A fourth mobile operator will launch in Moscow this month, jump-starting a price war by ‘aggressively undercutting its rivals.’ If you're in Moscow you may have seen the billboards?
Good news for consumers, if the expected 30% price fall materialises. Less good for the established mobile operators. Their ‘cozy’ world is about to be disrupted as dissatisfied customers - one-fifth of the entire market - exit through their doors first.
Are the big boys worried? Apparently not. Aside from their infrastructure advantage they are confident that ‘client loyalty’ will ensure they withstand any threat. But are they right?
As Mark Twain (is often wrongly attributed to have) put it “It ain’t what we don’t know that gets us into trouble, but what we think for sure that just ain’t so!”
Claims of customer loyalty are not idle boasts. Russia’s telecoms industry has some of the sharpest marketing professionals in the game (witness Beeline’s rapid ascent from obscurity to global brand). They will all have hard evidence, drawn from years of customer research, that suggests the Tele2 threat is nothing for them to lose sleep over.
But what if all their data is wrong?
CFO pressure forced marketing departments to rapidly improve over the last decade. Campaigns are now run with one eye to their return on investment. The focus on hard data has pulled marketing away from its core purpose - understanding why people behave the way they do.
A few years ago Starbucks wanted to understand which customers drank which coffees in its shops. When buying coffee customers were incentivised to fill out a short questionnaire asking their age, occupation and ‘how do you have your coffee?’
On most measures the campaign was a success - except one. The results were confusing. Most people had said they have their coffee black, but the point-of-sales systems were showing that almost no-one has black coffee in their shops. Something was wrong.
The answer is that it’s our perception about how humans behave that is wrong.
In contrast to the default thinking of conventional economists and management theorists, humans are not rational, self-interested actors in full possession of perfect information. When asked for what we do, (or what we think we do), we are utterly unreliable (e.g. we like our coffee black, but don’t order that).
When asked a question by someone face to face we consciously or sub-consciously gift the answers we think people want to hear, or game the system to project how we want to be seen. It’s one of the reasons focus groups are fatefully flawed in minutes.
‘Do I love your brand?’ Well, I don’t want to disappoint you so, ok i’ll say it. Am I satisfied with your offering? Well, sometimes I am, sometimes I’m not - how do I record that on a 5 point scale? (Most people will discover a safe score, which is why your customer satisfaction scores probably hover around a 4 on a 5 point scale or 7 on a 10 point scale).
So Starbucks changed their question to ‘how did you have your coffee today.’ Removing opinion (and therefore bias) from responses they focused customers on their experience. The result was a set of figures that bore a close resemblance to the hard numbers coming out of the cash registers.
The only true test of customer loyalty is how people act: did they sign on again, then they’re loyal, at least for now. True tests of customer loyalty are how people act, NOT how people tell you they will act.
So, if the telecom majors are confident that customer loyalty (rather than customer inertia) will deflect the competitive threat of Tele2, but those numbers are built on people’s opinions - then it may be time to re-think. The future isn’t just an extension of the past.
Establishing a weak signal detection unit will provide real-time experience (not opinion) based evidence of emerging shifts in attitudes and behaviours. This will support timely responses if the market dies start to be disrupted on price.
Make sure you’re not caught out by what you thought you knew for sure, but that just isn’t so!
Leaders have a unique challenge in the 21st century. The ecosystems (the countries, markets and industries) their organisations operate in are increasingly volatile, uncertain, complex and ambiguous. And missing critical signals amongst the increased noise risks exacerbating existing fault lines in their organisation. What should leaders do?
Subject matter experts solve complicated issues at functional levels. But complex questions (e.g. top line growth, corporate culture, change or risk management) cut across specialised silos. Complexity therefore is always escalated up; making managing complexity the key strategic challenge for executives in the 21st century.
Yet complexity remains widely misunderstood; described as something ‘very complicated’ or confused with chaos theory. Complexity science itself ascribes distinct characteristics (non-linearity, emergence, unpredictability) that render traditional 'solutions' (e.g. best practice, ideal leadership styles) entirely context dependent.
To face a complex issue means to deal with a ‘brownfield’ context - never a ‘greenfield’. Complexity is located in the system (e.g. the organisation, market, population) and always has a history, yet is constantly evolving. And as we engage with it, it changes - often in unpredictable ways. This is why answers in a complex system often appear only in hindsight - though this doesn't lead to foresight (e.g. it seems obvious now that sub-prime mortgages were a bad idea, but likewise, today's Quantitative Easing is variously described as the only thing saving the global economy or creating an even bigger future crash. Only time will tell).
In a complex world context is king.
Idealised futures are an illusion - as are strategies based on certainties designed to get you there. The collapse of Michael Porter’s Monitor Group in 2012 showed that while rigorous strategic analysis can help explain how excess profits were created in the past, it's a poor predictor of how to generate them in the future. Even the best formal strategising can trap leaders into believing the future will be an extension of the past. But if the future fails to conform to expectations we are left naked and fragile, exposed to the elements.
Like King Canut ordering back the tide, we discover powerful natural forces defy command and control.
Yet, the natural world itself - of which man is a part - has adapted wonderfully to exploit complexity. Evolution works through a process of increasing variation (of options), basing selection on what works now, and replication (or starvation) of options based on hard evidence of suitability. Can leaders learn something from nature about adopting a rigorous external focus, increasing awareness of options through rapid trial and error, and creating mechanisms to amplify or dampen options in order to thrive?
Effective horizon scanning uncovers emerging signals that signal where and what to act on before its too costly or too late. Technology is a great enabler in this, if one caveat is kept in mind: technology without human interpretation is meaningless. Google may find anything you ask, but can’t tell you what to ask for. Uncoupled from humans technology merely increases the noise surrounding the signals. Data is dumb - to become meaningful information human knowledge must be applied.
Humans should be at the front and back end of technologically-aided decision-making - defining the issues to explore and discovering its real meaning. Technology therefore must be designed to fit the human - the way we are now, rather than the way we'd like us to be. It must augment our natural sense-making abilities, which have supported human evolution through millennia (a best practice case?).
Critical knowledge flows through organisations in human networks. Navigating these flows effectively can reveal the origins and dynamics of change. And as humans share such knowledge naturally, extrinsic rewards aren’t required to tap this. Humans naturally create and share knowledge in the form of narratives - ‘micro-stories’ - that are both universal (every culture has them) and democratic (no barriers exist to sharing). These are the 'water cooler’ stories that spread insights and enable other people to make sense of the world around them so they can act better in it. Harnessing these narratives is critical to making sense of and navigating complexity.
Critical knowledge can be leveraged at little extra cost.
Leaders must create the conditions for contextually-appropriate knowledge to emerge. Managing for serendipity (‘pleasant surprises’) means seeking fresh insights, rapidly field-testing coherent ideas and replicating success. But as genuine breakthroughs don’t come from established thinking patterns. Leaders must learn how to break through the hard-wired autonomic brain we rely on - which seeks first-fit, rather than best-fit, solutions - and instead become receptive to novel ideas. Strategic leadership is less about engineering future visions than it is about increasing awareness of the critical factors in our ecosystem, 'identifying the biggest challenges in them and devising coherent approaches to overcoming them'. Real strategy is about seeking the truth of the current position.
Navigating and exploiting complexity means leaders must take multiple perspectives to discover genuine insights. Going beyond objective numbers to understand the why. Rapidly testing coherent ideas as ‘safe-to-fail’ experiments. and feeding success, whilst starving failure of resources. No-one can ‘cut through’ or ‘simplify’ complexity - nor should we want to. Complexity contains rich opportunities in a changing world. Leaders employing naturalistic approaches can exploit complexity profitably.
SenseMaker® - an innovative technology first deployed by the Singapore government to detect weak signal terrorist threats - taps into mass organisational knowledge flows and helps join up disparate information from silos to form actionable knowledge. It presents whole network perspectives leaders can rapidly see and understand, helping unlock the organisation’s present evolutionary potential.
For more information about how to make sense of, navigate and exploit complexity for organisational success contact firstname.lastname@example.org
Seeing the future as merely an extension of the past is a fundamental error. Complexity’s immense, volatile and unpredictable character will make tomorrow less resemble today than yesterday did. So navigating a journey through the rear-view mirror won’t help you avoid the brick wall up ahead.
Following the stock market crash of October 1987, value-at-risk (VAR) models became the rage in financial services. JP Morgan was an early convert and pioneer as VAR provided the Chairman, promptly at 4:15pm each day a single number that defined the extent of the bank’s risk exposure. The allure of sophisticated mathematics to simplify risk management fanned VARs popularity, with over 200 books published about it. The only problem was that it was nothing more than a “beautiful lie.”
VAR is driven by historical data and dependant on one huge assumption: that the future will follow the same pattern as the past (from where the data was taken). In other words, if you haven’t driven into a wall yet, you won’t. But as Nassim Taleb has pointed out, the highly improbable nature of rare events (black swans) must be considered together with the oversize nature of their potential consequences. Driving into a wall may be unlikely but, as it’ll probably kill you and everyone else in the car, you're probably best advised to remain aware enough not to do it.
The culture of financial service firms particularly predisposes them to VAR-type errors. Miles Kennedy, a PwC partner described the culture as a “tendency to place greater confidence in risk information that is data-driven, in the belief that this confers objectivity and truth.” But whilst objectivity is a noble aim in business - freeing us from cognitive bias and politicking - objectivity “doesn’t equate to truth” where the future is concerned, for “risk is about the future, and there are no facts about the future.” Substituting foresight about possible futures and consequences for forecasts that are pleasing yet flawed is, as the world has discovered over the last six years, dangerous.
The economics professor and writer, John Kay, describes this cultural bias as a “belief that a number based on the flimsiest of data is better than a qualitative, and necessarily subjective, judgement.” Although this bias is rampant in the ‘numbers professions’ - bankers, accountants, economists - it’s spreading to other organisations through the allure of big data. And where certainty is claimed about the future - a place where no certainty can exist - it'll be a treacherous guide to navigating an increasingly complex world.
The ‘relentless parade of new technology’ whipping up today’s data deluge adds to modern complexity. According to IBM, 2.5 quintillion (a billion billion) bytes of data are generated every day. The World Economic Forum blog put this into perspective - we are now ‘producing the same amount of data every 10 minutes as was produced in the last 5,000 years. McKinsey’s Global Institute argues this wave is still surging, as high-potential technologies ‘could have a potential economic impact between $14-33 trillion a year in 2025 - equal to almost half the global economy today.
Against this confusing backdrop executives must continue to contain increasing risks and costs and implement the right decisions that drive change to remain competitive. Yet, organisation’s whose strategies to thrive (or just survive) through efficiencies alone end up sailing ‘too close to the wind’ - risking the whip-end of ‘black swan’ events as, in a tightly-coupled world, they become ‘as weak as the weakest link in their chain.’
Now, as never before, executives put the attraction (and retention) of key skill central to their strategies for successfully navigating a highly volatile world. Yet, despite technological advances remaking the world anew ever more rapidly, workforce productivity growth remains stubbornly stagnant. Since 2005, overall Eurozone productivity has increased just 3% (and only 13% since 1995). Even in America since 2010 it’s been a measly 0.3% per year (compared to 1.5% over the previous 20). This raises the question - are organisations misusing technology advances and people’s skills?
Modern knowledge workers spend half the week on email; looking for or gathering information as tools are rarely made to fit the human. The success of Atos - a French IT-service supplier - to become a ‘zero-email’ company this year by integrating social-networking platforms for natural communication may be one the most significant - if less heralded - organisational developments of 2014.
Organisations are currently poorly structured to exploit new information, ideas and opportunities. Technology development often outstrips our evolutionary ability to ‘differentiate useful information from noise.’ This explains why even the printing press took ‘330 years and a million dead in battlefields for the advantages to take hold.’ How long will it take the modern organisation to adapt?
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