The Metro Outlook 2.0 Model

Why create a model?

Over time, we can concentrate only on the set of indicators that provides independent information about how the region is doing and whether it is moving in
the right direction.

Having identified goals, it is tempting to proceed directly to defining measures of them and see how we're doing. However, what we see depends entirely upon what we choose to look at. It is too easy to pick data that fits a predetermined conclusion; as others have often stated, we are what we measure.

The traditional approach to choosing indicators

To avoid cherry-picking information, most indicator projects divide the characteristics of successful regions into categories and assemble a group of subject experts in each category to pick the top five or ten indicators. There are two problems with this approach.

First, each subject expert has an implicit mental model of how things work that drives his or her view of which indicators are most important. Using a consensus-driven approach to indicator selection can result in indicators that tell different stories, and only parts of different stories at that. This makes analyzing the meaning of the indicators difficult.

Second, having different groups of experts separately define sets of indicators treats the different categories of regional progress as independent when they are really all interrelated. Making connections across categories — how influencing an indicator in one area may improve all areas down the line — becomes difficult. Yet, this is the most important thing to learn. Connections across categories are also the source of policy leverage, where a little change makes a big positive and permanent difference. By making linkages more difficult to see, a simple categorical approach to choosing indicators diminishes their value to policy-makers.

The Metro Outlook approach

Metro Outlook has chosen a second way to select indicators, which is to create an explicit model of how regions generate the quality of life necessary to attract, develop and retain talented people — the essential ingredient of an innovative, competitive economy. This makes it possible to describe the linkages between the goals, to define indicators of achieving the goals that work together by design, to identify likely high-leverage interventions and to provide indicators that track their success.

In essence, an explicit model allows Metro Outlook to make predictions — if we change this, that should change. Given the relative inexperience with this kind of model, it is important to understand that in its current state, the predictions Metro Outlook 2.0 makes may be wrong. The explicit nature of the model will help us find these shortcomings sooner rather than later.

Exposing the model behind the indicator choices to public and academic scrutiny encourages the criticism necessary to continuously improve the model. Consequently, over time, the region gets more efficient at making progress because it learns, records and embeds in the model which things actually work.

The more we discover how things are actually connected, the fewer individual indicators we have to actively monitor. Theoretically, the ideal number of indicators is one — change one thing and everything else we are concerned about falls in line like dominos.

Of course, this theoretical limit is unlikely to ever be reached. However, it illustrates the power of understanding linkages. Over time, we can concentrate only on the set of indicators that provide independent information about how the region is doing and whether it is moving in the right direction.

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