One idea I had recently is to take advantage of the fact that Steem generates useful data. This is big data which currently the community cannot effectively process. The idea is for an SMT which represents the data analytics capacity of Steem allowing for machine intelligence to make use of the big data.


   -  Big data analytics allows for big picture decisions.
    - Big data can and is being captured.
    - Steem blockchain has the data.
    - Sentiment analysis is currently possible using the data generated by Steem.

Manually our human brains cannot scale. I do not advocate we do only maximize utility manually. Once we apply machine learning to use the Steem data already generated we can make magic happen. This could indeed be an SMT and represent the data analytics or even predictive analytics functionality of Steem. This feature more than anything else in my opinion would have dramatic consequences toward utility maximization. 

Starting with capturing the real time sentiment analysis we can determine the thoughts and feelings of the Steem community. From here we can continue, to even try predictive analytics to determine whether a new feature will have a positive or negative impact. The SMT would essentially be the data analysis token which all on Steem must use to pose questions to the crowd.

> In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision making for candidate transactions.[3]

> The defining functional effect of these technical approaches is that predictive analytics provides a predictive score (probability) for each individual (customer, employee, healthcare patient, product SKU, vehicle, component, machine, or other organizational unit) in order to determine, inform, or influence organizational processes that pertain across large numbers of individuals, such as in marketing, credit risk assessment, fraud detection, manufacturing, healthcare, and government operations including law enforcement.

This untapped power can allow bloggers to adjust content according to what their followers actually want. This untapped power will inform developers by the data what features will be more appreciated. We can also apply these techniques to help solve the shared resource allocation problems.

Additional related posts:
===

[It's a very bad idea to power down or sell Steem right now](https://steemit.com/steem/@dana-edwards/its-a-very-bad-idea-to-power-down-or-sell-steem-right-now-1518490604)
[Steem must improve and the key metric for that improvement is "utility"](https://steemit.com/smt/@dana-edwards/steem-must-improve-and-the-key-metric-for-that-improvement-is-utility)
[Is there a formula to measure the expected value a blogger will bring to Steem?](https://steemit.com/steem/@dana-edwards/is-there-a-formula-to-measure-the-expected-value-a-blogger-will-bring-to-steem-1518528115)

References
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1. https://en.wikipedia.org/wiki/Predictive_analytics