Is open hardware strictlya technology choice? Just a commodity approach to saving money and avoidingvendor lock in?
Or, is it part of a silicon valley’s beachhead inside your organization?
Or, perhaps it is even a culture virus. As you and the people working for you adopt these technologies and participate in their communities will they be avector for silicon valley thinking to enter your company? I suspect both.
The center of gravity of effort is different. This is partially due to legacy requirements embedded in larger organizations, but it’s not the whole story. It’s certainly also about how they approach risk avoidance.
Why does it matter? You’ve probably heard of Boyd’s OODA loop. The organization that can make sense of its surroundings (market, competition, …) and respond more quickly wins. It’s like playing chess where your opponent gets two moves to each of yours.
But it’s not called the OO loop reason. If you can’t follow through to action it’s useless. Slow to code is like a fighter jet with a great radar and no stick for the pilot.With Big Data and all the myriad sensors we can access for data now on the web and elsewhere, we have new ways to Observe and Orient to our world. However, the “act” in often happens in software now. That’s where we make our decisions concrete either in real time or in the next generation of our business, so we need to build systems that are platform for maneuver and open systems / open software contribute to that.
In the military they have this notion of maneuver warfare, and on the battlefield maneuver happens in space and time. But increasingly maneuver in the strategic sense (and even in the tactical sense as it relates to cyber warfare and defense) happens in the rapid development of software.The more our businesses become digital businesses, the more this becomes true for us too.
Of course the easy answer is “Bureaucracy.” And while that might be a bit of a cop out, let’s explore it a bit further.- Idea: Bureaucracy is the perceived antidote to risk in an environment where hurdles are high.
Does your IT/IS department look anything like this? Architecture, development, requirements, program management, operations, maintenance… All of these separations of take a tax on initiative and ensure the continued top down approach to development (and maneuver) continues.. Are they necessary or just vestiges of the past? Are we applying new technologies to these vestigial organizations? Or are we using them to build something new?
And its impact on maneuver is predictable.
This talk, as you’ve probably guessed, really isn’t about technology. It’s about culture and how technology is an enabler to a massive shift in our world. So, since we’ve already gone abstract, let’s go really meta for a bit.
Bureaucracy is much maligned, but it grew up to deal with the organizational challenges of the industrial age. And it was effective at organizing these guys to run …
…this. The scale of these enterprises in terms of labor was enormous and it was an enormous challenge to coordinate their efforts.Btw, I visited the Ford truck plant that currently occupies the upper right hand corner of this picture last week, and while highly automated the people that built this would recognize it.
And that coordination of labor and the industrialization that went with it led to this. While the individual’s experience of bureaucracy may feel like one of those creatures from the Alien series stuck to your face, the industrial revolution and its organizing methods have led to the first sustained growth in individual wealth in the history of humanity.This chart makes me a fan of bureaucracy, but perhaps it’s an idea whose time is passing.
And here’s the really interesting meta point… James Watt and his contemporaries thought they were inventing a form of locomotion. Like engineers everywhere they focused on the practical aspects of their work, but in fact they were also unleashing a number of social gravitational forces.
Their machines and consequent industrialization needed labor – and lots of people left behind their dispersed agrarian lifestyles to concentrate in cities.
And that concentration made radically different kinds of political organization possible. Because in a pre-internet and telephony time they could now communicate and form dense networks. In a sense, the machine led directlyto political movements around the world. Three out of four of our “big” political isms sprang directly from the modernism made possible by all those machines and the bureaucracies that sprang up to organize us around them. Those structures also informed the corporate structures that we operate in.
They weren’t just creating political systems either, they were creating entire new modes of thought … Reductionism, for example, the notion that understanding could come from the decomposition of complexity into component parts came from our understanding of industrial age machine. Today these threads still run through our thinking – they are cognitive filters we probably aren’t even aware of – and probably interfere with our ability to understand complex dynamic systems where many of the “secrets” are in the time-variant patterns rather than fixed state or structure.
Which leads us back to the modernist enterprise that we are gradually replacing. The very large systems integrator I used to work for has spent the last forty plus years digitizing the corporate bureaucracy. From the first corporate payroll system to today they’ve been about the reimplementation of traditional bureaucracy in silicon and copper and every step along the way has been essentially hierarchical, reductionist, planned… Even today it’s in vogue to talk about the “industrialization” of IT – to mean somehow getting it sorted out. When large companies develop software for bureaucracies they do it bureaucratically.
The corporate enterprise, like any system, evolves. And it’s current level evolutionary maturity is probably about at the stage of the nematode; and we’ve been building its neural network. The nematode (or c. elegans) is widely studied because of its simple neural structures, structures that are focused on the very narrow regulation of homeostasis via on stimulus and response. The corporate digitalization of essentially neural processes are at a similar stage – with a focus on corporate homeostasis and the reimplementation of previously human-driven systems with productivity enhancing IT. But in many cases we haven’t changed the fundamental underlying organization or operation, we’ve just digitized them. (Note: there is some over simplification here. Collaboration tools etc. are beginning to make possible shadow organizations and networked modes of interaction, but the fundamental “big systems” like ERP’s are about digitizing former structures).
Some 30 years ago or so Leonard Kleinrock, Lawrence Roberts, Robert Kahn, and Vint Cerf thought they were building a computer network…Actually, given the time, and the reaction to the technocrats running the Vietnam war at the time, I think these guys were more aware of what they were doing in a meta sense than perhaps James Watt and his contemporaries were, but still… they might not have fully understood the implications of their work. However…
Tthe changes they have wrought are every bit is as dramatic as those caused by the steam engine and industrial revolution before it. The network age is ushering in a period of decentralized organizations…
…strained national sovereignty and rule of law
The long tail enablement of markets…
…utterly surprising forms of collective production…
new forms of political and governmental participation…
The emergenceof new kinds of complex non-linear (social) systems…
non-state (or tacitly-state-sponsored) cyber conflict and on and on…
The industrial age informed and created one kind of social fabric, the network / information age is creating another.The network age doesn’t just extend industrialization, it leaves it behind. Modernism and reductionism may be in their final steep decline. They are being supplanted by a new kind of network empiricism that will exert its own gravitational force on our social and organizational fabric. George Bush, with his perfect illustrations of reductionism (“You are with us or against us”) will probably be our last president of the modernist era. Reductionism remains intuitively appealing to us as humans in need of simple narratives of cause and effect but is increasingly out of step with our complex networked world.
And all of this is arriving inside of our traditional bureaucracies and causing them to evolve into hybrid hierarchy / networks. The post-bureaucratic enterprise.Bureaucracy is beginning to give way to other models of organization and some business, particularly on the web and other information focused industries, are beginning to fundamentally change what it means to be a business.
Talk aboutConway’s law
This leads us to a new, and more important, question. And I guess the point of this talk is to encourage us to think of open systems, open software, and open hardware as more than just cheap alternatives to the offerings from tier one vendors. in the context of this shift from modernism to a post-post-modern expansionist mindset. As futures go this one has been happening for a long time, but it’s beginning to happen with vigor inside of corporate organizations.
For example. We are in the habit of thinking of agile methods as in contrast to the waterfall model. But agile software development isn’t a software development methodology, it’s the post-bureaucratic shop floor quality circle applied to software. It’s as much (or more) about post-bureaucratic organizational models as it is about software per se.
Back to this broader question of the impact of the network age on the enterprise. We are used to thinking of the corporate enterprise as nice neat packets of planning immersed in the broader emergent market mediated by price signals. This separation of planned from emergent has worked well, and seems to have a natural balance that shifts with technology, organizational methods etc. But if there weren’t some natural limits to the expansion of planning and control Russia would still be a communist endeavor with a planned economy and General Electric would have stayed on an acquisition path until they owned everything.
So, in a way this means that we are intentionally blurring the boundaries of our organizations. You can see this in the way we participate in open communities now – for example many employees of Yahoo for a long time probably felt more affinity to the Hadoop project than to their employer.
So, here’s the core point of Intentional Emergence, at least as it applies to organizational and IT architecture, design the edge to better “impedance match” with the surrounding ecosystem. This means giving it both planning (intentional) and emergent properties.
As the corporate ecosystem becomes more connected the emergent challenges go beyond price. Increased corporate size and complexity, and more networked post-bureaucratic internal structures are making it very difficult for corporations to deal with all of the complexity they face. In fact, the bureaucratic model is further strained when the complexity exceeds the ability of the strategic corporate leadership to deal with in their decision making. (C is the complexity that management must deal with, C0 is the ability of a single person or small group to deal with complexity). When C is above C0 things come apart. The worst possible case is that C > C0 and you either don’t recognize it or refuse to accept it.
From command and control to act and adapt.
Our jobs in management are to modulate thisschizophrenia, to find the right balance.
Hayak was talking about markets here, but as complexity becomes more and more part of our landscape it seems to be applicable to the internals of the corporate enterprise and the IT systems that enable it.
So, we ask ourselves, how can we promote make it easier for flows of information to develop? For the river delta to form?
The result is a new aspirational enterprise software zeitgeist. Consider how an IT infrastructure approach can support it.
As technologists we have a natural tendency toward reductionist thought. Computers are rational after all. So it is our nature to deal with system failure by trying harder to control things. In technology this can often be counterproductive. More emphasis on governance for example can simply extend timelines and the risk absorbed with longer timelines is greater than the risk reduction you get from the governance. It is possible to squeeze too hard…
So instead of control, let’s focus on facilitation. Gall’s Law gives us a hint about what to facilitate. Building on Gall’s law, since there is no guarantee that simple systems will work, the implication is to build lots of little systems and attempt to facilitate adoption of successful work. Or… “let a thousand flowers bloom.”
It’s just math
If that Gall’s law idea is true, then what we want is lots of starts with an ecosystem of support that leads to adoption. On the web this is enabled with cheap hosting, open source software, ready venture capital, ubiquitous web distribution… Is it possible to replicate a similar ecosystem inside a company in order to achieve a cognitive force multiplier?
Just to be clear, we aren’t talking about eliminating the head of the traditional IT project distribution, but we are talking about intentionally enabling a long tail. A single person with modest skills should be able to start the process of solving his or her own problems in code, and then if the project is adopted and useful it can grow back towards the head.
And how do we do this? Generativity is a nice term used by Jonathan Zittrain to describe a set of attributes that encourage wide contribution.
Leverage: How strongly a system or technology leverages a set of possible tasks, meaning it makes our difficult tasks easier.Adaptability: adaptability to a range of tasks. The ease with which it can be modified to broaden its range of usesEase of Mastery: Compare the mastery that is needed to use an airplane and to use a paperAccessibility / Transferability:The easier it is to obtain the technology, tools and information necessary to achieve mastery - and convey changes to others - the more generative a system is
They aren’t just (or even mostly) about technology. Lots of things from technology to policy and organization contribute. Even something as simple as how time tracking is implemented can have a big impact on how generative a system is. In technology, the “approachability” is critical – for example a runtime mapping api (e.g. openmaps or google maps) is much more generative than a disk with ESRI server code on it.
If you want an example of generativity… Finding inspiration in unusual places. Scratch is inspirational because it has some interesting properties – the IP sharing approach is built in to the IDE (every project goes to a gallery), it is highly social in a way that supports co-learning, the tools are nicely sandboxed and designed for the capability curve…
With Carlos and Paul in mind, we proposed to the U.S. Army that instead of always building end use case systems, that they build a platform called the “battle command innovation platform”, whose end uses would not be known in advance, and provide tools, runtimes, and content to build usable systems in the field. We were looking to do something much more than just a PaaS runtime. There were strong community and content components to the vision that were targeted at the kind of users we expected to find in that “skunk works of one.”
We started with a question. Let’s finish with a couple. I didn’t talk much about the technologies because I wanted to focus on the ideas. The ideas lead to an invisible hand that can operate in your environment.
The intentionally emergent enterprise
The Intentionally Emergent EnterpriseJim StogdillOpen InfraShare SummitBostonMay 15, 2013
Q: The corporate enterprise and silicon valleyboth have the same technologies availableto them.So why do they deliver innovation sodifferently?
“It is no exaggeration to say that if we had had to rely onconscious central planning for the growth of our industrialsystem, it would never have reached the degree ofdifferentiation, complexity, and flexibility it has attained.…Any further growth of its complexity, therefore, far frommaking central direction more necessary, makes it moreimportant than ever that we should use a technique whichdoes not depend on conscious control.”Friedrich Hayak, The Road to Serfdom
Constructal Law:For a finite-size system to persist in time (to live) it mustevolve in such a way that it provides easier access to theimposed currents that flow through it.-From Design in NatureMore and more of the “currents” imposed on the moderncorporate enterprise are informational and digital.
Gall’s Law: A complex system that works isinvariably found to have evolvedfrom a simple system that worked.
Q: Assuming a Normal distribution,how many developers must have theopportunity to self select for (orinvent) a project in order to have a90% confidence that at least 1% ofthe actual participants will be 5 σabove the mean? You know, thecrazy smart ones.The ones youwant
“One” startshereBuilding the long tail of IT contribution.On purpose.
Generativity = “a system’scapacity to produceunanticipated changethrough unfilteredcontributions from broadand varied audiences.”
Make choices, investments, and policies thatincrease generativity.
Some things that contribute to generativityOpenSourceSoftwareOpenStandardsRuntimePlatformsLow hurdlesfor initialproject startSmall worldnetworksSimplerules20% time VariableCostOpen DataOpen API’s…Community
Q: At your workplace, whatchanges to policy,architecture, technology, orculture would enhance longtail emergence?
Q: How can we betterimpedance match ourorganizations to thedecentralized and emergentworld we are immersed in?
Recognizing that the scope of IT has become too great toeffectively centrally plan and manage, informationtechnology policy makers must work to explicitly enableemergent development in the enterprise. Emergentcapabilities won’t be expected to replace the systematicdevelopment of core line of business applications, but itwill complement them by enabling locally relevantinnovation. Such a strategy would enable “long tail”contributions throughout the enterprise and ultimatelywould also improve the way large programs aredelivered. The goal is apparent agility even if theenterprise’s supporting IT substrate evolves at a moremeasured pace.