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Apps as Machines — at Hochschule Darmstadt

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— Scott A. Nelson & Paul Metaxatos / HBR https://hbr.org/2016/04/the-internet-of-things-needs-design-not-just-technology IoT connectivity can enhance a product’s value, but it can never serve as the rationale for the customer purchase.
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Page 1: Apps as Machines — at Hochschule Darmstadt

— Scott A. Nelson & Paul Metaxatos / HBR https://hbr.org/2016/04/the-internet-of-things-needs-design-not-just-technology

IoT connectivity can enhance a product’s value, but it can never serve as the rationale for the customer purchase.

Page 2: Apps as Machines — at Hochschule Darmstadt

Apps as Machines @AppsAsMachines @H_DA

Hannes Jentsch Martin Jordan

Page 3: Apps as Machines — at Hochschule Darmstadt

Hello

Who are you? Why are you here?

Page 4: Apps as Machines — at Hochschule Darmstadt

Background: Product, Innovation, Design

Hannes Jentsch Design & Innovation Consultant, Freelance

@Kaffeetrinken

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Background: Service, Innovation, Design

Martin Jordan Lead Service Designer, Government Digital Service

@Martin_Jordan

Cabinet OfficeGovernment Digital Service

Page 6: Apps as Machines — at Hochschule Darmstadt

What happened so far

Page 7: Apps as Machines — at Hochschule Darmstadt

Conference workshops

Page 8: Apps as Machines — at Hochschule Darmstadt

University course

Page 9: Apps as Machines — at Hochschule Darmstadt

Newspaper

Page 10: Apps as Machines — at Hochschule Darmstadt

Terms & conditions

2 days, 12 hours

½ home work

100% attendance & contribution

Page 11: Apps as Machines — at Hochschule Darmstadt

Approach connected device projects from a user-need angle

Learning goals

Leverage human capabilities when designing for IoT

Crafting meaningful and relevant new offerings

Page 12: Apps as Machines — at Hochschule Darmstadt

What is the ‘internet of things’?

Question

Page 13: Apps as Machines — at Hochschule Darmstadt

Definition

The Internet of Things (IoT) is the interconnection of uniquely identifiable embedded computing devices within the existing Internet infrastructure.

”— Wikipedia, Internet of Things http://en.wikipedia.org/wiki/Internet_of_Things

Page 14: Apps as Machines — at Hochschule Darmstadt

Definition

It seems to mean everything and nothing. Like, is it RFIDs in airports to track luggage, combine harvesters driven by town-wide WiMAX, or web-connected receipt printers for the home? Too much.

”— Matt Webb / @Genmon, BergCloud http://blog.bergcloud.com/2014/04/02/four-types-of-iot/

Page 15: Apps as Machines — at Hochschule Darmstadt

Which devices come to your mind?

Question

Page 16: Apps as Machines — at Hochschule Darmstadt

Examples

FitBit Pebble

Apple Watch

Wearables

Sonos Apple TV

Chromecast

Media

Smartthings Belkin Wemo Philips Hue

Home Automation

Withings Nest

Cloudwash

Smart Appliances

Source: Bergcloud / ‘Four Types of IoT’ http://blog.bergcloud.com/2014/04/02/four-types-of-iot/

Page 17: Apps as Machines — at Hochschule Darmstadt

Wearables

Connected cars

Connected homes

Connected cities

Industrial internet

Transportation

Healthcare

Oil & gas

Source: Goldman Sachs Global Investment Research

IoT Landscapes

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What do they do for us?

Question

Page 20: Apps as Machines — at Hochschule Darmstadt

Expanding the definition of ‘machine’

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As we start to make Apps as Machines, what are the building blocks of rich physical experiences we can draw from?

Hypothesis

A physical experience offers usso many opportunities for cognitive, and thus, emotional engagement.

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Hypothesis

Page 26: Apps as Machines — at Hochschule Darmstadt

Setting their jobs to be done into context

Agenda

Solving the job by leveraging more human capabilities

Pitching your machine

Discovering what apps and their services do for us

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Uncovering what Dropbox does for us …

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APPS AS MACHINES — Uncovering the jobs behind

Dropbox lets you bring all your photos, docs, and videos anywhere and share them easily. Access any file you save to your Dropbox from all your computers, iPhone, iPad, and the web. With Dropbox you’ll always have your important memories and work with you.

Dropbox’s jobs-to-be-done*

Dropbox

— Jobs-to-be-done describe the tasks that a product or service is carrying out. People don’t just buy products or just want to use a certain service. They ‘hire’ them to do a job.

For example: Car2Go gets you from A to B. The drill hammer helps you to hang a painting on the wall. Pinterest supports you in collecting and remembering things. — @ClayChristensen, http://www.christenseninstitute.org

description and screens from Apple AppStore

have my documents always with me

retrieve my documents wherever I need them

secure copies of important documents

show photos to my friends & family

collaborate with my colleagues

store my memories of important moments

Page 30: Apps as Machines — at Hochschule Darmstadt

Definition

— @ClayChristensen, Professor for management http://www.christenseninstitute.org/

Jobs-to-be-done describe the tasks that a product or service is carrying out. People don’t just buy products or just want to use a certain service. They ‘hire’ them to do a job.

Page 31: Apps as Machines — at Hochschule Darmstadt

What is the task of wine?

Question

Page 32: Apps as Machines — at Hochschule Darmstadt

Source: Laurence Veale / ‘The jobs wine is hired for’ https://medium.com/@laurenceveale/the-jobs-wine-is-hired-for-272a929ea8be

How most wines are organised in wine shops

Page 33: Apps as Machines — at Hochschule Darmstadt

Source: Laurence Veale / ‘The jobs wine is hired for’ https://medium.com/@laurenceveale/the-jobs-wine-is-hired-for-272a929ea8be

Organising the retail space around a specific job: to make dinner a little better

Page 34: Apps as Machines — at Hochschule Darmstadt

Source: Laurence Veale / ‘The jobs wine is hired for’ https://medium.com/@laurenceveale/the-jobs-wine-is-hired-for-272a929ea8be

Organising the retail space for a second job: to look neither cheap nor foolish

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Your task

Set up your group

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Your task

6 jobs each3 apps1 user 2 hours

Page 37: Apps as Machines — at Hochschule Darmstadt

Interview for Empathy

Ask why.

Never say “usually” when asking a question.

Encourage stories.

Look for inconsistencies.

Pay attention to nonverbal cues.

Don’t be afraid of silence.

Don’t suggest answers to your questions.

Ask questions neutrally.

Don’t ask binary questions.

Only ten words to a question.

Only ask one question at a time, one person at a time.

Make sure you’re prepared to capture.

A.school (2010): bootcamp bootleg http://dschool.stanford.edu/wp-content/uploads/2011/03/BootcampBootleg2010v2SLIM.pdf

Page 38: Apps as Machines — at Hochschule Darmstadt

APPS AS MACHINES — Your first task

Investigation

YOUR USER:

DISCUSSED APPS:

over age of 60 and using a smartphone daily

grew up outside of Europe

young mother or father

under the age of 18, still going to school

flying more than 3 times per month

small business owner with a physical store

handicapped (with impact on everyday life)

Page 39: Apps as Machines — at Hochschule Darmstadt

APPS AS MACHINES — Your first task

Investigation

NAME OF THE APP:

JOBS OF THE APP:

YOUR USER:

DISCUSSED APPS:

Satisfaction:

Satisfaction:

Satisfaction:

Satisfaction:

Satisfaction:

Satisfaction:

Situation:

Situation:

Situation:

Situation:

Situation:

Situation:

Great

over age of 55 and using a smartphone daily

grew up outside of Europe

young mother or father

under the age of 18, still going to school

flying more than 3 times per month

small business owner with a physical store

handicapped (with impact on everyday life)

Great

Great

Great

Great

Great

Just right/ok

Just right/ok

Just right/ok

Just right/ok

Just right/ok

Just right/ok

Not really satisfying

Not really satisfying

Not really satisfying

Not really satisfying

Not really satisfying

Not really satisfying

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All clear? Ready to go?

Check-in

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— Theodore Levitt, American economist http://hbr.org/web/special-collections/insight/marketing-that-works/marketing-malpractice-the-cause-and-cure

People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!

Page 42: Apps as Machines — at Hochschule Darmstadt

Setting their jobs to be done into context

Agenda

Solving the job by leveraging more human capabilities

Pitching your machine

Discovering what apps and their services do for us

Page 43: Apps as Machines — at Hochschule Darmstadt

Who is your user? Which apps is s/he using?

What are their ‘jobs’?

Tell

Page 44: Apps as Machines — at Hochschule Darmstadt

Focus

The product analysis, design and sale should focus on:

developing the product

asking what users want

matching market trends

understanding the jobs that users try to get done

Source: Clement Génin, Jobs-to-be-done – A goal-driven solution framework http://www.slideshare.net/ClementGenin/jobstobedone

Page 45: Apps as Machines — at Hochschule Darmstadt

User Job

IoT Solution

Point of View

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Orientating in unfamiliar

area

Using mapping service

Point of View

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Getting to appointment

in timeTaking a taxi

Source: Pexels

Point of View

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Rewarding for a tough day at work

Getting dinner

delivered

Source: Pexels

Point of View

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Emotional / personal jobs

Functional jobs

Social jobs

Resource: Silverstein, D., Samuel, P. (2012): The Innovator's Toolkit. Hoboken, NJ: Wiley.

Kinds of jobs

Page 50: Apps as Machines — at Hochschule Darmstadt

Compact Disc

Jobs are solution-agnostic and remain valid over long time

Spotify Streaming

Vinyl record

Private concert

iTunes MP3

THEN NOW

Job of listening to music

Page 51: Apps as Machines — at Hochschule Darmstadt

Jobs of the milkshake by Clayton Christensen

Jobs of Snickers vs. Milkyway by Bob Moesta

Source: http://hbr.org/web/special-collections/insight/marketing-that-works/marketing-malpractice-the-cause-and-cure

Origin story

Page 52: Apps as Machines — at Hochschule Darmstadt

Milkshake Job: consume something now that will stave off hunger until noon

VS

Snickers Banana Bagel

Consideration Set

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Framework for developing & communicating products and services

Set of tools and methods for almost every part of the service development process

Mindset for understanding human behaviour, and why people switch from one offering to another

Perspective

Jobs-to-be-Done is …

Page 54: Apps as Machines — at Hochschule Darmstadt

Setting their jobs to be done into context

Agenda

Solving the job by leveraging more human capabilities

Pitching your machine

Discovering what apps and their services do for us

Page 55: Apps as Machines — at Hochschule Darmstadt

Setting their jobs to be done into context

Agenda

Solving the job by leveraging more human capabilities

Pitching your machine

Discoveringwhat apps and their services do for us

Page 56: Apps as Machines — at Hochschule Darmstadt

View

We frame every design problem in a Job, focusing on the triggering event or situation, the motivation and goal, and the intended outcome.

”— @AlanKlement http://alanklement.blogspot.de/2013/09/replacing-user-story-with-job-story.html

Page 57: Apps as Machines — at Hochschule Darmstadt

Rethink

The context defines what is needed to perform a job

Getting from A to B in the city

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Jobs vs solution

Local public transport “Get me to my destination during rush hour with a predictable time of arrival.”

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Jobs vs solution

Taxi & uber “Get me to the airport in the very early morning, but allow me to sleep as long as possible and save me time.”

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Jobs vs solution

car2go & Drive Now “Get me to my destination during an off-peak time of the day when I have something to carry that’s too uncomfortable for public transport. Or when I want to upgrade myself.”

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Jobs vs solution

Flinkster & CiteeCar “Get me out of the city with my family over the weekend.”

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Jobs vs solution

Call a Bike & Next Bike “Get me to work on a beautiful day when there is little time pressure.”

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Jobs vs solution

eMio “Get me and my partner to the brunch date with friends quickly.”

Page 64: Apps as Machines — at Hochschule Darmstadt

+ + + + +

Situation

Monday

Morning

RainAlarm

didn’t

ring

Usually

gone

at tha

t tim

e

Car in re

pair

Contextualise

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When

Wh

ere

Who

H

ow

Wh

at

season month weekday

daytime

occasion

location

type

category

attrib. profile/mode

social

devic

e

m

otio

n

u

ser a

ct.

rou

tine

tr

affic

fa

cebo

ok

c

ollec.

weather

Routinely used route

Routinely visited place

First time visit

Unknown area

Known area

…Historical traffic around location

Congestion/incidents on route

Congestion/incidents around loc.

…Visited by friends

Visited by me

Popular on facebook

Liked by friends

Liked by me

…In popular collection

In my friends collection

In my collection…

FreezingCool

Mild

Warm

HotNight

DayStorm

ySnow

yRainy

FoggyCloudy

Clear W

et seasonD

ry seasonW

interAutum

n

Summ

er

Spring

Janu

ary

Febr

uary

Mar

chAp

rilM

ayJu

neJu

lyAu

gust

Sept

embe

rO

ctob

erNo

vem

ber

Dece

mbe

r

Mon

day

Tues

day

Wedne

sday

Thur

sday

Frida

ySa

turd

ay

Sunday

Morning

Noon

Afternoon

Evening

Night

Sunrise

Sunset

At a planned appointment

Appointment scheduled in x hours

Leaving

In transit

Arriving

Early in month

Late in month (f.ex salary)

Commute

Travel

OutdoorIndoorNear POI of cat. XNear POI cluster of cat. XMoving towards X

Distance to destinationDistance to POI…

On streetIn buildingIn/at venue In parkOn mountainOn water

Airport

Department store

HotelCafe

RestaurantATM

Leisure

PT stationSightMall

Parking space

Junction

Highway…

Price range

Opening hours

Available parking…

…Com

mut

er

City

Dw

elle

r

Trav

eler

Age

30-3

9

Age

18-2

9

Age

< 18

Mal

e

Fem

ale

…With

ano

nym

ous

crow

d

With

kno

wn p

eopl

e

Alon

e

…Ro

aming

activ

e

Via 3G

etc

Via B

lueto

oth

Via W

iFi

Deskto

p

TabletPhone

…Asce

nding/descending

Trajecto

ry/bearing/direction

Driving WalkingStill

…Using app since 1d/1w/1m

Calculated a route to/from

ReviewedShared to/byCollected

Searched for

…Routine follow up action when x Situation

Consider

Page 66: Apps as Machines — at Hochschule Darmstadt

Enhance

ContextsPersonas

Page 67: Apps as Machines — at Hochschule Darmstadt

Amazon Dash

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Rephrase

Formulate each job into a statement (or job story)

When I want to So I canSituation Need Goal

Page 69: Apps as Machines — at Hochschule Darmstadt

Benefit

Describe a real user’s need

in context

Validate design

solutions

Communicate the design task

Page 70: Apps as Machines — at Hochschule Darmstadt

View

Often, because people are so focused on the who and how, they totally miss the why. When you start to understand the why, your mind is then open to think of creative and original ways to solve the problem.

”— @AlanKlement https://medium.com/the-job-to-be-done/af7cdee10c27

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The right machine for …

Adam 31, German moving to South Korea

Page 72: Apps as Machines — at Hochschule Darmstadt
Page 73: Apps as Machines — at Hochschule Darmstadt

APPS AS MACHINES — The right machine for …

JOB-TO-BE-DONE

STORY*

Adam

When (situation)

I want to (need)

So that (goal)

— “Job Stories are great because it makes you think about motivation and context and de-emphasizes adding any particular implementation. Often, because people are so focused on the who and

how, they totally miss the why. When you start to understand the why, your mind is then open to think of creative and original ways to solve the problem.” — @AlanKlement, https://medium.com/the-job-to-be-done/af7cdee10c27

31, German moving to South Korea

have personal documents always at hand

Page 74: Apps as Machines — at Hochschule Darmstadt

APPS AS MACHINES — The right machine for …

JOB-TO-BE-DONE

STORY*

Adam

When (situation)

I want to (need)

So that (goal)

— “Job Stories are great because it makes you think about motivation and context and de-emphasizes adding any particular implementation. Often, because people are so focused on the who and

how, they totally miss the why. When you start to understand the why, your mind is then open to think of creative and original ways to solve the problem.” — @AlanKlement, https://medium.com/the-job-to-be-done/af7cdee10c27

31, German moving to South Korea

I move to another country

and need to register there with banks and authorities

I can identify myself without having

to carry unique originals with me.

have easy access to my most important

documents

Page 75: Apps as Machines — at Hochschule Darmstadt

What is your main job?What is the situation?What are the needs?

Write

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Your task

30 Minutes2 Stories1 App

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How went your job story writing?

Tell

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Pitfalls & tips

Don’t include solutionsinto stories.

Don’t formulate storiestoo general.

Don’t include more thanone context and goal.

Write it like in the 70s –avoid mentioning tech.

If you struggle in writing,do further research!

Think in strugglesrather than outcomes.

Don’t Do

Page 79: Apps as Machines — at Hochschule Darmstadt

Setting their jobs to be done into context

Agenda

Solving the job by leveraging more human capabilities

Pitching your machine

Discoveringwhat apps and their services do for us

Page 80: Apps as Machines — at Hochschule Darmstadt

Setting their jobs to be done into context

Agenda

Solving the job by leveraging more human capabilities

Pitching your machine

Discoveringwhat apps and their services do for us

Page 81: Apps as Machines — at Hochschule Darmstadt

View

Those digital updates have little sympathy for any divisions of time or space we might to impose upon our days. We may find that we are ranking the ‘needs’ of our machines above our own.

”— @TomChatfield http://tomchatfield.net/2012/05/09/how-to-thrive-in-the-digital-age/

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Cloudwash

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Input for your creation

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Cheat Sheet

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Your task

4 Minutes1 Job Story 1 Question

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How might we +user

+ ?need

+insight

Ask

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user needinsight

Ask

How might we assist Adam who is moving to South Korea to have his most important personal documents with him so that he can identify himself without needing his unique originals?

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Ask

user needinsight

How might we assist Adam who is moving to South Korea to have his most important personal documents with him so that he can identify himself without needing his unique originals?

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Write

user + insight + need

APPS AS MACHINES

How might we assist Adam who is moving to South Korea to havehis most important personal documents with him so thathe can identify himself without needing his unique originals?

— Input for your creation

How might we … ?

Page 91: Apps as Machines — at Hochschule Darmstadt

How might we … ?

Tell

Page 92: Apps as Machines — at Hochschule Darmstadt

Constraints

Avoid screens Avoid keyboards

Page 93: Apps as Machines — at Hochschule Darmstadt

Example: Amazon Fresh

Source: Amazon

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Example: Amazon

Source: Amazon

Amazon App

Amazon Dash

Amazon Dash Button

Amazon Watch App

Amazon Echo

Page 95: Apps as Machines — at Hochschule Darmstadt

100 × Go for quantity

Keep it short

Encourage wild ideas

Defer judgment

Build on the ideas of others

One conversation at a time

Stay on topic

Be visual

Ideate

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Your task

3+7 Minutes99 Ideas1 Brief

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10 Minutes1 Idea 2 Concept

Your task

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What are your two fav concept ideas?

Report

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Note

What’s good? What to improve?

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Feedback

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Prototyping

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Prototyping with Makedo

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View

As technology moves into more and more things and ultimately into humans, we must ensure that it is enhancing the human experience not challenging it.

”— @Punchcut http://punchcut.com/perspectives/connecting-the-internet-of-things/

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Wayfindr

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Why prototype

Collaborate by doing, not talking

Show the thing, communicate with evidence

Learn with your hands

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Inspiration for your prototype

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Video app recommendations

Snapchat (10 sec)

Instagram Video (15 sec)

Spark (45 sec)

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Your task

90 Minutes1 Prototype1 Concept

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Your presentation

1 HMW 1 Advantage1 Concept

Page 115: Apps as Machines — at Hochschule Darmstadt

What is your machine?

Your show-timeShow

Page 116: Apps as Machines — at Hochschule Darmstadt

Note

What’s good? What to improve?

Page 117: Apps as Machines — at Hochschule Darmstadt

a user with a rather complex lifethe need to do grocery shopping online together with other family members.

Amazon Dash note-taking deviceis directly connected to the shop

the Amazon smartphone appDash is easy to use with a single hand

and even while multi-tasking

Communicate

For TARGETCUSTOMER

CUSTOMERNEED

CONCEPTNAME

MARKETCATEGORY

who has

that

Unlike

the

is aONE KEYBENEFIT

COMPE-TITION

.

.

UNIQUEDIFFEREN-TIATOR

APPS AS MACHINES — Acceleration tool

Elevator Pitch

Page 118: Apps as Machines — at Hochschule Darmstadt

Setting their jobs to be done into context

Agenda

Solving the job by leveraging more human capabilities

Pitching your machine

Discoveringwhat apps and their services do for us

Page 119: Apps as Machines — at Hochschule Darmstadt

Setting their jobs to be done into context

Agenda

Solving the job by leveraging more human capabilities

Pitching your machine

Discoveringwhat apps and their services do for us

Page 120: Apps as Machines — at Hochschule Darmstadt

What is your machine?

Your show-timeShow

Page 121: Apps as Machines — at Hochschule Darmstadt

IoT

Source: @Punchcuthttp://punchcut.com/perspectives/connecting-the-internet-of-things/

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Wrap-up

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In 2020

7.6 billion people

50 billion devices

6.58 devices per person

Source: Cisco, ‘Connections Counter: The Internet of Everything in Motion’http://newsroom.cisco.com/feature-content?type=webcontent&articleId=1208342

Page 124: Apps as Machines — at Hochschule Darmstadt

Not more information, but better

information

Less smartphone dependency, but objects as messengers

Focus on people, support, protect, empower them

Consider

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How the computer sees us

Source: Physical Computing, O'Sullivan & Igoehttp://www.amazon.com/Physical-Computing-Sensing-Controlling-Computers/dp/159200346X

Page 126: Apps as Machines — at Hochschule Darmstadt

— Brian Eno, artist http://archive.wired.com/wired/archive/7.01/eno_pr.html

Tools that endure have limited options. These limitations become sources of emotional meaning.

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1995– Internet via stationary computer

2005– Internet in the palm

2015– Internet in all aspects of life

Level of intimacy to user

Realise

Low High

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Realise

App layer

Connected objects layer

Service layer

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View

[The internet of things] will require businesses to fundamentally transform their approaches to be successful in this new era.

”— @Punchcut http://punchcut.com/perspectives/connecting-the-internet-of-things/

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No market need

Ran out of cash

Not the right team

Get outcompeted

Pricing / cost issues

Poor marketing

Ignore customers

Products mis-timed

Lose focus

Disharmony on team 13%

14%

14%

17%

17%

18%

19%

23%

29%

42%

Top 10 reasons young businesses fail

Source: Top 10 Reasons Startups Fail, based on an analysis of 101 post-mortemshttp://www.cbinsights.com

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Balance

Viable

DesirableFeasible

Business

UsersTechnology

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Do’s

Capture the context

State the problem

Clarify the benefit

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Question

What if your connected thing is being hacked? How can you make sure you harm its users the least?

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Consider

Credit card hacks (e.g. Target)

Services & servers hacked (e.g. Sony, Playstation)

Unprotected cameras (e.g. insecam.org)

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View

Minimal Viable Data – What is the least amount of data you can collect to create a good product and experience?

”— @GoldenKrishna https://twitter.com/Martin_Jordan/status/667336477349650432

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Scary Smart City

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R.I.P. Little Printer

Page 142: Apps as Machines — at Hochschule Darmstadt

R.I.P. Little Printer

Page 143: Apps as Machines — at Hochschule Darmstadt

Two last things

Documentation Publish your video project with sheets

until Sunday, 15 May

Feedback Tell us what you liked,

you wished, you learnt


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