I’ve always been a huge believer that customer service is one of the most valuable pieces of brand development. Companies who have superior customer service are recognized as a stronger brand and tend to have better sales numbers than those without. Associations who put customer service first tend to have a greater number of members than those who do not. The fact of the matter is that sales are directly proportional to customer service. The same can be said for economic development.
So, how are you manning the front lines of your economic development efforts?
Continue reading “Who’s on the Front Lines of your Economic Development?”
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.