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© 2017 Lean-Agile Partners Inc. All rights reserved.

Agile Adoption without Executive-Level Support:

An inside-out approach to team based Agile adoption

Nancy Van Schooenderwoert @vanschoo

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Nancy Van Schooenderwoert n  Originally an electronics and software designer n  15 years safety-critical embedded systems development experience n  Since 2002: Agile coaching of teams and managers in regulated industries n  Industries: Aerospace (Flight simulation), Medical Devices, Sonar

Weaponry, Scientific Instruments, Industrial Controls, Financial Services n  BSCE (Computer Engineering) from Rochester Institute of Technology n  Active in Agile New England & Agile Alliance n  Speaker at conferences worldwide

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Agenda

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n  What we achieved as a team n  New things our data told us n  Back to the “prequel” – team’s origins

n  Interaction part + 4 rules you can use n  Benefits we never expected

Opportunity to try for zero-defects code

n  First customer – agricultural

n  Based on new science, new CPU, new OS port, new NIR h/w sensor, new algorithm…

n  Agile team delivered 1st field units in 6 months

n  Surprise! New customer wants to use it for blood analysis - It’s now a medical device

Grain Monitor System (GMS)

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First we did these things as a team n  Reviewed the s/w design I had begun n  Chose a coding standard, tool use practices n  Decided that we wanted to know 4 things throughout

our work together n  Quality of our code n  Schedule performance n  Labor used n  Volume of work done

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Labor Distribution, 1st year

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0

5

10

15

20

25

30

35

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Detaile

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Code_

CSU_test

CSC_integ

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Proce

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s/w_m

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Tool_s

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Sys_in

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Per

cent

of T

eam

Lab

or

Source: “Embedded Agile Project by the Numbers with Newbies”, available at http://www.leanagilepartners.com/publications.html

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Labor Distribution, 2 Years

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Detaile

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Tool_s

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ead

Admin_

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ort

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Sys_in

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ion

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Requir

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Per

cent

of T

eam

Lab

or

0

5

10

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Detaile

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Code_

CSU_test

CSC_integ

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Proce

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abor

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Detailed_design

Code_CSU_test

CSC_integ_test

Process_devel

s/w_management

Tool_support

Technical_lead

Admin_support

CSCI_test

Sys_integration

Support

Requirements

Per

cent

of T

eam

Lab

or

Year 1 Year 2

First Iteration

Hardware evolving…

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Results n  29,500 lines of tested, working realtime embedded code

delivered (in C, non-comment lines), GMS app n  5,000 lines Windows utility code (VB) n  2,000 lines Perl code (Calibration Table builder utility) + other

utility code n  51 bugs total for project, active list <2 bugs n  1.5% bug rate would have given 442 bugs n  Stable software throughout development

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Defects: 3 years Development

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n  Defect injection rate of 0.22 defects/Function point n  Productivity 3x industry norm

Bugs - sorted by Severity level and time found

CriticalModerateCosmetic

Totals

51

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S/W Releases

Year 1 Year 2 Year 3

“Production Ready”

Field trials worldwide

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Quality level among the highest

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Team Defects/Function Point

Follett Software* 0.0128 agile BMC Software* 0.048 agile GMS 0.22 agile Industry Best** 2.0 traditional Industry average** 4.5 traditional

* Computed from data reported in Cutter IT Journal, Vol. 9, No. 9 (Sept 2008), page 10 ** Capers Jones presentation for Boston SPIN, Oct., 2002

Audited for GAMP compliance

3 day audit of software practices n  Done for pharmaceutical customer (use spectrometer

for blood and tissue analysis) n  Auditor impressed by thoroughness and consistency of

our work n  A few minor findings, easily fixed

n  E.g. make internal status flags readable without using debug tool

GAMP = Good Automated Manufacturing Practice

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Agenda

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n  What we achieved as a team n  New things our data told us n  Back to the “prequel” – team’s origins

n  Interaction part + 4 rules you can use n  Benefits we never expected

Code base and defects over time

Code base grows from zero for clean-start project. Expect same shape for open defects?

Time

Line

s of

Cod

e O

pen

Def

ects

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29.5K

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Open defects turned out to be flat. No correlation to code size!

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Defect difficulty not inherent n  Difficulty of troubleshooting a s/w defect

depends most on length of time it was hidden – not on the type of defect

n  Suggests that the strongest way to eliminate defects is to detect them quickly

n  Agile excels in doing exactly that!

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Def

ect N

o.

Defect Inserted Defect FoundR

eqm

ts

Des

ign

Cod

ing

Inte

g. T

est

Pos

t Rel

.In

tern

al

Pos

t Rel

.E

xter

nal

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Not a Bug (for us) - Partner's code has bug.30

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36 Not a Bug (for us) - Diagnostic PC code has bug.

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31 Not a Bug (for us) - Partner's code has bug.

Source: N. Van Schooenderwoert; “Embedded Agile Project by the Numbers with Newbies”; Agile 2006 Conference; Available at www.leanagilepartners.com/Publications

Defect Severity KeyCosmetic Defect - Could leave as is

Moderate Defect - Can work around, but must fix later

Critical Defect - Must fix immediately

Length of time from injection of defect till its symptoms were visible

Mobile spectrometer - results

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050

100200

400800

BestUS Europe

Malpractice0

500

1000

1500

2000

2500

3000

Defects Delivered to Customer

Total function Points

Defect Rate Data from Capers JonesTraditional teams injected many bugs, then removed most.

Spectrometer team injected fewer & removed most immediately

Spectrometer team performed here

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Agenda

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n  What we achieved as a team n  New things our data told us n  Back to the “prequel” – team’s origins

n  Interaction part + 4 rules you can use n  Benefits we never expected

n  (story, and discussion)

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Agenda

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n  What we achieved as a team n  New things our data told us n  Back to the “prequel” – team’s origins

n  Interaction part + 4 rules you can use n  Benefits we never expected

My guidelines n  Know when to walk away

n  “BATNA” – best alternative to a negotiated agreement n  Every negotiation has 2 tracks: substance, relationship n  Cannot trade substance for relationship & vice versa

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My guidelines n  Create a teamwork foundation

n  Something the group values… n  Could be a problem all want to address n  Coding standard, learning together, etc. n  For GMS team, learning more about embedded sys coding,

(and getting this project delivered!)

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My guidelines n  Action over debate

n  Debate rarely settles anything n  Instead do an experiment or try a change till next sprint

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My guidelines n  Use principled negotiation

n  See “Getting to Yes” by Fisher, Ury, Patton n  (role play on positional bargaining)

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Agenda

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n  What we achieved as a team n  New things our data told us n  Back to the “prequel” – team’s origins

n  Interaction part + 4 rules you can use n  Benefits we never expected

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Agility spread to hardware n  Only the s/w team was using Agile practices, but… n  Frequent s/w releases created many more

opportunities to improve h/w-s/w interaction n  Result was h/w became more Agile “without trying” n  Some examples (next slide)

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S/W team’s services to other teams n  Some measurements inconclusive due to voltages out of

range – so added s/w monitoring of h/w key areas

n  Field problems that could not be isolated to one area (opto, sensor, electronics) could be investigated thru special s/w releases for troubleshooting

n  Hand assembly of field units improved by downloadable collection of s/w drivers with command-line menu

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Whose bug is it? n  Hardware is presumed innocent n  But…

n  We gave EEs code to check h/w n  We gave simple tests to exercise s/w n  This saved other groups much time

n  By end of GMS project, even EEs were suspecting h/w before s/w!

n  S/W no longer “guilty till proven innocent”

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Contact Info

Nancy Van Schooenderwoert LeanAgilePartners

nancyv@leanagilepartners.com

@vanschoo

§  Lean-Agile coaching for software and hardware teams

§  Safety-critical, regulated industry coaching/ training is our specialty

§  Lean-Agile coaching for stakeholders and senior managers

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