Waste can be Good – it’s all relative

AbundanceAs businesses makes the transition to where the edge of the enterprise is wired into the operational processes of the business, we will start to consume our resources quite differently than we have in the past. We can use the abundance of computing capabilities to shed light on all the dark data currently available to develop a deeper contextual understanding of situations we encounter. Money may not be growing on trees, but there is much more we can be doing.

An article in Wired magazine back in 2009 discussed how: Tech Is Too Cheap to Meter: It’s Time to Manage for Abundance, Not Scarcity. In this world of exponential increases in capability, 2009 is ancient history, even so, the article is useful. It works through examples like how Alan Kay used the precious resources of the computer to display pictures on the screen instead of just textual data. George Gilder called this “wasting transistors” — making people more productive by using the transistors (computing capability) available.

The funny thing about waste is that it’s all relative to your sense of scarcity.

As we look to use higher levels of automation to handle more “normal” activities and focus people’s attention to turning anomalies into opportunities, we’ll use pattern recognition and other techniques that may appear to waste cycles. I hear people today complain about the expense of cloud computing and that it is out of control. That is more about what they use these resources for, how they measure impact and exercise control than anything to do with cost, at least from my perspective. As more capabilities become available and algorithms improve, we’ll need to do even more with more – not less.

The Wired article shows how behavior needs to change as we move from a perspective of scarcity to abundance:

From a perspective of Scarcity or Abundance

Scarcity Abundance
Rules Everything is forbidden unless it is permitted Everything is permitted unless it is forbidden
Social model Paternalism (We know what’s best) Egalitarianism (You know what’s best)
Profit plan Business model We’ll figure it out
Decision process Top-down Bottom-up
Organizational structure Command and control Out of control

This kind of shift in perspective is disruptive, useful and the right thing to do to take maximum advantage of a truly scarce resource – the human attention span.


Moore’s law turns 50

50thMoore’s law turns 50 on Sunday, after it was first published in the thirty-fifth anniversary issue of Electronics magazine back in 1965.

There have been a few stories out this week about Moore’s law turning 50 and how it may not make it to 60. IEEE put out a number of stories based on different perspectives of Moore’s law’s history and implications.

Few observations have predicted a shift with this level of impact on the world around us.

Even if we can’t continue to shift the size of transistors down at the rate predicted by Moore’s law, the innovations enabled will continue to drive us forward to new ways of tackling the world around us.

Future of AI podcast

AIFor those interested in Artificial Intelligence, automation and the possible implications on the future, last week the Science Friday podcast had a panel discussion asking AI questions like:

  • Will robots outpace humans in the future?
  • Should we set limits on A.I.?

The panel of experts discusses what questions should be asked about artificial intelligence progress.

What was nice about this discussion was it goes into a bit more depth than the usual ‘sound bite’ approach in most media articles.

One thing that is clear from these discussions is that the simple rules described by Asimov are not really up to the task. After all each of his Robot stories was about the conflicts that come from the use of simple rules.

The podcast also prompted T. Reyes to write a post: The Prelude to the Singularity that discusses the controls needed before we let this genie out of the bottle.

For some reason, I now want to reread The Moon is a Harsh Mistress.

A Technology Radar on Software Creation

radar (technology)I recently had the opportunity to look at ThoughtWorks Technology Radar. This is a document targeted primarily at developers, describing the emerging and trending technologies that are shaping software creation. It is grounded in tools that support the issues of: DevOps, Analytics and Security.

It is clear that those who put this position paper together are passionate about keeping up with the changes in the software development space, as well as internalizing the implications on how the software creative process will be performed in the future, and happy to share these views with others.

The technologies adoption profile is captured using a radar metaphor: emerging tech. around the edge and those technologies that should be adopted closer to the center. The model is divided into quadrants dedicated to techniques, platforms, tools and languages & frameworks. I can easily see this being used in a holistic, yet targeted discussion about what this shifts can mean to an organization and its software portfolio — in addition to facilitating a discussion among technologists.

Although industry analysts publish their vision documents regularly, it’s rare that a technology services organization gives their insight into the tools they are investigating or using publicly. I’ll leave it to your imagination why that’s not done much anymore.

There are versions of their technology radar going back a few years on the site (their goal is to publish twice a year), so if you’re interested in the development space, it’s worth a look.

If there was one suggestion I could make, it would be to include a vector estimating how soon the technology will advance to the next stage. This additional dimension should cause some very valuable discussions to take place.

Thoughts from a discussion about architecture

evaluationYesterday, I had a long discussion with Stephen Heffner the creator of XTRAN (and president of XTRAN, LLC). XTRAN is a meta transformation tool that excels at automating software work – sorry that is the best description I could come up for a tool that can create solutions to analyze and translate between software languages, data structures and even project work products. When you first read about its capabilities it sounds like magic. There are numerous working examples available of its capabilities so you can see its usefulness for yourself.

He and I were talking about the issues and merits of Enterprise Architecture. He wrote piece titled, What is Enterprise Architecture?, where he describes his views on the EA function. Stephen identifies three major impediments to effective EA:

  • Conflating EA with IT
  • Aligning EA with just transformation
  • Thinking the EA is responsible for strategy

We definitely agreed that today’s perspective in most businesses that the EA function is embedded within IT does not align well with the strategic needs of the business. The role is much broader than IT and needs to embrace the broader business issues that IT should support.

I had a bit of problem with the EA alignment with transformation but that may just be a difference in context. One of the real killers of EA for me is the focus on work products and not outcomes. The EA should always have a focus on greater flexibility for the business, addressing rigor but not increasing rigidity. Rigidity is aligned with death – hence the term rigor mortis. To me, the EA function always has a transformational element.

The final point was that the EA supports strategy and the business needs to have a strategy. The EA is not the CEO and the CEO is probably not an EA.  The EA does need to understand the current state of the business environment though. I was talking with an analyst one day who told me that an EA needs to focus on the vision and they shouldn’t worry about a current situational assessment. My response was that “If you don’t know where you are, you’ll not be able to define a journey to where you need to be.” Stephen agreed with that perspective.

My view is that there are 4 main elements of an effective architecture:

  • People – Architecture lives at the intersection of business and technology. People live at the focus of that intersection, not technology. Architectural efforts should focus on the effect upon the people involved. What needs to happen? How will it be measured? These factors can be used to make course corrections along the way, once you realize: an architecture is never finished. If it doesn’t deliver as expected, change it. Make the whole activity transparent, so that people can buy in, instead of throw stones. My view is that if I am talking with someone about architecture and they don’t see its value, it is my fault.
  • Continuous change – When you begin to think of the business as dynamic and not static, the relationship with the real world becomes clear. In nature, those species that are flexible and adjust to meet the needs of the environment can thrive – those that can’t adjust die off.
    Architectures need to have standards, but it also needs to understand where compromises can be made. For example, Shadow IT It is better to understand and facilitate its effective use (through architecture), rather than try and stand in the way and get run over.
    In a similar way, the link between the agile projects and the overall architecture need to be recursive, building upon the understanding that develops. The architecture does not stand alone.
    Architecture development can also have short sprints of understanding, documenting and standardizing the technical innovations that take place, while minimizing technical debt.
  • Focus on business-goal based deliverables – Over the years, I’ve seen too many architectural efforts end up as shelf-ware. In the case of architecture, just-in-time is probably the most effective and accurate approach since the technology and business are changing continuously. Most organizations would just laugh at a 5 year technology strategy today, after all many of the technical trends are predictable. So I don’t mean you shouldn’t frame out a high-level one – just ‘don’t believe your own press’.
    If the architecture work products can be automated or at least integrated with the tooling used in the enterprise, it will be more accurate and useful. This was actually a concept that Stephen and I discussed in depth. The concept of machine and human readable work products should be part of any agile architecture approach.
    From a goal-based perspective, the architecture needs to understand at a fundamental level what is scarce for the organization and what is abundant and then maximize the value generated from what is scarce – or at least unique to the organization.
  • Good enough – Don’t let the perfect architecture stand in the way of one that is ‘good enough’ for today. All too often I’ve seen architecture analysis go down to 2 or 3 levels of detail. Then people say “if 2 is good, let’s go to 5 levels of depth.” Unfortunately, with each level of detail the cost to develop and maintain goes up by an order of magnitude – know when to stop. I’ve never seen a single instance of where these highly detailed architecture definitions where maintained more than 2 or 3 years, since they may actually cost as much to maintain as it took to create them. Few organizations have that level of intestinal fortitude to keep that up for long.
    The goal should be functional use, not a focus on perfection. Architecting the simplest solution what works today is generally best. If you architect the solution for something that will be needed 5 years out, either the underlying business need or the technical capabilities will change before it will actually be used.

None of this is really revolutionary. Good architects have been taking an approach like this for years. It is just easy to interpret some of the architecture process materials from an ivory tower (or IT only) perspective.

When will 5G arrive?

Recently came across this interesting post on what 5G will mean for Consumers. In summary:5g wireless

  • Significantly faster data speeds: 10 Gbps, compared to one gigabit per second (max) with 4G.
  • Low latency (time to send a packet): one millisecond vs. 50 ms with 4G — great for those chatty applications being developed
  • The foundation for a more “connected world”: The Internet of Things (smart appliances, connected cars, wearables) will need a network that can accommodate billions of connected devices.

The most optimistic targets would see the first commercial network up and running by 2020, but even that may be too optimistic. As with LTE, it will take years for the network to become widespread.

What it will mean for businesses is the possibility for finer granularity across a wider geographic area. Hopefully, everyone is getting ready for IoT.

It does make me wonder about the future of relatively low speeds that many regions have as their entry level broad band for the consumer.

Abundance and the value potential of IT — things have changed…

Since I have moved to a new blog site I decided to update a post on my foundational beliefs about IT, the future and what it should mean to business.

A number of years back, I posted that the real value for business is understanding unique and separating what was abundant from what was scarce and plan to take business advantage of that knowledge.

I came up with this model to look at how things have changed:

abundanceToday, there is an abundance of data coming in from numerous sources. A range of connection options can move the data around to an abundance of computing alternatives. Even the applications available to run on the data continues to grow almost beyond understanding. Various service providers and options even exist to quickly pull these together into custom (-ish) solutions.

Yet there are elements of the business that remain scarce or at least severely limited by comparison. The attention span of personnel, the security and privacy of our environment and even actions based on the contextual understanding of what’s happening persist in being scarce. Part of every organizations strategic planning (and enterprise architecture effort) needs to address how to use the abundance to maximize the value from the scarce elements and resources – since each business may have its own set of abundant and scare components.

For IT organizations one thing to keep in mind is: almost every system in production today was built from a scarcity model of never having enough compute, data… Those perspectives must be reassessed and the implications of value for the business that may be generated reevaluated, since that once solid foundation is no longer stable. The business that understands this shift and adjusts is going to have a significant advantage and greater flexibility.