The Economist: Platforms, Something to stand on

According to The Economist, PROVIDING THE RIGHT platform is sometimes all it takes. This is pitting industry giants against one another in an epic battle t

The Economist gives a brief overview of the platformisation that is pitting the large players in the IT industry against one another.  The real battle raging between Amazon, Microsoft, Google, Apple, Facebook, Mozilla and others is about just that: each want to be a dominant platform player, each with its own take on the game. There are several fronts in these epic battles, but ultimately it comes down to raking up as much mindshare as possible, hence the purse holder’s attention and interest.  Microsoft and Google might be the only ones attempting to fight it on all fronts, it seems to me for example that Apple isn’t really going after Facebook (might have given up), and Facebook’s platform could be seen as both a PaaS and a SaaS play, they may not want or need to go for enterprise data centre market. Linux is also in the same game, though it’s interesting to see that actually Amazon and Google (soon Samsung and Intel via Tizen?) might indirectly doing Linux a favour. I can’t truly read Mozilla yet, Google being their largest source of revenue makes me inclined to think they root for Google in a kind of kinship manner.

I always find it amusing to read some pundits ripping apart one particular vendor, say Apple or Microsoft, and citing Google as a better role model for openness. Linux is the only player that is truly flying the liberal flag, though Linux is more of a movement and isn’t a single vendor in any way. Every vendor is vying for dominance, taking sides is just as much fanboyism as any. Nobody knows for sure where this will all lead us, but I think the consumer wins when there is choice. It’s always going to be daunting to switchover from one platform to another

Here’s The Economist article: Platforms: Something to stand on.

Software is hard: things get lost in translation

Software can be hard, especially when one is not prepared for it to be so. When something goes wrong, more often than not people are looking at the wrong place or laying blame at the wrong place. This blog provides an oversimplification of the issue.

It’s a euphemism to state that software is hard. It’s hard work. Anything seriously worthwhile is going to take grit and toil. Don’t let all the self-help marketing tell you otherwise, if you do you would actually make it even harder for yourself.

One reason software can be hard is that snowball effect is very common and can quickly result in avalanche-like consequences. So I wrote one reason, not the only reason, not the main reason, just one reason. I am not going to produce long studies, hard numbers or anything of that kind here. Instead, I give an oversimplification of the way the snowball effect, the trickle down with an ever-expanding area of influence, can be visualised.

Illustration, how small issues can trickle down
Illustration, how small issues can trickle down

Whenever something goes wrong, which is to say very often, a good way to go about finding solutions is in re-examining things all the way from the top and work your way down. Which place to start, which direction to go (top-down, or bottom-up ) is a matter of taste, choice, context, but usually just a personal one. Since, quite clearly, it is a complex matter, looking for solutions in a random manner can be extremely inefficient and may never yield any result.

A corollary of this situation is that, software can result in ever-expanding benefits if things go well. Such benefits could be much more than winning the lottery for example. If you revise the diagram, take expressions like “things can get in the way”, “human condition”, “distraction” and turn them respectively into “things can contribute”, “human insight”, “epiphany” or “serendipity”, and you have a different diagram and positive outcome.  Concerns like “fear”, “doubt”, “politics”, “unexpected changes” typically have a double-edged sword effect to them. These can have positive effects when properly leveraged, or negative effects when they actually lead us to inaction or unproductive behaviour.

With software, bad things and good things, don’t only travel top-down or bottom-up, they typically start somewhere and expand like fluid dropped on a piece of absorbing cloth.

Whether are a manager or a doer, next time people rush into quick explanations or laying blames, invite them to look just a little further, to take a deep breath, to just sleep it over, and reconsider their positions. More often than not, the outcome could be different. Taking that chance to just delay conclusions a tad is usually a good bet, a profitable investment strategy.

Should Users Run Their Own Cloud Crash Safety Harness?

It is clearly very hard to eliminate infrastructure outage, even for some of the biggest players in the industry. However, we are heading to an era where Cloud infrastructure may be ‘too big to fail’, are companies going to ensure they are ready for this? Ultimately, it is an issue of the economic value of risk. Those with sound risk management practice in place would have less to fear, I am not sure many have though.

The Cloud is becoming so essential to so many companies that there comes a point where provider’s infrastructure outage could cause serious liabilities. Every few months now a large Cloud provider experiences a technical incident that takes down many popular startup company web sites for several hours. These are not some odd amateur providers, we are talking about Amazon, Microsoft, Google, the biggest there is in this game. Such outages used to be the lot of Facebook or Twitter, those companies seem to have remarkably improved their infrastructure availability, it is the turn of smaller startups by way of their cloud providers.

It’s obviously very hard, if not impossible, to completely eliminate outages, but what surprises me is that these outages are taking a long time to recover from, for infrastructure serving hundreds of companies (if you consider the ripple effects).

A naive way to look at it would be to imagine that cloud providers are running specially crafted test lab that would continually run failure scenarios and teach the operations teams how to detect them, and hopefully leading to remediations that would be put in place before they are ever experienced in real-life. This may sound costly but it wouldn’t be for companies like Amazon or Google. Perhaps they actually do something like this. In this year alone, every time such Cloud incidents has occurred and were fully investigated, it turned out that the root cause could actually have been anticipated if not prevented. Arguably it’s very hard to stress and crash test a large server cluster, but these companies have the resources and know-how to model incident scenarios and run simulations. It may be that the growth rate is much higher than the occurrence of serious infrastructure incidents, making it a lower priority for provider to double down on incident prevention. I wonder then, should it be up to the users to plan for and protect themselves against such incidents?

I don’t want to oversimplify but I imagine it economical for those with high stake in the game to setup safety harnesses. The issue at hand is really that of the economic value of risk, easily determined for a business that trade by the hour, not so trivial for companies that make no money but are valued based on the user traffic they get.  Those with sound risk management practice in place would have less to fear, I am not sure many startups have though.

If a company’s valuation is determined by the traffic they generate with no associated monetary transaction then an infrastructure outage (that can be blamed on someone else) may not have such a high economic impact. However, online advertisement is a big source of income for many startups, some sell goods and services online. For these companies an untimely outage means less visitor traffic which means missed income, and for such companies it may be critical to put in place some form of cloud outage safety harness.

How to set effective metrics for Enterprise Architecture

To set effective metrics for Enterprise Architecture, don’t look for a magical list that you could just plug in. Instead, you must to develop your own set for this exercise to make any sense. In this post, initially published on Quora, I provide one practical technique to achieve this, it starts with a statement of purpose that you should make people feel comfortable with.

A recent article by Michael J Mauboussin on HBR reminded me my answer on Quora to this same question, so I realised that that answer should really be published on my own blog, and not somewhere else. That is the motivation for this post.

Don’t look for a magical set, you need to develop your own. Here is one practical technique to achieve this, it starts with a statement of purpose that you should make people feel comfortable with.

An effective Enterprise Architecture helps ensure that an organisation spends money wisely, that resource allocation is done in a way that supports your business growth. It should be an instrument for your most powerful decision makers. The scope is massive, this spans every tidbit of information that flows through your way of doing business, it is about your entire chain of information systems (in the widest sense of the term). It goes therefore that you need to know how resource is allocated (respectively how value is created), what the triggers are and how those triggers can be influenced. Your Enterprise Architecture practice must identify and use the levers that control these events and event triggers, for it to be effective.

With the above statements in mind, proceed as follows:

  1. List the metrics that have the most impact/visibility in your organisation’s success, put them in a priority order that makes the most sense to your best people. This works best if you interview and discuss with a mix of key people: people with good delivery track record, people most intimate with your business, and people with powerful decision making power. Don’t look outside your organisation for such a list, you might quickly fall into an anti-pattern trap.
  2. Now armed with your prioritised list, benchmark where you are as you start this exercise, take snapshots of these metrics at regular intervals. Define the intervals to closely match your business activity cycle: from resource allocation to value creation. Start with a high frequency (must be realistic though), and adjust the sampling frequency as necessary, compare the measures every time and with varying sampling windows.
  3. Share the intermediate results you are getting with the people you worked with in Step 1). Try to gather their feedback on the measures that are starting to show, look for trends. Don’t hesitate to change the metric priorities, drop what doesn’t make sense.
  4. As you gain insights into what is driving effectiveness, try to make small educated changes to the metrics, and perform Step 2) and 3) again.

This is rather crude, but if done right, some solid metrics will rapidly emerge for you, and your process in itself embodies an educational and buy-in mechanism, which reinforces your Enterprise Architecture effectiveness.

With Windows 8, Microsoft is staging the biggest startup pivot in history

Microsoft is effectively undergoing a startup pivot with the sweeping changes they’ve been doing culminating in Windows 8. This is an extraordinary effort that deserves very close attention, lots of learning opportunity here.

What Microsoft is doing with Windows 8 is effectively a pivot, just like a 12 month old startup would define it. I’ve not read of it being described that way yet, but that’s all I can think of. Microsoft couldn’t be called a Startup or Lean, but I’m curious how they internally think about themselves nowadays in light of the sweeping changes they’re introducing.

Right from the start Apple had gone for intimacy, premium products whilst Microsoft had chosen for cost effectiveness and mass scale. It seems that Apple is continuing on their path, and that Microsoft is now changing strategy. Good analysis abound, I won’t dig any further than this.

If you like this subject, search “startup pivot” and read up the various definitions given of it, it is fascinating to think of Microsoft in the current context.

This is a tremendous learning opportunity, I am excited to see how it all goes.