The uncertainty of digital products

During the last posts I have written of the importance of process in high uncertainty situations and the idea of strategy as a framework. In this and the following posts we will explore why I believe this uncertainty is higher in digital product companies than most other companies.

First consider the integrated steel companies in the 70-80s and the disruption they faced from the new mini mills. As described famously by Clayton Christenssen the novel but worse performing mini mills started in the low margin, low quality rebar market. However they then worked their way up market, improving their quality and taking market segment after market segment, to the point where now there is only a few integrated steel mills left in the US. No question this is a story of disruption, change and uncertainty.

In one area where the steel mills faced some amount of certainty though was in the predictability of demand. In steel, if you could produce steel at the right quality (as could be measured objectively) for the right price and have acceptable distribution demand was not that unpredictable. For this types of products, the lower uncertainty in demand also extends to new products. Demand for new products can be estimated looking at segments in the market that would likely be interested in the new product and the price could be estimated based on how much extra value the product new product would provide.

I believe this is radically different in digital products. In digital products a main dilemma is usually not whether its possible to build something but rather if anyone want to use it.  Lean Startup author Eric Ries formulated it well: “Just because it can be built doesn’t mean it should be built”. An easy way to exemplify this is to draw to memory all social products that traditional companies have launched and failed with. The underlying assumption in many of these products was likely: “if x% of our customer base started using this product it will bring us benefit A, B and C”. Unfortunately the share was usually 0%. It turns out that estimating the adoption of new digital products is usually very hard and the traditional [customer base * adoption rate] is usually way more off than for traditional products. 

So why are digital products different? This is a topic I will explore over several posts but I believe the difference come from two fundamental properties of digital products and software in general. The first property is the zero marginal cost of producing an additional copy of the product which leads to price per unit is taken out of the equations. The second property is the high malleability of digital products which means it’s possible to make changes quickly and continuously. In the next post we will explore these two properties further.