data-Fab

Introduction to data-Fab (dF)

  • data-Fab was created by practitioners to provide high-quality, reasonably-priced data on local and regional economies with the intents of greatly reducing expenditures on data and analytics and freeing resources for strategy development; and closing the information gap between small and large businesses and communities and investors.
  • data-Fab’s products represent significant improvements over current alternatives in: coverage, data quality, cross-pollination, geographic specificity, timeliness, speed, value, and project support.

Link to data-Fab website to purchase data: coming soon!

Coverage

data-Fab generates point estimates for every industry in every U.S. county, providing the data necessary for high-quality analytics on conditions and trends

Data Quality

By using all available local, state, and national data to estimate every data point, data-Fab produces data that are unmatched in quality; streamlined back-end processing allows for centralized quality control and assurance; the data-Fab team monitors and analyzes new data releases from sources, automatically sharing updated data in the event of data corrections

Note: Includes all industries (2D-6D) where the state value is given; data is for the state of California and is from 2016

Cross-Pollination

By creating functional bridges between information sources, data-Fab generates new data on local and regional economies

 

A New Industry Typology Based on Distinct Market Areas

Traditional approaches classify individual industries as “local” or “traded.” However, based on analysis of ~11K zip codes and ~600 counties in the 100 largest MSAs, UDP has identified three distinct market areas: neighborhood, regional, and traded. This improved understanding of industry market areas is critical for land use planning and for developing inclusive growth strategies.

1.) One industry moved from Local to National/Global (not shown in graphic)

 

Market Area Industries and Characteristics

Evidence of three distinct market areas and industry types is supported by information on sales, establishments, and wages.Size of market area strongly influences average firm size and wages in an industry.

 

Sample Application: Columbus, GA Study

Source: Mass Economics, 2020

 

Stages of Innovation and Applying Those Stages to Tasks

The Innovation Trajectory

Moving from ideas to job creation is a staged process from ideation/research/discovery (I) to prototype development (P) to commercialization (C) to scaling (S). Once scaled, the product/service delivery can be classified as routine operations and management (R).

Assigning Categories to Tasks

Based on the description of 18,000 tasks performed by US workers, each task was assigned an (I), (P), (C), (S), or (R) based on the nature and function of the work. (In cases where a task was relevant to more than one stage, the “higher” stage was used.) Using occupation-task matrices, each occupation in the US economy was then assigned an (I ), (P), (C), (S), or (R) based on the relative importance of each type of activity. These “stages of innovation” analytics can be used to identify innovation strengths, gaps, and opportunities in districts, cities, and regions across the U.S.  

Sample Application: Understanding Innovation Activity in Kendall Square

Kendall Square

Stage Jobs LQ
Ideation 9,600 5.7
Prototyping 8,400 1.4
Commercialization 7,800 2.6
Scaling 6,700 1.4
Routine Operations 25,700 0.6
Total 58,200

Source: Mass Economics, 2014 and 2016

Map Legend
ID anchors
Other ID assets
3 largest employers (private)

Geographic Specificity

data-Fab can provide extensive, high-quality information for sub-regional geographies (counties, cities and towns, neighborhoods, districts, corridors)

Timeliness

data-Fab utilizes data sources that are available sooner, allowing for more timely applications; data-Fab provides granular employment data for three units of times – annually, quarterly, and monthly – to illustrate current highly-localized and current trends

Note: Quarterly data are considered preliminary until their final release with the annual data; BLS estimates that typically only 0.05% of entries are revised with new quarterly releases; nearly all (95%) of subsequently-released preliminary county totals for 1Q2020 are within 1% of their initial release

Speed

Data sets that used to take weeks or months to be created can be delivered within hours

Value

By using estimation algorithms and highly efficient data transfer protocols, all-in costs of producing data have been substantially reduced, efficiencies that are reflected in data-Fab pricing

Project Support

data-Fab’s online tool can price any set of options, allowing users to calculate all-in data and analytics costs for internal budgeting and proposal development; data-Fab staff are available to discuss project data strategies

Link to data-Fab website to purchase data: coming soon!