If you’re in any kind of business, you’ll know who your clients are: you deal with them every day. And serving their needs will no doubt take up much of your attention, too.
And you, or someone in your organisation, will know who your prospects are – the people who aren’t clients yet, but who could or should be at some time in the future. Finding them, relating with them and paying attention to their present and future needs will take up a lot of someone’s time and attention, even if it’s not your own.
But do you know who your anti-clients are? Are you even aware that they exist – or how much impact they can have on your enterprise? Because if you don’t – and you don’t pay attention to their needs too – you could well find yourself out of business…
To make sense of who or what those ‘anti-clients’ are, and why they’re so important, you may need to think sidewise for a while, perhaps taking in a more expanded view of ‘the market’ and a broader-than-usual understanding of ‘enterprise’.
The enterprise and the market
The quick summary is that every market is the intersection of at least three very different ‘economies’: transactions, attention and trust. (The trust-economy is also known as the reputation-economy, because reputation is a kind of secondhand trust that we garner from others.) For much of the past century, most organisations focussed almost exclusively on transactions, sometimes barely even recognising the existence of the other economies – or else assuming that they didn’t matter, because large organisations could monopolise attention through mass-media, and ignore customers’ concerns by sheer dominance in the marketplace. But in the past decade or so, ubiquitous access to the internet and mobile-media have changed the game completely. The old days of control and the one-way one-to-many broadcast have gone: welcome instead to a new age of business transparency, where your products, your prices, your customer-services, your mix-ups and mistakes, your honesty (or lack it), your everything, is almost wide open for everyone to see – and you have no control over any of it at all. So that means that the attention-economy and trust-economy come right to the fore, as almost the only choice you have in this. Which means that you now must pay real attention to your anti-clients – or they’ll crucify you. With glee… whether you deserve it or not…
The other key to this is to recognise that the enterprise is always greater than the organisation. Once we understand this, it becomes useful to categorise the people beyond our organisation in five different ways:
Clients and prospects are straightforward: they’re people who’ve done business with you, and/or who probably will do so in the future. Every business knows how to work with them, or it wouldn’t be in business – that’s what CRM systems and shops and service-centres are for, for example.They matter a lot, obviously, but we can skip over them for now.
Ex-clients are people who’ve been clients at some point in the past but who, for a wide variety of reasons, no longer engage in transactions with the business; non-clients are people who’ve never done business with the business, and are never likely to do so. They’re not prospects, and they’re not clients – hence in terms of the transaction-economy alone, of no apparent value to the business. Hence many businesses either ignore them, or else try to demand their attention via the scattergun strategies of mass-marketing – those dreaded seven-o’clock-in-the-evening calls that consist of nothing but pre-scripted spiels from the commission-driven klutz at the call-centre. Which is extremely dangerous, because either way it’s a quick way to convert ex-clients and non-clients into anti-clients – and that’s not a wise move in the internet age.
Anti-clients are people who are the active opposite of clients. Your ex-clients and non-clients are merely not-interested: they’ll reject your organisation, but only in the form of a passive non-engagement. But anti-clients are different: not only will they not engage in transactions with you, they will actively reject engagement with your and your organisation – and incite others to do the same. In some cases – such as environmental activists, for example – you may have no direct contact with them at all. Even if you’re not aware of them, they can still destroy your reputation before you know what’s happened. And if you lose your reputation, you’ve lost people’s trust; if you lose trust, you’ve lost people’s attention; if you lose people’s attention, you’ll have lost their transactions, which in turn means you’ve lost any possibility of profit. Without trust, your prospects evaporate, your clients become ex-clients – and unless you’re aware of your anti-clients, you’ll have no idea why.
But the worst part of this is that we convert ordinary people into our anti-clients, through our own actions or inactions. For example, many marketers think that using call-centres and the like is just a numbers-game – which it is, but not in the way that they might expect. Call-centres might make profit if just one cold-call in a hundred converts into a real transaction; with online spammers it can be as low as one in a million. But what they do in the process is annoy a vast number of people who are not interested at all and don’t like having their attention stolen by the spammers – which can turn them into active anti-clients. Would you buy double-glazing from someone who rings you up whilst you’re in the shower? – or are you more likely to avoid doing business with them in future? If the time-wasting phone-calls become more than just annoyance – the seventh time this evening, for heaven’s sake! – aren’t you likey to become an active anti-client for that firm, seeking to do anything you can to stop those darn calls coming in? Now imagine that happening hundreds, thousands, millions of times a day: that’s a lot of anger building up there, and at some point someone is going to cop the lot… That’s what happens when we create anti-clients.
A real example: ‘United Breaks Guitars’
Musician Dave Carroll had been an ordinary everyday client of United Airlines, until the day that careless baggage-handlers broke his very expensive guitar. Quite reasonably, he asked for compensation to cover repairs; but as he explains in a statement on his weblog, just about everyone in United, at every level, gave him the run-around, for almost a year:
At that moment it occurred to me that I had been fighting a losing battle all this time and that fighting over this at all was a waste of time. The system is designed to frustrate affected customers into giving up their claims and United is very good at it. However I realized then that as a songwriter and traveling musician I wasn’t without options. In my final reply to [United's Customer Service representative] I told her that I would be writing three songs about United Airlines and my experience in the whole matter. I would then make videos for these songs and share them on YouTube, inviting viewers to vote on their favourite United song. My goal: to get one million hits in one year.
The first song, complete with catchy chorus and happily satirical video, was duly posted up on YouTube a few months later: United Breaks Guitars. Someone in United Airlines finally realised they had a significant PR problem by the time the video had already had 50,000 hits – barely an hour or two after it was first posted. And there was nothing that United could do to stop it: it was on a popular public website, with no libel or anything else that any lawyer could reach. Three days later, the video had already gone well past the million-hits mark, and had appeared many times on national and then international TV news – with United left floundering in full-on damage-control, their vaunted reputation visibly in tatters. Not trivial at all.
In reality, United’s complicated buck-passing games to avoid paying a customer’s entirely reasonable claim would almost certainly have cost them more money overall than if they’d paid up-front in the first place – a good example of a failure to understand whole-of-system costs. But in this case those games to ‘save’ the relatively small sum of $1200 ended up costing the company untold millions of dollars in many different ways, both direct and indirect. That’s the amount of damage that just one committed anti-client can do to a very large, very powerful corporation: just how much damage could your anti-clients do to yours? And what could you do to prevent that from happening?
Step 1: Recognise that anti-clients will always exist, and that they can cause very serious problems for your organisation.
Step 2: Recognise that your anti-clients are never going to be under your control. (This is where distinguishing between ‘organisation’ and ‘enterprise’ is helpful: an organisation is bounded by rules, and you can control within those bounds; but an enterprise is bounded by shared-commitment, where control doesn’t work – but honest negotiation can.)
Step 3: Recognise that your anti-clients’ grievances are real to them – and that’s all that matters in practice. Whether or not those grievances seem real or fair to you is almost irrelevant – and arguing about it is not going to work.
Step 4: Recognise equally that ‘giving in’ to every complaint is not going to work for you. (Or, ultimately, for the anti-clients either, but they may be too angry to understand that at first). You need to establish common ground where negotiation can take place – preferably before it gets to the level of active anti-client action.
Step 5: Establish the common-ground by identifying the ‘vision‘ and values that provide the common-cause for every player in the extended-enterprise. (See ‘Vision, Role, Mission, Goal‘ for more on how to do this. Note that this is not a marketing exercise! In United’s case the Vision would be something like “safe, convenient, reliable travel”, with United taking a Role of “provider of medium- to long-distance travel by air”.) In effect, these define what quality means within the enterprise – and hence within your own organisation too.
Step 6: Compare and review the organisation and its procedures against those values and the vision – starting with any customer-facing activities, but eventually extending throughout every aspect of the organisation. This needs to be understood as a quality-review in the most fundamental sense: any improvements here will improve quality within the whole organisation and in its relationships with the broader enterprise – which should reduce the risk of creating anti-clients through carelessness.
Step 7: Use the vision and values as a rallying-point to connect with all of the organisation’s stakeholders on their terms, via the various ways in which they they themselves engage with the same vision. In general, this will not and should not be linked directly to the organisation’s marketing. (For an excellent example of how this can work, see The Responsibility Project, created and sponsored by US insurance company Liberty Mutual [more detail here].)
Step 8: Maintain an active watch on social-media, and wherever practicable engage respectfully with all actual or potential anti-clients. One of the most useful tactics to help you in this is to view your anti-clients as allies who can assist in keeping you ‘on track’ towards the ‘vision’ of the enterprise.
Repeat indefinitely. Doing this will not only help to pre-empt any potential anti-client problems, long before they cause serious damage, but will also improve your overall quality – and your bottom-line as well.
One of the most common business metaphors is the market. But what exactly is a market? And how does that metaphor help us understand the wider economy within which the business will act? It’s worth thinking sidewise for a while to make better sense of this. First, whilst we may talk about ‘the economy’, there are actually at least three different ‘economies’ in action:
- the transaction economy – the exchange of goods and services
- the attention economy – the personal and shared use of our time and attention
- the reputation economy – how and why (and whether) we trust each other, to do business with each other and spend time with each other
All of these are interweaving in the market at every moment: transactions depend on attention, which in turn depends on mutual trust, and so on. And the market itself has at least four distinct dimensions:
- markets are transactions
- markets are conversations
- markets are relationships
- markets are shared purpose
Markets are all of these, all together, all at the same time. So let’s wander around the market for a while, to see all these in action. First, it’s obvious that markets are transactions, because that’s the most visible part of what’s going on. Goods and money changing hands, services ordered, bills paid, and so on. Markets are transactions.
Price matters, of course. But despite the theories of ‘monetarist’ economists, markets aren’t only about price: if we look around, it’s also clear that markets are conversations. Not just that there’s a lot of talking (shouting!) going on, but also advice on how to use things, what sauce would be best with this cut of meat, warnings about torque-wrench settings for worn-out parts on the old engine you’re fixing up. Sometimes the conversations might include a bit of ‘up-selling’, but if you push it too hard you’ll lose the whole of the sale. And if we’re too busy shouting “My bananas are the best in the market!!”, we probably won’t even notice the quiet guy at the side of the stall who’s too timid to ask to buy them – so we can lose the sale that way, too. One of the most important lessons in both marketing and sales is that markets are conversations, not a shouting-match – and we need to pay attention if we want to be paid in a subsequent transaction. Markets are conversations.
Often a conversation may have nothing to do with the transaction at hand, but are more about creating longer-term connections between people, because markets are relationships too. Transactions only happen when there is trust, and one of the key components in that trust is a sense of relationship. This is part of how brands come into the picture, but it also has a strong personal element as well: for example, you exchange a smile with the woman at the cheese-stall, which may not lead to any immediate transaction – such as because you don’t need to buy cheese today – but may well leave you more willing to go there on the next time you do need to buy cheese. Markets are relationships.
Yet we could also note that there’s more than just one ‘the market’. In fact, there are many different markets, each with its special emphasis. Many towns and villages have their own open-air street-market, like the one in the town I’m staying in right now, with stalls for every kind of small everyday thing that anyone might need: meat and bread and cheese and beans and vegetables and clothes and footwear and the inevitable bootleg-videos. But there’s also the stock-market, where they sell cattle, and the other stock-market, where they sell shares and bonds and hope; there’s the farmer’s market, the specialist cheese-market, the craft-market, and so many others, each with their own special place and setting, their own rules and regulations, their own ways of trading, their own rituals and culture, and so on. Ultimately, markets are shared purpose: they provide a literal and metaphoric space where people can gather to share transactions and conversation, build relationships, and so on, all towards a common aim. And even if that shared aim is not explicit, it’s always there in some form: we know we go to the cheese market for cheese, not stocks and bonds; we go to the used-car market for information on used-cars, not the information on the best tortillas in town. (Okay, we might find that information there, but that isn’t the purpose of the market itself!) Markets convene around a shared purpose.
And markets engage in all three economies: transactions, attention, trust. Although often ignored or forgotten, trust is probably the most important of these: transactions won’t happen unless there is both attention and trust, and attention itself will not be gained without trust. And trust in turn is an economic value because it can be created, and destroyed, by third-parties as reputation: “don’t buy anything from Margarita at the market”, a friend whispers in your ear, “her tortillas are not even fit to feed the pigs…”. Reputation matters: we need to grow it and maintain it just like any other personal or corporate asset. (To imagine a world in which reputation itself could be the key currency of trade, see Cory Doctorow’s novel about a future Disneyland, “Down and Out In The Magic Kingdom”.) The market is all of these, all at once.
So when you hear a reference to ‘the market’, stop for a moment, and consider what that actually means – and what it means for your business, too. Are they talking only about transactions? Or do they – and you – acknowledge the conversations, the relations, the implicit purpose of the market itself? And do they – and you – understand the way in which reputation, trust and the earned ‘right’ to others’ attention all underpin the transactions of the real, live market?
Perhaps something to think about, anyway.
How do you and your staff learn new skills? And what can be done to make it quicker and easier to learn those needed skills? One answer is to explore the patterns in the skills-learning process.
On the surface, each skill is different, and different for every person; yet there are also patterns in the learning-process that are the same for every skill. The most common view, perhaps, is that skills-learning occurs in a linear sequence, with identifiable periods of practice needed to achieve distinct levels of skill:
- pick up the basics (typical: 0~10hrs)
- start out as a trainee (typical: 10~100hrs)
- learn a bit more as an apprentice (typical: 100~1000hrs)
- apply the skill as an independent journeyman (typical: 1000~10000hrs)
- achieve acknowledged mastery (typical: at least 10000hrs)
Whilst that’s largely true, the learning-process within each of those overall stages is nothing like a simple linear progression. Instead, thinking side-wise, it follows a pattern that’s more like the classic seven-turn single-path labyrinth found in ancient Crete and many other cultures around the world.
There’s only one path in a labyrinth: as long as we do keep going all the way, we’ll achieve the end-point – in this case, mastery of the skill.
In colloquial English labyrinth is generally synonymous with maze, but many contemporary scholars observe a distinction between the two: maze refers to a complex branching puzzle with choices of path and direction; while a single-path (unicursal) labyrinth has only a single, non-branching path, which leads to the center. A labyrinth in this sense has an unambiguous through-route to the center and back and is not designed to be difficult to navigate.
So in principle, “not difficult to navigate”. But despite the simplicity, there are all too many opportunities to get lost along the way… So the following is a brief summary of the various stages in the journey through the skills-learning labyrinth, using traditional names for each respective phase.
(prelude) Beginner’s Luck
Starting from Beginnings, we move almost immediately to a point where we seem to have a kind of mastery – but only for a moment. We often succeed, in fact, because we know so little about what we’re doing – which itself can be a source of many difficulties further down the track. We then have an explicit choice: to back out, avoiding any commitment to the skill; or ask “How did I do this?” – and start on the Journey.
(1: Third loop) Control
This phase emphasises Training, moving slowly towards the Apprentice stage. Much of the time the focus will be on rules – the ‘Simple’ domain, in Cynefin terms – and on analysis – the Cynefin ‘Complicated’ domain. Those rules and analyses do seem to give a sense of control, though it’s nothing like the ‘instant mastery’ we achieved back at the very beginning. Yet every now and then things seem to break down – the ‘best-practice’ rules somehow don’t work for us, in our own specific context – and it becomes clear that we are part of the process. At some point, then, we must change direction, and look inwards. Until this point, everything we’ve done should (in principle, at least) have been the same for everyone; this change in direction is also the moment at which the practice changes to a true personal skill.
(2: Second loop) Self
In this circuit we explore our own involvement in the process – the parts of the skill that are specific to us alone. Often there there’s an new emphasis on patterns, on emergence – the Cynefin ‘Complex’ domain. But despite the increasing excperience, and despite knowing more – and having to face challenges of our own that we now need to address – we find our mastery seems to be getting steadily worse. The further we move along this path, the worse our skill will seem to get – until eventually it seems no better than that of a rank Beginner. At that point, it seems self-evident that looking at self was the wrong way to go: so we change direction, trying to revert to ‘the Rules’ to get our skills back on track.
(3: First loop) Survival
This doesn’t do what we expected. The turn-round takes us outward, not inward; far from bringing us back to Control, it takes us to the Cynefin domain ‘Chaos’… Although ‘the Rules’ haven’t changed, we have – and it’s all too easy here to fall into the dreaded ‘sophomore slump‘. In particular, there’ll have been a key personal shift, from ‘unconscious incompetence’ to ‘conscious incompetence’: but an unfortunate side-effect of that increased awareness is that we can now see that ‘incompetence’ – hence it will often seem that nothing works. Stuck on the outer – in several senses – this can seem like a struggle for survival, an endless cycle of “practice, practice, more #!%*&%*! practice”. And comparisons with others only make it worse: everyone seems better at this than we are. This is the worst stage of the Labyrinth, and by far the longest… and as with the previous loop, the longer it goes on, the worse that feeling gets.
(key-point) Dark Night of the Soul
Then comes a key point – classically the day before the exam, or just before (or after) the presentation to the Board – where we’re brought face to face with our apparent incompetence. We realise we’re further away from mastery than when we first started: seems we’re not just worse at this than a Beginner, some raw recruit, we’re no good at all… Traditionally described as the ‘Dark night of the soul‘. this bleak moment of despair can also be called the “Oh, @#!* it!” point.
- It’s crucial to understand here that this period of despair is a normal and necessary stage of the skills-learning process – a crescendo of ‘conscious incompetence’ that is the gateway to the beginning of ‘conscious competence’.
Whilst the despair is all too real, and may well seem as if it will last forever, there is a way through – if we can find the strength to keep going. The danger here is that if we give up at this point, walk straight on and break out of the Labyrinth – as the steep turn encourages us to do – we lose everything we’ve gained, except for a large dose of disillusion… Instead, the key is to trust – ‘to listen to the heart’ – and choose to care about the skill for its own sake rather than for any extrinsic reason. By accepting that we know we don’t know and can’t know – a return to the Cynefin core domain of Disorder, a “surrender to the ‘cloud of unknowing’ and the ‘cloud of forgetting’”, in traditional terms – there’s a sudden breakthrough, a change as fast as that at the beginning: from Chaos we suddenly find ourselves almost at the centre once more. A brief moment of calm: then the Journey continues, changing direction again.
(4: Fourth loop) Caring
Here, for the first time, our effective skill at last extends beyond the best of training – though it’s been a long haul to get here. It also never falls back below that level, as if at least this level of skill has become ingrained into our very being. But there’s another important twist, because, as indicated by the current scientific research on extrinsic versus intrinsic motivators, the usual external ‘carrot and stick’ motivators – promises of reward, or threat of punishment – that pushed us to succeed at the Training levels not only cease to work here, but often make things worse, damaging the quality of decision-making and the like. (In that sense, banks’ bonus-schemes were almost certainly a primary cause of the current global financial crisis.) What does work is caring: finding value in the work itself, and what it means in terms of personal and shared values. So to go further into the skill, we need to care about what we’re doing and why we’re doing it, and care about the skill for its own sake: in effect, “a commitment of the heart as well as of the head”.
(5: Seventh loop) Meditation
At another key point, the quiet euphoria of the previous stage fades as a new focus comes to the fore. This is a different form of observation and self-observation which could be described as ‘thinking about feeling’ – a kind of meditation, a deep, often intense and personal absorption in the work and its processes, yet at the same time seemingly almost detached from it, as if observing from the outside. This sense of engagement in the context is essential for successful action in the Cynefin domain of true Complexity. For a while – and especially to outsiders – this may well seem like mastery: yet there’s actually still quite a way to go before we get there.
(6: Sixth loop) Mind
In yet another disorienting shift of perspective, ‘thinking about feeling’ becomes ‘feeling about thinking’, as the previous changes in practice become embedded at a much more visceral level. For some skills this will literally be ‘embodied’, as in the development of ‘mechanics’ feel’, or the subtle delicacy of touch so essential to true musicianship. In the ‘knowledge worker’ skills that are more common in the business context, this would be embodied more as the deep-learning expressed in an experienced manager’s intuitive grasp of a complex real-time business process, a product-designer’s ability to elicit customers’ real unspoken needs, a trader’s test and trust in hunches and ‘gut-feelings’ about the subtle ebbs and flows of the market. This kind of awareness and sensitivity is essential to work well in what Cynefin describes as the Chaotic domain – the domain of inherent uncertainty, the salesman’s ‘market of one’, this person, unique, right here, right now. The mind here helps us make the link, back through principles and patterns to everyday practice, though in a way that sometimes seems quite opposite to the way we used the mind when – so long ago – we thought we were in Control.
(7: Fifth loop) Communication
Another mode of thought comes through, to provide reflection and review between sessions of practice – typified by techniques such as the US Army’s deceptively simple After Action Review. Sometimes it may seem as if the skill-level is falling once more – an apparent echo of the struggle back at the Survival stage – but in fact this impression arises solely because we’re paying more attention to the fine-detail of the work. To help us learn more, and also to challenge us to greater competence, we’re also likely to need mutual support from and with our peers – a community of like-minded people with similar skills and similar concerns and interests. The other key theme of communication here is that of helping others to find their own skill. Often this will spring from a kind of altruism: the renewed self-doubt, though much quieter than that in the Survival stage, leads to a sense that even if we ourselves may never reach the pinnacle of mastery, we can perhaps do so by proxy, through helping others to reach it in our stead. Yet this activity of educating others also helps us in our own process of reflection: it’s often said that the last stage of learning is to teach it to others. The result, usually unexpected, unheralded, and without any warning…
…is that we discover that we’ve reached mastery of this specific skill. Yet here we also find that the skills-learning labyrinth has an even stranger twist: it’s recursive, nested, fractal, in that the same overall pattern occurs simultaneously on many different levels. We can be struggling with the Survival level in one skill, or one part of a skill, whilst also experiencing the elation of Beginner’s Luck, the quiet of Meditation, the information-overload of Control and the despair of the Dark Night of Soul in others, all at the same time. Hence plenty of opportunities for confusion, for losing one’s way even in such a simple structure with only one path.
There’s also a social dimension in this. With each circuit, the path alternates from clockwise to counter-clockwise, with the result that everyone on the immediately parallel path – usually either one step ‘later’ or ‘earlier’ – will seem to be going the opposite direction. On top of this, earlier skill-levels will often seem ‘better’ – closer to mastery – than later ones: things seem to get steadily worse as we go onward yet outward from Control to Self to Survival, for example. So others will often try to ‘help’ by telling us we’re going the wrong way, or that we’re doing the wrong things; and we’ll no doubt do the same for them. And even though our immediate cohort would in principle be facing the same way as us, they’re just as likely as we are to be confused by all of this – so they’re likely to ‘help’ us in the wrong ways, too. Tricky…
Learning each new skill takes us into the labyrinth all over again: the tangled, twisted, tortuous path that at times can seem torturous too. Yet in the end, there’s just one simple rule to help us achieve mastery in any new skill: all we have to do is work with whatever comes up at each moment, and keep going, keep going, one step at a time.
Continuous-improvement is the cornerstone of many recent innovations in the business world – Shewhart/Deming quality-management, Six-Sigma, Agile software-development, kaizen process-improvement and lean-manufacturing, to name just a few. The mantra of “release early, release often” has been a factor in the success of many Open Source software projects. And there many other important advantages to continuous change: improvements take effect much quicker, feedback-cycles are faster, there’s better engagement on the shop-floor, and so on. When applied well, such improvements echo all the way down to a much-improved bottom-line – whatever the ‘bottom-line’ may take for that enterprise.
Yet though we may need to think side-wise somewhat to spot it, there’s also one important catch to continuous-change. Continuous improvement depends on large numbers of small incremental changes; the smaller the change, the faster that all-important feedback/improvement cycle can run. But in perceptual psychology, small changes are invisible – a change has to be of significant size or occur at a significant before it becomes noticeable In a well-designed continuous-improvement process, often the whole point is that each change should be almost invisible, because it can reduce the stress of change, and allows potentially-challenging changes to be introduced by respectful ‘stealth’ rather than in a single overwhelming ‘big-bang’. But the more that the improvement-process succeeds in that task, the less anyone will notice each change – which means that the change-team may appear to be doing no work at all. Which is not a good career-move…
Worse, if no-one notices the change, and no-one seems to notice it, then perceptions of product or service may be stuck at first-impressions – which may be long out of date. As ITWorld columnist Esther Schindler put it, in her perceptive article “Why Users Dumped Your Open Source App for Proprietary Software“:
One thing that became apparent is that the lack of features is a perception that may have dated from a previous version. That is, “I tried it a few years ago, and it didn’t do what I needed then, so I chose something else… and haven’t thought about adopting the [software program] since.” If someone tried your app three years ago, back when it was all raw edges and bare metal, how will she know that it might be time to re-evaluate the options? … [She] may not realize that the version she can download today is far improved. Unless she goes out of her way to look, how likely is she to find out?
Sometimes the classic ‘big-bang’ Waterfall-style projects seem successful because their long release-cycles mean that the step-change introduced with each new release is large to be noticed. To quote Esther Schindler again:
One attribute of commercial releases is that major feature upgrades are announced with a lot of fanfare. That happens with open source applications that are household names (assuming an appropriately-geek household), but it’s rare.
…which means that some proprietary projects look better because they use a less-effective change-process. Not exactly a desirable outcome…
Part of this is marketing, of course: a big step-change gives a good excuse for an ‘event’ that’s much more noticeable than a quiet, continuous, stolid, ‘steady as she goes’. Yet that is a tactic that’s worth adopting in continuous-improvement processes: invent an ‘event’ of your own, to celebrate change and advertise the improvements that have been implemented since the last ‘event’. That way you’ll make the work more noticeable – and more valued.
There’s a subtle trade-off here. You’ll want every change to be noticed, but if you set the spacing of ‘events’ too close together, not only will the events blur together too much to be noticeable, but you actually run the risk of increasing people’s ‘change-fatigue’. A common practice in open-source software-development is set formal ‘release-events’ at six-monthly or yearly intervals, even though there’ll often be many ‘point-releases’ in the intervening period. Another useful tactic there is to use names rather than numbers to designate each major change.
Some typical themes in a ‘release-event’ might include:
- Summary of key groups of changes – keep this list short, no more than 5-7 items
- Acknowledgement of key people involved in inventing or implementing significant changes
- Linking process-enhancements to key performance indicators at the whole-of-enterprise level
- Celebration of the value of change itself
Keep each change and each change-cycle small enough to enhance improve effectiveness every day; yet also ensure that overall change is large enough to be visible and valued. That’s the balance we aim to achieve here.
People who know me would recognise that I’m no great fan of the money-economy. Yet that objection isn’t about “money is the root of all evil” and all that, but much more that it’s so incredibly inefficient. To put it bluntly, it simply doesn’t work.
Sure, at a simplistic first glance, it might seem that “money makes the world go round”. But once we start to look at the bigger picture – transactions at a whole-of-system scale – the reality is much more like “money makes the world go stop”. And nowhere is this more evident than at the moment of transaction: if you want to see where pointless, purposeless delays will almost certainly be introduced into a system, look for a place where money changes hands.
This fact was forcibly was brought home to me (more accurately, brought not-home) in yet another snarl-up on the dreaded M25, London’s notoriously problem-prone orbital freeway. “Traffic Congestion Junctions 1-4″, said the overhead sign, “80 Minutes Delay”. True, the traffic did keep moving, but at an agonising crawl: three lanes of jostling frustration, mile after mile. Delay indeed.
After almost an hour, we finally arrive at the cause of all this chaos: the toll-booths on the Dartford river-crossing. Past the stop, go, stop, go, of the toll-booth, and the £1 toll paid, everything eases up, and the traffic flows smoothly again at full speed. Yet that’s another hour of my life gone, wasted to no point and no purpose in a traffic-jam. And I’m not the only one whose life has been frittered away in this manner: all those ahead of me, behind me, and mile upon mile of lock-up for the traffic going the other way on the other side of the freeway. A quick back-of-the-envelope calculation shows that there’s something like 10,000 people stuck in each hour’s-worth of this miserable farrago. Ten thousand hours wasted in that one hour alone, day after day: how much is that costing the country’s economy?
If we take those calculations a bit further, things start to get seriously scary. (I can’t remember if it’s a public utility or a private corporation that runs that toll, but it doesn’t actually matter for this purpose – the sums come to much the same either way.) We’re only dealing with ball-park figures here, so let’s allows ourselves some simple assumptions for this. Let’s say that there’s one person per vehicle, and every vehicle is charged the same flat £1 toll; that there are ten toll-booth operators per side; and that everyone involved in this one-hour scenario is charged out at the same flat £10 per hour. This gives us the following:
- company income: 10,000 vehicles at £1/vehicle: £10,000
- company labour-cost: 10 staff x 2 sides x £10/hour: £200
- company gross profit/loss: £10,000 less £200 = +£9,800
All looks good so far, doesn’t it? As long as we think only of the ‘transactional system’ from the company’s perspective, it all seems to make economic sense. But when we widen the scope to include the overall context, we gain a very different picture:
- total transaction income: £10,000 vehicles at £1/vehicle: £10,000
- total transaction labour cost: 10,020 people at £10/hour: £100,200
- total transaction gross profit/loss: £10,000 less £100,200 = -£90,200
Not so good, is it? And that’s not including the resultant future medical and other costs from all those people stuck in that mess, which could well be many times that figure. Ouch…
Everywhere we look, we find the same problem at the point of transaction. Classic economic measures such as GDP show only the direct monetary profit; but whenever we remember to include all those ‘externalised costs’ in the calculation, what we’ll find is a huge overall loss at the larger scale. All those hours spent waiting in supermarket queues, or waiting on hold; all those days that magically disappear between the time a bank takes the cheque compared to when the money actually appears in the account: it all costs someone. And in the kind of globalised economic system we have today, those costs don’t disappear: they’re real, and they have to be accounted for somewhere in the overall system. The blunt reality is that it’s only by keeping all those all too real costs hidden away in the ‘imaginary’ realm that the money-economy can be made to seem to work – when in fact it doesn’t work well at all.
So to me it’s always interesting to note where some ignored ‘someone’ finally loses patience and starts to fight back, highlighting the fundamental flaws in the system. One well-known example is Marilyn Waring’s classic critique of conventional economics, If Women Counted: A New Feminist Economics. But it’s perhaps even better illustrated in a post that came through on Twitter today, pointing to Paul McCrudden’s website #sixweeks:
For the six weeks from mid-June to end-July 2009, I recorded all the time and money I spent as a consumer. And, having invoiced over 50 companies, I’m now waiting for them to pay me for this time I’ve spent with their brand.
The way I see it, my time on this planet is limited and as such I want to spend it as wisely as possible. It frustrates me therefore that every day of my life I have to waste time standing in queues waiting to buy some product or service that, in the big scheme of things, I don’t really care about.
What riles me is that all this time ultimately helps the company’s bottom line and market share – and I get nothing back for my time as a result. The fact that I’m in [one shop] and not [another] on any particular day results in the former having my attention – and wallet – dedicated to their brand, as opposed to their competitor’s. And yet this time and attention is not reflected in the cost of these companies’ products and services. Prices instead are dictated by raw costs, overheads and item mark-up, with a calculation made as to the number of customers, covers, viewers or users who will support that brand over a period of time. At no point in this calculation is any credit given to consumers for spending their time with a brand – and I believe it should.
So he’s billed those companies for his time – at a generous 75% discount. Most, of course, have treated him as a rogue nutcase; but a few have recognised that there’s a real issue here, especially in terms of its impact on the parallel attention economy and reputation economy, which can indeed destroy “company’s bottom line and market share” if they’re not treated with respect. It may sound like a joke at first: but fact is that it’s not a joke at all.
The money-economy doesn’t work: we know that now. The catch is that as yet we don’t have anything to replace it – a fact that’s seriously scary in itself, given that there’s a very real risk of global economic failure here. And by definition it’s far larger than we are, so there’s not much that we as individuals can do to change it. Frustrating indeed: like so many other aspects of the business world, it doesn’t work, but we’re stuck with it. Oh well.
What we can do is take a closer look at that point of transaction – the moment where money changes hands – because in practice that’s where so many of those pointless delays will occur. Irritation and frustration can cost a lot, especially when potential clients and customers start to take proper account of the effective monetary-cost and life-cost of their time. So if it takes longer to pay for groceries than it does to select them from the shelves – as happens all too often in the local supermarket here – you can be sure that some of those people stuck in line will give up in disgust: they’ll take their business elsewhere, to places that do respect their time. How long are you willing to be stuck on hold, listening to that repeated pretence that “your call is important to us”? How much money are you willing to spend with a company that spends your time as if it was worth nothing? Then turn this round: how do you spend others’ time in their transactions with you?
So think side-wise for a while, and take a more ‘whole-system’ view of the overall time expended in overall transactions: not just the time your own company pays for, but the time of everyone in each transaction. No doubt it’ll be an eye-opener at first: not comfortable at all. But worth it – in every sense of the word.
If you work in a large organisation, no doubt you’ll have analysts everywhere; you may well be one yourself. You know who they are, what they do, what part they play: financial analysts, business analysts, process analysts, quality analysts and the like, keeping track of activity, performance, change.
But what about your business anarchists? Do you know who they are, what they do, what part they play, in managing the overall needs of the business? And how much your business depends on them?
And no, I’m not joking: every business does have a real need for its anarchists, every bit as much as its need for its analysts. For example, take a look at the list of ‘Six Essential Skills for Exponential Times‘, by brand consultant and social-media strategist Michelle Tripp (and also expanded on by Burton Group consultant Mike Rollings in his post ‘What to do when waking out of an EA induced coma‘):
- Skill #1: Rule-breaking – “Rule breakers will be ready to consider possibilities that others are told ‘don’t make sense’ or ‘aren’t the way things are done around here.’”
- Skill #2: Entrepreneurial – “Seeking out new opportunities and new ways of connecting and creating … finding them even when there isn’t an available mentor or an established path.”
- Skill #3: Self-Educating – “More proactive than ever in learning independently and not relying on structured programs … don’t sit back and wait to be taught … searching for information and charting their own educational course.”
- Skill #4: Bonding – “Bonding will be a matter of how much value you can provide to the people you’ve promised it to. … Those bonds can be through adding value to people’s lives through technology, information, guidance, validation, or friendship.”
- Skill #5: Revolutionary – “Revolutionaries are at the forefront, creating the future. … Brains that thrive on change, innovation and invention, high information uptake, and leveraging technologies are geared for the future.”
- Skill #6: Visionary – “Everything is changing faster than ever. … Having the skill of vision allows you to imagine what’s possible, imagine what’s next, and predict the needs and values of tomorrow.”
In short, the skills of thinking side-wise.
These aren’t the skills that we would expect from an analyst: far from it, in fact. In Cynefin terms, the tasks of an analyst sit squarely in the squarely in the domain of the ‘Complicated’ – calm, calculated, everything according to the rules. Which works just fine as long as everything stays much the same. But when the world changes, becomes uncertain – when we move into the Cynefin domain of the ‘Chaotic’, where the assumptions that underpin the analyst’s so-certain rules no longer apply – those analyst-skills may well be worse than useless, giving us nominal ‘right answers’ to what turn out in practice to be the wrong questions. That’s when we need a very different set of skills, to find out what questions we really need to ask. That’s when we need those skills above; that’s when we need people who are comfortable with the chaos and confusion of change. That, in short, is when we need our business-anarchists.
Don’t worry: we’re not talking about ‘kiddies-anarchy’ here – pointless disruption for disruption’s sake, or the classic student stupidity of “all property must be liberated, but don’t you dare touch my stuff!”. There’s no discipline there, no awareness of personal responsibility in a complex social context. Instead, each of those skills above have their own distinct disciplines, and, like the analysts’ skills, will rely on many years’-worth of experience to do well. The catch is that, as the Cynefin model demonstrates, the business-anarchist’s disciplines and experience are structurally different from those of the analyst – so if we try to measure them in the same terms as for the analyst, we’ll be in deep trouble straight away.
What we need from an analyst is depth of experience, in what marketers would call a vertical domain. Analysts are specialists – many years of practice in a single domain, steadily developing their skills and, especially, their speed at the work. As Cynefin shows, the core tactic is ‘sense / analyse / respond’, and the key driver is a kind of ‘outer truth’, with that ‘truth’ identifiable in concrete, repeatable terms. In that sense, the analyst’s performance is relatively easy to measure, and the tasks easy to monitor, too.
But what we need from an anarchist is breadth of experience – horizontal rather than vertical. Anarchists are generalists – many years of practice at connecting across multiple domains, cross-fertilising, creating conversations between them, linking different ideas and experiences via analogy and metaphor. Yet here the key drivers are principles or values, and, as Cynefin shows, the core tactic is ‘act / sense / respond’ – we have to do something to shake things up enough to sense what’s going on and which way to go. So performance is hard to measure, because there are no clear rules to measure against; and tasks are difficult to predefine, too, because by its nature much of the work deals with inherent uncertainty. Tricky…
Generalists are the ‘glue’ that hold the organisation together: without them, there would be no end-to-end processes, nothing of practical use towards the organisation’s aims. But another problem here is that the generalist’s experience in any single domain will necessarily be less than those of an equivalent specialist who’s worked only within that one domain: so the generalist will almost always come off worst in any single skill-for-skill comparison – often leading to some very misleading performance measures. Worse, if most of our measures are ‘vertical’ (as they usually are in large organisations), then, according to those measures, the more that generalists do their real work of ‘horizontal’ connection, the less they’ll appear to do – which again can lead to some very misleading ideas about performance, with less-skilled generalists appearing to do more work than the most experienced ones. Tricky indeed…
So when do you need those business-anarchists? Who on your existing staff would be good at this kind of role – or already is? How can you tell the good from the not-so-good? And what support would they need from you to do that role well?
When do you need business-anarchists, and for what purpose?
When the world is certain, you don’t need an anarchist shaking things up: that’s when you’d be better to stick to plain ol’ everyday analysis. But fact is that the business world is not certain – especially not at the present time, where stability is more the exception than the norm, and where the roller-coaster-ness of the ride sometimes seems to get rougher by the day. Whether you like it or not, you’re going to need people who thrive on coping with chaos – the business-anarchists.
The trick here is to identify what changes, and what doesn’t – which is where business-architecture and enterprise-architecture would come into the picture, because those are key tools to help you tell the difference. Where things don’t change, or don’t change much – and there’s still a lot of those, even in the most innovative business – stick to the analysis: don’t rock the boat just for the sake of doing so. Efficiency will always matter; so will operations excellence. Use statistics and the rest wherever appropriate. But remember that statistical analysis only works well when you’re dealing with large numbers of things that are exactly the same – or supposed to be the same: for example, by definition, Six Sigma makes little sense unless you’re dealing with literally millions of identical events. If the products or tasks have a high degree of inherent variance, or have any significant ‘one-off’ elements, you’ll need to apply anarchist-like approaches to those parts that change.
Who would do this work well?
Look for the natural generalists on your staff: the people who can get interested in anything, and like making connections between different domains, different levels of abstraction, different professions, different people. You need people with both breadth and depth, and intimate knowledge of your industry and context: outside consultants may help, but experienced ‘insiders’ usually have the most to offer.
Natural talents and tendencies may help: for example, people with Myers-Briggs xNxP ‘types’ may tend to think and act in an anarchist mode by nature. But much more important is experience: people need to know ‘the rules’, and know them well, in order to understand how and when and why to bend them to make things work better.
What are the critical success factors?
Analysis depends on the quality of algorithms and data. By contrast, the business-anarchist depends on the clarity of the organisation’s principles and values, to act as the beacon or ‘guiding star’ in conditions of inherent uncertainty. Use a structured framework such as vision, role, mission, goal to aid in anchoring those principles into everyday practice.
As above, experience is a key factor here – especially experience across a wide range of domains, and at every different level of those domains. Unlike analysis, theory alone is not enough here: it also needs to be grounded in practice, in hands-on experience, yet also with enough awareness to be able to break out of the “do it the way we’ve always done it” trap.
And there also needs to be discipline in moving between the domains: a dilettante ‘scattergun’ approach to new ideas will not be enough, especially in developing sustainable business-anarchist skills over the longer term. (See here for a ‘cheat-sheet’ on moving between disciplines in a rather different set of skills: the domains may seem strange at first, but the same principles do apply even in everyday business.)
What support do your business-anarchists need from you?
In a context where things are inherently uncertain, we need to make it safe to fail, or at least safe to seem to ‘not-succeed’ in the expected way. Where ‘command and control’ would require everything to be ‘fail-safe’, here we need to allow for safe-fail – for ‘graceful failure’, for practice-space, for fallback to a known recovery condition, and so on. The purpose of an experiment is to learn, to probe into the unknown (the ‘emergent’ domain, in Cynefin terms) so as to arrive at some new understanding – so if we only allow so-called ‘experiments’ that will tell us what we already know, we fail before we start.
You will only get appropriate innovation happening within the business if you make it safe for people to ‘fail’. Simple as that.
Your business-anarchists also need protection in several different senses, often right up at the executive levels:
- business-anarchists must necessarily break the rules: to do their work, they will need official sanction to ‘break the rules’ appropriately
- business-anarchists and other generalists must often bridge across the silos, necessarily breaking through bureacractic boundaries: they’ll often need formal authority to do this
- by definition, cross-functional generalists will usually have multiple reporting-relationships, often skipping over or sidestepping the ‘normal’ hierarchies: they’ll need protection from possibly-disgruntled managers in order to do this
Hence another clear, simple point: you will only gain business value from your business-anarchists and other generalists if you make it safe for them to do their work.
And in the same way that, in Six Sigma and the like, everyone is an analyst, everyone needs to be an anarchist in their own way too. Many innovative companies allocate work-time for everyone to explore their own new ideas and new business practices: India’s Tata Group, for example, allot everyone an hour a day for personal experiments, whilst at Google and 3M it’s the equivalent of a full day each week. Sure, most experiments may well go nowhere: but those that do succeed bring huge returns that repay that ‘wasted’ work-time many, many times over – and it took a real ‘anarchist’ mindset to turned a ‘failed’ experimental glue at 3M into the almost immeasurable business success that is the ubiquitous Post-It® note.
So who are your business-anarchists? And how can you help them do their work, to help create your company’s success? A question that’s worth pondering in practice, perhaps…?
Success often arises just from avoiding failure. For example, consider the ‘ten commandments for business failure‘ listed by former Coca-Cola CEO Don Keough:
“You will fail if you quit taking risks, are inflexible, isolated, assume infallibility, play the game close to the line, don’t take time to think, put all your faith in outside experts, love your bureaucracy, send mixed messages, and fear the future.”
This list has been used, for example, to summarise current operational and strategic problems in Britain’s National Health Service (though that specific example does perhaps prioritise political point-scoring over practical review). But if we think side-wise, we can also re-use these known ‘anti-patterns’ for failure as pointers to strategies for business success:
Failure #1: Stop taking risks – How do you make it safe for people to take risks? How do your people know when risks are appropriate, and when not? What ‘safe-fail’ fallback mechanisms could you use to enable people to take safer risks?
Failure #2: Be inflexible – All those rules and regulations may seem to give little room for manoeuvre, but there are always some options for choice, for chance, for innovation: what are they? How can you use those chances to enhance your organisation’s ability to adapt to changing business contexts and conditions?
Failure #3: Isolate yourself – Management hidden away in a bunker, no-one talking to anyone else: many corporations have killed themselves that way. What do you do to ensure you know what’s going on, both inside and outside the organisation?
Failure #4: Assume infallibility – Often a problem of arrogance, this one: Enron’s high-flyers famously described themselves as “the smartest guys in the room“. Instead, what can you do to ensure that you follow Cromwell’s Rule, the exhortation of the English Civil War leader and general Oliver Cromwell to “think it possible you may be mistaken”?
Failure #5: Play the game close to the foul line – Enron again provides all too many examples of this, such as its ‘Death Star’, ‘Ricochet’, ‘Fat Boy’ and other scams through which they stole over $11bn by ‘gaming’ the US West Coast electricity market. The short-term gains are invariably outweighed by the long-term losses – or long jail-sentences… So corporate social responsibility isn’t a ‘feel-good’ fad: as Deming, Shell and others have demonstrated, it’s an essential survival strategy, especially in the longer term. We need to be clear about our own business-principles – and stick to them.
Failure #6: Don’t take time to think – In present-day business, the pressure’s always on, always pushing us to do more with less. One of the first things to get sacrificed when it all gets too much is time to think, time to reflect. But if we don’t take the time to think about what we’re doing, and why, we’re likely to find ourselves running full-tilt into a dead-end, powering over the proverbial cliff. Simple techniques such as the After-Action Review can make a huge difference: so by what means can you help shift the mindset from “We don’t have time to do this stuff!” to “We don’t have time to not do this stuff!”?
Failure #7: Put too much faith in outside experts – Often a corollary of Failures #3, #4 and #6: hiding in a corner and using blameable ‘outsiders’ to do our thinking for us… Consultants and contractors do have their roles, especially in helping us avoid falling into ‘groupthink‘, but as Deming also demonstrated, the most important sources of information are usually within the business itself, especially those close to the everyday action. What can you do to to build the right balance between ‘outside’ and ‘inside’? What you do to create an innovation culture within the business?
Failure #8: Love your bureaucracy – Bureaucracies do have a real business function, providing ‘normal’ paths for business communication, to guide, monitor and manage. But whenever we try to use them as a means of control in business, they grow and grow like an out-of-control cancer that kills communication and creativity, and eventually the organisation itself. Direction is real, but control is a myth: it doesn’t exist. So monitor the monitors, cut away all those meaningless measures, kill off pointless reports that no-one reads: rein in that bureaucracy, and never let it grow without a clear, explicit, ‘on-purpose’ business reason.
Failure #9: Send mixed messages – Social networks and increased scrutiny mean that mixed-messages will not only be spotted, but may well be interpreted as ‘playing the game close to the foul line’ – see Failure #5 – with serious impacts on risk and reputation. One of the best ways to keep consistent on message is to be clear about the linkage between vision, role, mission and goal – and to have a clear and meaningful business-vision in the first place!
Failure #10: Fear the future – This one is often the real driver behind other ‘commandments’ to failure, especially Failures #1 and #8. Formal futures techniques such as business scenarios, environmental scanning and causal layered analysis will help to ease those fears – and guide your organisation with what will always be an inherently uncertain future.
How much are you at risk of setting up your business for failure? Turn it round: use this list above to set it up for success.
[to the tune of "Where have all the flowers gone?"]
Where have all the good skills gone?
Long time passing
Where have all the good skills gone?
Long time ago
Where have all the good skills gone?
Gone to robots every one
When will they ever learn?
When will they ever learn…
This one’s really a corollary or implication of the previous post – 10, 100, 1000, 10000 – on how long it takes to learn real skills.
We hear frequent complaints about skills shortages, in almost every industry. Talented, experienced people are hard to find, it seems. Yet few people seem to be considering the possibility that we’re actually creating that skills shortage by the way we design and ‘engineer’ our businesses. From a sidewise view, it seems likely that the skills shortage isn’t something that’s ‘just happened’, but is a direct consequence of the current fad for ‘re-engineering’ everything, converting every possible business process into automated form. ‘Lean and mean’ and the like will seem great ideas, in the short term especially – but without care, and awareness of the subtle longer-term impacts, they can easily kill the company. Not such a great idea, then…
There are ways to deal with this – but to do so needs a better understanding of skill – and especially of how skills develop, and where they come from.
The first key point is that not every process can be automated. If you read the sales-pitches of some of the proponents of business process re-engineering, for example, it might seem that every aspect of the business can be converted to automated web-services and the like. But the reality is that simply isn’t true: the percentage will vary from one industry to another, but the bald fact is that on average, less than a third of business activities are suitable for automation. The remainder are ‘barely repeatable processes‘ that are not only unsuitable for automation, but require genuine skill to complete.
Which brings us to the second key point: any process which requires genuine skill can never be fully automated. The inverse of that statement is possibly more accurate: an automated process cannot implement the range of skilled decision-making. Automation can do a subset – sometimes a very large subset – but it cannot do it all: which means that if we rely on automation alone, the business process will fail whenever the automated decision-making is not up to the task.
To understand why this is so, look at the Cynefin model, also referenced in that previous post on skills. Cynefin covers the whole scope of decision-making. Given an initially unknown context – which is what we have whenever we start a business process – we have four classic ways to resolve the ‘unknown’: rule-based, analytic, heuristics, principles. In effect, as in that “10, 100, 1000, 10000″ post, they’re a hierarchy of skill-levels, from minimal (rule-based) to extreme (principle-based). Most automation – especially in physical machines – is rule-based: the exact same decision-path is followed, every time, regardless of what else may be in play. IT-based systems can also handle varying levels of analytics, requiring more complicated or calculated decision-paths, and often at very high speed. But everything there is still dependent on the initial assumptions: and if those assumptions no longer hold – as they often don’t in true complexity, let alone in the subtle chaos of the real world – then automation on its own will again fail. Hence the need, in almost every conceivable business process, for ‘human in the loop’ escalation or intervention, to make the decisions that cannot or should not be made by machines alone.
But as machines and IT-systems take on more and more of the routine rule-based and analytic decisions – the ‘easily repeatable processes’, the ‘automatable’ aspects of business – a key side-effect is, almost by definition, that the skill-levels needed to resolve the ‘non-automatable’ decisions will increase. But because it seems so easy to automate some parts of processes, it’s easy to ignore the non-automatable decisions: at best, they get shoved to one side, tagged with the infamous label “Magic Happens Here”. And because the automatable parts of the process can be done ever faster with increasing compute-power and the like, the pile in the ‘too-hard basket’ just keeps growing and growing, until it chokes the process to death, or causes some kind of fatal collapse. Worse, the more simulated-skill we build into an automated system, the higher the skill-level needed to resolve each item which can’t be handled by the automated parts of the overall system. In short, the more we automate, the harder it becomes to resolve any real-world process.
To give a real example, consider sorting the mail. It all used to be done by hand, at the main sorting office and at the local branch post-offices. Sorting staff developed real skills at deciphering near-illegible scrawls; local delivery-staff used their local knowledge to resolve most of the mis-addressed mail. But manual processes like that are slow; so to handle large volumes, two key components were introduced: machines, to read the more easily-interpretable addresses; and post-codes, both to make it easier for the machines, and to pass more of the routing-decisions onto the person or system writing the initial mail-address.
The machines ‘succeed’ because they only have to make a subset of the decisions within the overall sorting process. Anything they can’t handle on their own is handballed to a human operator to resolve. But we now require two different skillsets in human mail-sorters: machine-operators, who can handle another subset of decisions at high speed, to keep pace with the machines; and the expert interpreters, who have somewhat more time to do the best they can with the really indecipherable scrawls. In Cynefin terms, the machines do rule-based decisions (simple interpretation of printed post-codes) and analytics (algorithmic interpretation of handwriting); the operators tackle much of the complex domain (heuristic interpretation, plus decision to escalate to the experts); and the experts, who deal with the complex and chaotic domains.
But there’s a catch: how do those ‘humans in the loop’ learn the skills needed to do the job? By definition, they’re doing difficult work – too difficult for the machines to do their own. To put it the other way round, the machines do all of the easy work, and (usually) do it well: but that means that all the hard work is left to the humans. (That it often isn’t even acknowledged as skill is an interesting point in itself – a common cause of failures in classic Taylorist-style assembly-line process designs, for example.) But the way that humans learn skills is in a hierarchy of levels: first the rules, then the more complicated analytic versions of the rules, then the heuristic ‘exception that proves the rule’, and then finally a full almost intuitive grasp of the principles from which those apparent rules arise. If we try to skip any of those stages, everything falls apart: it’s possible to use principles straight off, for example, but without that firm foundation of knowing how and when why the rules exist, in order to ‘break the rules’, we can’t trust it in the real-world. Maybe in an emergency, perhaps, but not on a production-line – and it’s the latter that we’re concerned with here.
So people learn the skill by learning the rules, then the more complicated rules, and so on. The ’10, 100, 1000, 10000 hours’ rule tells us roughly how long it’ll take: a trainee will take a day to get started; at least a couple of weeks to make some degree of sense of what’s going on; and six months or so to even begin to be able to make contextual heuristic decisions that are better than the built-in ‘best-practices’ of the machines. If we don’t allow them that time, and don’t give them access to the decisions that are embedded within the machines, there’s no way that they can learn. On top of that, if we don’t make it safe to learn – if there isn’t a ‘safe-fail’ practice-space in which people can safely learn from their mistakes – there’ll be a serious disincentive to learn the needed skills. And business-specific skills can only be learnt on the job – they can’t be hired in from elsewhere. All of which can add up to serious business problems, especially in the longer term.
So what to do about it? The simplest way, perhaps, is to focus on questions such as these:
What decisions need to be made within each aspect of the business? What skills are needed to underpin each of those decisions? What level of skill – rule-based, analytic, heuristic, principle-based – is needed in each case?
What guides each of those decisions? Are the rules imposed from outside – such as via regulations, industry standards or social expectations – or from the business’ own principles, policies, procedures and work-instructions?
By what means are decisions escalated? Rules are always an abstraction of the real world: there’ll always be situations where they won’t work. The same applies to analytics, and to heuristics: at the end – as typified in so many business stories – everything can depend on principles. But how is each decision escalated from one level to the next? What skills are needed to understand how and when and why to escalate in each case? What mechanisms are used to signal such escalation, and pass the decisions up and down the skills-tree?
If decisions are embedded within automated systems, how may people learn the means by which those decisions are made? Machines and IT-systems can handle rule-based and algorithmic decisions: but people who need to take over those decisions in business-continuity and disaster-recovery need to know what those decisions are, and how to make those decisions themselves. These first- and second-order skills are also the foundation for higher-order escalated decisions: we need to know what the rules are, and why they are, before we can be trusted to break them. We also need to people to be able to take over when the machines fail, or simply when they’re overloaded – as occurs every Christmas in the mail-sorting context, for example. This is one key reason why disaster-recovery planning is a good place for trainees to start to learn the business – and business-continuity a good place to put that knowledge into practice.
What incentives exist for people to learn the skills the business needs? For that matter, how can we make it safe for people to learn? Most people learn by learning from their mistakes, so if it’s not safe to make mistakes, no-one will dare to risk learning anything. If people are to learn the higher-order skills, they need safe ‘practice-space’ where their inevitable mistakes will have minimal impact on the business and its clients; and they need time to learn, too. All these can work if the right incentives are in place – or, perhaps more important, if there are also no serious disencentives to learning.
Where have all the good skills gone? Lost in automation every one, if we’re not careful. But sidewise questions such as those above can help to retrieve the skills that we need – and keep improving quality and value throughout every aspect of the business.