Ask any analyst or economist what would make their day, and apart from the obvious (genie in a bottle, world peace, their team winning the cup, etc.), the answer to the question will likely include “data”. It’s not sexy, it’s not exciting, and it won’t win you friends (except among those economists and analysts) but data is really important to the people whose jobs are to answer questions. And for that reason, we should all care about it.
It doesn’t matter if you’re looking back in time (“what happened when . . .?”), at today (“what is happening. . . ?“) or to the future (“what will happen when. . . ?) — a really useful starting point to answering a question lies in tracking down good data.
Now, data comes in lots of forms (qualitative, quantitative, estimated, modeled, extrapolated, time-series, cross-sectional, polling, case study, and the list goes on. . . ). The key thing is that without data of any sort, it’s really hard to make the leap from theoretical answers (or worse, guess work) to real-world scenarios. So when you’ve got data on hand and a means of using it, do it.
The challenge is that often data and numbers just aren’t available for answering questions, particularly when it comes to some of the most interesting questions about the impacts of our activities on the environment. Let’s say we want to know what impact a new renewable energy program is having. Well, if we care about the economic impacts, we’d have to have some data on jobs and expenditures to use in our analysis. And if we can about the environmental impacts, we’d have to have some information about the state of the environment before and after. Those sound like easy questions, but try looking for data and statistics to answer that question and you’ll invest many hours before you find good information.
So, making the case for more and better data is easy, the flip side of the argument, however, is that all data collection and production comes at a cost – time, money & other resources are all needed to secure good information. As a result, societies have to prioritize what data is collected and in what way. This is not an easy task, but if having good answers to some of the most challenging questions (like “what is the impact of humans on the globe?”) is important to us a whole, we need to give it higher priority.
If we had good information on the physical state of our natural environment and on the value of what it provides to us, along with good information on our activities (like resource extraction, energy flows, production of goods and services) and their impacts (like pollution and land use and species loss), combined with great socio-economic data (like income, health and education levels), we’d be able to have better-informed conversations about our economic and environmental choices.
We’ll never have data at hand to answer every interesting question, but if we think ahead to what the big questions of the next decades will be, we can plan now to have a reasonable set of energy, economy and environment data available. In the meantime, if you have access to data and can share it in any real way (I’m talking to you, governments, industries and organizations of all sizes), get it out to the world so we can all use it (data is a public good after all). And for now, don’t be surprised when you read an academic or policy report that has among its conclusions a call for better data.