Fourth Economy continues to be involved in developing and implementing cluster strategies that move beyond the data, focusing more on tangible marketing opportunities for regions across the country. Once identified, regions can bring together common industry partners to solve challenges and help grow their respective markets – all of which helps to distinguish and add value to a particular region or community. Continue reading “Water Economy Network to Host National EPA Water Technology Innovation Cluster Leaders Meeting”
Many state governments have devoted a great deal of resources over the past decade to mitigating and responding to climate change through energy and urban planning related efforts. Planners and energy experts are fluent in the language of sustainability, adaptation, resiliency, and mitigation. But ask an economic development official what climate change means to them and it’s possible that they can barely utter the word. Many in the business community have feared that climate change will simply mean more costly equipment upgrades to reduce greenhouse gas emissions. In too many communities, time is still spent debating the veracity of climate science instead of recognizing the impacts already occurring. Economic development officials have a responsibility to help businesses understand the greater implications of climate change – how they can protect themselves from the effects of climate change; how they could develop new products or services in response to climate change; and how they should prepare themselves to recover from climate-related events. Continue reading “Preparing your Local Economy for Climate Change”
After hundreds of hours speaking with the leaders of America’s transformed cities, analyzing data until our eyes crossed and summarizing all of our findings in an action oriented report, I am ready to provide you with the cliff notes. To summarize, we found that there are nine key themes to consider if you are looking to transform your community.
The practice of economic development is like driving using only the side view mirrors – you can’t even see exactly where you’ve been, but you can see the edge of the path you’ve been taking. We try to guide ourselves forward with tools that are built for where we’ve been. Part of this rear-view navigation results from using a lot of tools that were developed to fix the problems of the past. But it is also because we have very little useful predictive information about the future. The majority of economic data is old. If we have any information about what happened even a month ago, it is somewhere between a guesstimate and an approximation of the actual conditions. By the time we manage to collect and verify the best information we can get, it is still incomplete and its shelf-life is expired. Despair.com makes a poster, “Economics: The science of explaining tomorrow why the predictions you made yesterday didn’t come true today.”
So while we can’t do a very good of predicting where the economy is headed, there are some trends coming up in our side view mirrors that are closer than they appear, or already passing by. Continue reading “3 Economic Development Trends that are Closer than they Appear”
IBM estimates that we create 2.5 quintillion bytes of data every day. They do not, however, estimate how much of this data is duplicated – all of the documents emailed between friends and coworkers that get stored on personal devices, corporate servers and cloud machines. By my own unscientific and completely arbitrary estimate, at least 55 percent of our daily data production is duplication.
Big Data includes a lot of transactional data – what you purchase from stores as well as your Google searches or the fact that Person A sent an email to Person B, as well as the content of that email. There is also data from sensors used in industrial production as well as climate, weather and traffic monitoring. It includes Twitter and other social media posts, digital photos, Wikipedia entries and data produced by researchers, scientists, corporations and government agencies.
Big Data is often unstructured but it is usually timely. It is not simply an aggregation of a bunch of data. The challenge is to structure this data and make sense of it. Economists and regional developers have been behind in tapping into Big Data but it can be useful in a number of ways. Much of it enables firms to better segment customers or develop next generation products. It can also provide value in itself by selling access to that data for specific types of users and uses.
One of the problems we have with a lot of economic data is that it is too structured or aggregated to make it useful for data mining and other Big Data analytical techniques. For instance, our use and definition of industry sectors (NAICS) hampers analysis of emerging industries. This structure is used to provide anonymity and confidentiality but it also distorts the kind of variation that is useful to better understanding how our economy works. For one, we have no idea what happens within a nondisclosed NAICS code. But even within a sector we don’t know how many firms are growing or declining or the magnitude of those changes. For most economic developers working within a local or regional economy, it can make a big difference whether an apparent “industry trend” is broadly shared by companies in the sector or if there are diverging patterns.
Currently there are few sources of Big Data for economic development analysis, but job postings, social media feeds and patent data are a few that Fourth Economy has been working on to yield new insights on economic trends. Patent data has been particularly ripe for this analysis, in part because it is so unstructured that it is difficult to analyze with traditional tools and techniques. These can be frustrating times for analysts and for anyone seeking answers. There is a wealth of data out there, but too often we aren’t able to hammer it into useful information.
We’ve set up a quick poll to gather some data of our own. It’s only one question, so share your thoughts.