New computer science

It might seem odd, given I make my living helping organisations with their IT, that I am what marketing types call a “late adopter”. I was just about the last person I know to get a DVD player and even my mother got a high definition TV at home before me. I skipped the first 3 iPhones and I am only a month into my first tablet. But being a late adopter doesn’t mean being ignorant about the latest developments. I may be a late adopter but I am also an early monitor; trying to keep up with new ideas so that I can, hopefully, help others. Adopting new ways of working or technologies should be a well informed decision not a reflex.

Here are a variety of areas that I am monitoring, as they may develop into useful tools in the future, together with some research topics which I think deserve more attention than they are currently receiving.

What new developments do you think we should be tracking now? Add a comment or use the buttons at the end of this post to let me know what you think?

Promising developments

Anti-fragility

Fragile structures and systems are destroyed by failures - think about dropping a glass tumbler. The key characteristic of anti-fragile systems is that they grow stronger through failure. Many examples exist in nature, such as how bones can thicken following a fracture. Some people are thinking about how to apply these ideas in IT systems to make them more reliable and useful - Netflix’s Chaos Monkey is a famous example. The link below is a good introduction to the ideas and I think there is a lot of potential here.

• Great anti-fragility resources
• Replay of the Flowcon keynote by Adrian Cockcroft

Stream data

Databases and systems which look after them have dominated IT for decades. There is plenty of long standing computer science devoted to this area (do students still study 3rd normal form?). Databases have scaled pretty well for a long time but some of the problems we are now trying to solve don’t always suit them very well. Solving problems by thinking about data streams rather than databases may help and provide workarounds some of the constraints of doing all of our computing in the cloud. It will probably be some time before the computer science catches up.

• Mining High-Speed Data Steams
• Stream mining essentials
• The promise of big data meets the harsh reality of large-scale legacy IT
• From Databases To Dataclouds
• Amazon’s streaming data service
• Streamtools
• Putting Apache Kafka to Use: A Guide to Building a Stream Data Platform
• Differential Dataflow

Technical debt

Financial debt allows organisations to consume resources or acquire assets in advance of earning the income to pay for them. Taking on debt involves additional costs but the benefits of early access to resources or assets may be even greater. It can be useful to think about unresolved problems in IT systems in the same way and this has started to be called “technical debt”. It might be a good idea for organisations to take on technical debt, for example, to get a product or service into the market quickly, but, just like financial debt, servicing technical debt can be expensive and could bring the organisation down if it is not carefully managed. At the moment technical debt is used as an analogy or thought experiment (first link below) but I think it has some potential as a quantified management tool and some organisations are exploring this kind of thing (second link).

• Technical Debt vs. Time-to-Market
• http://techdebt.org/
• Technical Debt: Adding Math to the Metaphor

Needs more work

Information asset value

Information is valuable. The giants of IT spend millions fighting over intellectual property and the stock market valuation of many global firms can only be explained by considering the value attached to their customer databases, brands or other stocks of information. So it would be reasonable to assume there would be a wealth of useful material on measuring and managing the value of information assets. Unfortunately this is not the case. Most work on IT asset management concerns software licences - effectively looking after someone else’s assets! Here is a link to one of my previous blogs which covers this problem and the implications for CIOs.

Related @CIOPortfolio blog post

Distributed security

Distributed security has not been neglected in the same way as information asset management but there is still plenty of work to do. This isn’t just about stopping hackers getting to my email or taking over my twitter account. Not all of my email and tweets are equally important and need the same level of protection. Some are the digital equivalent of a friendly wave. Some emails in the personal and work domain are commercially sensitive. Why are our controls tied to the device or application we are using rather than the information we are processing? Here are links to a couple of relevant initiatives.

• Collaboration Oriented Architecture
• UK Government ID Assurance

Social architecture

No, this has nothing to do with Facebook’s mobile applications or Twitter’s data centres. Social architecture is about understanding how individuals, teams, communities and large populations behave and then using this insight to design the social structures that you need to achieve your objectives. You then need to develop the products, services and operating models that are needed to encourage the emergence of your social architecture. Many still assume that this is just a smart way of handling marketing and advertising but some disruptive organisations which are making an impact with co-creation and collaborative consumption are showing that the potential is much greater than this. Don Tapscott and Anthony Williams spotted this potential earlier than most people and there is a lot about social architecture in their 2007 book, Wikinomics. Here are some links to follow up if you are interested.

• Adapting to the era of deep engagement
• Community Managers: The Hub of Social Business
• Related @CIOPortfolio blog post
• Social power structures