how european first-movers manage iot analytics projects … · 2016-11-16 · major lessons learnt?...

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Copyr i g ht © 2016, SAS Ins t i tu t e Inc . A l l r ights reser ve d .

Thomas Rohrmann, Michael Probst Analytics Experience 2016, Rome

Intelligence for the connected worldHow European First-Movers Manage IoT Analytics Projects Successfully

Copyright © 2015, SAS Inst i tute Inc. Al l r ights reserv ed.

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INTERNET OF

THINGSJUST A HYPE?

2012

2014

2015

2016


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INTERNET OF

THINGS75 FIRST MOVERS COMPANIES INTERVIEWED

Executives and IoT Project Leads


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INTERNET OF

THINGS75 FIRST MOVERS COMPANIES INTERVIEWED

sas.com/iotebook

Download


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SURVEY FINDINGS & THOUGHTS

Expectations and Risks

Lessons Learnt

Organizational Impact

Challenges

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SURVEY


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Expectations and Risks

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SURVEY


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SURVEY FINDINGS

& THOUGHTSEXPECTATIONS FROM IOT INITIATIVES?

Source: SAS IoT Impact Study, September 2016. N = 75. Multiple responses allowed.

Q1: What does IoT or the 4th industrial revolution mean for your customers, your business, your competitors?

Fig 1: Diverse expectations


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SURVEY FINDINGS




Fig 1: Diverse expectations Efficiency & Cost


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SURVEY FINDINGS




Fig 1: Diverse expectations Efficiency & Cost Offering & Revenue


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SURVEY FINDINGS

& THOUGHTSRISKS OF NOT ENGAGING?


Q8: What do you see as the biggest risks associated with not fully exploiting Internet of things opportunities?

Fig 8: IoT expected to re-define addressable market


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SURVEY FINDINGS

& THOUGHTSRISKS OF NOT ENGAGING?


Q8: What do you see as the biggest risks associated with not fully exploiting Internet of things opportunities?

Fig 8: IoT expected to re-define addressable market Efficiency risks Revenue risks


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RECOMMENDATIONS EXPECTATIONS AN RISKS

Efficiency Revenue

Company

Optimization of production & logistics• Operational efficiencies• Better resource management

Up-/Cross-Selling, New Business• Disruptive new products • Innovative new services


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Competitor C

RECOMMENDATIONS EXPECTATIONS AN RISKS

Competitor A Competitor B New guy in town

Efficiency Revenue


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“Don’t focus on a specific project.

Set up an IoT infrastructure!”

KEY TAKEAWAY


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Lessons Learnt

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SURVEY


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SURVEY FINDINGS

& THOUGHTSHOW TO DEAL WITH SPEED OF IOT?


Q9: How do you assess if your appetite and initiatives around Internet of Things is moving as quickly as the market demands?

Fig 9: Benchmarking


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SURVEY FINDINGS

& THOUGHTSHOW TO DEAL WITH SPEED OF IOT?


Q9: How do you assess if your appetite and initiatives around Internet of Things is moving as quickly as the market demands?

Fig 9: Benchmarking Invest in innovations


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SURVEY FINDINGS

& THOUGHTSMAJOR LESSONS LEARNT?


Q3: What were the main lessons you learnt from these initiatives that will guide how you plan future IoT ventures?

Fig 3: Design thinking imperative


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SURVEY FINDINGS

& THOUGHTSMAJOR LESSONS LEARNT?


Q3: What were the main lessons you learnt from these initiatives that will guide how you plan future IoT ventures?

Fig 3: Design thinking imperative Test, test, test, retest and scale it up


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RECOMMENDATIONS AGILE DATA DISCOVERY & MODEL DEVELOPMENT

Data Scientist

EngineerProject Analyst

Is the time series data

complete?

How does my data distribute

and how can I interpret the content?

Are there relevant pattern

and correlations visible?

Which model fits best?

How do I prepare my

information for project and

top management?

Can I identify outliers that

point to measurement flaws?


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Data Scientist

EngineerProject Analyst


Develop models

Overview / integrity

Understand contents

Identify analytical relevance

Visualize, communicate

Plausibility

Is the time series data

complete?

How does my data distribute

and how can I interpret the content?

Are there relevant pattern

and correlations visible?

Which model fits best?

How do I prepare my

information for project and

top management?

Can I identify outliers that

point to measurement flaws?


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RECOMMENDATIONS ANALYTICS LIFE CYLCE

Prepare

Explore

Model

Ask

Iterative

Leading Edge

Experiments

Fail Fast

Data Science

Interactive

New data

Innovation

Deep Learning

DATA

Discovery


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RECOMMENDATIONS ANALYTICS LIFE CYLCE

Implement

Act

Evaluate

Governed

Robust

Automated

Regulated

Actions

Consistent

Documented

Decisions

Deployment

Prepare

Model

Ask

Iterative

Leading Edge

Experiments

Fail Fast

Data Science

Interactive

New data

Innovation

Deep Learning

DATA

ExploreDiscovery


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RECOMMENDATIONS HOW TO GET STARTED?

Prepare

Explore

Model

Implement

Act

Evaluate

Ask

DATA

Discovery Deployment

IoT Analytics FactoryIoT Analytics Lab

Exploration

Analysis

Fast model development

Quick validation

Model Deployment

Performance Management

Stream-Processing

Decisions and actions

Identify & evaluate Operationalize


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Keep the analytical life cycle in mind!

Support agile testing and smooth deployment.

KEY TAKEAWAY


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Organizational Impact

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SURVEY


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Cross-organisational

SURVEY FINDINGS

& THOUGHTSVISION OF ORGANIZATIONAL IMPACT

Source: SAS IoT Impact Study, September 2016. N = 75. Multiple responses allowed. Q7: Thinking about the businesses and support

functions across your organisation, which would you consider to be the top 3 today in terms of mature use of IoT?

Fig 7: Breaking organisational silos


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RECOMMENDATIONS APPROACHABLE ANALYTICS


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Expand analytic

toolkit.

Code in the

language of your

choice.

Scale methods

without rede-

fining code.

Easily wrangle

data.

Interactively

interrogate.

Discover insights

through visual

interface.

Embed analytics

in applications.

Documented,

public REST

APIs.

Centralized

management of

analytic assets.

One governed

environment.

Multi-cloud for

flexibility. Failover

protection.

Guided

workflows.

Visual interface

accelerate

investigations.

Analytic intelli-

gence built-in.

Consistent,

trustworthy

answers.

Use current

hardware and

extend existing

skills sets.

Nurture

innovation for

production.

RECOMMENDATIONSAPPROACHABLE MEANS HAVING MANY PERSONAS

AND NEEDS IN MIND


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RECOMMENDATIONS APPROACHABLE ANALYTICS JOURNEY

Value


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RECOMMENDATIONS APPROACHABLE ANALYTICS JOURNEY

Mobile

ONE INTEGRATED SOLUTION FOR ALL ROLES

Office Integration

Cloud


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IoT Analytics must be accessible and approachable

for many organizational units and persons.

KEY TAKEAWAY


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Challenges

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SURVEY


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SURVEY FINDINGS

& THOUGHTSCHALLENGES – TECHNOLOGY, CHANGE & SKILLS


Q4: What were the challenges associated with exploiting the IoT fully?

Fig 4: Predictable challenges


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Technology

SURVEY FINDINGS






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Technology Change & Skills

SURVEY FINDINGS






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SURVEY FINDINGS



Q5: What skills did you find most useful during your IoT deployment?

Fig 5: Skills surprise


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SURVEY FINDINGS



Q5: What skills did you find most useful during your IoT deployment?

Fig 5: Skills surprise Wide skill range needed


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PEOPLE

PROCESS

TECHNOLOGY

RECOMMENDATIONS STRATEGY & INFRASTRUCTURE

Copyright © 2016, SAS Insti tute Inc. Al l r ights reserved.

Other actions

(eg. API Call)

ActuatorSensor

RECOMMENDATIONS DATA DRIVEN APPROACH TO IOT ANALYTICS

Easy data access

Enterprise Data

Datastore(z.B. Hadoop)

Enrich

Collect

Data management

SAS/Analytics

Streaming

Analytics

Realtime

Decisions

Exploration Analytics

„ Engineer“ Data Scientist

Collaboration

Fast and scalable in-Memory technology


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PEOPLE

PROCESS

TECHNOLOGY

RECOMMENDATIONS STRATEGY & INFRASTRUCTURE


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RECOMMENDATIONS SENSE – UNDERSTAND – ACT

DeployETLData

Alerts / Reports / Decisioning

IoT DataIntelligent Filter /

TransformStreaming Model

Execution

Data Storage

Deploy


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RECOMMENDATIONS

ESP Engine

Fog

Company CloudProduction Flow

Alert /

KPI’s

Storage

Visualization / Analysis / Root Cause /

Model Development & Management

Batch

ABT

SAS Cloud

Other Cloud Applications

Other Data Sources

EXAMPLE IOT ANALYTICS ARCHITECTURE

ESP to control

Deploy


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RECOMMENDATIONS MOVE ANALYTICS TO THE EDGE

Databases

Edge of Network

Operational Apps

Operational Data Store

Enterprise Data Warehouse

Gateways

Sensor Readings

Analytics

Sensor


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CISCO & SAS GLOBAL ALLIANCE SINCE AUGUST 2016

Announcement:

EDGE-ANALYTICS

VALUE

Leaders Coming Together


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People, process and technology need to work

hand in hand so that IoT analytics create value.

Be ready to apply analytics into the data stream

… where real-time action matters.

KEY TAKEAWAY


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INTERNET OF

THINGSMORE ON IOT

sas.com/iotebook

Download

IoT demo stations

Visit

Smart Home Demo:

The DEMOtic Home

Connected Truck Demo:

SAS and Intel

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Thank you

how european first-movers manage iot analytics projects … · 2016-11-16 · major lessons learnt?...

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