I have been doing some personal retrospectives on past client engagements to identify what patterns to carry forward and what is better left behind.  My most successful projects have included not only cross discipline teams, but team members who have cross discipline curiosity.  What is cross discipline curiosity?  I'll define cross discipline curiosity as a desire to know or learn something outside of your specific purview.  When you are curious about other disciplines you are able to collaborate at a deeper level.  

Curious teams ask the following questions:

• As a team member, how do the decisions I make in my discipline impact marketing/design/product/quality?
• As a team member, how have decisions made by other disciplines impact my objectives?
• As a team member, what questions do I need to ask/conversations do I need to have to ensure we produce the best possible outcome?

Encouraging this type of collaboration will ultimately increase team confidence and result in a better product.  Embrace your curiosity to increase the success of your teams.

It appears that the tunnel on the left is blocked off while the tunnel on the right goes through the mountain.  Most people would look at this picture and quickly choose the tunnel on the right. 

Based on the limited information you have, you made a judgement without questioning if other information is available.  This is an example of the psychological effect "What you see is all there is" (WYSIATI) named by Daniel Kahneman.   This cognitive bias is based on the concept that there are two thinking modes co-existing in our minds.  System 1 is fast and automatic; often responsible for our "knee jerk" reactions.   System 2 requires mental effort and is sometimes referred to as the rational mode. 

The word friction is used a lot in product design.  "Create a frictionless experience." "Reduce friction for our consumers." But what is friction? A common misconception is asking the user to interact with a product anything more than the absolute bare minimum creates friction.  This drives product owners to employ techniques such as strict limits to the number of steps, removing consumer input prompts, and doing too much "on behalf of" the user with limited data.  On its own, requiring the consumer to interact with a product does not create friction.  What creates friction is increasing the likelihood of a failure through poor implementation. 

Take this example:  Rhonda wants to help out her mother by ordering groceries and having them delivered to her mother's house.  She launches the app, selects a store, creates an order, and goes to checkout.  On the checkout screen she  the address is set to her address so she changes it to her mother's house and taps submit.  Her mother's address is not within the store's delivery range so she is presented with an error. 

At this point Rhonda has experienced a clash of wills with the app and is an unhappy consumer.  Had she been able to set her address up front she would have been able to select a store that delivered to her mother and not wasted so much time.

Techniques to Reduce Friction

• When setting data on behalf of the user make the values selected obvious.
• Use defaults, but also make it easy for the user to change them.
• Front load decisions that may result in an error later in the flow.
• If you have to limit interaction points, focus on the decisions that have the greatest likelihood of resulting in a success or failure.
• Consider changing scope if you are unable to minimize the opportunity for failure.

Square pegs do not fit into round holes and frustrated consumers do not use your product.  Be explicit, allow the user to provide input, and fail early to reduce friction in your products.

I have been thinking on the topic of perspective and how it applies to product decisions.  So often we get into a myopic state where all we think about is the immediate goal in front of us.  This can lead to short sighted decisions and a product that only meets the needs of a small segment of target consumers.  

Play with perspective to identify shortcomings or hidden opportunities during product design.

• What is the critical task all (or nearly all) users want to complete?
• What is the critical task you want your users to complete?
• Does your product support those critical tasks?
• To whom is each feature important?
• Are there features that are unimportant that can be removed?
• How do external factors affect the use of your product?
• Can you control for external factors?
• How do users want to use your product?
• How do they have to use your product based on what you've designed?
• Are there limiting factors for users in other markets?

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Go beyond user stories and look at environmental, technological, and other factors that may affect how users interact with your product.  Implement the features that provide the greatest benefit to the highest number of users in a manner they find accessible.  At the end of the day, you will get the result you want if you build the product they need.  

AI and predictive design is very popular right now, but relies on a very large, historical data set to be successful. ​I work with a diverse set of clients across an array of industries and find myself having the same conversation regarding including AI in new products.  

Most new products simply do not have enough historical data to create accurate training data for a specific problem. Anticipatory or predictive design is intended to make decisions on the behalf of the consumer to reduce cognitive load.  The wrong decision creates friction and overall dissatisfaction with the product.  Until you have enough data, it may be better to have your consumers tell you what they want rather than try to guess their intent.

Just because you are able to execute the shiny new thing it doesn't mean you should.  Take a step back and take time to gather data.  Once you have enough data to reliably understand your consumer's  behavior you can incorporate predictive design  practices successfully.