Thibi decided to focus on their current subnational counterparts and direct more resources to ensure adoption and uptake. The workshops were insightful not only for the participating organizations, but also in highlighting the need to expand the definition of scaling up. In the process, workshops and discussions in which these tools were used helped several organisations to discover that what they really want and need to do, under the context of their programs, is not to expand their program, but to further ensure that changes are more embedded within their counterparts’ systems. PLJ, along with Instellar, were invited to help design and facilitate these workshops for two Myanmar organisations, Thibi and Renaissance Institute (RI), as well as Kopernik, which is based in Bali, Indonesia. From October-December 2020, Saraswati and The Asia Foundation (TAF) Myanmar developed tools to help organisations who were conducting pilots or programmes at a small scale to identify ways to scale up. Such a variant of scaling up, it turns out, is not exactly the exception to the norm. PLJ’s version of pilot to scale-up turned this model on its head: the Lab’s “pilot” relies on a large number of projects to demonstrate potential scaling up shrinks down PLJ’s portfolio to ensure uptake and adoption as the path to scaling overall impact. PLJ’s journey is reminiscent of the traditional development “pilot to scale-up” model, but with an interesting twist. A year-long transition process has led to PLJ’s repositioning strategy to shift from being merely a “data innovation facility” to becoming an “analytic partnerships accelerator.” One of the key features of this strategy is to reduce the size of the Lab’s portfolio, allowing reallocation of resources towards working with counterparts to develop capacity, set up systems, build coalitions, and ensure ownership of data innovation-driven solutions. In the absence of such capacity, uptake and effective adoption are unlikely to occur.īy the end of 2019, PLJ shifted its strategy from demonstrating what is possible to focusing more on providing support for government and development counterparts in adopting and integreating solutions that are based on data innovation. More importantly, there needs to be adequate capacity to interpret the information generated by those tools into policy and decision-making insights. While the potential benefits were immense, sustainability required maintenance, data management and regular ground-truthing. Haze Gazer, for instance, was developed to provide the Indonesian Government with a viable tool to monitor potential forest fires and haze-related issues in real time throughout the year. For the most part, the types of solutions that data innovation offers are intended to provide continuous insights, which would then feed into policy making or social intervention design processes. Going from awareness to strong adoption of data innovation, however, requires strategic systems-thinking, capacity building and trust building. This strategy was effective in building awareness of and, subsequently, demand for data innovation in the development and humanitarian sectors. By 2017, PLJ’s portfolio covered more than two dozen projects every year, with each project a demonstration of “what is possible” with data innovation. As such, PLJ needed to focus on showcasing potential solutions that these new resources could provide. When Pulse Lab Jakarta (PLJ) was established in 2012, the concept of leveraging big data, artificial intelligence and human centred design for development and humanitarian work was still novel. However, under certain contexts, focusing on stronger uptake and adoption, as opposed to expansion or replication, is a more appropriate follow up for a pilot. The premise of the model is very logical - considering there is an abundance of unknown variables that are not accounted for during the design of a policy or social intervention, running a pilot would allow decision-makers to gather information on what works and what does not at a relatively smaller cost than implementing the programme in question at scale. The “pilot to scale-up model” is a widely used approach when introducing social interventions or new policies.
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