Previously, I studied the works of Clayton Christensen on disruptive innovation. In this post, I will be building on those notes with a specific focus of attempting to forecast the disruptive innovations in the software industry.
Framework to forecasting the disruptive innovation in Software
Keller and Hüsig (2009) noted that there is “a lack of definite frameworks for [forecasting] identification of disruptive innovations”. Thus, they developed a new framework to answer their thesis question of “whether web applications post a disruptive threat to incumbents or a disruptive growth opportunity for entrants“.
What I found interesting is that they combined the following disruptive innovation forecasting approaches:
- The disruptive threats for incumbents – (Rafii and Kampas 2002)
- Industry change due to innovations – (Christensen et al. 2004)
- Disruptive potential of a technology – (Hüsig et al. 2005)
As a result, they developed a framework consisting of two parts;
- Criteria sheet – a score-card like system for helping forecast the disruptive innovation for both the entrant and the incumbent
- Trajectory map – mapping the performance attributes of the entrant and the incumbent
Criteria Sheet for forecasting potential of disruptive innovation
Rafii and Kampas suggest that “since disruptive is generally a serial process, a very strong disabling factor can prohibit it early on”. Therefore, Keller and Hüsig, had three phases to the criteria sheet:
- Foothold market entry: the innovation grows successfully in a market niche
- Main market entry: the innovation enters the mainstream market
- Failure of incumbents: incumbents fail, because they cannot successfully implement the innovations themselves
Each of the criterion are checked for fulfilled, not fulfilled or unknown for both the entrant and the incumbent. Below, is an example provided by the authors for comparison between Google docs and Microsoft office:
Trajectory map for forecasting potential of disruptive innovation
Like Christensen’s graphs, the trajectory maps mapped the performance attributes. Keller and Hüsig were specifically looking for the following criteria:
- The performance trajectory of the PDI intersects the (lower) demand trajectory
- The performance trajectory of the established technology overshoots the (lower) demand trajectory
- The performance trajectory of the PDI shows a steep curve (fast attack on incumbent)
- The price trajectory of the PDI intersects the price trajectory of the established technology from above or stays always below
Here are two examples provided by the authors:
Applying this framework for forecasting in the software industry
Keller and Hüsig (2009), have put forward a pragmatic framework in attempting to answer a critical question for product managers and leaders in the software industry. Is company x disruptive company y? The authors have also provided an in-depth analysis of Google’s office products (google docs) vs Microsoft’s office suite.
I hope to apply this framework in the future when evaluating and understanding the landscape for software products.