---

As the return of the concept-testing of the rural cyberspace and analytics platform (now COMP@SS Analytics) nears, here are major highlights of the first one and a half years, and the future outlook for the next one year.

In the first one and a half years, critical progress was made by coming up with a clear explanation on what generally challenges the adoption of digital solutions, as well as most productivity and sustainability innovations. It was an exciting and rewarding moment to obtain the evidence that low adoption rates of innovations in Malawi are mainly a result of the incompatibility of their user experience designs (UXDs or user designs) and the preferences of the targeted rural populations.

This new knowledge helped to discover that in some cases, the incompatible user designs of innovations are locally modified to suit local preferences and capacity. When modified, the rest of the community members access and use the innovation in some other way than that designed and expected, through one or few innovative users who have adopted it as initially designed. It is a fascinating phenomenon that demonstrates the creativity and adaptability of rural users, as well as the potential for social learning and diffusion of innovations in rural settings. The process was defined as the “indirect diffusion of value” (iDoV). It’s not a new concept, it is believed to be basically the process that underlie the emergency of taxis, the informal music burning centers and many other popular businesses, and somehow including the internationals like Uber and Airbnb. It might be argued that it is simply innovation or entrepreneurship. Yes, but there are some subtle conditions that make it get distinguished into another phenomenon.

When the innovators modify the technology use design, the developers or services providers are often not aware of this other use design. However, once modified and in use, it follows the traditional models of adoption, and the impact can be measured using the existing approaches. This entails that the most important part of the iDoV is the modification stage and its effect.

The concern is to understand how a technology use design gets locally modified and how this affects the extent of diffusion of its value or the number of units impacted as well as the level of impact. The assumption here is that if we could improve the effectiveness and efficiency of the iDoV process, we would be able to unleash the potential of the existing innovations and see them create a revolutionary impact in a blink of an eye. IDoV is about the impact of local innovative modification of an existing innovation (opportunity), not simply as an innovation or entrepreneurship.

By understanding how the use design of technologies are transformed, we can predict or estimate the probability of modification, the extent of diffusion, the specific driving factors, who can modify it and the availability of modifiers or diffusion points by looking at its design and/or local situation. It is believed that this can help in quick and cost-effective designing of interventions and their upscaling approaches or any other avenues that can offer an accelerated rural transformation such as enhancing the effectiveness of iDoV models, the designs of the innovations themselves or something else different.

IDoV is so far believed to be a product of the need (U), opportunity (X), trust (T) and local transformative innovation (Y) to the power of investment (Z), that can be roughly (unproven) represented mathematically as impact of modification = UXT(Y^Z). In the next one year, more effort will be put into understanding this concept to see if it may offer a wormhole to an accelerated diffusion and impact of digital and associated practical innovations.