The UK Government Digital Marketplace (GDMP), which offers Government tender opportunities, secured funding to setup the digital marketplace and associated reforms in emerging economies worldwide. By opening up procurement of digital, data, and technology (DDaT) products and services it can reduce corruption often associated with these tenders. In order to move forward successfully, the GDMP engaged us to assess DDaT capability and maturity in each of the target governments.
Understanding DDaT capability and maturity is an essential first step to plan investment and strategy to help with transformational change in these overseas governments. Our goal was, amongst other things, to assess where their DDaT strengths lay and to understand their progress to date in transformation to digital services, with a view of how much knowledge was held in house and how much was external.
Alongside our own research and assessment model there are many others already available from the likes of the United Nations, The Organisation for Economic Co-operation and Development, and Harvard Kennedy School. We initially spent a number of weeks reviewing around eight approaches to learn what they offered and were largely satisfied they all had their place. However they were not designed to help us directly with inputs to making decisions on where the GDMP should invest next and why for DDaT.
We needed a model for assessment that could help decision makers understand the value of different DDaT interventions. Our existing ‘nine-box model’ was designed for that, identifying in a prioritised fashion where change is needed, so we refined this for the engagement. By collating research into boxed categories it becomes easy to find potential impact, where strategies are failing, and also about what will likely happen in the future.
We used and iterated on the model across five countries in the scope of the GDMP mission: Mexico, Indonesia, Malaysia, Colombia and South Africa, conducting small targeted visits with around a week spent with governments of each country. Research depth and quality varied with each government as attitudes to being open differed, but insights were nevertheless forthcoming from the raw data.
Using our model, we were able to start telling stories but realised we couldn’t yet allow others to do the same without needing to train them first. This alerted us to the need for another model asset, one that would enable the report to be interpreted by non-specialist readers. We were particularly keen to support senior decision makers who need to act on the findings and need to be able to process the information in isolation without it requiring any explanation.
The outcome was simple, readable information for the purpose of advising investment decisions and changes to strategy across digital, data and technology in these governments. The approach has now been iterated and validated, and is applicable to any large to small organisation looking to invest in improving its use of DDaT and where to scale up it’s capability.