Redesigning the Banana

(#innovation for @chrislawer @GrahamHill )

Dave McCoy asks: Who is the process owner of opening a banana? Not humans, obviously. Dave points out that monkeys have a more efficient method.

But here's my answer. The process owner for banana-opening is obviously the banana tree. The process goal is to trick the primate into supporting the propagation objectives of the tree. That’s why the banana skin is designed just so.

Humans and monkeys are both primates. In this particular case, the process owner (e.g. banana tree) probably doesn’t need to differentiate between different species of process user. The banana tree has spent a lot longer evolving the banana skin than various primates have spent working out how to open it, or how to use it for comic effect.

Who is really the process owner? Perhaps this is the kind of question that doesn't have a single correct answer. We can almost always put any given system or process into an alternative frame, thus making sense of things in multiple ways.

So that provides a context for Chris's question How to innovate the banana , which quotes a story from the Boston Globe Yes we have one banana (March 7 2007). Innovation for whom? Design for whom?

Graham thinks the answer is straightforward:

"Innovation is ultimately only for one group of people - Customers. You should have target customers for innovation in mind. They may be new customers. Otherwise you are just guessing. Current, potential, even former customers. Innovation always has some customers in mind. By definition."

But when I ask "innovation for whom", it's partly because I don't know who exactly the customers are. I also don't think that the customers for an innovation to a service are necessarily the same as the customers for the service itself. Process or production innovations may be invisible to the customer - they are often focused on improving the outcome for the process owner.

Checkland's CATWOE lens makes a clear distinction between actor, customer and owner. From the perspective of the fruit tree, the primate that eats the fruit is both a customer (receiving a gift from the tree) and also an actor within the system (dumping the seeds together with a small deposit of fertilizer in a suitable location).

However, when humans try to innovate, they usually reframe the system so that human interests and values are uppermost. The interests of the fruit (to produce more fruit trees) are subordinated to the interests of the supermarkets (to produce commodities with long shelf-life). From a human supply chain perspective, apples are better than pears because they stay fresh longer. See my previous post Comparing Apples and Pears.

Thinking about the stakeholders for the banana redesign project puts me in mind of a well-known example of syntactic ambiguity (attributed to Groucho Marx): "Time flies like an arrow; fruit flies like a banana." Framing a system is a bit like parsing a sentence - often there is more than one meaningful answer.

One of the things that interests me most about this kind of systems thinking debate is how people think they know which perspective to choose.

Walking in my son's shoes

This week my 15-year-old son has been doing "work experience". A lot of new experiences for him: travelling into Central London on his own; spending the day with adults he hardly knew; a much longer day than a normal day at school, with an entirely different rhythm of work.

One lunchtime he met a schoolmate along the street, who was doing his work experience at a hospital in another part of London. (His father is a doctor.)

My first thought was: how unlikely is that? I have been to Central London many thousands of times, and I have hardly ever met people I knew in the street. (Not counting people working in the same building or heading for the same event.)

But not so fast. The streets are full of people, but most of them are adults. Although there are lots of kids on work experience this week, these only amount to a tiny fraction of the total street population. Some more perceptive adults may notice that there are more kids around than usual; meanwhile the kids possibly pay more attention to each other than to the adults. So if there are two 15-year-old boys in a crowded street, they are perhaps more likely to see each other than two 45-year old men would. Just a theory, but it would help explain the improbable event of my son's meeting his schoolmate.

Of course, we don't always have to find an explanation for something just because it seems unlikely. But an unlikely event often stimulates this kind of enquiry. Note how my hypothesis required me to creatively imagine how a crowded street in Central London might look to my son.

Perhaps more generally, people who have something in common (born in the same village, similar vices, or whatever) have a higher than random chance of meeting in a crowd. Or it might be that we only remember those meetings that have a greater significance. Fiction often picks out such meetings, and some authors build elaborate plots around unlikely coincidences; but we may not wish to take fiction (or human memory, which is sometimes barely distinguishable from fiction) as a reliable guide to the significance of everyday life.

Technology Hype Curve 2

I wrote a critique of the #Gartner Technology Hype Curve (it's not a cycle) back in September 2005, pointing out some of the reasons why it shouldn't be taken too seriously.

Obviously I'm not arguing with the existence of the phenomenon of hype, but the evidence that this phenomenon follows a standard curve looks extremely weak. The hype curve appears to make falsifiable predictions about the expected hype-status of a given technology on a given future date. If we are being asked to take this curve as serious empirical science, we need to see some kind of scientific proof - for example, looking at the accuracy of these predictions, and using empirical data to calibrate the shape of the curve.

But although this curve has been used by Gartner for over twenty years, I have not seen any statistical analysis, whether from Gartner or anyone else, that would help us to assess how accurate these predictions have been. The shape of the curve seems to have remained remarkably stable, despite a widespread belief that innovation has been getting faster. I made all these points in my earlier post.

I understand that some people use the hype curve as a planning tool, to decide the appropriate investment and placement of technology. I'd be very interested to know how this works, and what practical conclusions can be drawn from the curve.

Another methodological problem with tracking technology hype through time is that technological jargon isn't always stable - the meaning and identity of the hyped items shifts over time. So the same buzzword on the curve in different years doesn't necessarily refer to the identical technology - we might collectively change our minds as to what exactly a given buzzword really signifies. Technology concepts may emerge slowly through a complex social process; the sociologist Bruno Latour refers to these emerging concepts as Black Boxes. If we accept that there may be a separation between the perceived progress of technology (as represented through hype and jargon) and the actual progress of technology (which we may sometimes only be able to infer indirectly), then the hype curve presumably measures the first of these. And if that's true, what value can the hype curve provide to whom?

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Parts of this post were contributed to a discussion on The Enterprise Architecture Network, via Linked-In.
See also Jorge Aranda: Cheap Shots at the Gartner Hype Curve (October 2006)