Index

Numerics

5S, 261–262

for large Internet service companies, 281–283

seiketsu, 273–277

seiso, 270–273

seiton, 266–270

shitsuke, 277–278

sort (‘seiri’), 262–266

for start-ups, 278–281

A

A3 problem solving, 427–432

accountability, governance and, 435–436

accuracy, 43, 169–172

action, 26

after action reviews, 79–80

Agile, 4, 10, 41, 77, 102, 447, 451

agility, 10

Alexander the Great, 57

alignment

service operations synchronization and improvement, 400

strategic cycle, 421–423, 424–432

tactical cycle, 400–402

daily standup, 408–411

kickoff, 403–408

Queue Master brief, 402–403

retrospective, 411–421

through iterative approaches, 397

kanban, 399

Scrum Sprint model, 398

top-down approach, 397

all-in-one tools, 275–277

ALM (Application Lifecycle Management), 277

analysis paralysis, 134

analytics, data collection and, 292

anchoring bias, 46, 162

Anderson, D., 351

Andon, 350–351

anti-goals, 68–69

APIs, 121

assessment. See also maturity model

review processes, 187–188

standardized testing, 185–187

automation, 257–258, 261, 318. See also Tools & Automation Engineering

bias, 47, 162

build and CI system, 311

ecosystem conditions, 258–260

governance and, 458

implementing 5S principles

for large Internet service companies, 281–283

for start-ups, 278–281

tools, 268

availability, 223–224

bias, 46

awareness, 95–96, 99, 115, 214. See also situational awareness

development, 312–314

fog, 205–207, 222

eliminating, 209–214, 219–220

identifying what you can or cannot know, 214

operational, 206–207

SE Lead and, 246–248

AWS, 124

B

Babel, 11–12

backbriefing, 63, 69–71, 194

Battle of Kasserine Pass, 176

best practices, 273–274, 451

bias, 161–162

anchoring, 46

automation, 47

availability, 46

cognitive, 46–47

confirmation, 290

execution, 35–36

hindsight, 47, 51–52

representativeness, 46

solution, 34, 35

Big Data, 43, 289, 326

Blockbuster Entertainment, 7

Boyd, J., 4, 18, 23, 24–25, 28, 33, 36, 40–41, 74, 77, 83. See also OODA loop

Aerial Attack Study, 24

“Destruction and Creation,” 77

bugs, 271, 305, 314

bullwhip effect, 116–118

business continuity planning, 204, 236

Business Intelligence, 43, 69, 214, 289

C

CABs (Change Advisory Boards), 14–15

CEO, 68

change management, 317–319, 447–449

Chaos Engineering, 47, 79, 216–217

chaotic contexts, 137–139

dictators, 139–141

firefighter arsonists, 141–142

clear contexts, 131–133

cloud environments, 96–97, 124, 202

Clousewitz, C., 62

coaching practice, 193–195

code(ing), 10, 13, 41, 48–51, 92, 95–96, 112–113, 136, 233, 241, 251, 252, 268, 271, 319. See also software

defects, 89

metrics, 311

Power Peg, 266

quality, measuring, 224–225

queryable, 321

cognitive bias, 46–47, 161–162. See also bias

collaboration, incentivizing, 251–252

color coding, 90

Commander’s Intent, 63–66, 211

communication, 95. See also information

disconnects and, 348–349

implicit, 73

Queue Master role and, 385

competitive objectives, 96

complexity, 135–137, 351

environment, 128–129

kanban board and, 360–362

unpredictability and, 61

complicated contexts, 133–134

configuration management, 274, 277, 317–319

confirmation bias, 162, 290

confusion, 143

constraints, 68–69, 345

context, 43, 141–142, 261, 306

chaotic, 137–139

dictators, 139–141

firefighter arsonists, 141–142

clear, 131–133

complex, 135–137

complicated, 133–134

of confusion, 143

disconnects and, 347–349

target outcomes and, 144

continual improvement, 75–77, 84

coaching practice, 193–195

kata, 191

day-to-day, 191–192

improvement and problem solving, 192–193

outcome-directed learning, 188–190

continuous delivery, 4, 10, 41, 218–219

continuous integration, 233, 259, 280, 283, 312

contracts, 442–445

coupling management, measuring, 239–241

CRM, 39

C-suite, 116

culture, information flow and, 177–178

customer engagement, 242

cycles. See strategic cycle; tactical cycle

Cynefin, 129–130, 210. See also context

D

daily standup, 408–411

Dark Matter, 340–342. See also friction

preventing, 359–362

Queue Master role and, 379–380

dark pools, 266

dashboards, 312, 314

data

collection, 291–292

determining the purpose and value of, 293–294

buying furniture online, 294–295

getting successfully treated at the hospital, 295–297

knowing the consumer, 297–299

capture and presentation distortions, 301

language mismatches, 299–301

monitoring, 324–325

presenting, 321–322

service, 326–327

sources, 302–303

timeliness, 305–306

trustworthiness and consistency, 303–305

day-to-day kata, 191–192

DBAs (datase ddministrators), specialization, 100–101

DBE (Database Engineering), 101

decision-making, 21, 22–23, 144, 221–222, 396. See also Mission Command; situational awareness

on the battlefield, 25

cognitive bias and, 46–47

contexts

chaotic, 137–142

clear, 131–133

complex, 135–137

complicated, 133–134

of confusion, 143

execution bias and, 35–36

friction elimination, 39–42

improving, 53–54

information

accuracy, 43

context, 43

dis-, 45–46

timeliness of, 43

knowledge and, 44

learning and, 48–51

making the best choice the easiest choice, 145–147

OODA loop, 25

action, 26

decide, 26

nonlinear looping, 28

observe, 26

orient, 26

PDCA cycle and, 28

risk, 129

situational awareness, 42–44

solution bias and, 34, 35

target outcome, 30–33

target outcome and, 16

trust and, 44

unpredictability and, 58

defects, 47, 88–91. See also failure(s)

causes of, 89

in code, 89

spotting, 90–91

“Defend against the Madman” approach, 121–122

delivery, 221–222

“as code,” 284

continuous, 4, 10, 41, 218–219

ecosystem, 197

fog, 205–207

eliminating, 209–214, 219–220

identifying what you can or cannot know, 214

friction, 37, 57

dependencies and, 41

eliminating, 39–42

feedback and, 42

multitasking and, 42

reducing, 9–11

targeting, 11–12

hygiene, measuring, 232–234

ilities, 207–209

metrics, 36–39

“mistake proof,” 90

outcome-directed approach, 190

pipeline, 238

speed, 201

teams, 15

demand

bullwhip effect, 116–118

unexpected variability in, 114–116

Demming, E., 28

dependency(ies), 41, 357

failures and, 237

instrumenting, 314–316

management, 269–270

serial loopback, 102

team, 313

deployment, automation and, 260

development environment, instrumenting, 310–314

DevOps, 4, 9, 10, 15, 18, 33, 40, 53, 76, 151, 168, 197, 199, 251

Einheit, 74–75

governance, 453

flexibility and, 458–460

intent, 454

proposals, 456–457

requirements compliance, 458

transparency, 454–456

production services and, 253

retrospectives, 192–193

Strategic Reviews, 192–193

uptime, 65

waste. See also waste

defects, 88–91

excessive processes, 106–109

handoffs, 101–103

overproduction, 91–93

overspecialization, 97–101

systemic impediments, 94–97

task switching, 105–106

WIP (“work in progress”), 103–104

dictators, 139–141

direct interference, 438–439

directive briefing, 66

anti-goals and constraints, 68–69

execution priorities, 67–68

situational overview, 67

statement of desired outcome, 67

disaster recovery, 236

disconnects, 343–346

communication, 348–349

resolving, 347–349

disinformation, 45–46

Docker, 97

Donaldson, L., 296

downtime, 123

E

ecosystem, 183, 204, 221, 222

5S, 261–262

seiketsu, 273–277

seiso, 270–273

seiton, 266–270

shitsuke, 277–278

sort (‘seiri’), 262–266

automation and, 258–260

complexity, 61

delivery, 197

development environment, instrumenting, 310–314

dynamics, 169–172

hygiene, 232–234

IT, instrumenting, 331–333

logging, 323–324

monitoring, 324–325

observability, 147–151, 307–309

rebuilding, 323

situational awareness and, 154–156

transparency, 243–244

unknowns, 310

education, formal, shortcomings of, 51–52

effectiveness, 57–58, 198

Einheit, 71–75

EM (Energy-Maneuverability) theory, 24, 83

engagement, measuring, 241–243

entry management, Queue Master, 378–379

Equifax, 9

execution bias, 35–36

execution priorities, 67–68

experimentation, 135–137

exploits, 8

F

failing to learn, 48–51

failure(s), 181, 211

dependencies and, 237

single point of, 239–241, 314

feedback, 46, 135–136

friction, 42

timeliness of, 306

Fingerspitzengefühl, 74

firefighter arsonists, 141–142

flexibility, governance and, 458–460

“fog of war,” 58. See also awareness

“follow the sun” model, 384–385

other work when on duty, 386–389

sync point management, 385

formal education, shortcomings of, 51–52

Fortran, 48–51

Fowler, M., 119

frameworks. See also Mission Command

Cynefin, 129–130

governance, 445–449

maturity model, 222, 223–224

areas of interest, 228–229

configuration management and delivery hygiene, measuring, 232–234

engagement, measuring, 241–243

incentivizing collaboration and improvement, 251–252

information flow and instrumentation, measuring, 229–231

levels, 225–228

measuring code quality, 224–225

single point of failure mitigation and coupling management, measuring, 239–241

supportability, measuring, 235–239

OKR (Objectives and Key Results), 37

service management, 13–14

framing, 164, 204

finding and fixing problems in organizations

customer engagement, 165–167

locally focused metrics, 168–169

output metrics, 167–168

Fredendall, L., 176

friction, 9, 14, 37, 57, 83, 84, 459–460. See also waste

configuration, 204

dependencies and, 41

elimination, 39–42

feedback and, 42

governance and, 437–438

multitasking and, 42

reducing, 9–11, 359–362

speed and, 40

targeting, 11–12

waste and, 85–86

G

“gemba walk,” 307–309, 430–431

Gilb, T., 208

Gitlab.com, 12

goals

anti-, 68–69

competitive objectives, 96

governance, 13, 112

accountability and, 435–436

common mistakes, 440

out-of-the-box process tooling and workflows, 450–453

poor requirement drafting and understanding, 440–445

using off-the-shelf frameworks, 445–447

DevOps, 453

factors for successful, 434–435

maintaining situational awareness and learning, 438–440

meeting intent, 435–437

no target outcome interference, 437–438

flexibility and, 458–460

intent, 454

process and, 447–449

proposals, 456–457

requirements compliance, 458

transparency and, 454–456

H

handoffs, 101–103

hindsight bias, 47, 51–52, 162

Hölzle, U., 123

hooks, queryable, 321

human brain, 154–156. See also mental models, situational awareness and

I

IDE (integrated development environment), 90

IKEA effect, 47

ilities, 207–209, 217–218, 221–222, 223, 224

known manageables, 214–215

known unmanageables, 216–217

unknowns, 217–219

implicit communication, 73

improvement and problem solving kata, 192–193

incident management, 179, 238, 338

indirect interference, 439–440

industry best practices, 13–14

information, 396. See also data

accuracy, 43

capturing, 290

context, 43

flow, 169, 198–199

cultural disconnects, 177–178

disconnects, 347–349

ecosystem dynamics and, 169–172

measuring, 229–231

SE Lead and, 246–248

tracers, 172–173

transmission mismatches, 173–176

trust and, 178–180

visualizing, 349–351

timeliness of, 43

innovation, 7, 8, 48–51

instrumentation, 291, 293–294, 295, 305, 306

configuration management, 317–319

dependency, 314–316

development, 310–314

interpreting, 300

IT ecosystem, 331–333

measuring, 229–231

observability and, 310

packaging, 314–316

production, 320

security, 325–326

testing, 319–320

tool, 316

wastewater management, 328–331

intent, governance and, 434, 435–437, 454

interference

direct, 438–439

indirect, 439–440

target outcome, 437–438

internal cloud, 97

intuition, 73, 74

Invisible Gorilla, The, 155

irregularity, 83

IT, 197

cloud environments, friction and, 96–97

ecosystem, instrumenting, 331–333

failures, 8, 13

friction, 86

governance, 433

information flow, 175

mura (“irregularity”), 113–114

overproduction, 92

risk, 127

service management, 337

service providers, data resilience and recovery, 204

snowflakes, 119–120, 121

specialization and, 100–101

task switching, 105–106

ITIL, 13, 452–453

J-K

JM (Job Methods), 84

JMX (Java Management Extensions), 321

kaizen, 272, 356

kanban, 10, 349–352, 399

flow and, 368

kaizen, 356

limits of a workflow board, 367

managing the board, 367–368

simplicity and, 360–362

state columns, 352–355

swim lanes, 355–358

tally boards, 359–360

task cards, 358–359

timestamping tasks, 364

using the board, 362–363

WIP (work in progress), 365–367

work blockages, 364–365

kata, 191, 272

day-to-day, 191–192

improvement and problem solving, 192–193

kickoff, 403–408

Klein, G., 158

Knight Capital Group, 9, 263–266, 301

knowledge. See also learning

decision-making and, 44

-execution mismatches, 108

operational, 206–207

“single points of failure,” 120

skills and, 185

unpredictability and, 59–60

known

knowns, 131

manageables, 214–215

unknowns, 133

unmanageables, 216–217

Koçulu, A., 11–12

Korean War, 23, 24, 40–41

Kubernetes, 10, 97

L

large Internet service companies, implementing 5S principles, 281–283

leadership, 55

Commander’s Intent, 63–66

effective, 57–58

service delivery, 3

top-down approach, 58

Lean, 77, 80, 83, 125–126, 145, 147–148, 350

5S, 261–262

seiketsu, 273–277

seiso, 270–273

seiton, 266–270

shitsuke, 277–278

sort (‘seiri’), 262–266

kanban, 349–351

flow and, 368

kaizen, 356

limits of a workflow board, 367

managing the board, 367–368

simplicity and, 360–362

state columns, 352–355

swim lanes, 355–358

tally boards, 359–360

task cards, 358–359

timestamping tasks, 364

using the board, 362–363

WIP (work in progress), 365–367

work blockages, 364–365

kata, 272

day-to-day, 191–192

improvement and problem solving, 192–193

mura (“irregularity”), 113–114. See also unpredictability

bullwhip effect, 116–118

minimizing, 120–122

snowflakes, 119–120

unexpected demand variability, 114–116

unmanaged variability, 118

Muri (“overburden”), 109–110

overloading releases, 111–113

people and, 110–111

outcome-directed learning, 188–190

“stop the line,” 90

“walking the gemba,” 307–309

waste and, 84, 90

learning, 48–51, 183

continual improvement and, 75–77

effective leadership, 57–58

formal education, 51–52

hindsight bias and, 51–52

kata, 191

day-to-day, 191–192

improvement and problem solving, 192–193

outcome-directed, 188–190

skills and, 184–185

standardized tests and, 185–187

Legal and Compliance teams, 300–301, 442–445, 454

locally focused metrics, 168–169

logging, 323–324

M

MacArthur, D., 85

managers, 210–214, 277–278, 371–372. See also Queue Master; Service Engineering Lead; teams

managing

micro-, 278

risk, service delivery, 12–15

waste, overproduction, 91–93

manufacturing

waste. See also waste

defects, 88–91

excessive processes, 106–109

handoffs, 101–103

overspecialization, 97–101

task switching, 105–106

waiting, 94–97

WIP (“work in progress”), 103–104

maturity model, 222, 223–224

areas of interest, 228–229

incentivizing collaboration and improvement, 251–252

levels, 225–228

measuring code quality, 224–225

metrics

configuration management and delivery hygiene, 232–234

engagement, 241–243

information flow and instrumentation, 229–231

single point of failure mitigation and coupling management, 239–241

supportability, 235–239

Maven, 270

Meltdown, 8

mental models, 45, 157–158

cognitive bias and, 161–162

data interpretation issues, 160

disinformation and, 45–46

problems with, 158–160

resilience, 160–161

mentoring, 194–195, 211

method-driven management, 340, 446–447

metrics

availability, 223–224

code, 224–225, 311

configuration management and delivery hygiene, 232–234

delivery, 36–39

engagement, 241–243

information flow and instrumentation, 229–231

interpreting, 300

locally focused, 168–169

output, 167–168

single point of failure mitigation and coupling management, 239–241

for success, 294–295

supportability, 235–239

Microsoft Azure, 13

misalignment, 60–61, 396. See also alignment

Mission Command, 3, 33, 55–56

after action reviews, 79–80

anatomy of, 62–63

backbriefing, 69–71

Commander’s Intent, 63–66, 211

continual improvement and, 75–77

directive briefing, 66

anti-goals and constraints, 68–69

execution priorities, 67–68

situational overview, 67

statement of desired outcome, 67

Einheit, 71–74

organizational impacts of, 80–81

origins of, 56–57

staff rides, 78–79

target outcome, 62–63

unpredictability, 58–59

ecosystem complexity and, 61

misalignments and, 60–61

through knowledge and awareness weaknesses, 59–60

unpredictability and, 56–57

Mobius outcome delivery approach, 3

Moltke, H., 62, 66, 72, 77, 78, 80, 83

monitoring, 324–325

MTBF (Mean Time Between Failure), 123

Muda, 86–88, 115. See also waste

multitasking, 42

mura (“irregularity”), 113–114. See also unpredictability

bullwhip effect, 116–118

minimizing, 120–122

snowflakes, 119–120

unexpected demand variability, 114–116

unmanaged variability, 118

Muri (“overburden”), 109–110, 115

overloading releases, 111–113

people and, 110–111

N

Napoleon, 57–58, 72

negative events, 75

Netflix, Simian Army, 122–124, 216–217

Node, 11–12

nonlinear looping, 28

O

observability, 295

ecosystem, 147–151, 307–309

instrumenting for, 310

observation, 26

office hours, Queue Master, 382–383

off-the-shelf tools, 303–304, 305

Ohno, T., 83, 85

OKR (Objectives and Key Results) framework, 37

on-demand service delivery, 205

OODA loop, 25, 135

act, 26

decide, 26

nonlinear looping, 28

observe, 26

orient, 26, 43–44

PDCA cycle and, 28

open source software, 10

Operation Millennium Challenge, 25, 40

optimism bias, 162

ordered systems

clear contexts, 131–133

complicated contexts, 133–134

organizational impacts of Mission Command, 80–81

organizations

finding and fixing framing problems

customer engagement, 165–167

locally focused metrics, 168–169

output metrics, 167–168

overburden and, 110–111

specialization and, 98–99, 100–101

orientation, 26

origins of Mission Command, 56–57

outages, 122, 272

outcome-directed learning, 188–190

output metrics, 167–168

overburden, 83, 109–110

overloading releases, 111–113

people and, 110–111

overproduction, 91–93

overspecialization, 97–101

ownership, building a sense of, 199

P

PaaS (platform-as-a-service), 10

partially done work, 103–104

Parvin, A., 35

PDCA cycle, 28

performance, 207, 208. See also ilities

PII (personally identifiable information), 438–439

“playing it safe,” 76

POMs (project object models), 270

Pony Test, 64–65

Power Peg, 266

pride, building a sense of, 199

process(es), 201. See also governance

excessive, 106–109

failure, 48–51

CRM, 39

OODA loop and, 28

governance and, 447–449

review, 187–188

standardization, 275

workflow and, 337–339

production, instrumenting, 320

productivity, 84

Puppet, 10, 97

pure waste, 86–88

Q

QA (quality assurance), 319

queryable hooks, 321

Queue Master, 75, 91, 104, 106, 147–148, 175, 181, 220, 372–373, 404–405

daily standup and, 408–411

“follow the sun” model, 384–385

other work when on duty, 386–389

sync point management, 385

retrospective and, 414, 415

role mechanics, 374

Dark Matter handling, 379–380

entry management, 376–377

maintaining flow, 380–381

office hours, 382–383

pattern recognition, 381–382

rotation, 374–376, 386

sorting and dependency discovery, 378–379

rollout challenges, 389

junior team members as Queue Masters, 391–393

pushy Queue Masters, 391

sync points, 394

team members not seeing the value, 389–390

traditional managers thwarting rollout, 390–391

tactical cycle and, 400–403

typical day of, 386–389

R

rebuilding the ecosystem, 323

reflection, 396

releases, overloading, 111–113

reliability, 207

representativeness bias, 46

resilience, 160–161, 204

retrospective, 192–193, 411–413

general meeting structure, 413–415

learning and improvement discussion, 415–421

review, 187–188

kaizen, 356

strategic, 424–432

risk management, 127, 143–144

decision-making, 129

chaotic contexts, 137–142

clear contexts, 131–133

complex contexts, 135–137

complicated contexts, 133–134

confusion and, 143

making the best choice the easiest choice, 145–147

ecosystem observability, improving, 147–151

ilities, 208

service delivery, 9

downsides of targeting, 14–15

managing, 12–14

rotation of duties, 142, 240

Queue Master, 374–376, 386

Service Engineering Lead, 244–246

S

SaaS (Software-as-a-Service), 200

satisficing, 47

Scharnhorst, D., 72

On War, 58

Scrum, 10, 77, 214, 314, 398, 404–408

SDK (software development kit), 445

security

breaches

Equifax, 9

SolarWinds, 128

tracking and analysis, 325–326

seiketsu, 273–277

seiso, 270–273

seiton, 266–270

“Selective Attention Test,” 155

separation of duties, 435–436, 439

serial loopback, 102

serverless architecture, 136

service delivery, 3, 4, 15, 17, 204–205, 221

agility, 10

availability, 223–224

data, 326–327

on-demand, 205

disconnects, 343–346, 347–349

fog, 205–207

eliminating, 209–214, 219–220

identifying what you can or cannot know, 214

friction, 57, 83

dependencies and, 41

eliminating, 39–42

feedback and, 42

reducing, 9–11

waste and, 85–86

ilities, 207–209

known manageables, 214–215

known unmanageables, 216–217

leadership, 3

maturity model, 223–224

areas of interest, 228–229

configuration management and delivery hygiene, measuring, 232–234

engagement, measuring, 241–243

incentivizing collaboration and improvement, 251–252

information flow and instrumentation, measuring, 229–231

levels, 225–228

measuring code quality, 224–225

single point of failure mitigation and coupling management, measuring, 239–241

supportability, measuring, 235–239

measuring, 17

metrics, 36–39

Mission Command, 33

outcome-directed approach, 190

risk

downsides of targeting, 14–15

managing, 12–14

situational awareness, 205–207

speed, 9–10, 201

systems thinking, 80

target outcomes, 16, 18, 293–294

unknowns, 217–219

uptime and, 65

Service Engineering Lead, 243–244, 380

challenges, 250–251

on the delivery team, 250, 253

duty rotation and, 244–246

operational, 249–250

organizational configurations and, 248–250

overcoming the operational experience gap, 254–255

retrospective and, 414–415

tactical cycle and, 400–402

team awareness and, 246–248

Shingo, S., 87

shitsuke, 277–278

silos, 136–137

Simian Army, 124, 216–217

single point of failure, 120, 239–241

situational awareness, 2–3, 4, 16, 42–44, 111, 114, 115–116, 120, 206. See also kanban

backbriefing and, 69–71

cognitive bias and, 161–162

Dark Matter, 340–342

disconnects, 343–346, 347–349

Fingerspitzengefühl, 74

framing, 164, 165–169, 204

governance and, 438–440

human brain and, 154–156

information flow, 169, 206

cultural disconnects, 177–178

ecosystem dynamics and, 169–172

measuring, 229–231

tracers, 172–173

transmission mismatches, 173–176

trust and, 178–180

mental models, 157–158

data interpretation issues, 160

problems with, 158–160

resilience, 160–161

method-driven management and, 340

operational knowledge, 206–207

strategies for improving, 163, 181–182

unpredictability and, 59–60

workflow and, 336–337

Skillman, P., 183

skills, 184–185

SLAs (service-level agreements), 202, 203, 445

Snowden, D., 129, 131

snowflakes, 119–120, 121, 136

software

buggy, 271

customization, 279

development, overloading releases, 111–113

open source, 10

packaging, 234

SMARS, 266, 301

SolarWinds, Sunburst exploit, 128

solution bias, 34, 35

sort (‘seiri’), 262–266

specialists, 98

specialization, 98–99, 100–101, 102–104

Spectre, 8

speed

friction and, 40

service delivery, 9–10, 201

Spotify, 99

sprints, 214, 404–408

staff rides, 77, 78–79

standardization, 273–275, 281

all-in-one tools, 275–277

test, 185–187

start-ups

development awareness, 312–314

implementing 5S principles, 278–281

state columns, 352–355

strategic cycle, 421–423

review, 192–193, 424–425

A3 problem solving, 427–432

structure, 426–427

success, 24, 294–295

Sun Tzu, 25

sunk cost fallacy, 162

supply chain friction, bullwhip effect, 116–118

supportability, measuring, 235–239

swim lanes, 355–358

sync points, 400

synthetic transaction monitoring, 304

systemic impediments, 94–97

systems thinking, 80–81

T

tactical cycle, 400–402

daily standup, 408–411

kickoff, 403–408

Queue Master brief, 402–403

retrospective, 411–413

general meeting structure, 413–415

learning and improvement discussion, 415–421

tally boards, 359–360

target outcomes, 16, 17, 18, 30–33, 62–63, 67, 214, 293–294

Commander’s Intent and, 63–66

context and, 144

current state and, 188–189

governance and, 437–438

metrics, 36–39

Pony Test, 64–65

task(s), 371. See also kanban; workflow(s)

black holes, 346

cards, 358–359

Dark Matter, 340–342

identifiers, 311

structured approach, 183

switching, 105–106

team-based approach, 189

Taylor, F. W., The Principles of Scientific Management, 37

TCO (total cost of ownership), 146–147

TDD (test-driven development), 122

teaching to the test, 186–187

teams, 198, 199. See also Queue Master; Service Engineering Lead

dependencies, 313

eliminating fog, 219–220

gauging maturity of, 238–239

Legal and Compliance, 300–301

operational experience gap, 254–255

rotation of duties, 142, 240

seiketsu and, 274

separation of duties, 435–436, 439

Service Engineering Lead, 243–244, 253

awareness and, 246–248

duty rotation and, 244–246

organizational configurations and, 248–250

telecommunications, legacy voice products, 92–93

Terraform, 97

testing, instrumenting, 319–320

Three Mile Island, 159–160

tiger teams, 194

tight coupling, 96, 97, 102

tools, 24, 43, 44, 90, 95–96, 203, 207, 217, 221–222, 250, 251, 274. See also Cynefin

A3 problem solving, 427–432

all-in-one, 275–277

automation, 258–260, 268

Dark Matter and, 342

instrumenting, 316

off-the-shelf, 303–304, 305

out-of-the-box, 450–453

problem-solving, 193

seiketsu and, 274

Simian Army, 124

target outcome and, 16

Tools & Automation Engineering, 283–284

organizational details, 285

retrospective and, 435

workflow and sync points, 285–287

top-down

alignment, 397

leadership, 58

Toyota, 74, 83, 85, 87, 125–126

tracers, 172–173, 309

trading systems, 272–273

transparency, 121, 136, 207, 214, 243–244

governance and, 454–456

standardization and, 273–277

trust, 52, 73

decision-making and, 44

information flow and, 178–180

TWI (“Traning Within Industry”) program, 4, 84

U

unknown unknowns, 135

unordered systems, 134–135

chaotic contexts, 137–139

dictators, 139–141

firefighter arsonists, 141–142

complex contexts, 135–137

confusion, 143

observability and, 148

unpredictability, 56–57

continual improvement and, 75–77

ecosystem complexity and, 61

“fog of war,” 58

managing through, 58–59

misalignments and, 60–61

through knowledge and awareness weaknesses, 59–60

workload, 335

uptime, 65, 202, 207, 445

V

variability, 123

demand, 114–116

minimizing, 120–122

standardization and, 273–277

unmanaged, 116–118

visualizing, workflow, 349–351. See also kanban

W

“walking the gemba,” 307–309, 430–431

war-gaming, 78–79, 182

waste, 83, 84–85, 106–109

defects, 88–91

causes of, 89

in code, 89

spotting, 90–91

friction and, 85–86

handoffs, 101–103

mura (“irregularity”), 113–114

bullwhip effect, 116–118

minimizing, 120–122

snowflakes, 119–120

unexpected demand variability, 114–116

unmanaged variability, 118

Muri (“overburden”), 109–110

overproduction, 91–93

overspecialization, 97–101

partially done work, 103–104

process, 106–109

pure, 86–88

systemic impediments, 94–97

task switching, 105–106

waiting, 94–97

wastewater management ecosystem, instrumenting, 328–331

WIP (work in progress), 103–104, 365–367

Woolworths Australia, 17

work environment, 95

workflow(s). See also kanban

board, 362–363

flow and improvement, managing, 368

limits of, 367

managing, 367–368

simplifying, 360–362

state columns, 352–355

swim lanes, 355–358

task cards, 358–359

timestamping tasks, 364

WIP (work in progress), 365–367

work blockages, 364–365

Dark Matter and, 340–342

disconnects, 343–346, 347–349

managing organically, 339–340

out-of-the-box, 450–453

patterns, 381–382

processes and, 337–339

Queue Master role and, 380–381

situational awareness and, 336–337

visualizing, 349–351

World War II, 24, 79, 85, 176