The Use of Dashboards to Monitor Cluster Health

“‘Data! Data! Data!’ he cried impatiently. ‘I can’t make bricks without clay.'” 

 Sherlock Holmes

It is hard to make decisions without good data and being informed of the events and changes in the market. To sell the value of joining and investing in a cluster will be difficult if one doesn't not know what they are offering. Therefore, data that creates a holistic view of a community can help in creating stronger evidence based decision making where many compounding factors are difficult to decipher. A method of creating a level of broad understanding can lead to long term improvements in outcomes as each decision and understanding influences the decisions of key figures but also the many businesses and people within a cluster. 

One of the best ways to understand the market is to have data that can summarize the activities of the area as well as open up opportunities cross compare data to find realtions and with luck cause and effect. One might even consider the ability to measure how clusters form and change based on market changes. For example, does a new manufacturing facility lead to tax revenue increases and property value (i.e. net positives) or how might $5K in new advertising increase vacationers and investors. The ability to manage and understand the functioning health and appeal of a cluster can come from a well designed dashboard that is updated to determine cluster changes. 

Cluster Dashboard Examples:

Dashboards are increasingly being used in managing and understanding how cities function. Sometimes these metrics are geared around traditional needs. There are often new metrics that can be implemented that would provide data for businesses within clusters to make decisions. Because government and business are related but slightly different a dashboard in a cluster would be focused more on investability, social development retention (activites, quality of life, clubs, recreation, etc.), human capital development (education, skills available, etc.), loss & prevention (crime/law enforcement, etc.), industrial sites available (amount, value, type, etc.), infrastructure (rail, internet, etc.), institutions (cost, effectiveness, etc.), or industry (i.e. tourism, hotel occupancy, amount spent per visit, advertising, etc.) and others. One can design the metrics how they see fit for making decisions. 

(San Diego has a Dashboard you can look at San Diego Peformance Dashboard. For a cluster I would change this around and likely have the main benchmarks on a single page and when I click them they go down into the secondary measurements/data.)

The dashboards not only improve decision making but also provide sufficient data to start drawing some casual relationship between events and that can do wonders in seeing if an event/activity is working for the community cluster or if it hasn't had much of an impact. For example marketing to entrepreneurs and investors might lead to increased investment in the same way as an effective marketing strategy might improve vacation revenue. 

Other times we can create interaction of how one industry impacts and supports another and increase the health of the whole. For example, let us say the rest of the economy takes a downturn but the unique industry and community mix of a cluster shows that most of the businesses didn't experience this same downturn. Perhaps the industry of X widget manufacturing declines globally but we find that it grew within the cluster. We would never know the effectiveness of the cluster or how to improve it without having some level of bencharkable measurements. 

Key Points:

-Dashboards provide data for decision making on the various aspects of the cluster. 

-Dashboards can be created around cluster needs and can be unique to that cluster. 

-Dashboards might help find relationships between industries and/or cuase and effect of activities.

-Dashboards help improve decision making.

-Dashboards can help determine whether a cluster and/or industry is beating the market.

-Dashboards can measure long term changes and performance in clusters.

(Speeding up the writing of this book a little because it just looks like a good time to sort of get it out and done and move on.)