Strengthening regional economic and entrepreneurial performance with 'mission' data.
It’s been almost 30 years since Harvard Business School professor Michael Porter introduced a concept called “clusters”—geographic concentrations of interconnected firms and supporting organizations. Since then, this concept has actualized and made a considerable impact across the globe.
The Impact of Clusters
Strong clusters promote innovation through their dense knowledge flows, strengthen entrepreneurship by boosting new enterprise formation, enhance employment growth in industries and positively influence regional economic performance.
There are countless examples that highlight the diversity of clusters, such as, Vermont’s Artisanal Cheese Cluster, Michigan's Clock Cluster and even the Wichita Aviation Cluster. For now, we’re going to focus our attention on innovation clusters—environments that favour the creation and development of high-potential entrepreneurial ventures, like St. Louis’s Bioscience Cluster.
U.S. Cluster Mapping
Innovation clusters can range in size. With some boasting over 15,000 well-paying, highly-skilled jobs across 150 growing companies, and others representing a humble 50 employees. Large or small, innovation clusters play a significant role in their region’s economic prosperity and are just as prone to the challenges faced with data collection.
Collecting Data isn't Easy
Data collection is a challenge faced across a variety industries for a variety of reasons. For innovation clusters, collecting data is challenging because of the high volume of people, programs, companies, sponsors and partners that can be involved in a single cluster.
How do they measure their economic impact? How do they track the companies they work with? How do they ensure their programs are effective? How do they guarantee those metrics are backed by defensible data? And, how do they avoid getting lost in the large amounts of data that they can collect?
By remembering that measurement only matters if it changes the way you act.
More specifically, if the collected data doesn’t relate to the bigger, more meaningful picture, tracking metrics doesn’t achieve much. So, here’s what innovation clusters should keep in mind when embarking on their data collection strategies journey.
Focus on 'Mission' Data
Most innovation clusters track their performance by metrics like dollars raised, number of companies served and overhead costs. Though this data is important, it is not high quality and does not measure a cluster's main objective—achieving its mission.
That’s why every innovation cluster should start its data collection journey by identifying its mission and measuring its progress in fulfilling that mission. How is this achieved? There are three options.
1. A cluster can narrowly define its mission so that progress can be measured directly.
2. A cluster can invest in research to determine whether its programs and activities do help to mitigate the problems or to promote the benefits that the mission involves.
3. A cluster can develop micro level goals that, if achieved, would imply success on a grander scale.
Data is an essential element of business intelligence. With good data, innovations clusters can answer the questions listed above, and make analytical, data-driven decisions that will positively impact the companies and communities they support.
How to Collect the Data
Thousands of startups and over 80 innovation organizations rely on Hockeystick for analytics and stakeholder reporting.
Hockeystick is the first software platform designed to help innovation clusters measure their impact. Incubators and innovation organizations rely on good data to measure their performance and track the companies they work with. But collecting data is a manual process using a patchwork of tools like Excel, email and CRM products.
Hockeystick is a complete end-to-end system that includes custom metrics design, automated data collection and built-in visual dashboards and reports.