A short review: The Agile Team Onion

This is a quick and pithy review of Emily Webber’s free e-book, “The Agile Team Onion“. At about 20 pages of content, it’s a concise enough work itself – I personally appreciate the laser-like focus on a single subject; in this case, it’s thinking about the various factors that affect agile team make-up, sizing and interfacing with other people and teams.

A few negatives first, to get them out of the way. The big one for me is that the book is silent on the customer. This is a hobby-horse of mine, because I see this constantly: teams will have some kind of “stakeholder”, “customer champion”, or other stand-in for the real thing. I call these roles “decoy customers”: it distracts us from noticing that the team doesn’t actually have real contact with a customer, and (more importantly) these people are often more chicken than pig. Sales may be important to them, for example, but they’re not fundamentally representative of the users.

In my opinion: teams that do not have constant customer interaction (or, worse, are one or more steps removed from the customer) will build more features that customers do not value, than ones who do have that interaction.

Looking at the agile manifesto, we see the word “customer” appears twice (notably, in the first two principles) and “business people” only once. I’m not sure that’s deliberate, but I like that ratio. It’s sad in a sense that many manifestations of agile, such as scrum, don’t recognise the customer as a specific role in the team – I think that’s an oversight, brought about by the agile principles not really calling it out. The agile manifesto places great emphasis on “customer collaboration” and responding to change, and the best way I know to do that is to have customers actively engaged with the team in multiple ways.

Second, while the book places great emphasis on Dunbar’s number (rightly so), I think it misses other reasons to think about small team sizes. Small teams will communicate efficiently, as the book states, but they will also produce artefacts that are:

  • limited in scope in terms of their overall complexity (and therefore are likely to be more amenable to testing, service-oriented design and less likely to be too-tightly coupled)
  • abstracted from the overall design of the organisation.

That second point is subtle, but important. Conway’s law states “organizations which design systems [..] are constrained to produce designs which are copies of the communication structures of these organizations”.

Small agile teams that are fundamentally multi-disciplinary transcend the strict chain-of-command organisational boundaries, and allow end product (the software) to be designed in more broad, abstract ways. Do we break free of Conway’s law entirely? No, of course not: small teams with well thought out communication lines to other teams they rely on look an awful lot like microservices, so it’s no co-incidence that service-oriented architecture is all the rage, but there is a lot to be said for loose, independent coupling through well-designed APIs: I think this is effectively the software equivalent of the organisational structure that Webber argues in favour of.

So, onto the positives, and there’s a lot to like about this short book. As I said before, I think the brevity is highly appreciated, and there are plenty of points in here which should get people thinking about how their agile teams function currently.

Recognising silo thinking is absolutely crucial. I think everyone notices this in different ways according to their experience – mine is hearing within programme teams that certain features or requirements had been mandated by “the business”. Of course, I never managed to find out who that shadowy cartel was made up of – suffice to say they communicated solely through intermediaries – but it was a classic information silo in the way Webber describes.

I particularly like the accessibility of this book. I may well end up giving this to teams to help them think about their own team design – and I think this could be a useful tool to re-enforce self-organisation – but actually, I’m very interested to start sharing this with people outside of my agile teams. Not everyone understands the reasoning behind the team design and make-up, and there are some great easy-to-understand points in here which communicate this very well.

There are lots of useful questions in this book, which will really aid people both in the division of pigs/chickens, but also ensuring influence is measured and/or limited as necessary. There is always a massive risk of people senior on the organisation chart attempting to throw their 2p in at opportunities given to them, and being clear about who the decision makers are, how decisions are made and communication, and (importantly) when not to take decisions, is a very powerful tool that teams can use to shield themselves.

All in all, I’ll be recommending this book to people thinking through these problems: there are a lot of resources focussed on “how to be agile”, but very few on the “who”, and although I think that’s a relatively limited problem, I also think it’s crucial to get right.

Quote

“Our highest priority is to satisfy the customer through early and continuous delivery of valuable software.” – first principle, Agile Software Manifesto (my emphasis)

Deadlines, estimates, predictions

Project management is always guaranteed to bring out some strong opinions, and a recent Twitter discussion was no different – but, while the core discussion on Twitter was great, it really deserves a much longer-form treatment. Paul Johnston wrote up his thoughts about getting people to talk about predictions instead of deadlines – and much of it is hard to argue with, but I have a bit of a different perspective.

To my mind, there tend to be approximately two types of deadlines:

  • fixed deadlines: these involve an independent event which must be met. A caterer who is supplying a wedding, for example, has a fixed deadline. In the product world, these tend to be rare – writing a mobile app for the Olympics 2016 would be a fine example, but writing a mobile app for Athletics news would not. Sales/marketing would definitely want it out before the Olympics, but that’s not the same thing.
  • soft deadlines: there is no independent event that must be met. This is the usual type of deadline; often a piece of work needs to be done for a deadline in order to co-ordinate with other work happening (press releases, other product development, rebranding exercises, etc)

The core difference between these two things is Paul’s “after deadline epoch”: in the case of a fixed deadline, we’re really saying (in the case of software) that the artefact will have little or no value past a given date. This is like a punnet of strawberries; once it’s gone past the use-by date, it’s no good.

In the soft deadline world, this is not the case – the potential value of the artefact is largely unchanged. However, value is only one side of the equation; a deadline moving backwards represents incrementally increasing cost. And this is where we get to the nub of the business problem: what is our opportunity cost?

A quick aside: I had a wonderful conversation with a recently-qualified project manager a few weeks ago. We were talking about the benefits and drawbacks of a framework like PRINCE2 for running projects, and to what extent using it in real-life looks like the theory. I made one claim that shocked her, though: that I had never, ever seen a project manager shut down a project of their own volition.

Those with extensive commercial experience are probably entirely unsurprised by that statement. But, to a PRINCE2 “theorist”, this is amazing: a core tenet of PRINCE2 is the continual checking and questioning of whether a project will deliver its aims, the planned value. This is called “Continued Business Justification”, and it should happen throughout the project lifecycle – and if there is no justification, you stop the project.

People who have interviewed project managers will often hear the refrain, “Well, my PID (Project Initiation Document) is my Bible”, but when talking of the PID the interviewee rarely mentions the business case – which is practically the most important document in PRINCE2

It’s easy enough to understand why. We’re all subject to the Sunk Cost fallacy, and particularly because it’s more obvious if projects are failing toward the end of their plan (because people are also great at deluding themselves), it means the sunk cost tends to be pretty large.

What do this have to do with deadlines? Well, when a business decides to initiate some work – whether it’s in a project format, or somehow else – it generally should have some kind of business case, whether formal or not. But if you cannot articulate the cost of doing something, it’s difficult to articulate the net value, and it’s difficult to compare to other options. That’s why people often want a deadline – the project costs need to be constrained, so that different options can be evaluated and the business can take a view on what to actually invest in.

Equally, when it comes to delivery, missing a deadline usually means additional cost (which implies declining business value), but the additional cost tends not to be incremental: it’s quite often catastrophic, in fact, particularly if recognised late in the day.

So, all this together, I think deadlines are inevitable, a fact of life, and I think in many cases the word “prediction” is wrong: while that’s fine for the development side of the deadline (it is indeed an estimate) it’s wrong to think of that goal as a whole as a prediction.

I think the better question is, in the context of software development, “How do we do this better?”. And there’s a few suggestions I have, most of which I try to put into practice (although often there are antagonizing factors that weaken them – that’s a whole blog post in itself).

First, separate the development estimates from the deadline. A set of development estimates should never, ever be a single value – it’s not possible to say “We think we can complete this functionality in two months”. We can (or, should be able to) make statements like, “On balance, we believe it is likely this functionality can be completed in two months” – and it should be possible to put some kind of likelihood on that. 90% probability sounds pretty good, but it means in practice we still expect one project in ten to be late, and most estimates are not 90% certainty. The rest of the business needs to understand that.

Figuring out the likelihood is tough. I like the “triangular estimate” practice for individual stories, but when combining these together we actually need a little bit of statistics. I prefer to pretend they’re a Poisson distribution (and this tends to fit in practice), but equally you could turn them into pure PDFs and run Monte Carlo. I could go into a series of posts about this, and probably will, but you can also just look at some historical projects to get a feel: take the estimates for previous projects, and compare to the actuals. You’ll have a probability distribution there that you can just reapply to your current estimates to give you a feel for worst-case and likelihood.

Second, slack people, slack! Lots of project managers will build slack into a project, but don’t understand it. A common mistake is that people come up with a development estimate, and they say “Ok, let’s turn this into a deadline. But we know just taking this date (as it is) is wrong, so we’ll stick some slack on the end”. Padding, it feels so good! You did a great estimate, and then you gave yourself room to move. Problem is, it’s not actually slack – the critical path is almost certainly still too tight, so it sits like a pot of free time that tends to get used up rapidly.

The correct mechanism to use slack is to sprinkle it through the project. You actually need more up-front, because that’s where the team are settling into the project and progress is most unpredictable. There should be lots of little pieces of slack, and then – critically! – if you use up any piece of slack, that causes an immediate and automatic change to the delivery date.

This is a great control point to revisit your project justification: if I’m 10% and 30 days through my project, and I’ve used all 5 days of slack available at this point, it doesn’t matter if I still have another 20 days of slack in the remainder of the project – the project is way off schedule. I expected to do this work in 25 days, not 30, so I’m over by 20%. I can expect to be 50 days late.

Lastly, agile practices. I am absolutely a subscriber to agile methodology in the right place and time, especially on those projects where the end outcome is not yet really known. It’s much easier to plan out a project where the steps are reasonably well-known; true R&D projects are nothing like that.

I still maintain that the guiding principle here is one of business value. At the point at which we don’t think we’re going to achieve value, we shut the thing down: crucial here, then, is our definition of Minimum Viable Product (if that’s the process we’re using), or the conversations with users. The first point of the agile manifesto contains the (para)phrase “deliver valuable software early“, so while we might not have a deadline for the end artefact itself (delivery when it’s ready/done), we certainly should have deadlines along the way by which point we’ve delivered some measurable value. If we don’t meet those, then again, shut the thing down.

I’m a big fan of Dan Ward’s writing since being introduced to it, and I have been particularly inspired by how he talks about deadlines. The F.I.R.E. book is excellent, and if you haven’t read the book then Dan’s “Change This” manifesto on Igniting Innovation is a good precis. I will quote this little bit, but the whole thing is a must-read:

“setting a firm deadline acts as a forcing function for creativity and helps nudge teams in new directions” – Dan Ward
Last point. I don’t think deadlines are, in themselves, a brilliant metric. As a judge of whether or not business value has been delivered, they’re exceptionally poor – anyone can ship a pile of rubbish to a deadline. Where any delivery involves significant challenge or unknown, it’s ridiculous to set a date as being bullet-proof. But all that said, the commitment of a deadline is extremely useful, and using them as a proxy for the likely delivery of value I think can be powerful.

 

Brexit confirms: storytelling is dead

This is not a post about Brexit; this is about conversations. Storytelling rose in the 80’s as a key marketing tool – phenomena like the Nescafe “Gold Blend” adverts demonstrated how the ability to tell a story could convincingly engage consumers en masse. Truth be told, this was nothing new – the “soap opera” is so-called because those ongoing serial dramas used to be sponsored by soap manufacturers. But, the key insight by the storytellers was that creating a story around a message you wanted to communicate (rather than simply being associated to or referenced by the story) was very powerful.

Now, Nescafe coffee had only a tangential bit-part within their famed serial adverts, and indeed broadcasting on television is a remarkably expensive way of telling a story – so in fact, the technique didn’t really start to take off until the early 2000s, with the advent of the internet. Of course, big names continued to tell stories in the way they had – Guiness being the more modern exemplar – but now smaller organisations could do it; they felt it built relationships with their consumers.

There is a lot to be said about discerning what is storytelling and what isn’t. Critically, a story ought to have an arc – a beginning, middle and end at least – but at a deeper level ought to have a structure which creates emotional engagement. Shakespeare was a master of the five-act structure, and most blockbuster movies to this day retain a very similar make-up. Advertisements alone do not lend themselves to that level of sophistication, but people started applying storytelling in many different areas of business – although seen as a marketing tool, it quickly leaked into sales, the boardroom, investment decks and beyond.

Many people get benefit from story-thinking without necessarily having a huge amount of structure. The process of thinking editorially about their message, and trying to frame that in the form of a story is difficult and restricting. In a similar way to writing a Tweet, the added restrictions make you think carefully about what you want to say, and it turns out these restrictions actually help rather than hinder – a message has to be much more focussed. However, those restrictions (while helpful) are not the power of storytelling – more the power of subediting / thinking (which, is seems, it less common than you’d think).

People have said before me that storytelling is dying – Berkowitz’s piece on becoming storymakers rather than tellers is well-cited. It’s a very marketing-oriented perspective, and there’s lots to agree with, but I think it’s dead wrong for digital-native organisations.

Politics is an awful lot like marketing and product development in some key ways; in many ways, it actually resembles the market before software-as-a-service:

  • highly transactional nature (votes instead of money)
  • very seasonal sales periods, often years between sales
  • competitive marketplace for a commodity product
  • repeat customers very valuable, but profit function dependent on making new sales on the current product line

Not just that, but crucial is the engagement of the “customer” (the voter) in an ongoing fashion, to ensure that the party is developing policies that they believe will be voted for. Interestingly, in blind tests, the Liberal Democrat and Green policies rate very highly – so we can see that while the product is important, market positioning is critical to ensure customers have a specific formed belief about your product.

Within continuous delivery thinking, the digital organisation is concerned primarily with conversations to drive the brand rather than positional or story-oriented marketing. However, what was particularly interesting with the Brexit debate: this conversational engagement was writ large across the whole leave campaign.

Things we can note about the campaign:

  • meaningful engagement on social platforms like Facebook and Twitter. Of course, campaigns have done this before (Corbyn would be another example), but while others have been successful at deploying their message, Leave were highly successful in modifying their conversations quickly
  • a stunningly short period of campaigning. Who knows why this happened: the Scottish referendum on independence was over a period of 18 months. The UK Brexit debate was complete in 4. There was no way a campaign could hammer home messages; each thing they said had to be well-chosen and timely
  • absolute control over the conversation. While Leave conversed freely with their own supporters, they meaningfully achieve air superiority in terms of the conversation in the debate. Their messages were the ones discussed; they created the national conversation. People are shocked by how “untrue” many of their statements were: but people can recall them readily. I doubt many could recall anything Remain said other than vague threats about the economy.

The speed of the conversation here was crucial. They adapted in a truly agile fashion, and were able to execute their OODA loop significantly more quickly. In the end, it was a tight contest, but it really should not have been.

Storytelling is a blunt instrument in comparison. It’s unresponsive, it’s broadcast, and it’s not digital native. Its time is up.

Containing incestuousness

Having droned on a little the other day about duplication in Stackanetes (in hindsight, I had intended to make a “it’s turtles all the way down” type jibe), I’ve been delighted to read lots of other people spouting the same opinion – nothing quite so gratifying as confirmation bias.

Massimo has it absolutely right when he describes container scheduling as an incestuous orgy (actually, he didn’t, I just did, but I think that was roughly his point). What is most specifically obvious is the fact that while there is a lot of duplication, there isn’t much agreement about the hierarchy of abstraction: a number of projects have started laying claim to be the lowest level above containers.

It comes back to this; deploying PaaS (such as Cloudfoundry, which I try to hard to like but seems to end up disappointing) is still way too hard. Even deploying IaaS is too hard – the OpenStack distros are still a complete mess. But while the higher level abstractions are fighting it out for attention, the people writing tools at a lower level are busy making little incremental improvements and trying to subsume new functionality – witness Docker Swarm – they’re spreading out horizontally instead of doing one thing well and creating a platform.

I don’t think it’s going to take five years to sort out, but I also don’t think the winner is playing the game yet. Someone is going to come along and make this stuff simple, and they’re going to spread like wildfire when they do it.

Stackanetes

There’s a great demo from the recent OpenStack Summit (wish I had been there):

OpenStack is a known massive pain to get up and running, and having it in a reasonable set of containers that might be used to deploy it by default is really interesting to see. This is available in Quay as Stackanetes, which is a pretty awful name (as is Stackenetes, and Stackernetes, both of which were googlewhacks earlier today) for some great work.

I’m entirely convinced that I would never actually run anything like this in production for most conceivable workloads because there’s so much duplication going on, but for those people with a specific need to make AWS-like capability available as a service within their organisation (who are you people?!) this makes a lot of sense.

I can’t help but feel there is a large amount of simplification in this space coming, though. While “Google for everyone else” is an interesting challenge, the truth is that everyone else is nothing like Google, and most challenges people face are actually relatively mundane:

  • how do I persist storage across physical hosts in a way that is relatively ACID?
  • how do I start resilient applications and distribute their configuration appropriately?
  • how do I implement my various ongoing administrative processes?

This is why I’m a big fan of projects like Deis for businesses operating up to quite substantial levels of scale: enforcing some very specific patterns on the application, as far as possible, is vastly preferable to maintaining a platform that has to encompass large amounts of functionality to support its applications. Every additional service and configuration is another thing to go wrong, and while things can made pretty bullet-proof, overall you have to expect the failure rate to increase (this is just a mathematical truth).

CoreOS in many ways is such a simplification: universal adoption of cloud-config, opinion about systemd and etcd, for example. And while we’re not going to go all the way back to Mosix-like visions of cluster computing, it seems clear that many existing OS-level services are actually going to become cluster-level services by default – logging being a really obvious one – and that even at scale, OpenStack-type solutions are much more complicated than you actually want.

 

 

Some notes on Serverless design: “macro-function oriented architecture”

Over the past couple of days I’ve been engaged in a Twitter discussion about serverless. The trigger for this was Paul Johnston‘s rather excellent series of posts on his experiences with serverless, wrapped up in this decent overview.

First, what is serverless? You can go over and read Paul’s explanation; my take is that there isn’t really a great definition for this yet. Amazon’s Lambda is the canonical implementation, and as the name kind of gives away, it’s very much a function-oriented environment: there are no EC2 instances to manage or anything like that, you upload some code and that code is executed on reception of an event – then you just pay for the compute time used.

This is the “compute as a utility” concept taken more or less to its ultimate extreme: the problem that Amazon (and the others of that ilk) have in terms of provisioning sufficient compute is relatively well-known, and the price of EC2 is artificially quite high compared to where they would likely want to go: there just is not enough supply. The “end of Moore’s law” is partly to blame; we’re still building software like compute power is doubling every 18 months, and it just isn’t.

Fundamentally, efficiency is increasingly the name of the game, and in particular how to get hardware running more at capacity. There are plenty of EC2 instances around doing very little, there are plenty doing way too much (noisy neighbour syndrome), and what Amazon have figured out is that they’re in a pretty decent place to be able to schedule this workload, so long as they can break it down into the right unit.

This is where serverless comes in. I think that’s a poor name for it, because the lack of server management is a principle benefit, but it’s a side-effect. I would probably prefer macro-function oriented architecture, as a similar but distinct practice to micro-service oriented architecture. Microservices have given rise to discovery and scheduling systems, like Zookeeper and Kubernetes, and this form of thinking is probably primarily responsible for the popularity of Docker. Breaking monolithic designs into modular services, ensuring that they are loosely coupled with well-documented network-oriented APIs, is an entirely sensible practice and not in some small part responsible for the overall success Amazon have had following the famous Bezos edict.

Macrofunction and microservice architectures share many similarities; there is a hard limit on the appropriate scale of each function or service, and the limitation of both resources and capability for each feels like a restriction, but is actually a benefit: with the restrictions in place, more assumptions about the behaviour and requirement of such software can be made, and with more assumptions follow more powerful deployment practices – such as Docker. Indeed, Amazon Lambda can scale your macrofunction significantly – frankly, if you design the thing right, you don’t have to worry about scaling ever again.

However, one weakness Paul has rightly spotted is that this is early days: good practice is really yet to be defined, bad practice is inevitable and difficult to avoid, and people attempting to get the benefits now are also having to figure out the pain points.

It’s worth saying that this architecture will not be for everyone – in fact, if you don’t have some kind of request/response to hook into, frankly it won’t work at all – you’re going to find it very difficult to develop a VPN or other long-lived network service in this environment.

Many of the patterns that should be applied in this scenario are familiar to the twelve-factor aficionado. Functions should be written to be stateless, with persistent data discovered and recorded in other services; configuration is passed in externally; et cetera. Interestingly, no native code is supported – I suggest this is no surprise, given Amazon’s investment in Annapurna and their ARM server line. So, interpreted languages only.

A lot of this reminds me a lot of the under-rated and largely unknown PHP framework, Photon. While this is not immediately obvious – Photon’s raison d’etre is more about being able to run long-lived server processes, which is diametrically different to Lambda – the fundamental requirement to treat code as event-driven and the resulting architecture is very similar. In fact, it was very surprising to me that it doesn’t seem to be possible to subscribe a Lambda handler to an SQS topic – it’s possible to hack this via SNS or polling, but there is no apparent direct mechanism.

It’s difficult to disagree that this is the wave of the future: needing to manage fewer resources makes a lot of sense, being able to forget about security updates and the like is also a major win. It also seems unlikely to me that a Lambda-oriented architecture, if developed in the right way, could ever be much more expensive than a traditional one – and ought to be a lot less in practice.

On Hiring A-Players

“Steve Jobs has a saying that A players hire A players; B players hire C players; and C players hire D players. It doesn’t take long to get to Z players. This trickle-down effect causes bozo explosions in companies.” ― Guy Kawasaki

A few times recently I’ve bumped into what I call the “A-Player Theory”. This is a close relative of the “10x Engineer Theory”, and in its usual formulation states that only the best want to hire their equals or betters: everyone else, for whatever reason, hires down. If only you were brave enough to hire people better than you, you’d be creating great teams in no time!

Like a lot of ideas in the tech arena, it feels like this idea has come from the world of elite sports, and this is no bad thing. When I want to explore ideas about peak performance, it’s natural to look to different types of people and try to apply their ideas to my own. However, I don’t think that that this theory is actually that helpful, and it’s simple to explain why.

First, I think there is a simple problem with the formulation in that hiring is a two-way street: not only does the hirer need to want to find the best people, but the best people will need to be attracted to the hirer. I think this second effect is actually the more important: the quality of the talent available to you, as a hirer, will be directly proportional to the quality of your culture. This is a difficult statement to support in this post, and is something I will explore further in the future, but I do believe that this is the case.

But second, and more importantly, I just don’t think the theory holds in elite sports. Now granted, things are rather different in American elite team sports: for example, team-building is crucial in American Football, but processes like “the draft” are  deliberately designed to ensure that C-teams hire A-players (at least in the beginning), so that some degree of competitive parity is ensured.

I’d like to give some examples from the world of soccer, instead. I’ve chosen this sport for a few reasons – partly, I’m very familiar with it, but mainly because it’s a global sport with the requisite elite element, and sufficient money floating about that players move between teams, leagues and countries with extreme ease. If any teams were going to be calculating about hiring A-players, you’d see them in soccer.

To be fair, there are absolutely teams who do this. The most obvious example is the galáctico policy pursued by Real Madrid. However, this turns out to be pretty rare: teams will transfer players for a variety of different reasons, and rate them in different ways, and while there are large-money transfers for world-class players, these make up a small amount of activity at even the largest clubs as a rule.

The absolute best teams in soccer are not associated with world-class A-players; they’re actually a function of the manager. My favourite example right now is Leicester City: not least as I grew up in Leicester, but (correct at the time of writing this) because they’re flying high at the top of the Premiership with one of my favourite managers, Claudio Ranieri. Their leading scorers, with 36 goals between them, are those huge names “Jamie Vardy” and “Riyad Mahrez” (you will be forgiven if you don’t follow soccer for having never heard of the pair of them).

Vardy at least was a record signing: Leicester paid £1 million for him from a non-league club (and reportedly, the deal could even be worth more). Let’s be clear about this, though: for a premier league player, that sum is an absolute pittance. Mahrez came from a league club to be sure – Ligue 2 AAS Sarcelles – for an undisclosed fee, which again will be small in the scheme of the league (and in fact, both players joined before the team were promoted to the Premiership). Both players now absolutely have a market value in tens of millions.

Leicester did not sign A-players; in fact, they signed a bunch of low-league and non-league players in order to rise out of the Championship, and then made the very sensible decision not to attempt to parachute in Premiership stars, and instead stick with the team they had built. This work is largely attributable to their previous manager, Nigel Pearson, and does not particularly break the mold in many ways – this is a well-trodden path that has seen many clubs rise through the leagues at the hands of an excellent manager (e.g. Nottingham Forest in the Clough era, before which they were largely forgettable and underachieving, or Leeds United under Revie, who started as an awful side that struggled to attract youth players let alone professionals).

If anything, in fact, the record of teams within this league that have gone out to buy the best has been pretty awful – Chelsea have done well but at an absolutely enormous cost, and many teams inflated by A-players have quickly fallen once the money ran out (Newcastle, West Ham, as examples).

The manager with the most enviable record for team-building, of course, must be Alex Ferguson. While his best Manchester United teams were full of world-class players, many of whom had been bought in at some cost, his career was partly defined by the number of A-players he allowed to leave the club. Paul Ince was a huge loss to the club, as was Hughes and Kanchelskis, and (not for the first time in his career) Ferguson came under significant pressure to resign. Instead, he opted (having failed to sign some names) to bring in members of the youth team – names who are now instantly recognisable, like the Nevilles, Beckham, Scholes. Commentator Alan Hansen characterized their opening loss with the immortal words, “You can’t win anything with kids”. He also let go Cantona, and Ronaldo (who left at the height of his powers) brought an almost £70 million profit to the club upon sale. Sure, Ferguson also spent money (and brought in players who didn’t perform – Taibi, Djemba-Djemba, Tosic, Zaha, Bebe, to name but a few – some of them real A-players, like Andersen), but Manchester United were one of the most sustainably successful clubs for a long period of time under his leadership.

All of this brings me back to my central point. It’s not the player that is important; it’s the team – and the decision about who to bring into a team, when, and how, is the responsibility of the manager. It’s very easy to say “I’m going to go and hire only A-players!”, but actually, it’s probably one of the worst things you can do for a team. In football terms, you need balance in a side – people with different strengths, abilities and points of view. Football is notorious for great players who leave one club for another, and become totally anonymous shadows of their former selves: this is not because they’re B- or C-players in disguise, but because if a team doesn’t have a A-player shaped hole, that player will not be able to perform like an A-player.

It is incumbent on the best team leaders to develop the team first and foremost; the aim is that based on the performance of the team others will look back and say, “That is a team of A-players”. It’s easy to state how to do this, but remarkably difficult in practice:

  1. set the right culture for the team, right from the off. This is a whole topic in and of itself, and the culture creates the environment for performance but importantly does not trigger performance itself
  2. where an existing team is in place, plan out how to adapt and grow the people within the team, guided by the culture
  3. for each new member being added to the team, think hard about the gap they’re filling and whether or not they are the right “shape” to fill the gap.

Think about the levers in the team that are used to create and maintain performance. Most managers will automatically turn to metrics and reports; these are amongst the least powerful tools. The crucial factors here are ensuring clarity of purpose, adequacy of tools and resources, autonomy to perform and passion for the work. Passion burns most fiercely when fuelled by success, and as a team leader that is your end goal. Hiring is important, it’s best to start in the best place possible, but I don’t believe it’s anything more than a good start.

“The quality of a person’s life is most often a direct reflection of the expectations of their peer group.” ― Tony Robbins

Tech2020 followup

The various videos of the speakers from Tech2020 – including yours truly – are up and available for Skillsmatter members. Going back to my previous blog post, I can heartily recommend the speakers who I was excited about, but have to say, I was blown away by the overall quality of the conference. Even those topics I didn’t think would hold much interest or news for me turned out to be incredibly interesting, and I daresay the next editing of this conference will be something to watch out for.