many STEM graduates are struggling to find work, while the reality remains that there are hundreds of thousands of jobs that can’t be filled that require these skills.

The problem isn’t with STEM, rather it is that not all STEM pathways are equal. It isn’t any one skill that is needed, but rather it is a flexibility and willingness to learn. Even more important, it is the combination of STEM foundational skills with a natural curiosity and willingness to explore.

In a world that is changing fast, none of us can assume any existing approach to our work will serve us well even into the near future. We need to be willing to play in order to find the new rules that are going to define the business answers for the coming years.

The great news is that there is a child in all of us!

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Where is the digital-fuelled growth?

We’ve had about 50 years of computing in business and about 20 years of the digital revolution. How are we faring on the question of digital fuelled growth and productivity? Many economists are coming to the surprising conclusion that technology may not be providing the boost we had expected.

This question really matters as politicians around the world are grappling with a voter backlash at disruption to industries and the promise of growth providing new jobs seems to be wearing thin. The population wants jobs but many fear that the new employment, relying on technology, are not going to be relevant to their individual skills or geography. New tech jobs are ending-up being concentrated in a few locations and requiring skills that are out-of-reach to those that have been displaced by global trends driven by digital channels.

Robert Gordon (author of The rise and fall of American Growth) splits productivity into three industrial revolutions: 1770-1840 (steam and transport), 1870-1920 (electricity, cars, city infrastructure, chemicals and working conditions) and 1970- (ICT). He argues that the second revolution provided about three times as much productivity growth as the other two. Worse, when he breaks-down the third revolution he argues that productivity growth has stagnated since early in this century.

The last part of the 20th century saw almost universal growth driven (arguably) by mass liberalisation of trade and the opening of new markets. Many assumed that technology was providing a virtuous boost. It seems that the rise of the web, digital technology and the smartphone have driven consumer demand but more economists like Gordon are questioning whether it has made the supply of that demand any more efficient.

So where has the productivity gone? I’ve argued before that Trading your way to IT simplicity In addition, we’ve lost some of the traditional ways of encouraging organisations to leverage their investments. Many of the online tools that we all use (such as search, collaboration and workflow) are fantastic but they don’t cost very much (and are often free) resulting in little governance to make sure that the benefits are realised.

Without a clear focus on realising productivity as the main aim of technology, many benefits are pleasing but of little benefit to the economy. For example, is there a real gain for the economy being able to check-in to your aircraft in half a dozen different ways? What about buying soap with a QR reader?

Ergonomics matter but much of what we implement is about gimmicks that are pleasing but don’t improve society.

That doesn’t mean that productivity growth for our economy isn’t coming, rather just that it may not be as easy or clear cut as we had expected. As we approach a new generation of robotics and artificial intelligence what do we learn? The problem is that the combination of genuine displacement of people without economic benefits mean there aren’t resources available to grow the job pool in other ways.

There have been thousands of words written about the threat of automation and I’ve previously given my view that Our machines won’t outsmart us. I’ve also written about Why aren’t I working a 4 hour day?.

We need to pivot our focus from whether jobs will be lost (they will, but new ones can be created) or whether machines will lead us into a terminator style future (they won’t), but rather how we change the trend on productivity.

The last 200 years have been amazing. Angus Maddison was an eminent economist who estimated the world’s long-term economic growth to be surprisingly small. According to Maddison’s work, from the Middle Ages through to the Industrial Revolution, the normal annual growth was less than 0.07%, far less than the numbers we assume today.

Without a change to the status quo, including new approaches to technology which unlock productivity growth, it could be that we are heading back to a world where growth is near zero. By the middle of the century, even population growth won’t help the world economy.

This is so important that it may be that there is a role for government regulation to ensure investment in technology results in productivity that is seen in the economy. It is in all of our interests to change the equation and find a way to turn our digital revolution into a new wave of productivity and wealth that everyone can share in.

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Is the crowd dumbing us down and killing democracy?

One of the most exciting features of the Internet is the ability to get the voice of the crowd almost instantly. Polling of our organisations and society that would have taken weeks in the past can be done in hours or even minutes. Ideas are tested in the court of public opinion in real time. This is potentially a huge boost for participation in democracy and the running of our businesses, or is it?

Our governments and businesses have long worked with a simple leadership model. We select our leaders through some sort of process and then give them the authority to act on our behalf. In the past, we asked our leaders to report back on a regular basis and, most of the time, we left them to it. In democracies we used elections to score the success or failure of our leaders. If they did well, we gave them another term. In business, we relied on a board selected by shareholders.

This really started to change with the advent of the 24 hour news cycle. Rather than curate 30 minutes of news once a day, the TV needed to find stories to fill all of the day. Unlike newsprint which had time for analyse, speed to air was a key performance metric of reporters and an initial, even if uninformed, sound bite was enough to get something to the public.

There is a popular movement to open-up government even further with regular electronic plebiscites and a default to open data. At its core is the desire to make the machinery of government transparent to all citizens. While transparency is good, it is the consequence of having “too many cooks in the kitchen” that leads to problems. Having everyone have their say, either through direct contributions or through endless polling means that the fundamental approach to decision making has to change. While fulltime politicians have the time to get underneath the complexity of a problem, the mass of voters don’t. The result is that complex arguments get lost in one or two sentence explanations.

This is happening at exactly the time that our global societies are becoming more complex and need sophisticated responses. Issues such as migration, debt and global taxation are too complex to be boiled down to a sound bite. It is telling that few have suggested turning our judiciary over to the court of public opinion!

H. L. Mencken, a well-known journalist from the first half of the 20th century who wrote extensively on society and democracy, once said “For every complex problem there is a solution that is concise, clear, simple, and wrong.” An overly crowd oriented approach to democracy results in these simple answers which are dumbing down our decision makers.

The danger doesn’t stop at our leaders, it also extends to the running of our organisations. We work more collaboratively than ever before. Technology is enabling us to source solutions from the crowd to almost any problem. This can work brilliantly for many problems such as getting a quick view on whether a brand message is going to resonate, or if a product would appeal to a particular demographic.

Where it can let us down is when we start trying to ask too many people to provide input to complex problems. Great design, sophisticated modelling and radical new product offerings don’t lend themselves well to having a large number of people collaborate to find the answer.

Collaboration and the use of the crowd needs to be targeted to the places where it works best. This is going to be more important than ever as more people move to the “gig economy”, the movement where they use platforms like 99designs, Expert360, Topcoder or 10EQS to manage their work. The most successful organisations are going to learn what questions and problems the crowd can solve for them.

Questions that require a simple, technical answer seem to suit this form of working well. Similarly, problems that can be solved with well-defined technical solutions are well suited to handing out to a group of strangers.

The crowd either completely rejects the status quo (the crowd as a protest movement), with little to offer in terms of alternative approaches or it slightly tweaks current solutions (the crowd without depth). Even the individual sourced through the crowd seems to be unlikely to rock the boat due to a lack of context for the problem they’re trying to solve.

The way we work and solve problems as a society and in our organisations is changing. The one thing we know for sure is that we don’t yet know how this will really work!

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The singularity and the future of intelligence

Everywhere you turn there is a discussion about the impact of technology on our future, whether it be how we work or how we live. Of particular concern is the encroachment of automation into virtually every part of our world.

Estimates vary, but it is credible to suggest that about half of all white collar work will be automated in the coming decades. However, the real revolution is often termed the “singularity”, in effect, the point where computers are smarter than we are.

Way back in 1962, John F. Kennedy said “I regard it as the major domestic challenge of the ’60s to maintain full employment at a time when automation is replacing men”. With just a little rewording, the same statement could be made today. We learn two things from this, the first is that the threat of automation is not new, the second is that properly managed there is no reason for the total number of jobs to decrease.

There will, however, be disruption which has social and economic implications. The jobs that will be created haven’t even been invented yet and not everyone working today will be equipped to take them up. Already we have worldwide and local shortages of technology workers while other sectors are shedding staff.

As machines get smarter, our role with them will become more complex. The trouble with the term smarter is that is that it conjures up images of a machine that is equivalent to us. As I’ve previously written, the limit of current technology is the ability to make “cognitive leaps”, that is the ability to determine something new from available data rather than repackage up an association that has been previously made. This boundary will protect many workers (see Your insight might protect your job).

However, as our technologies advance, the day is getting closer when we have to seriously think about what intelligence really means. The problem is we don’t know how the human brain achieves its feat of consciousness or how we achieve those cognitive leaps that are central to our intelligence.

Eminent quantum physicist Nicolas Gisin argues that free will and a conventional view of physics are in conflict (see New Scientist: Physics killed free will and time’s flow. We need them back). Gisin is well known for having successfully applied quantum mechanics to create commercial applications and also to have demonstrated some of the more controversial conclusions of the field such as quantum teleportation.

Gisin asks “Are we passive laundry machines through which thoughts happen to pass? Or are we active agents free to influence our thoughts and decisions?” He goes on to argue that modern science tends towards the machine view, he says “In a deterministic universe, where one thing leads inevitably to the next, any conception we have of free will is an illusion.”

Meanwhile, another physicist, Matthew Fisher, has speculated that our brains probably rely on quantum mechanics to achieve the magic of consciousness (see New Scientist: Is quantum physics behind your brain’s ability to think?).

Until now, the objectives of the many teams racing to develop quantum computers have been to solve algorithms that are in the domain of conventional computers but too ambitious for today’s processors. I’ve argued that these projects may not live up to their promise (see The Quantum Computer dream could be killed by information management).

It is possible that the really interesting outcome from current research into Quantum Computing could be a machine that displays many of the same qualities as our own brain. Until the workings of such a machine is designed, any date for the “singularity” is nothing more than speculation.

Of course, when we do design such a machine, there will be some very difficult ethical and social considerations. I’ve argued before that despite the threat that such machines pose, ultimately Our machines won’t outsmart us, mainly because we are tough evolutionary creatures and we will assimilate the technology before we will let it rule us.

Regardless of when we manage to invent machines that can take the next step in artificial intelligence, there is no doubt that to both live and work in the twenty first century we need to be prepared to adapt, and quickly.

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