itecture - Amazon Web Services...Completed IBM Design Thinking Workproducts • Empathy Maps •...

itecture

Using Creativity to Evaluate Capability

Donna MuellerIBM WW Enablement LeaderSoftware Client [email protected]

I am the technical “trusted advisor” to my

clients.

I help my client become a leader in their

industry via the solutions I propose.

I drive the enterprise

innovation agenda in my

client(s).

It is difficult to maintain

my technical expertise

and have a sales quota.

I don’t have enough exposure to non-

IT organizations, at my client.

Millennials…hmmm. Smart but

not as experienced as me.

Articulates clear, quantifiable

business value of IBM strategic

solutions and platforms.

Translates business requirements

into comprehensive technical

requirements. Hangs out in IT

”Herds cats” – mobilizes technical expertise

across a broad portfolio.

Challenged to keep up

with all IBM offerings &

market forces.

Pressure to focus on tactical

transactions vs. long term

strategic opportunities

Annoyed with executive demand for

testing to ‘demonstrate’ expertise.

My Constituency: IBM Worldwide Software Architects

Role• IT Architect professional

• Responsible for overall technical

solution design across all brands

(e.g. Cloud, Analytics, Security,

Commerce, Watson, IoT, Social, etc.)

Personal• Very confident in abilities.

• Very experienced: Average time in role:

8+ years; 40+ years old; 15+ years: IBM

• Deep & broad domain expertise.

• Large IBM network of SMEs.

• Strong architectural & IBM Design

Thinking experience

• Demonstrated, hands-on contemporary

skills

Challenges• Find it / share it fast: all channels

• Exposure to Client’s LoB Execs

• Need occasional guidance —

• Deep technical

• Complete reference

architectures for my domain.

-The Perceived Business Problem-My Problem• Software Sales Down? Execs:

• Must be a knowledge/skill problem - Training!

• Test them. Yes! Let’s test them!…

• Except, I say• How do we know this is a knowledge/skill problem? Root Cause Analysis?

• Recent Skills Assessments disprove this

• The Idea• Demonstrating capability is better than high test score

• Use a face-to-face enablement session

• Engagement: • real life competitive ‘bake-off’ environment

• get highest level technical roles, in the company, to participate

Learning Objective

Given:

A case study description of a competitive opportunity for IBM, where the client, their business environment and a current business problem are described….

With your team, collaboratively design a compelling business and technical solution to the problem.

You will then have 15 minutes to describe the solution and convince the C-level exec that your solution should be selected to win the business.

The winning solution will demonstrate your knowledge of the situation, business value to the client, innovation, technical feasibility and it will be compelling.

You may use slides, whiteboard, or no props at all.

Learning Delivery Concept

• Industry organization teams of 5

• Revered SMEs present up front

• Complex business case authored by SCA Industry Leaders

• Day long series of exercises to develop solution and architecture

• Teams present to the panel of Sharks (SMEs) who select winner

Breakout RoomsBanking Government IndustrialRetail Insurance

Team

1Team

1

Team

1 Team

1Team

1Team

2

Team

3

Team

4

Team

5

Team

6

Team

7

Team

2

Team

3

Team

4

Team

5

Team

2

Team

3

Team

4

Team

5

Team

2

Team

3

Team

4

Team

5

Team

2

Team

3

Team

4

Panel of Banking Sharks

Panel of Government

Sharks

Panel of Retail Sharks

Panel of Insurance

Sharks

Panel of Industrial

Sharks

GIVEN

Case StudyClient backgroundBusiness imperativesPain pointsBusiness & Technology ReqGeneral ObservationsKey Players

Completed IBM Design Thinking Workproducts• Empathy Maps • Client User• Client Business Leader• AS-IS Scenario Map• Architectural O/V Diagram

USE

IBM DesignThinking Exercises

Agree on the ProblemIdeationIdeation PrioritizationHills StoryboardPrototypeSolution Prep

DEMONSTRATE

Evaluation Rubric

Understand the ClientSuccinctly describes

the Problem, the Solution the Business Value

Innovation/WOW factorTechnical solution

accurate key components

Compelling

Lessons Learned

• Had so much fun doing this. It was so much work !

• Good design for experienced, skilled• enables demonstration of capability, layers of skills

• demands knowledge of content OR where to get it

• presentation, teamwork, negotiation, innovation

• Critical • Executive Support & Communication

• Community Leaders: Case Study & Room Leaders

• “Given” depends on time available for exercises (need at least 1 full day)

• SMEs: credibility

• Exercises: structure, iteration: IBM Design Thinking*

• You: • Project Management and Communication

• Content Knowledge & Design –know (learn) enough to be dangerous

• Give the rubric earlier.

• Time management issues; assistants 7

itecture

Using Creativity to Evaluate Capability

Donna MuellerWW Software Architect Enablement LeaderIBM [email protected]

backup slides

9

Criteria

Not so

good, “I’m

out”

good but

no ‘Wow’

factor”

Exemplary Total Comments

1 - 2 3 - 4 5 -6 Possible Earned

Understands client

1.Demonstrates clear

understanding of the client and

the business problem 6

Describes business

solution and value

2. Describes the solution from a

business outcome standpoint.

Provides a clear description of

the TO BE state. In English, not

techno-language

6

Innovation / WOW

factor

3. Level of creativity, WOW-

factor, innovation in the solution.

The level to which this blows

you, the shark, out of the water.

Ha

6

Technical solution -

accurate & contains

key components

4. Includes appropriate and

necessary components; has IBM

Strategic technologies, as

appropriate e.g. cognitive, cloud,

Analytics, SaaS, is secure

6

Compelling

5. How compelling is the story –

do you want to go forward with

this vendor? 6

Total 30

Shark Evaluation FormTeam________________________

IBM Design :: IBM Confidential :: © 2015 IBM Corporation

IBM Design Thinking “Pre-Hills” work

EmpathyMap

As-isScenario Map

Big IdeaVignettes

How can our team quickly collaborate

to identify a range of possibilities

to meet our user’s needs?

Idea Prioritization

Which of these ideas are most important and

feasible within our given release or planning period?

Needs Statements

Why do we think these ideas are so important and impactful for our user? What does our user actually seek?

What opportunities are presented when we understand our

users and their work?

Design Thinking Exercises

2. Validation & Pain Point Prioritization(15 minutes)

11

Team Discussion: Tell the roomReview the Empathy MapsReview stated Pain PointsUse the AS-IS Scenario to zero in on THE PROBLEM.

Team to agree on THE PROBLEM.All future exercises will be in support of this PROBLEM.

The agreed upon problem is the output from this exercise.

8:30 – 8:45

Insurance:9:30 – 9:45

3. IDEATION / Brainstorming (30 min)

12

Individual WorkTell the room:Each team member: create a pair of sticky notes

1st sticky: Brief Overview of idea or solution: a 1 or 2 word headline2nd sticky: A ‘visual depiction’ of the solution: a single frame of a storyboard; e.g. rough prototype of a UI

Post as a pair (of stickies) on the blank flip chart.

(Members encouraged to create multiple pairs – one pair for each idea)

15 MINUTES

15 MINUTESTeam Discussion: Tell the room:Discuss and Cluster similar ideas togetherConverge on and circle a set that you would like to explore.

8:45 – 9:15

Insurance9:45 – 10:15

• Rate the circled ideas based on • importance / impact to the client

• feasibility of us to deliver

Tell the room

Individually

• Place red dot(s) on the Clusters that will be the most important to the client

• Place a green dot(s) on the Clusters that are the most feasible for IBM to implement.

13

10 minutes

4. Ideation Prioritizationpart A

9:15 – 9:25

Insurance10:15 - 10:25

4. Ideation PRIORITIZATION, Part B

14

15 minutesObjective: Evaluate ideas for 1. Importance to the USER2. Feasibility to IBM

TeamsTell the roomPlace the ‘idea pairs’ on the X-Y Graph wherex – axis reflects feasibility to IBM, low to highy – axis reflects importance to the user, low to high

Does it make sense? Dependencies?No-brainers?

9:25 – 9:40

Insurance10:25 – 10:40

IBM Design :: IBM Confidential :: © 2015 IBM Corporation

A sales leader can assemble an

agile response team from across

IBM in 24 hours without

management involvement.

6. Storyboard – Communicate ideas visually by telling a user-centric story (55 min)

17

20 MINUTES Individual Tell the roomImagine your scenario as a story, with characters, plot, conflict and resolution

Place 6 sticky notes or frames on a piece of paper.For each frame, draw a quick sketch and annotate with a brief caption.Story should have beginning, middle, end.

35 MINUTESAs a teamTell the roomAs a TEAM Share stories with each other.. Choose best parts of each teammates story & weave into one refined ‘master’story that represents the entire team’s thinking.

10:35 – 11:30

Day 2: Schedule for Case Study Work - INSURANCEstart stop dur Exercise Participation Description

8:00 8:30 AM 30

1. Opening,

Introductions, Objectives,

Schedule,Logistics

Team - led by Bertrand

& Valeria

Introduction to Insurance Community

Introduction to Case Study Structure and Schedule

SHORT review of case study (they will have received the case study 2 days before).

8:30 9:30 AM 60 Watson IoT for Insurance Phil Schwartz Industry trends

9:30 9:45 AM 152. Validation & Pain

Point Prioritization Team

Discuss persona, empathy maps, AS-is Scanarios

Agree as a team on the top pain points to address

9:45 AM 10:15 AM 30 3. Ideation Individual / Team Each team member generates three ideas to address pain points and as a team cluster ideas into similar

groups

10:15 AM 10:40 AM 25

4. Ideation Prioritization

Part A (10 min)

Part B (15 min)

Individual / TeamVote on best ideas in terms of feasibility and importance then tally votes to identify no brainers and big bets

ideas

10:40 AM 11:25 AM 45 5. Hills Individual / TeamCreate a hill that contains Who/What/Wow to create a very compelling new business scenario for the

customer

11:25 AM 12:25 PM 60 Lunch

12:25 PM 1:15 PM 50 6. Solution Design Team Considering the As-Is IT Ecosystem, To-Be state, and potential reference architectures/accelerators, create

an architecture roadmap to address how to make the new story real for the customer.

1:15 PM 2:45 PM 90 7. Proposal Preparation TEAM

2:45 PM 3:00 PM 15 Break (Sharks come in)

Sharkitecture Timing

19

3:00 PM 3:15 PM 15 Team 1 Presentation

3:15 PM 3:25 PM 10 Panel Feedback - Team 1









© 2016 IBM Corporation20

itecture

2016 SCA SDL UniversityDay 2Automobile Manufacturing Case Study

© 2016 IBM Corporation

A Major AutoCo Business Initiative- Maximizing Manufacturing Uptime

2

1

The Account team working on the IBM Integrated Account at AutoCo will find an extremely mature company in terms of business

model longevity (leader in global vehicle sales for 77 consecutive years, 1931-2007), while also noting recurrent operational and

quality issues related to excess complexity, masses of equipment in various conditions requiring excessive attention, and sometimes

archaic IT support. Rebounding from quality, safety and brand perception issues as well as financial difficulties in recent years,

AutoCo needs to reinforce product quality and inherent safety as their prime goals, while also driving undeniable and superior value

to the end user consumer. Economically, AutoCo must rein in challenges around capital expenditures, equipment/tooling and

personnel costs in order to remain profitable and progressive. Of prime focus according to manufacturing line personnel and

supervision has to be the maximization of operational accuracy and service lives for factory floor tooling. An integrated approach for

prediction that starts with quality evaluation stations and moves across AutoCo to end-to-end production lines has been envisioned

for the customer, and appropriate small-scale pilot deployments using existing IT infrastructure have been initially requested by

AutoCo. A longstanding (opened 1954) Texas assembly facility for mid- to large-scale Sport Utility Vehicles has been chosen as the

starting point.


Improvement of Car-Body Welding Processes – Case Study Overview

22

You are the SCA on the AutoCo account, one of the largest global manufacturers of automobiles. The company has struggled to

compete on quality and warranty issues in several key manufacturing-process areas such as paint, stamping, and welding. Welding

has been particularly problematic in that an increase in car production has strained the existing monitoring and alert system, and

more weld-robot faults are leading to dangerous weld defects. Embracing advances in IoT, the company has installed new ultrasound

and laser inspection sensors, which are multiplying the data to be analyzed. The company’s longstanding statistical-process-control

system cannot keep up, and process engineers on the plant floor are frustrated that they are unable to leverage all the new data.

You brief the plant manager and process engineers on IBM’s BD&A PoV and modern prediction capabilities. They have asked you to

develop a solution that analyzes and makes it easier to make process-improvement decisions based on all the data being generated

by the sensors. Plant manager Pete mentions to you privately that they were able to hire Sarah, a top-notch engineering graduate,

who also had an offer from Tesla, so the solution must have high wow factor! You will be presenting your solution to the Division VP


Client Background – AutoCo

Multinational consumer and commercial vehicle manufacturer and marketer

–American corporation, headquartered in Northern US, >100 years old

–Publicly traded (listed on major US exchange, market bellwether)

–~400 locations on six continents

–Production facilities in ~40 countries

–~225,000 direct employees

–~10 million units produced/year

Does business in over 120 countries worldwide

–Five business units

• North America

• Greater Germany Group

• International Group

• South America

• Finance Group

–Four major vehicle divisions

–Thirteen distinct, solely-owned and marketed brands

–4500 US dealers

–Partial ownership holdings in other vehicle manufacturers

–Multiple joint ventures in multiple countries across multiple continents

$152B revenues in 2015

– Income: $10B

–Assets: $195B


Restore and build public acceptance and trust

– Resolve existing litigations and complete open recalls

– Employ positive, image-conscious advertising

• Families plus performance-oriented consumers

– Offer comprehensive, retention-focused accessories, parts and service

Anticipate disruptive change

– Develop and demonstrate leadership in hybrid electric offerings across multiple vehicle sizes, capacities and utilities (i.e., trucks)

– Continue pioneering work with all-electric, alternatively-powered (hydrogen, FlexFuel) and self-driving vehicles

– Maintain active and vital R&D programs, continuing auto industry innovation leadership

Relentlessly drive brand loyalty

– Maintain leadership in environmental initiatives

• Adoption of landfill-free, production waste recycle/reuse

• Explore and sponsor experimental technology trials

• Support growth for Corporate Average Fuel Economy

– Vehicle purchase incentives and assistance through financial arms

Bolster and streamline public interfaces

–Consolidate, simplify and increase utility for “one source” online presence

–Drive consistent and “one voice” dealer experience delivery

–Grow publicity for significant industry innovation and engineering accomplishments

–Promote recruiting and intake programs for new hire pipelines

Become omnipresent across the consumer vehicle ownership lifecycle

–The OEM partner of choice for vehicle acquisition, ownership, utilization, maintenance and retirement

24

Client’s Business Imperatives


Outstanding product quality claims and issues

–Safety-related litigation

–Product recalls

–Governmental regulatory actions

–Escalating warranty costs

–Lower rankings in quality surveys

–Too-high PP100 scores

Mounting manufacturing problems associated with

specific functions

–Painting quality

• Frequency of rework

• High energy costs, 70% of plant on industry average

–Chain (line conveyor) break

• Extremely expensive downtime (typically millions of dollars)

• Potential equipment damage, worker injuries

–Frame turnover errors

• Near misses

• Collateral damage to item, conveyor

–Welding quality

• Cold welds

• Scrapping and rework

–Stamping tooling maintenance

• Reactive versus proactive

• Unnecessary extra downtime

Failure to leverage automation to meet ROI goals

–Labor costs have not shrunk proportionally

– Incoherent sensor/actuator and supporting IT deployment

schemes

– Inadequate analytics capabilities and tools for sensed (but “dark”)

data interpretation

–Disparate, inconsistent and unmanaged hardware/software

versions for deployed units/PLCs

–Proliferation of special-case “calibration data” that tends to end

up lost

–Aging tooling “passively” maintained

• Always break/fix rather than proactive

• Still within economic lives, so “stuck” with them

Responsiveness challenges

–Delivery of end user satisfaction driven largely through humans

with associated communication delays

–Failures and gaps in dealer channel personnel education and

knowledge

–Complaints escalated to press/social media first and quickly

–Need to be out ahead of emerging quality, safety, engineering

issues

25

Client’s Pain Points


Client’s Primary Business Requirements

26

Maximize product quality

–Begets safety and reliability, both also top priorities

–Resolve past claims in both fair and economically-survivable manners

–Achieve ever-higher rankings in external initial quality surveys

–Minimize Problems Per 100 Vehicles (PP100) counts across all brands

Drive increased manufacturing efficiencies

–Reduce labor costs

–Maximize safety scores via elimination of recordable workplace accidents

–Minimize tooling and facility downtime and maximize lifetimes via move from reactive to proactive maintenance

–Derive and develop insights into product and process improvements

–Reduce energy consumption and carbon footprint

Build substantial and comprehensive visibility across operations

– Integration of SCADA, IoT, and real-time analytics-processing to form a coherent sensing hierarchy

–Development of unit-addressable dashboards yielding spot check and temporal monitoring

–Evolution of comprehensive reporting with roll-up from facility up through enterprise levels

– Integration of existing asset management systems with predictive and proactive maintenance drivers

–Acquisition of deep analytics and modeling skills around equipment performance data and service/operation recommendations

–Develop and implement comprehensive and consistent quality assurance methods and testing across all product lines

Leverage existing facilities and IT capabilities first for enhancement of ROI on past spending

–Building of analytical and operational expertise amongst current staff a plus

–Outsourcing of capabilities not available locally when most cost effective

–Partner with Cloud provider best poised to maximize value for internal and external spend


Technology Requirements

Volume: Product quality and asset maintenance systems and processes must support ~10-million-unit/year production

targets plus 5% annual growth

Scalability: System implementations must utilize existing and planned IT capital spending levels, rolling out to 37 US

manufacturing facilities post-pilots, eventually to ~100 worldwide; Cloud and on-demand additional capacity as possibilities,

but direct ownership only and no outsourcing

Governance and Control: All automation augmentations, extra processing/storage capacity and massive amounts of new

structured business data and unstructured sensor data must be integrated into current plant/region/division operational

analytics and views and dashboards, with current remote management capabilities supported across the board

Timeliness: Models must be continually updated, view frequently refreshed to be able to make timely decisions and changes

to the process.

Data Security: New augmentations, capacity and data storage/handling must meet all applicable corporate standards for

plant isolation, cross-plant communications and encryption

Self-serve: Enable individual plant management roles with comprehensive “own facility” operational views that include

tooling performance and analytical reporting

High availability: Support three production shifts at 90% line availability 7 days/week, 315 days/year via hardware clustering

w/failover, re-routable automation workflows27


General Observations

Traditional approaches to data storage, with still some manual entry/onboarding (i.e., CSVs, spreadsheets, forms)

Well-supported, multipath and extremely reliable high-bandwidth corporate intranet reaching all facilities, with partitioning

between administrative and operational functions

Substantial on-premise data processing facilities distributed both near-HQ and around the world; very mature and time-

honored processes in place

Factory automation and IT groups typically at odds around perceived on-floor and visibility needs

Some advanced analytical dabbling by industrial engineers at corporate HQ and the Technology Center, along with lots of

data collection from existing automation (uploads along intranet), but almost all “dark” and untapped

Resurging profits around successful vehicle lines have driven improvements in capital planning and budgets of late

Aging tooling and facilities along with labor costs contribute to too many production outages; potential high for optimization

opportunities

28


Key Players

CIO – steeped in traditional IT and on-premise approaches, but willing to listen on Cloud and dynamic capacity

Division VP – have product success/revenue responsibilities, tend to be friendly toward analytics, enhanced visibility and process

optimization

Regional Manager – focused on plant group operations, lowering costs and making target production and overhead reduction

numbers; interested in seamless, non-disruptive transformation yielding high ROI

Plant Manager – caught up in Regional Managers’ priorities, open to low-impact technology improvements and increased insights

into individual asset performance, along with emerging and future plant issues; drives to achieve/exceed targets for scrap reduction,

inventory balance, overtime, etc.

Production Line Manager – concerned with maximum line uptime, minimal interruptions and totally-predictable (and minimized time

loss) maintenance

Plant Process Engineer – into process improvements driven by technology, analytics, and visibility/insight into previously unused or

“dark” data

Plant Maintenance Manager – wants machinery working in predictable manner, allowing outage and spare parts supply planning,

etc.; desires visibility into details and health scoring for individual equipment, including prescriptive action recommendations

Quality Control Manager – looks to leverage dashboards and scorecards to decision and avoid production stoppages for quality

issues; high degree of reporting and support for spotting and intervening in quality issues originating at suppliers

29


30

Empathy Map for Sarah, Plant Process Engineer

I can’t keep up with all this data from the new acoustic and laser sensors.

With all this new data I’m getting in real time, I could greatly improve the welding process.

Ensures that welding process is performing well

Researches and drives process improvement

Gotta find a way to update my models continually with all this new data.

Frustration that she doesn’t have the data management system and tools to deliver a corrective action to a problem in a timely manner.

The old SPC methods are really not enough when we have all these newer AI and cognitive analytics methods we could be using.

Pressure to analyze the torrent of new sensor data, make process improvements, and report results to the plant manager.

My model results have to be immediately reportable to the plant and quality managers, with enough drilldown detail so they can tell how much improvement we’re achieving.

Excitement about what the new data could tell her about process problems, and the potential for newer analytics methods she could use to solve them.

SCAU – Automobile Manufacturing Case Study

I need better analytics tools and more data processing capability.

Improves overall department operations—quality, production, & equipment health


31

Empathy Map for Pete, the Plant Manager

“I need higher visibility and more rapid and easier-to-read reports tied to my engineer’s modeling.

“We need to make use of all the sensor data we’ve invested in.”

My engineers need faster modeling tools so that we can anticipate problems earlier

Schedules daily plant operations

Monitors overall plant performance

Coordinates production activities

I need higher visibility and more rapid reporting so that I can reduce downtime and cost overruns.

Needing to be able to leverage all the data coming from the new sensors that he just recommended.

If only my engineers could determine the root cause of problems quicker…and report to me on their results right away.

Pressure from senior management when downtime increases and plant production declines

My engineers need to be able to run their models continually on many times more data than in the past.

The need to enable his engineers to better optimize the process in a more timely manner.


Drives the adoption of new methods and tools amongst the plant engineers.


DOING

THINKING

FEELING

STEPS

AutoCo’s Welding Process AS-IS Scenario Map

32

Monitor Evaluate Remediate Enhance Report

Examining PLC

statuses for

timing

compliance

Checking quality

scoring at line

exit

Machine health;

input

voltages/current

s, etc.

Inspection fault

totals

Station

tracing/attribution

Visual weld

checking

Comparative

quality scoring

/SPC across

runs/lots

Line interruptions

for tip change-

outs

Line route-

arounds for

maintenance: 50%

capacity loss

Trying to increase

line speed to

compensate for

outages

Getting limited

and useful

visibility to gross

indicators

Reporting failure

counts to

management, not

causal factors

Sending line

output counts, not

wasted/retry time

Only major

maintenance

events, not ad-hoc

Lack of visibility

into sensor and

process data

means we’re

finding things

out too late.

Now we’re

sensing more

and more line

data, and still

managing to do

even less with it!

We’re not getting

the tip/electrode

wear we should

be; machines are

down too often.

We’ve got to get

out in front of

these

deteriorating

quality issues,

like now!

Lack of budget

means getting

the most out of

what we’ve got,

not replacing it.

Equipment

performance

analysis lags the

present, with what

to address not

clear; need

intelligent

recommendations.

Current reports

are delivering

simple metrics,

but no real insight

for equipment

health and

lifetimes.


My stations are

the worst and

consistently

holding things

up, and I’m

looking bad...not

my fault!

I absolutely have

to have more

insight into

what’s going on

or going to

happen in order

to produce

measureable

improvements!

Management

needs to see

cold, hard facts

around what

we’re facing

every day!

Depending on PLC

diagnostics, tip

wear, visual/laser

to indicate

trouble; not much

else

Laser weld

checking

Introducing new

tooling as can

from limited

budget

Trying for more

sensor locations


AS-IS System

33

Process

Improvements,

Statistical Model,

Optimized Quality

Inspection Plan

Products from suppliers

Manufactured products (Semi-finished and finished)Sampling and Analysis

History of

inspections and

analysis results

SPC

Analytics

Field and

Environmental Data

Optimization

Resources availability

& skills (personnel,

instruments,…)

Quality Inspection,

Process improvement Objectives

Process

Constraints

History of

inspections and

analysis results

(relational dbms)

Other structured and

unstructured process

data from several new

sensor systems including

DAS ultrasound and laser

Offline Optimization Model

Summary reports & dashboards for

Plant & Quality Managers

Resources

cost

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