Can a Computer Write a Script? Or an Ad? Or Manage a Marketing plan?

A writer of ads, or a manager of marketing plans learns what works based on results in context.  So why not?      The idea of 'a script' was used in the earliest days of AI to create directions and goals to forge results.  We did parts of what is described here to efficiently fit ads into TV and radio slots.  The idea is not far away.  And a marketing plan is a known process based on data, so use it to deliver.

Can a Computer Write a Script? Machine Learning Goes Hollywood   By Los Angeles Times 

The idea of using machine learning programs to help write scripts and other tasks is becoming increasingly popular in Hollywood.

Entertainment companies are using the technology to color-correct scenes, identify popular themes in book adaptations, and craft successful marketing campaigns.

In addition, talent agencies are using the technology for suggestions on how to market actors and actresses.

Machine learning can provide vast amounts of data on why certain movies or TV shows work and why others fail.

Last year, the Entertainment Technology Center presented analysis showing correlations between a movie's story structure and how well it performed worldwide at the box office.

For example, films that led with action sequences did more than 13 times better at the box office on average than films that started with memory sequences.

Machine learning can also identify which stories are resonating online, pinpointing specific scenes or characters about which viewers are most passionate. .... " 

Can AI Fix Disaster Relief?

Visuals are interesting here in the linked article below.  Another example of where there needs to be strong, real-time collaboration with human interactions.

Disaster Relief Is Dangerously Broken. Can AI Fix It? 
By Katharine Schwab in FastCompany

The use of artificial intelligence in disaster relief is gaining favor as weather-related catastrophes grow in frequency and severity. For example, a startup founded by Stanford University's Ahmad Wani has launched a machine learning platform to help cities respond to floods with specialized maps that update in real time so emergency crews can determine where aid is most needed. Wani said a key challenge was enabling rapid, city-wide analysis of structural engineering to better predict damage. The Flood Concern risk map was based on an earlier algorithm that digests building construction and retrofitting data, integrated with information on building materials and surrounding soil properties, to predict earthquake damage. Flood Concern crunches vast data volumes based on water-flow physics, previous flood data, and satellite imagery to approximate water depth, direction, and speed and localize areas at most risk; demographic data is layered atop the prediction so emergency planners can anticipate areas with the most likely at-risk residents. .... " 

Effective Scenario Planning

In McKinsey:   Has been a while since I have worked with this technique, some good ideas and hints to make it useful.   Not the same thing as Business Process Modeling, but some of the suggestions are similar.   I would like to hear of examples where they have been used together and produced real value.

" ... Overcoming obstacles to effective scenario planning
Scenario planning can broaden the mind but can fall prey to the mind’s inner workings. Here’s how to get more out of planning efforts.Overcoming obstacles to effective scenario planning. .... 

When scenario planning has worked well, it has proved enormously useful to a wide range of organizations as a tool for making decisions under uncertainty. First popularized by Shell in the early 1970s, the approach should be a natural complement to other ways of developing strategy—especially when executives are as concerned about geopolitical dynamics as many are today. It would probably be more widely used if it hadn’t been such a disappointment to many executives. In fact, 40 percent of those we surveyed in 2013 described it as having little effectiveness.   ... " 

Function and Process

In the APQC Blog:  Good piece about how they can work together.  Had never thought of them at odds, but can see it as described. Thoughtful blog.

Simulating for Success

In Fortune:  My early work with analytics was building simulations systems at the Pentagon.  This article describes well how this is done in Defense.  And its improved much since then.  It has been attempted in the enterprise, but not done very well.

The header of the article makes an excellent point:  " ....  Simulating real-world scenarios, and talking about what went wrong, can vastly improve performance. ... " .  The phrase implies the use of techniques like the After Action Review (AAR), which takes the time to understand failures to keep from repeating them.  Rare in the enterprise.  

And it's about culture too:  " ... Business leaders would be wise to learn from the military world, which has created a culture that emphasizes the value of simulating difficult situations and learning from the results, writes Geoff Colvin. For this to work, leaders have to be humble enough to realize that there is always room for growth and learning, he writes ... " 

P&G Moves Toward Continual Marketing Analysis

This is the future, providing continuous analysis to key measures  and making sure the right people get the data at the right time.

Procter & Gamble is working with Nielsen and DemandTec to monitor the results of market spending in real time, instead of after the fact. The goal is "continuous measurement and scenario planning," said a P&G spokesman, so marketing efforts can be continually changed based on what is working. Advertising Age