Data-driven decision making in cities can help save money, improve citizen safety, make us healthier and improve quality of life through an exciting range of applications. As a concept, it sounds relatively simple; gather data related to your challenges, analyse it in ways that answer your questions and then take action based on insights made available through the analysis. Through this process, and by sharing methodologies for the experiments and data collection, cities have the potential to communicate clearly and transparently the how and why of their decisions. Approaching decision making in this way could increase trust in government, foster citizen participation and stimulate the improvement of decision making practices.
So, if data-driven decision making has so much to offer then why aren’t we using it more?
The concept may sound simple, but to begin a rigorous data-driven decision making process, there are a number of technical and non-technical pre-requisites to address. These pre-requisites have been well documented and I’d recommend this read. However, from a city-oriented decision making perspective I’d like to suggest that there are three particularly important things to be mindful of before going in search of data-driven knowledge.
First, ensure that you can get the data at the beginning of the challenge. This data must not only exist, but you (or collaborators) must have the time, knowledge and resources to provide it. This is particularly true if your question is likely to rely on repeated data provision. Where possible incorporate time for data acquisition in your research plans and be ready for delays. Second, all collaborators need to be confident that the use and sharing of data conforms to legal and security requirements. Without a clear explanation of how your research is responsible, collaborators may delay or block data supply. Ensuring that collaborators have full confidence in legal and security practices is difficult and emphasising clear explanations of legal and security requirements can help keep things moving. Finally, be aware that not all data-driven projects will yield a) the answer you were hoping for, or b) an answer at all. Even with a well-planned, timely supply of clean, relevant, and secure data, the answer to your question may not be available with the information at your disposal. Though it may be hard to accept, this element of risk exists in many data-driven research endeavours.
Each of the seemingly small pre-requisites summarised above and those detailed elsewhere can act as a significant blocker in any data-driven project. Though these items may seem technical, many of them require people with the time and expertise to address them. For example, ensuring that data are used securely and within the bounds of the law requires specific domain knowledge. Likewise, collecting data relevant to city challenges may require expertise in Big Data, Geographic Information Systems, or even the Internet of Things.
Though the pre-requisites listed above are just a selection of the potential blockers to data-driven decision making, cities and analytics experts can work together to facilitate the growth of data-driven decision making and overcome these barriers. If you’re a city keen to make use of data then consider the following:
1. Start small and focus on a specific challenge. Consider a challenge for which you know data exists and can be used (such as non-personal data). Doing so will make it more likely that the pre-requisites discussed above are met.
2. Set SMART goals for the data-driven decision making. The same data can be used to answer many different types of questions and it helps to focus on the ones important to you. Use specific questions to focus your process.
3. Publish and update citizens on your intentions, methodologies and findings. Citizens may help with data collection and could provide feedback or even analysis that saves time.
4. Work with what you have to begin with, the technology and skills that you need will reveal themselves. Do not worry about purchasing an extensive cloud-based technology stack if you don’t have one. Simple analysis skills and a spreadsheet can go a long way. Once you have exhausted this, then consult experts.
5. Consult other cities, they may have similar challenges to you.
6. Share your data and communicate your challenges. Citizens, businesses and academia will want to help. There will be some challenges where blockers prevent this, but by identifying opportunities where data could add value and providing access to data in machine readable formats, collaborators can provide more informed assistance or suggestions.
If you’re a company and want to help cities to improve their data-driven decision making there’s a few things that you can do to make it easier for cities to work with you.
1. Identify specific data-driven challenges that you know can be solved and explain how. Don’t offer something that can solve ‘all the data challenges’. Cities need to develop confidence with data-driven decision making and developing a portfolio of use-cases will facilitate this.
2. Recognise the limitations of civic staff to dedicate time to tasks outside their current remit. Collaborating with analytics companies is not usually something that civic staff can dedicate their time to. If you have the capacity to address the pre-requisites mentioned previously and elsewhere do so if possible. For example, provide data use agreement templates or make it clear that you are taking the required security precautions to provide peace of mind.
3. Offer to take on some of the risk. If you have confidence that your data-driven approach can save money or improve lives, arrange your business model appropriately. If the city pays a fee based on your impact or has the capacity for a trial period they are more likely to work with you.
4. Finally, acknowledge that some of the wicked problems encountered in cities won’t have a clear solution and may be rife with uncertainty. As a result, you may not be able to act on all data-driven insights, but at least you’ll take a step toward informing the debate.
Leveraging data-driven decision making in cities is an opportunity. Through it, we can positively impact lives and increase the efficiency of our natural resource consumption while simultaneously learning and sharing knowledge. Cities are complex systems with institutional inertia, lots of barriers and legacies that can make leveraging data difficult. I believe that making cities better places, sharing knowledge and informing policy mean that it’s a challenge worth facing.
This guest post was supplied by Dr Joseph Bailey of the Future Cities Catapult