Mastering the S-Curve

“Thanks to Moore’s Law the S-Curves in technology are frighteningly short.”

The S-Curve, or more correctly the Sigmoid curve is a mathematical model that gets its name from its shape that approximates a stylised S. The model has been used by many people as a way of depicting the natural life cycle of just about everything. The curve has three general phases. A start up or initial phase, which is characterised by significant learning and adaption but little apparent growth, an explosive growth phase followed by a peak and decline. The essential point is everything has a natural lifecycle and nothing lasts forever.

When it comes to innovation and business in general, the S Curve was perhaps most famously used by Charles Handy. Handy’s basic thesis is that the path to ongoing success is to begin to invest in the next curve before the last curve has peaked. You need to invest before the previous curve peaks so you have the resources you need to get through the initial learning phase.

From an IT perspective the insight that the S Curve provides is that technology follows a reasonably predictable life cycle and for organisations to be sustainably successful in a digital era requires them to be very good at managing the technology S-Curves as they apply to their specific business.

The problem is that thanks to Moore’s Law the S-Curves in technology are frighteningly short. A specific technology can go from differentiator to commodity in a few years and in this environment it is difficult to know when to invest. Let’s look at customer relationship management (CRM) systems as an example.

Organisations have been investing in CRM systems of some form for many decades now. The CRM movement however, really took off in the 1990s with the emergence of sophisticated end to end CRM systems from the likes of Siebel Systems. Large organisations around the world spent $10s of millions and sometimes $100s of millions implementing these CRM systems. Those who succeeded (and many didn’t) gained significant advantages over their competitors as they gained increased visibility into their customers and began to leverage that information for their own benefit and for the benefit of their customers. Then in 1999 Salesforce.com launched the first major SaaS solution for CRM and made this functionality available to everyone for a few dollars a month. First movers assumed the pathfinders risk, spent millions to differentiate themselves and were effectively neutralised within a decade (and that was in the comparatively slow moving 1990s).

One of the side effects of this constant differentiation and commoditisation is the rapid accumulation of technologically obsolete systems. Yesterday’s strategic platform is today’s expensive legacy system that is holding the organisation back. Even though we are still a comparably young industry established organisations maybe running technology from 3 or 4 different eras. Needless to say, these technologies were not built to easily work with each other. Not a great set up for agility. To truly add value the CIO and their team, acting as the digital strategist for the organisation, needs to break this cycle or perhaps more appropriately learn to use this cycle for their own benefit.

They do this by being very adept at identifying new and emerging technologies that matter, implementing and leveraging these technologies in a way that adds value and then commoditizing them to industry standard as that technology and underlying capabilities mature and spread. Of course all of this needs to be done in a way that ensures these new and commoditizing capabilities are seamlessly integrated with previous investments and appropriately secure. No small task.

This cycle is illustrated in the diagram below.

 

 

Because of the speed with which technology S-Curves move, you will notice that there are several cycles in motion at any one time. The digital strategist needs to effectively work these cycles simultaneously. Identifying emerging technologies that differentiate them in the market (ignoring those that don’t), implementing and leveraging these technologies in a way that drives value for their organisation and customers and then commoditizing their once distinctive capabilities (perhaps with the help of an IT Operations counterpart), as there is little justification in continuing to maintain expensive bespoke capabilities that your competitors can replicate through standard systems and processes. And they need to do this all at the same time.

In a digital world competitive advantage is measured in a few years if you’re lucky and months if your not. That is, the time you have to turn an emerging technology enabled capabilities into cash, is short. You cannot afford to invest on the assumption that the advantage you gain will be sustainable for a significant period of time besides, not all technologies will follow the full S-Curve, many will never get out of phase 1. This means that while investment is necessary to remain relevant, any one investment is risky. This drives the experimentation approach to investment early in the S-Curve.

The purpose of the experiments is to identify which innovations are likely to add significant value to your business and customers as early and as cheaply as possible. Those that work need to be implemented, leveraged and monetised as quickly as possible, because comoditisation is just around the corner. When comoditisation does catch you, you need to transition your specific processes to an appropriate “industry standard” approach. There is no longer a premium for what you are doing so you need to eliminate the overhead of complex customised solutions, besides you will not have the time to continue to maintain them as by now you will likely be well into leveraging your next cycle.

The process never ends, new emerging opportunities will get quickly commoditised to be replaced by new emerging opportunities. Well, that’s not strictly true. Digital like all innovations will have its own lifecycle and eventually digital’s power over business will wain. When will this happen? When Moore’s Law stops, or slows to a crawl, and all new technology advancements are evenly distributed across all businesses. When will this happen? Not soon, but really, your guess is as good as mine.

 

First published on www.istart.co.nz