Like all school, college and university students I was fed a diet of simple, linear and well-behaved problems with easy-to-define solutions.  And whilst this academic convenience made it easy for teachers and professors to set exam problems and grade and assess the performance of their students, I later found it to be a far cry from the real world experiences of industry.  Throughout my professional life those initial ‘innocent simplicity’ assumptions of linearity may have started as a point of nucleation for my early thoughts, but they have inevitably been cast aside at an early stage!  How come?  The universe and everything in it, including our networks and working environment, is essentially non-linear and complex, and for the human race it is becoming ever more so with each new layer of technology and the insights that it affords.

Sources of complexity

Where does this complexity come from?  Well, it really is all about networks, connectedness and delay.  Quite remarkably, and until very recently, all human progress was founded on simplistic models of the physical world, technology, society and peoples.  And this was really successful because communication and interaction were disjointed and slow, and it was possible to get by with simple-to-understand models and basic decision trees involving a small number of parameters.  But because the non-linear effects occurred slowly the perception was one of well-behaved linearity.  Of course there were a few exceptions that were not fully understood at the time such as the financial collapse of the 1930s, Eastern Seaboard (USA) Power Brownouts during the 1970s, telephone network voting, which suddenly imposed massive traffic demands, and of course a raft of military and political decisions.

Unfortunately, the growth of connectedness combined with the removal of delay increasingly confounds the simple world-view, and it is now clear that the occurrence of linearity is the (rare) exception.  Take banking and finance: I think we can safely say that recent global events have shown that no one understands how it all works.  The rapid rise of chaos (in the mathematical sense) that crashed the world economy can be assigned to greed, a lack of understanding, high-speed networks (connectivity) and the reduction of transaction delay driven by competition.  In effect, it was as if the entire system was riding a bicycle and got into a speed wobble, and the rider was unable to get back to stability without having an accident!

On another plane of simplicity; the proponents of genomic decoding thought that individual genes would be responsible for individual effects.  How very unlikely!  It not only turns out that combinations of genes are responsible for given effects, such as defective human organs and disease, but this is also influenced by the function of proteins.  This is far more complex than anyone first imagined and will take considerable computing power to unravel.  One supposition that does seem likely, but has yet to be proven, is that cancer is merely a communication problem between protein and genome rather than something induced by food or our unhealthy habits.  The snag is that proteins are about 1,000-fold more complex than the genome, and the computational effort will therefore be far greater.  The good news is that Gordon Moore’s Law will see silicon computing power continue to double and take care of the shortfall in a very short time!

Complexity is now visibly pervasive in everything from our IT to the workplace, government and everyday living.  Global warming, recycling, energy, food, water, logistics, sustainable manufacturing and most other important issues are not simple, isolated and bounded problems.  The thinking and models of the past industrial revolution and experiences of past centuries cannot solve these problems as we try to engineer a future that will support a growing population without destroying our environment. 

There are lots of simple solutions to complex problems – unfortunately they are all wrong!

Not surprisingly then managers and politicians are struggling to make wise decisions.  Their world-view is from a past era of infinite supply, linearity, disconnectedness and continual growth.  If we are to engineer a world that is sustainable we have to think afresh and move away from the simplistic management of growth, profit and return on capital to something that encompasses the welfare of everyone and everything.  This will involve the rethinking of industry and supply, our logistic systems, mode of trade, and the way we value commodities and increasingly rare materials.

Money alone is far too crude a measure to make any decision and we need to at least account for Ecological Impact and Social Consequence

To survive and prosper in the long term we have to embrace new opportunities that span the worlds of the organic, inorganic and technology, with base solutions that are holistic and resilient, and our core mission from now on has to be:

More from Less for More and More People
and not:
More from Less for The Few

How do we achieve this?  First; we only have one visible route to sustainability, which is at the intersection of IT, nano and bio-tech.  The ability to manipulate materials at a molecular and atomic level, and to programme their behaviours, opens up new avenues that use minimal energy and achieve nearly 100% reuse of materials.  At a simple level the first car was printed last November, and we can now 3D print adjustable spanners and gearboxes in one pass.  No multiple parts to be assembled, but a single integrated process. 

To date our biggest successes are printable and programmable plastics, but we are making inroads into metals.  So there is an expectation that production will be simplified and products distributed in ways that involve a much lower logistics cost.  On an entirely different level, organic computer screens, devices and batteries have also been produced along with sensors more capable than a ‘dog’s nose’.  An ability to detect a single molecule of a substance in a sample will transform medicine, food production, farming and the fast-growing care industry.

What was science fiction will soon become science fact

For example; all the components to make a ‘Tri-Corder’ (aka Start Trek – the TV series) are available, and in principle, the task is now one of ‘mere engineering’.  So we might anticipate some very big changes in society and industry with new understandings and capabilities:

Machines smarter than people in specific sectors, more mobility and sensors, everything and everyone online, greater individualisation, new networks and networking modes, more accurate modelling and decision support.

The continued expansion of the internet, computing power and mobility is about to undergo another big change with The Cloud.  Computers will collaborate on line, and the processing power of mobile phones, automobiles et al, including your TV and hi-fi, will be on the same network.  Most importantly, this new ‘society of things’ will see sensors that will increase the information flow and intelligence with significant benefits for everything from integrated transportation to logistics, retail, and human creativity and problem-solving.

Today we are constantly surprised by Artificial Intelligence (AI) systems and the answers they contrive, and on many occasions we lack the facility to fully understand.  But that does not preclude us using the results.  For example; IBM with Deep Blue, Blue Gene and Watson presented us with the first public surprises, but Siri on your iPhone 5 is now probably the most public, whilst Watson is being used by the medical profession in the USA.  Almost by osmosis we have gradually realised that the solution of many industrial, scientific and governmental problems will continue to defy human abilities.  So the question is; could AI provide further and significant enhancements to the world of business and problem-solving?

Undoubtedly, the answer has to be yes!   But machine intelligence has been around for decades and we have to ask; why don’t machines understand?  The answer is simply because we have only recently assembled sufficient data and a number of ‘common sense cases’ to afford them some context to the human situation.  Also, the computational power required for cognition has not been available – but now it is!  More importantly, AI systems are now capable of learning from a vast set of real-time inputs in the form of text, audio, video, and animations and simulations, plus the impending roll-out of dedicated sensors embedded in billions of mobile phones.  On a professional level; AI systems provide far better medical diagnoses and prognoses than a human doctor, and systems are now being rolled out along with all the legal trappings!

The lack of sensory devices to give computers continual input and some form of self-awareness has been a misunderstood subtlety

So where is AI today?  The big successes go largely unnoticed and include control systems in industry and aviation, financial trading systems and telecom network control, the design of integrated circuits, and complex industrial process and plants.  AI systems also populate many control systems for our cars, elevators, trains and domestic appliances.  On the more esoteric side AI systems now make discoveries in science and invent/innovate in technology and engineering.

Science fiction writers mostly predict Armageddon and the machines taking over, pushing us aside and becoming malevolent.  My prediction is that we will be happy to let go of a lot of things, like mundane processes and production work, and form a partnership with machines so we can embrace the more creative and productive aspects of work.  At least that has been the history so far!

All of this prompts one key question: will we be smart enough to recognise new intelligences when they spontaneously erupt on the internet or within some other complex system?

Of course, there is another question that you might want to ask as a manager and/or a player in business, government or some institution: what does this all mean for me, my work and my organisation?  It depends on where you are in the organisation and your sector.  In the military and defence industries people are already enmeshed in and trying to deal with mounting complexity, whilst charities seem to be largely unaware.  So my advice is to scan other industries to see what they are encountering, read, attend conferences, look out for the latest tools, and start thinking about business models, modelling and applications.

At the two ends of the spectrum we have the producers of commodities; concrete, steel, cars and food et al where everything about the process is known and the variability of demand and specification is always on the move.  Here, hierarchy and clear job demarcation works!  Here chaos comes in the guise of weather, fashion, seasonal demand and rabid competition.

In complete contrast, and at the other end of the spectrum, we have R&D, design and consultancy where even defining the problem can be difficult and might not be stable!  And hierarchy would certainly be the kiss of death.  Agile, free thinking, multi-role and multi-talented people/organisations are the name of the game here with customers often satisfied with any kind of a solution.

And so the most complex organisations embrace the complete spectrum and the managers need the wisdom to recognise that ‘one size does not fit all’ and each department has to have the freedom to operate in the mode that is best for it to achieve its objectives.

If the suits (managers) and sandals (researchers/creatives) can’t mix, then the result is usually divorce.

For the vast majority of organisations it pays to remain fluid, prepared to change and adapt, and always be ready to adopt the next wave of technology and management solutions.  An acceptance that modelling and AI will be an increasing element of that change is also an essential.  And if you don’t you can be assured that your competitors will!

I welcome your thoughts.

Peter Cochrane
peter.cochrane@formicio.com

Download as a PDF:
Formicio Insights_The Rise of Killer Complexity

Shared Services are not new, they have been around for decades and we all rely on them to varying degrees. While the most common examples include IT, HR, Finance, Facilities Management and Procurement, other services are increasingly being shared across the enterprise: for example Legal, PR and Communications, and Business Intelligence. This trend towards the horizontally integrated enterprise was the topic of a recent Formicio article, where our colleague David Trafford discussed the challenges of moving to this type of organisational model. In this article we focus on the service agenda, and argue that a number of factors need to be assessed and then addressed if Shared Services are to fulfil their service promise in an affordable way.

In the majority of cases the rationale for moving to Shared Services is to reduce operating costs. This is underpinned by the argument that to ‘centralise’ resources into one dedicated Shared Service organisation, which delivers services through standardised processes and systems, must be cheaper than individual business units doing it themselves. A second, less tangible argument is that by centralising expertise, service quality will also improve. Many organisations have taken this cost-driven thinking further by choosing to outsource all or part of their Shared Service operation to external providers, many of whom operate off-shore. Shared Services are now an established part of our organisational landscape, and they will continue to evolve as the requirements of its users change and new sourcing strategies emerge. But how can we ensure that the focus is not solely on cost, but also on higher levels of service quality?

Factors that determine service quality

Over the past 20 years, the body of knowledge on Shared Services has significantly increased, and during this time we have developed a point of view on the factors that influence service quality and value. We believe there are 10 of these factors and they are described below. It’s important to note that these factors cannot be addressed in isolation as they are very closely interrelated. An holistic approach therefore needs to be taken to developing a change plan, which considers how changes to one factor will result in changes having to be made to others. We believe that people are fundamental when it comes to service quality; what we’ve described below are the factors that create an environment and context within which people are able to deliver their best.

1.       The value proposition, operating model and mindset need to be aligned
Essentially the value proposition is a product of the business strategy and defines what the Shared Service organisation must deliver to the customers they serve and the added value the customers get. The operating model defines how services get delivered, and the mindset defines how people should perceive their role. If these are out of alignment – for example if the proposition is to provide superior customer service and the mindset of people (shaped by their experience) is to close service requests as quickly as possible – it’s most unlikely that customers’ expectations will be met.

2.       An operating model comprises a number of facets
The operating model of a Shared Service organisation is complex as it comprises a number of facets including processes, structure, measurement systems, services portfolio, governance and external suppliers, all of which must work together as a well-tuned machine. Furthermore the outcomes that an operating model delivers must be aligned with the value proposition.

3.       Demand and supply mature over time
Organisations, like individuals, mature over time; what was normal practice yesterday may not be acceptable tomorrow. In a Shared Service context, customers (the demand side of the relationship) will expect colleagues in Shared Services to deliver greater value, for the services they provide to be more integrated, and ultimately for them to become true business partners in that they enable innovation and new business possibilities through the services they provide. If the leaders of Shared Services (the supply side of the relationship) don’t recognise this trend and stay focused only on providing low-cost transactional services, the relationship will break down as customers look elsewhere for the products and services they need to deliver their strategy and plans.

4.       ‘One size does not fit all’ – authentic differences must be accommodated
A challenge that has been present throughout the development of Shared Services is how best to handle authentic differences. If all users require exactly the same services and service levels, then the delivery of these services would be relatively straightforward; the services could be defined, introduced and continually improved. The reality is that while a lot of the services or service levels required by users are common there is also a need for services or service levels that are authentically different. These differences are determined by factors that have a direct impact on the success of the businesses being served, and examples include market conditions, country-specific regulations and business unit strategies. These differences inevitably create a degree of complexity within a Shared Service organisation, which in turn could drive up cost and compromise service quality. The challenge is therefore keeping the number of authentic differences to a minimum whilst maintaining a high degree of common and shared services.

5.       Best practice frameworks are useful but have limitations
Best practice frameworks like ITIL in IT service management and Dave Ulrich’s 3-box model for HR are useful sources of information and ideas, but their application inevitably brings risk. Essentially, they are predicated on a ‘one-size-fit-all’ philosophy where it is assumed that the practices advocated can be applied successfully in all situations. In reality each organisation and its context are unique, whether due to its size, culture, technology or process maturity. As a result, it is dangerous to apply these frameworks without first understanding the context in which they are applied or the strategic and operational outcomes the organisation aims to achieve.

6.       Behavioural change is more difficult than process change
Establishing the value proposition, introducing best principles and changing the operating model alone will not deliver service quality and value; it is the people with the right mindset that ultimately makes the difference. A mindset is a set of assumptions, methods or systems held by one or more people or groups of people. They are usually so established that they create a powerful incentive to continue to adopt or accept prior behaviours, choices or tools. Changing well‐established and often deep‐rooted mindsets is much more difficult and takes longer than changes to underlying cost bases, operating models, structures and processes. Changing mindsets to ones that are service-focused is possible, but it is neither quick nor easy. However, it is impossible if you don’t know the drivers of the current mindset. The challenge of changing mindsets is discussed in a recent Formicio article entitled Sustained Change Requires Mindset Change.

7.       The role of leaders is to put in place the conditions for success
Often leaders perceive their role as coming up with the answer rather than creating the conditions where others – who are often much closer to the issues – are allowed to use their own creativity and judgement. The role of leaders should be to identify and then establish the necessary conditions for success.

One of the best ways of describing what is meant by conditions for success is to draw upon a gardening analogy. Those of you who know about gardening will understand that certain conditions need to be in place in order for a garden to flourish, fertile soil being the most obvious. The more successful gardeners know that some of these conditions can be controlled and others cannot. For example, they know that soil quality can be improved and that particular plants will never do well in certain types of soil. They also know that some plants need to be pruned in spring and others in autumn. If these conditions are not understood, or are ignored, gardening can be a costly and disappointing pastime. The challenge of establishing the conditions for change success is discussed further in a recent Formicio article.

8.       Leaders should focus on introducing operating principles not practices
It’s widely accepted that operating principles can be successfully transferred across different organisations, while practices on the whole cannot; it’s the application of a principle in a specific context (ie within a specific organisation) that establishes the practice. If the context is different across organisations, then the application of operating principles will lead to different practices. It is for this reason that it is always dangerous to import best practices rather than apply best principles.

9.       Organisational clarity drives productivity
As Shared Service organisations become more complex, both in terms of the services they provide and the number and variety of external service providers they use, it is important that the organisation maintains organisational clarity around how and why it is doing what for whom. A way of defining what is meant by organisational clarity is to use the rowing boat racing analogy. When all the rowers are in perfect harmony and staying on course, there is enormous power in the boat. If the coxswain loses focus, or the rowers don’t remain aligned and in harmony, chaos occurs and the boat slows down or goes way off course. Shared Service organisations that lack organisational clarity become that slow boat or, even worse, the fast boat heading in the wrong direction!

10.   Collaboration across boundaries drives engagement and continuous improvement
Since Adam Smith published his seminal book The Wealth of Nations in 1776 we have sought to organise our resources based around specific capabilities, which inevitably creates boundaries that need to be managed. Organisational boundaries are inevitably a source of delays and errors as work passes across them. However, irrespective of what criteria we use to design our organisation, there will always be boundaries. The challenge is to minimise the friction between them and manage them in a way that does not impede performance. Collaboration between people across boundaries, between functional areas and organisational units is imperative if they are to share ideas and deliver to a common purpose. Unfortunately, experience tells us that organisations tend to be more successful in building boundaries between functional silos than building collaborative cultures.

A framework for continual improvement

Our point of view is that the 10 factors described above ultimately determine the service quality and value delivered by Shared Service organisations. An assessment of each of these factors, in terms of the extent to which they are in place, is a powerful leading indicator of future performance, unlike customer satisfaction surveys that are lagging indicators.

Their assessment can therefore be used as a framework for the planning of continual improvement and change. As previously discussed, it’s important to remember that these factors cannot be addressed in isolation as they are very closely interrelated. An holistic approach therefore needs to be taken, which considers how changes to one factor will result in changes having to be made to others.

A further value of such an assessment tool is that it can be used to measure progress towards the goal.

We welcome your thoughts.

Peter Boggis
peter.boggis@formicio.com

Peter Turgoose
peter.turgoose@formicio.com

Download as a PDF:
Formicio Insights_Powering up the ‘Service’ in Shared Services

It is widely acknowledged that only a very small proportion of large-scale change programmes are successful. In fact this figure is only 5% according to John P Kotter, author and professor emeritus at Harvard Business School. Yet over the past 30 years there have been thousands of papers and books published on how to manage change. So what’s going wrong? Are we not following the methodologies described in the books, or is there something more fundamentally challenging about the very nature of change?

Whilst there are probably as many reasons for this situation as there are change managers – and change gurus who write the books – my contention is that there is one underlying reason change initiatives rarely meet expectations, and that is because the necessary conditions for change success are rarely identified, established or maintained.

Good gardners understand conditions for success

One of the best ways of describing what is meant by conditions for success is to draw upon a gardening analogy. For those of you who know about gardening you’ll understand that certain conditions need to be in place in order for a garden to flourish, fertile soil being the most obvious. The more successful gardeners know that some of these conditions can be controlled and others cannot. For example, they know that soil quality can be improved and that particular plants will never do well in certain types of soil. They also know that some plants need to be pruned in spring and others in autumn.

If these conditions are not understood or are ignored, gardening can be a costly and disappointing pastime.

Identifying the conditions for change success

A good place to start when looking for the necessary conditions for change success is to begin by fully understanding the target outcomes and then asking “what needs to be in place to ensure that they are achieved?”. Whilst they typically include things like management sponsorship, governance and engagement they could include more context-specific conditions like cross-functional collaboration and working relationships with off-shore partners.

Example conditions for change success

Listed below are a set of conditions for success that typically need to be in place for a change initiative to have any chance of success. It should not be taken as a definitive list and used only to prompt ideas. It’s important to first understand the context of a particular change initiative and then use the list to help identify which conditions for success need to be put in place, remembering that it’s very possible that additional conditions are needed that are not on the list below.

1. A compelling case for change. The ‘default future’ is not a desirable place to be and the organisation needs to move to an ‘improved future’.
2. There is clarity of what success will look like, a definition of the ‘improved future’.
3. The chosen approach to delivering the change is appropriate to the type of change and organisational culture.
4. People who will be impacted by the change are engaged in the process and thereby feel ownership.
5. There are sufficient resources, in terms of numbers and experience, to lead the change.
6. The change is supported by appropriate programme management and governance.
7. Leaders of the organisation understand the target future in sufficient detail to enable them to ‘pull’ the rest of the organisation into the future state.

 Typically there would be between 7 to 12 conditions for success. If there are more it suggests that the key conditions have not yet been identified. One of the benefits of having a small number of conditions for success is that they can be easily monitored over time. This can be done in two complementary ways.

Self assessment

The aim is to get a ‘pulse’ check of how people view the change initiative by inviting a representative group to complete the self assessment, ideally online. The assessment essentially asks people to give their views on:

1. How important they consider the condition for success to be, on a scale of 1 to 5. If the condition is considered to be of low importance then it’s unlikely that it will be given attention. Equally, the fact that people consider it to be of low importance does not mean it’s not important, just that they don’t currently recognise it as such.
2. The extent to which the condition is currently in place, again on a scale of 1 to 5. If a condition is generally considered to be important and not in place, it helps to identify where priority attention needs to be given. 

The results of the assessment can be presented in many ways. One useful way is to present it as a ‘spider’ diagram as illustrated on the right. In this example it can be seen that Programme Management and Governance are important, but not yet sufficiently in place. It also shows that the leaders of the organisation are ‘pulling’ to the future, but it is not considered to be important.

These diagrams can be presented for each individual who completed the assessment or overlaid with many assessments to get a composite picture.  

Qualitative interviews

Often undertaken in conjunction with the self assessments described above, these interviews aim to understand the thinking behind the assessments given and identify if a condition for success has been missed or a new one is emerging. Furthermore, they are a useful source of ideas as to what actions could be taken to strengthen the conditions for success.

Whilst not trying to stretch the gardening analogy too far, in my judgement all too often the focus is on doing change stuff (the equivalent of buying and planting) rather than spending time understanding what conditions for change success need to be established and maintained.

It is not the purpose of this article to describe a comprehensive approach to change, but simply to highlight a common mistake that is often taken when shaping a change initiative. It is hoped that the ideas presented in this article will stimulate you to think about whether you have the necessary conditions for success in place for your own change initiative.

I welcome your thoughts.

David Trafford
david.trafford@formicio.com

Download as a PDF:
Formicio Insights_Establishing Conditions for Change Success

What is ‘strategy’?

There is much talk – and also much confusion – about strategy. So let’s be clear and let’s be simple: strategy is about choices. More specifically, it is about making a small number of choices about things that once decided upon are difficult, if not impossible, to reverse or un-do. A strategic choice about outsourcing all or part of a company’s supply chain or IT services is not a decision that can be un-done either quickly or easily. A strategic choice to focus on growth from new and emerging markets – whilst exiting more mature markets that have flat-lined – is not one that can be reversed easily. A personal decision to emigrate to another country or take up a new position is not one that can be easily reversed.

So, if strategy is about choices, it follows that other options must have been considered, evaluated and rejected in favour of those options selected. As Michael Dell, CEO of Dell Computers, said over a decade ago:

“It’s as important – if not more important – to be clear about what we have decided NOT to do as it is about what we have decided to do.”

One way to think about strategic choices is that we are explicitly selecting between two or more credible options. Take sourcing as an example. As a company or organisation, we can decide between two equally valid alternatives:

 “We are self-sufficient in everything we do within our supply chain.” Or

“We focus on those parts of the supply chain where we can add most differentiated value to customers – and find partners to be excellent at those parts that we choose not to excel at ourselves.”

It is not that one choice is right and the other wrong – it’s more the case that each choice has a very different set of implications. One of the best ways of understanding a choice is to fully understand and stress-test the implications of each choice. For example, the first choice above implies that we will have or develop ALL the capabilities, skills and competencies required across the whole of the supply chain. The second choice implies that we will have, or we will have to develop, critical new capabilities, skills and competencies that are essential to managing third-party relationships for maximum value.

Strategy therefore involves a small number of critical choices about what we will and will not do when faced with a spectrum of options.

What does strategy cover?

Let’s make another, important and clear distinction: strategy is about making choices that deliver on a small number of critical business outcomes. Strategy is not an end in itself – its key purpose is to deliver on the small number of critical business outcomes that define success for the enterprise. Having clarity and alignment of the leadership team around these outcomes is therefore a pre-requisite for a strategy to be successful.

So, if strategy is about choices, what kinds of choices are involved? This is the cause of most confusion in setting strategy – not least because different parts of the organisation will focus on different areas of choice, and the choices they make may not add up to a coherent whole, or worse, may actually be in conflict with one another.

For example, in financial services, the private banking arm would probably focus on a value proposition of customer intimacy or excelling at the quality of the private banking customer experience. However, the back-office services arm, which is often shared across private, retail and corporate banking customers, would most probably focus on a value proposition of operational excellence – which will seek to optimise service levels and cost. These two choices may actually be in conflict unless there are explicit discussions at the right level.

In most commercial organisations, the domains of strategy typically cover:

• Marketplace choices – the products, services, customer-market segments, geographies and channels to market.
• Enterprise Operating Model choices – the degree to which the enterprise is horizontally integrated (see Formicio Insight article The Challenges of Horizontal Integration).
• Sourcing choices – the extent to which services are sourced from external partners.
• Customer choices – the experiences we want our customers to have.
• Culture choices – how we want colleagues to feel about their organisation and their work.

Who decides strategy?

The role of functional leaders is to explore and debate critical choices within their own functional areas; the role of the CEO and the leadership team is to reconcile and synthesise across these choices, to identify and resolve conflicts, and make the best overall choices for the enterprise as a whole.

Taking our private banking example above, the enterprise may well decide that delivering a superior private banking client experience is absolutely the correct choice; and that whilst operational excellence is the right choice for Operations, part of its service delivery will be ‘tuned up’ for higher levels of service for Private Banking – and the additional cost will be passed on to the higher-margin Private Banking business. It is essential that these choices – and their implications – are taken consciously and explicitly. Far too often these choices and their implications are ‘fudged’ or compromised rather than being debated in the open.

What is strategy useful for?

So, if strategy is about conscious, explicit choices across a spectrum or landscape of options, what is the on-going value and purpose of strategy once it is formulated? We believe the fundamental uses of strategy include:

• Creating a clear line of sight between the small number of critical business outcomes and the strategies and plans for achieving and sustaining them. Clarity of these outcomes and clarity of the choices we have made to achieve them are essential for strategy to be successful. Best-in-class companies will talk about ‘strategy on a page’ – a single page or picture that clearly articulates those business outcomes and the strategies to achieve them. One global executive recently described his version of this as being a single slide for the executive board, 10 slides for the leadership/management team and 15-20 slides for the rest of the organisation!
• Creating alignment around and commitment to the choices taken on the part of the enterprise’s leadership team. We call this building ‘collective leadership’, as opposed to simply ‘individual leadership’. This enables and sustains consistent communication to the whole of the enterprise and the right context for decision taking.
• Creating another clear line of sight between the top-level strategic choices and the day-to-day decision-making, planning, operations and implementation of the strategy.
• Providing a context for prioritisation and decisions about where to commit the enterprise’s scarce resources. When John Rice (now Deputy Chairman of GE) was CEO of GE’s Power Systems business in Atlanta, he used to personally chair the Prioritisation Committee and ask how each proposed new initiative contributed to one or more of his three strategic thrusts or themes: Profitability, Growth and Connectivity (with customers and suppliers in the whole eco-system of designing very large power plants).
• Communicating to and engaging with everyone in the enterprise around the right priorities – and therefore harnessing the entire wisdom, experience and capabilities of the enterprise in pursuing and implementing the strategy.

What’s the greatest risk?

For most organisations the greatest risk is not the choices they make, but the capability to implement them. If strategy is about making choices that take the organisation in a direction it’s not currently headed, then it’s highly probable that it doesn’t have the capabilities it needs to succeed in the new world. To misquote the famous management guru Mike Tyson: “Everyone has a strategy until they get a punch in the mouth”. Inevitably when implementing strategy organisations will get the equivalent of a punch in the mouth, things will not go according to plan and there will be setbacks. It’s therefore important that when making strategic choices due consideration is made to:

1. The organisational capabilities needed to successfully implement the strategy, and which in turn will need to be developed or acquired.
2. The challenge of changing existing mindsets. If people see the world in a particular way it will take more than the publication of a strategy to get them to see the world through new lenses.

Making strategic choices is deceptively simple and inherently difficult

Strategy is both deceptively simple – involving a small number of critical choices that cannot easily be reversed in the pursuit of a small number of critical business outcomes – and inherently difficult – requiring, grown-up, adult, ‘crucial’ conversations within and across the leadership team about the rationale for one choice versus another. Furthermore, strategy should not be confused with planning and prioritisation, which although difficult and complex do not involve the kind of irreversible choices involved in strategy. In a fast-moving and constantly-changing world, strategy should be living and dynamic, rather than static and some kind of one-off exercise.

An ancient Japanese proverb says: “Vision without action is a daydream; action without vision is a nightmare”.  In our world, strategy and execution are both equally and critically important to succeed.

I welcome your thoughts.

Peter Boggis
peter.boggis@formicio.com

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Formicio Insights_Strategy

A simple straw poll of any group of senior executives shows us that our companies and corporations are being led by very well educated groups of people. A significant proportion of the people in the room will have a degree and a large number will have obtained a post graduate qualification of some kind. When asked about more recent training, many will be able to recall the company run management training programmes that they attended in the earlier days of their careers, and some will talk about classes they have attended to learn about developments in their areas of professional expertise. However, when asked what their current personal development plans are most will shrug their shoulders and admit that, despite requiring it of the people who work for them, they don’t have any current plans because they are too busy dealing with the ever increasing and complex problems they face leading their parts of the organisation. The unfortunate reality is that most senior executives are relying heavily on old, and sometimes outdated, learning, and don’t have either the time or the motivation to attend classroom-based development programmes that take them away from business critical issues.

Experiential learning cycle

Of course, this does not mean that senior executives are not continuing to learn. David Kolb’s seminal work on experiential learning in the 1980s[1] taught us that we continuously learn through a four-stage cycle of; Concrete Observation > Reflective Observation > Abstract Conceptualisation > Active Experimentation. In other words, we see something, we think about it, we consider how we might apply it to our situation and we try it – we learn through experience. This process works well for managers in their early careers as a lot of what they are observing is new and presents them with a multitude of opportunities to further their learning and development. However, as time progresses less and less of what managers observe can appear to be new, no new insights are regularly introduced, and they begin to do things the way they always have because it has worked in the past. In the worst case scenario, when managers face a new situation that all of their past learning and experience has not equipped them with strategies to deal with, they revert to old tried and tested strategies that are inappropriate and lead to ineffective outcomes.

Powerful learning experiences

When a group of senior executives are asked to describe their most powerful learning experiences, ones where they feel they have really grown as a result, it is very rare for them to cite their time in further education, their attendance at a conference or even a training course. In most cases senior executives refer to a time when they successfully faced a challenging situation that took them out of their comfort zone and stretched them both intellectually and emotionally. They will often refer back to the fact that they were learning with others whilst delivering something important, and that there was someone who was guiding them along the way. 

When senior executives are describing their most powerful learning experiences the context within which they have occurred generally falls into one or more of three categories. Powerful and lasting learning occurred for people when;

1. They took up a new role or assignment within the organisation, where they found themselves in a situation that took them out of a current comfort zone and stretched them both intellectually and emotionally.
2. They were thrown together with colleagues to solve a specific problem or develop a new organisational capability, often when the approach and solution was new to all involved.
3. They were collaborating with peers outside of their organisation to explore a novel situation or issue that was of particular importance to the future of their organisation.

Another set of common themes that come through from senior managers describing their most powerful learning experiences are those relating to what they believe made the learning effective, which are that;

1. They felt that they were guided by an individual who was able to direct them towards powerful insights and then help them reflect and conceptualise how the insights might influence the choices they were making.
2. They valued the fact that the learning process was not defined at the outset. What was important was that the organisational outcome was always kept in sight and the learning process was adaptive, it was constantly reviewed with the target outcome in mind. The guide would provide access to learning opportunities such as visits to suppliers or other companies, access to thought leaders, appropriate reading, mentoring etc, at a point in the process where the maximum value could be gained.
3. They were, at all times, anchored by an organisational need. They were motivated by the need to improve their organisation by applying what they had learned and reviewing the impact that they had had.

Senior executives’ descriptions of their most powerful learning experiences are, in most cases, about experiential learning and can be summarised in the diagram below.

Guided, adaptive, anchored

The choice of the learning guide is critical as they will ensure that the learners are clear on their destination and the desired outcome for the organisation, are heading in the right direction, are seeing the right things along the way, and are learning from the experience. An experienced learning guide is a catalyst who;

• Asks questions, not only to draw out individual answers, but also to encourage fundamental insight into the issue at hand.
• Regularly reviews what has been learnt and adjusts the journey accordingly, introducing access to new insights as required.
• Ensures that the learner is actively involved in the experience.
• Helps the learner spend time reflecting on the experience.
• Helps the learner use analytical skills to conceptualise the experience.
• Helps the learner use the new ideas gained from the experience.

An experienced learning guide will make a huge contribution to the success of a learning journey, but ultimately the learner must;

• Be willing to move out of their comfort zone.
• Be willing to be actively involved in the experience.
• Be able and have time to reflect on the experience.
• Possess and use analytical skills to conceptualise the experience.
• Possess decision-making and problem-solving skills in order to use the new ideas gained from the experience.

The role of experiential learning in executive development

In conclusion, as a manager’s career progresses they have less time for, and learn less through classroom based development programmes, but potentially learn more and more from challenging experiences in the work place. If their experiential learning is not guided, adaptive and anchored they face the danger of recycling old, tried and tested experiences, which result in the development of strategies that are inappropriate to the new and complex challenges they face. When senior executives find themselves facing a new context they should enlist the support of an experienced learning guide to help shape the developmental experiences and resultant learning necessary for them to deliver a successful business outcome.

I welcome your thoughts.

Peter Turgoose
peter.turgoose@formicio.com

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Art, science, mathematics, technology, engineering and medicine became concentrated in silos around the time of the reformation. This both accelerated the disciplines whilst holding back the benefits to be gained from their linking. Today they are coming back together as a much-required force for innovation and understanding at a time when we are being progressively overtaken by vast amounts of data. This in turn demands complex combinations of modelling and visualisation to engender understanding, establish confidence and aid decision-making.

To put human progress in perspective it is worth remembering that all of our achievements up to the industrial revolution were eclipsed in the first 200 years immediately after. Similarly, the information revolution eclipsed this progress in just 20 years. This is the nature of exponential progress – machines breed better and more powerful machines, but in a much shorter time. This powers further discovery and leads to more information and understanding. Human knowledge is now estimated to double every two years. Unfortunately, our wisdom seems to progress at a somewhat slower pace!

Whilst visualisation is the fastest way for us to assimilate and understand complex situations, we remain limited in our ability to comprehend dynamic multi-dimensional situations beyond level 4 or 5. This dictates the use of additional machine support and more senses than sight alone. Animation, modelling and haptic interfaces are now at the forefront of our efforts to come to terms with complexity.

Here we sample some of the tried and tested visualisation techniques and then go on to examine the rise of Artificial Intelligence (AI) and how it might further impact our efforts to understand the ever more complex scenarios that we face today and in the future. At the cusp of this work is the very understanding of intelligence itself.

Technology perspectives

In the period 1975–95 all the technologies of visualisation we enjoy today were in their infancy. Electronic displays, Virtual Reality (VR), Augmented Reality (AVR), 3D, Stereo and Surround Sound, Tactile Gloves and Haptic Feedback all existed. But, it was all basic, big, power hungry, expensive and the preserve of corporate, government and university laboratories with sizeable budgets. Since 1995 technology advances have seen huge improvements in resolution, fidelity, sensitivity, power consumption, size, weight, and dramatic reductions in cost.
 
In addition, computing power and memory have grown exponentially, with optical fibre and wireless connectivity becoming near ubiquitous. There has also been a realisation that networking is a primary mechanism for collaboration and advance. Further developments of note are those in humanoid and non-humanoid robotics, telepresence, artificial life, modelling and games, 3D replicators, nano-structures, bio-manipulation and design, plus of course the rise in machine-based intelligence.

However, the word ‘visualisation’ conjures TV or PC screens, VR headsets and caves. We conjecture that we need more because human awareness mostly involves five senses and not one! At the very least we can engineer three of these today: sight, sound and touch. The remaining two are not impossible, but they are difficult and generally have less impact in this field.

There is now one outstanding dimension we should also consider for inclusion. In real world environments most animate objects respond in some way that can be interpreted to be ‘intelligent’. So the question is; could AI provide further and significant enhancements to the world of visualisation? Certainly the world of computer games and virtual worlds would suggest so!

Big problems

The technologies of search, navigation and interaction are now established and understood in the world of the PC and the internet. Their shortcomings are also well documented and the need for further advancement is abundantly clear. What use is a search engine that tells you that there are 97,763,400 references on AI, and here are the first 10? Similarly, a computer output to a problem that runs to 120,000 x A4 pages! Clearly, we have some way to go.
 
How could AI help? How about monitoring our activities and any collaborators in order to narrow searches, present relevant data when we ask, and take pre-emptive action when we do not? And how about identifying individuals and teams that are working on similar or symbiotic problems so we could link, share results and collaborate? But there is a bigger prize! We also need computer models, situational awareness and decision support.

Whilst building facsimiles of the real and unreal worlds is difficult, expensive and time consuming, AI systems should be able to ‘guide our hand’. After all, AI has done so for some time in other spheres such as designing the chips, boards and wiring in this computer I am using to type these words for example.

What kind of intelligence?

When Gary Kasparov was defeated by Deep Blue (1997), he and the world of chess were outraged. Sound bites included: “something strange is going on; it didn’t play a regular game of chess; it didn’t play like a human; it didn’t play fair”, etc. No one asked the most important question; how did it win? The key here was a new intelligence had entered the game; a powerful computer that didn’t, or couldn’t, think like us; and nor should it, because it was bringing something new – a new dimension, a new way of solving the problem. That was the value of Deep Blue – a new approach.
 
Today we are constantly surprised by AI systems and the answers they contrive, and on many occasions we lack the facility to fully understand. But that does not preclude us from using the results! We have gradually realised that the solution of many industrial, scientific and governmental problems will continue to defy human abilities.
 
So far our partnership with machines has proved profitable, and what lies before us is an even richer future, where the combination of AI with Artificial Life (AL) will almost certainly see the spontaneous creation of new intelligences.

Defining intelligence?

There are well over 100 published definitions of intelligence. Unfortunately, none of them provide any real understanding, enlightenment, or an iota of quantification. Worse, the long established IQ measure by Alfred Binet (1904) is both a flawed concept and a really unhelpful idea in this instance. 

In engineering a commonly used comparison technique is to count the number of processors and interconnects, and then multiply the two to create a single figure of merit. This seems far too simplistic to be meaningful and does not reflect any notion of intelligence. In fact, estimates of machine intelligence on this basis would suggest HAL 9000 (2001: A Space Odyssey) should be alive and well at this time, but clearly he is not! Recent research has shown that individual neurons are not mere ‘on–off switches’ with synapses that discharge into a network of fixed interconnections, but individually intelligent entities that dynamically reconfigure.

So all the prior art that assumes that a brain scales linearly appears to be flawed, and the mechanism has to be far more complex and subtle. To put this in context we can relate many real life experiences, observations, signal theory and thermodynamics.

Cutting to the chase, the primary argument goes along the following lines:

1. Slime moulds and jellyfish (et al) exhibit intelligent behaviour without a distinct memory or processor – they have ‘directly wired’ sensors and actuators.
2. Our machines have distinct memory and processing entities, but this is seldom so in organic systems where there are overlaps in functionality.
3. Whilst intelligent behaviour is possible without memory or processor, and simple sensors and actuators alone can furnish that facility, the converse is not true – sensors plus actuators are a prerequisite to intelligence.
4. All forms of intelligence encountered to date invoke state changes in their own, and external environments with an expansion or compression of the quantity of the original information input. For example; the answer to the question “why is the sky blue?” would contain far more words, whilst the reply to “do we know why the sky is blue?” would be a simple yes!

So it seems reasonable to assume an entropic measure to account for the reduction or increase in the system information or state change. We therefore define our comparative measure of intelligence as:

The Change in Entropy = Ic = IEi –EoI

Where Ei = Starting entropy and Eo = Completion entropy

A reasonably general formula for simple machines results from a combination of analysis and adjustment to meet practical system limitations as follows:

Ic = K log2[1 + AS ( 1 + P.M)]

Where the parameters S = Sensor, A = Actuator, P = Processor, M = Memory, are related to weightings of the complex operators involved.

We can now confirm two essential properties: with zero processor and/or memory power intelligence is still possible, but with zero sensor and/or actuator power it is impossible. This is consistent with our life experience and experimental findings.

There is now a further observation, one that flies in the face of the conventional wisdom of those that worry about ‘The Singularity’ of the machines taking over because they outsmart us, that the speed of intelligence growth is logarithmic and not linear.

So, a 1,000 fold increase in the product of Processing and Memory (P.M) power, only sees intelligence increase 10 fold by virtue of the log2 function. Hence a full 1,000,000 increase in P.M sees intelligence grow by a factor of 20 times. This is far slower than previously assumed and goes some way to explain the widening gap between prediction, expectation and reality!

A further important observation is that sensors and actuators have largely been neglected as important components of intelligence and visualisation to date. This oversight is one that we should now be addressing as we advance the science and application of both fields.

What does all this mean?

With the arrival of a myriad of sensor components and their rapid deployment on the periphery of networks, the internet, robotics, large and small systems, we are much closer to creating true (artificial) intelligence than ever before. And when combined with our existing and established approaches to visualisation it could result in some significant advance in the way we view, experience and react to complex situations.  

Interestingly, this will also see a marked change in the way our systems react to us! So if this is only a matter of when, and not what if, there is only one question left to ask; will we be smart enough to recognise a new intelligence when it spontaneously erupts on the internet or within some other complex system we build?

I welcome your thoughts.

Peter Cochrane
peter.cochrane@formicio.com

This paper was first presented at the BCS EVA Conference, London, 5-7 July 2010

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Formicio Insights_Artificial Intelligence Will Help Us to See and Understand

While there is no shortage of ideas on what changes to implement, many IT organisations find it difficult to incorporate one set of changes before the next new idea presents itself. Equally, many are attempting to incorporate so many changes that it’s difficult for them to see the inter-dependencies and take a holistic view of how the whole should operate. As a result, many changes take longer to implement than planned and fail to deliver the full expected value.

The ability to incorporate new ideas faster and coherently is therefore an increasingly important issue for many IT leaders. So what can be done to make the IT organisation more agile and better able to incorporate new ideas faster?

The following slideshow is Formicio’s point of view on making IT organisations more agile. It argues that IT agility is an organisational capability that can be developed or destroyed by the actions of leaders, and that organisations are more likely to be agile if they adopt agile operating principles. The point of view has developed and evolved over many years. We hope you will find it interesting and helpful.

David Trafford
david.trafford@formicio.com

The following slideshow is Formicio’s point of view on experiential learning. It discusses the different forms of experiential learning, the principles of effective experiential learning, the role of the learning guide and the conditions for learning success. The point of view has developed and evolved over many years. We hope you will find it interesting and helpful.