Optimal Exercise Point

April 13, 2010

Although I have been making use of them over the last 18 months in various presentations and the real options tutorial, I recently realised I’d omitted to publish graphs illustrating the optimal exercise point for real options on this blog. As a result, here they are:

The dotted blue line represents risk entailed by the agilist’s Cone of Uncertainty, and covers technical, user experience, operational, market and project risk – in short anything that could jeopardise your return on investment. The way this curve is negotiated is detailed below, by driving out mitigation spikes to address each risk.

The dotted brown line represents risk from late delivery. At a certain point this will start rising at a rate greater than your mitigation spike s are reducing risk, creating a minimum in the Cumulative Risk curve denoted in red. Remembering that

Feature Value = ((1 - Risk) x Generated Value) - Cost

this minimum identifies the Optimal Exercise Point.

One point worth exploring further is why Delayed Delivery is represented as risk rather than cost. The reason is because Cost of Delay is harder to model. For example, let’s say we are developing a new market-differentiating feature for a product. Let’s also say that there are X potential new customers for that feature in our target market, and that it would take Y weeks of marketing to convert 80% of those sales. Providing whenever we do launch, there remains Y weeks until a competitor launches a similar feature then then the cost of delay may be marginal. On the other hand, if we delay too long and a competitor launches their feature before us then there will be a massive spike in cost due to the loss of first mover advantage. However the timings of that cost spike will be unknown (unless we are spying on the competition), and therefore very hard to capture. What we can model though is the increasing risk is of that spike biting us the longer we delay.

I have found it very helpful to think about this using the insightful analysis David Anderson presented during his excellent risk management presentation at Agile 2009 last year. He divides features into four categories:

  • Differentiator: drive customer choice and profits
  • Spoiler: spoil a competitor’s differentiators
  • Cost Reducer: reduce cost to produce, maintain or service and increase margin
  • Table Stakes: “must have” commodities

Differentiators (whether on feature or cost) are what drive revenue generation. Spoilers are the features we need to implement to prevent loss of existing customers to a competitor, and are therefore more about revenue protection. And Table Stakes are the commodities we need to have an acceptable product at all. We can see how this maps clearly onto the example above. The cost of delay spike is incurred at the point when the feature we intended to be a differentiator becomes in fact only a spoiler.

This also has a nice symmetry with the meme lifecycle in product S-curve terms.

We can see how features start out as differentiators, become spoilers, then table stakes and are finally irrelevant – which ties closely to the Diversity, Dominance and Zombie phases. There are consequences here in terms of market maturity. If you are launching a product into a new market then everything you do is differentiating (as no-one else is doing anything). Over time, competitors join you, your differentiators become their spoilers (as they play catch-up), and then finally they end up as the table stakes features for anyone wishing to launch a rival product. In other words, the value of table stakes features in mature markets is that they represent barrier to entry.

More recently however, I have come to realise that these categories are as much about your customers as your product. They are a function of how a particular segment of your target market views a given feature. Google Docs is just one example that demonstrates how one person’s table stakes can be another person’s bloatware. Similarly, despite the vast profusion of text editors these days, I still used PFE until fairly recently because it did all the things I needed and did them really well. Its differentiators were the way it implemented my functional table stakes. The same is true of any product that excels primarily in terms of its user experience, most obviously the iPod or iPhone. Marketing clearly also plays a large part in convincing/co-ercing a market into believing what constitutes the table stakes for any new product, as witnessed in the era of Office software prior to Google Docs. The variation in the 20% of features used by 80% of users actually turned out not to be so great after all.

So what does this mean for anyone looking to launch a product into a mature market? Firstly, segment you target audience as accurately as possible. Then select the segment which requires the smallest number of table stakes features. Add the differentiator they most value, get the thing out the door as quickly as possible, and bootstrap from there.

The phrase “Agile in the Large” is one I’ve heard used a number of times over the last year in discussions about scaling up agile delivery. I have to say that I’m not a fan, primarily because it entails some pretty significant ambiguity. That ambiguity arises from the implied question: Agile What in the Large? So far I have encountered two flavours of answer:

1.) Agile Practices in the Large
This is the common flavour. It involves the deployment of some kind of overarching programme container, e.g. RUP, which is basically used to facilitate the concurrent rollout of standard (or more often advanced) agile development practices.

2.) Agile Principles in the Large
This is the less common, but I believe much more valuable, flavour. It involves taking the principles for managing complexity that have been proven over the last ten years within the domain of software delivery and re-applying them to manage complexity in wider domains, in particular the generation of return from technology investment. That means:

  • No more Big Upfront Design: putting an end to fixed five year plans and big-spend technology programmes, and instead adopting an incremental approach to both budgeting and investment (or even better, inspirationally recognising that budgeting is a form of waste and doing without it altogether – thanks to Dan North for the pointer)
  • Incremental Delivery: in order to ensure investment liability (i.e. code that has yet to ship) is continually minimised
  • Frequent, Rapid Feedback: treating analytics integration, A/B testing capabilites, instrumentation and alerting as a first order design concern
  • Retrospectives and Adaptation: a test-and-learn product management culture aligned with an iterative, evolutionary approach to commercial and technical strategy

When it comes down to it, it seems to me that deploying cutting-edge agile development practices without addressing the associated complexities of the wider business context is really just showing off. It makes me think back to being ten years old and that kid at the swimming pool who was always getting told off by his parents “Yes Johnny I know you can do a double piked backflip, but forget all that for now – all I need you to do is enter the water without belly-flopping and emptying half the pool”.