Index
A
A/B testing, 16
Accenture, center of excellence model, 207
Acquah, Victor, 78
actions based on decisions, 98
activity, engagement versus, 72
advertising results assessment, web data for, 66-68
airline reservation proprietary data example, 40-41
Amadeus, 41
analyst sandbox, 129
analysts
business knowledge of, 182
centralized organizational model, 185-186
defined roles for, 183
maintaining skills of, 184
organizing, 157
CAO (Chief Analytics Officer), 173
coordination methods for analysts, 163-165
goals of organizational structure, 158-159
organizational models for, 160-162
refining organizational model, 169-172
variables to consider, 165-168
qualities of, Sears Holdings Corp. (SHC) case study, 235-237
analytical applications, 129
analytical ecosystem, building, 175-176
analytical intelligence, as analyst quality, 236
analytical orientation, analyst organization, 168
big-data analytics, 2-4, 16-17
business analytics
attributes of, 123
business unit-driven, 126
central coordination of apps, 132
complexity, 125
exclusively quantitative, 126
multipurpose capabilities, 124
nonbusiness-sector analytics versus, 15
Partners HealthCare System case study, 225-226
premises-and product-based, 125
separation from application environment, 123-124
single-purpose industry-specific apps, 130-131
staged data, 124
vendor integration, 133
vendor specialization, 127
business intelligence versus, 11-12
business solutions focus, 112-113
decisions and, 135
automated decision systems, 144-145
decision execution, 150
decision-making process, 146-150
future of decision management, 150-151
information and analytics provision, 147-148
in organizational strategy, 146-147
structured human decisions, 141-144
descriptive analytics, 12-13, 249-254
embedded analytics, 129, 171, 245-246
enterprise analytics, defined, 2
global capability for, 203
center of excellence model, 206-207
centralized coordination, 205-206
coordination methods, 205
governance of, 187
descriptive versus predictive analytics, 198
relationships with other governance bodies, 200
stakeholders and decision rights, 196-197
predictive analytics, 13
actions based on decisions, 98
cooperation between business and IT departments, 100
data issues, 101
timely model deployment, 99-100
ROI (return on investment), 19
audiences for, 28
cash flow and, 21
complexity of business environment, 23-24
Freescale Semiconductor example, 28-33
traditional ROI calculations, 19-24
web analytics, 16
assigned customers, analyst coordination, 164
AT&T Labs, 184
attrition modeling, web data for, 62-63
audiences for ROI (return on investment), 28
automated decision systems, 97, 144-145. See also production scale analytics
actions based on, 98
decision design, 149
B
Banco Santander, global capability for analytics, 204
Bernard Chaus, Inc. case study, 249-250
business unit and IT collaboration, 253-254
supply chain visibility, 249-253
“best home” model for analyst organization, 161
BI. See business intelligence
big data
proprietary data as, 38
advertising results assessment, 66-68
missing elements of, 50
as new information source, 51-52
purchase paths and preferences, 56-57
360-degree view of customer data, 48-50
Blumenthal, David, 218
Brigham & Women’s Hospital analytics, Partners HealthCare System case study, 229-231 Brownstein, John, 224
Bucnis, Rebecca, 47
business analytics
attributes of, 123
business unit-driven, 126
complexity, 125
exclusively quantitative, 126
multipurpose capabilities, 124
premises-and product-based, 125
separation from application environment, 123-124
staged data, 124
vendor specialization, 127
central coordination of apps, 132
single-purpose industry-specific apps, 130-131
vendor integration, 133
nonbusiness-sector analytics versus, 15
Partners HealthCare System case study, 225-226
business decisions
in cloud-based predictive analytics, 112-113
in production scale analytics, 100
business environment complexity, effect on ROI calculations, 23-24
business group (ROI audience), 28
business intelligence, 9
as analyst quality, 236
defined, 11
business knowledge of analysts, 182
business structure, analyst organization, 166-167
business unit and IT collaboration, Bernard Chaus, Inc. case study, 253-254
business value assessment. See ROI (return on investment)
business value, Commercial Analytics and Decision Sciences group (Merck) case study, 243-245
C
calculations. See measuring engagement; metrics; ROI (return on investment)
CAO (Chief Analytics Officer), 173 case studies
Bernard Chaus, Inc. case study, 249-250
business unit and IT collaboration, 253-254
supply chain visibility, 249-253
Commercial Analytics and Decision Sciences group (Merck) case study, 241-242
decision-making partnerships, 242-243
Partners HealthCare System, 215
analytical challenges, 223-225
Brigham & Women’s Hospital analytics, 229-231
HPM (High-Performance Medicine) initiative, 220-223
Massachusetts General Hospital analytics, 226-229
Sears Holdings Corp. (SHC) case study, 233
analysts, qualities of, 235-237
projects, components of, 237-238
cash flow, ROI and, 21
center of excellence model
for analyst organization, 162
for global analytical capabilities, 206-207
centralization
of analysts, 157-158, 161, 185-186
of global analytical capabilities, 205-206
Partners HealthCare System case study, 215-218
Chief Analytics Officer (CAO), 173
churn models, 62
cloud-based predictive analytics, 111-112
business solutions focus, 112-113
Commercial Analytics and Decision Sciences group (Merck) case study, 241-242
decision-making partnerships, 242-243
community, analyst coordination, 164
Competing on Analytics, 9, 179, 190
complexity
of business analytics, 125
of business environment, effect on ROI calculations, 23-24
compliance issues in production scale analytics, 100-101
consolidation of analysts, 168-169
consulting model for analyst organization, 161 consumer payment data example (proprietary data), 42-45
data ownership, 45
enhanced customer services, 44-45
macroeconomic intelligence, 42-43
contextual information needed for next best offers, 88-90
conversion, engagement versus, 71-72
coordination methods
for global analytical capabilities, 205
center of excellence model, 206-207
centralized coordination, 205-206
cost of capital, 21
credible ROI (return on investment), 21-22
customer data. See also web data
decision-making behavior, 51-52
differentiation among customers, 64-65
needed for next best offers, 87
customer engagement. See engagement
customer satisfaction, engagement versus, 72
customer segmentation
customer services, enhancing from consumer payment data, 44-45
CVM (customer value management), 209-210
D
data cloud, modeling with, 115-116
data issues in production scale analytics, 101
data mining
defined, 14
data ownership, consumer payment data example (proprietary data), 45
data scientists, defined, 179
Davenport, Tom, 179
decentralized model
for analyst organization, 162
for global analytical capabilities, 207-210
decision execution, 150
decision management systems, 97. See also production scale analytics
actions based on, 98
increased analytic value of, 117
decision rights in analytics governance, 196-197
decision support systems, 9
decision-centered analytics, 171
decision-making behavior
in analytics governance, 197
Commercial Analytics and Decision Sciences group (Merck) case study, 242-243
decisions, analytics and, 135
automated decision systems, 144-145
decision execution, 150
decision-making process, 146-150
future of decision management, 150-151
information and analytics provision, 147-148
in organizational strategy, 146-147
structured human decisions, 141-144
defined roles for analysts, 183
Deloitte, center of excellence model, 207
deployment patterns for cloud-based predictive analytics, 113-116
Bernard Chaus, Inc. case study, 249-250
business unit and IT collaboration, 253-254
supply chain visibility, 249-253
governance of, 198
designing decision-making process, 148-149
differentiation among customers, 64-65
Dykes, Brent, 16
E
early adopters of cloud-based predictive analytics, 117
elastic compute power for modeling, 116
embedded analytics, 129, 171, 245-246
activity versus, 72
business knowledge of, 182
centralized organizational model, 185-186
defined roles for, 183
maintaining skills of, 184
customer satisfaction versus, 72
customer segmentation by, 76-77
enhanced customer services from consumer payment data, 44-45
enterprise analytics, defined, 2. See also analytics
enterprise commitment, analyst organization, 168
evaluating investments. See ROI (return on investment)
execution of next best offers, 90-92
executive information systems, 9
experts, defined, 180
F
faceless customer analysis, 53-54
federation, analyst coordination, 164
feedback behaviors, collecting in web data, 59-60
finance, analyst reporting structure, 175
finance group (ROI audience), 28
five-stage maturity model, 169-170, 190
Franks, Bill, 17
Freescale Semiconductor example (analytics ROI), 28-33
frequency value metrics, 49
functional model for analyst organization, 161
function-specific analytics, 171
funding sources, analyst organization, 167
future
of Commercial Analytics and Decision Sciences (Merck) case study, 246-247
of decision management, 150-151
G
geographic variation in global analytical capability, 203-205
Glaser, John, 216, 220-221, 223, 224, 230
global capability for analytics, 203
coordination methods, 205
center of excellence model, 206-207
centralized coordination, 205-206
governance of analytics, 187
descriptive versus predictive analytics, 198
relationships with other governance bodies, 200
stakeholders and decision rights, 196-197
Griffin, Jane, 119
Gustafson, Michael, 229
H
H&M, customer location information, 87
High-Performance Medicine (HPM) initiative, Partners HealthCare System case study, 220-223
home location, analyst organization, 165-166
Hongsermeier, Tonya, 219-220, 224
hospital case study. See Partners HealthCare System case study
HPM (High-Performance Medicine) initiative, Partners HealthCare System case study, 220-223
HR functions case study. See Sears Holdings Corp. (SHC) case study
HR intelligence, as analyst quality, 236
I
IATA (International Air Transport Authority), 40-41
IIA (International Institute for Analytics), 4-5
indices, measuring engagement, 74-75
industry-specific analytics, 130-131, 171
information. See analytics
information and analytics provision in decision-making process, 147-148
information technology (IT), analyst reporting structure, 174
infrastructure, analyst organization, 167
internal rate of return (IRR), 22
International Air Transport Authority (IATA), 40-41
International Institute for Analytics (IIA), 4-5
IRR (internal rate of return), 22
issue management, in analytics governance, 199
IT and business unit collaboration, Bernard Chaus, Inc. case study, 253-254
IT group (ROI audience), 28
K
Al-Kindi, 10
knowledge management, Partners HealthCare System case study, 218-220, 223-225
Krebs, Valdis, 111
Kvedar, Joe, 224
L
leadership roles in analytics, 173
legacy systems, predictive analytics for, 114-115
linking decisions and analytics, 138-145
automated decision systems, 144-145
decision execution, 150
future of decision management, 150-151
information and analytics provision, 147-148
in organizational strategy, 146-147
structured human decisions, 141-144
location information. See SoMoLo data (social, mobile, location)
loosely coupled analytics and decisions, 138-141
M
macroeconomic intelligence from consumer payment data, 42-43
market for cloud-based predictive analytics, 116-118
analyst reporting structure, 175
targeted marketing from consumer payment data, 43-44
Massachusetts General Hospital analytics, Partners HealthCare System case study, 226-229
matrix, analyst coordination, 164
McDonald, Bob, 206
Merck case study. See Commercial Analytics and Decision Sciences group (Merck) case study
ROI. See ROI (return on investment) types of, 22
MGH (Massachusetts General Hospital) analytics, Partners HealthCare System case study, 226-229
Microsoft, offer strategy design, 86
Middleton, Blackford, 218, 224
mobile information. See SoMoLo data (social, mobile, location)
modeling
elastic compute power for, 116
statistical modeling, 13
monetary value metrics, 49
Morey, Daryl, 38
Morison, Bob, 179
N
NBOs. See next best offers
net present value (NPV), 22
Netflix, 184
new product development, proprietary data and, 37-38
customer data needed, 87
purchase context information, 88-90
nonbusiness-sector analytics, business analytics versus, 15
nonstandard data analytics, 171
NPV (net present value), 22
O
OLAP (online analytical processing), 9
online engagement. See engagement
optimization, 14
organizational goals for analytics, 159-160
organizational strategy, decisions and analytics in, 146-147
organizational structure, goals of, 158-159
organizing analysts, 157
CAO (Chief Analytics Officer), 173
coordination methods for analysts, 163-165
goals of organizational structure, 158-159
organizational models for, 160-162
refining organizational model, 169-172
variables to consider, 165-168
ownership of data, consumer payment data example (proprietary data), 45
P
P&G, centralized coordination of global analytics, 205-206
Partners HealthCare System case study, 215
analytical challenges, 223-225
Brigham & Women’s Hospital analytics, 229-231
HPM (High-Performance Medicine) initiative, 220-223
Massachusetts General Hospital analytics, 226-229
PaxIS example (proprietary data), 40-41
payback, 22
payment data example (proprietary data), 42-45
data ownership, 45
enhanced customer services, 44-45
macroeconomic intelligence, 42-43
PBS example (engagement), 77-79
performance management, in analytics governance, 199
permissions, consumer payment data example (proprietary data), 45
personalized offers. See next best offers
Philly.com example (engagement), 79-81
pooled data, in cloud-based predictive analytics, 118
predictive analytics, 13
business solutions focus, 112-113
governance of, 198
actions based on decisions, 98
cooperation between business and IT departments, 100
data issues, 101
timely model deployment, 99-100
preferences, collecting in web data, 56-57
prescriptive analytics, 13-14, 16
principles for analytics governance, 188-189
prioritization, Sears Holdings Corp. (SHC) case study, 233-235
privacy
of proprietary data, 40
process-specific analytics, 171
product data needed for next best offers, 87-88
production scale analytics, 97-98
actions based on decisions, 98
cooperation between business and IT departments, 100 data issues, 101
timely model deployment, 99-100
program management office, 164
projects, components of (Sears Holdings Corp. (SHC) case study), 237-238
propensity modeling, web data for, 63-65
proprietary data
consumer payment data example, 42-45
data ownership, 45
enhanced customer services, 44-45
macroeconomic intelligence, 42-43
privacy of, 40
purchase context, needed for next best offers, 88-90
purchase paths and preferences, collecting in web data, 56-57
Q
Qdoba Mexican Grill, execution of next best offers, 91
R
real-time data, in cloud-based predictive analytics, 118
recency value metrics, 49
Redbox, offer strategy design, 86
reporting structure, analyst organization, 166, 174-175
research behaviors, collecting in web data, 57-59
response modeling, web data for, 63-65
return on investment. See ROI (return on investment)
Rocha, Roberto, 224
ROI (return on investment), 19
audiences for, 28
cash flow and, 21
complexity of business environment, 23-24
Freescale Semiconductor example, 28-33
traditional ROI calculations, 19-24
rotation, analyst coordination, 164
S
SaaS (software as a service), predictive analytics for, 114
salespeople, offer delivery, 91
scientists, defined, 179
Sears Holdings Corp. (SHC) case study, 233
analysts, qualities of, 235-237
projects, components of, 237-238
segmentation of customers
Sense Networks, location information, 89-90
shared services, analyst reporting structure, 175
SHC (Sears Holdings Corp.) case study. See Sears Holdings Corp. (SHC) case study
Sheppard, Colin, 182
shopping behaviors, collecting in web data, 55-56
single-purpose industry-specific apps, 130-131
skill development for analysts, 184
social media information. See SoMoLo data (social, mobile, location)
software as a service (SaaS), predictive analytics for, 114
SoMoLo data (social, mobile, location), 87, 89
Sony, purchase context information, 89
sponsors, defined, 179
sports, proprietary data in, 38
staged data for business analytics, 124
stakeholders in analytics governance, 196-197
Starbucks, execution of next best offers, 91
state of market, for cloud-based predictive analytics, 116-118
statistical modeling, 13
Stone, John, 226
strategic planning in analytics governance, 199
strategy design for next best offers, 85-87
strategy group, analyst reporting structure, 174
strategy of organization, decisions and analytics in, 146-147
structured data, in cloud-based predictive analytics, 118
structured human decision environments, 141-144
supply chain visibility, Bernard Chaus, Inc. case study, 249-253
systems intelligence, as analyst quality, 236
T
target setting, in analytics governance, 199
targeted marketing from consumer payment data, 43-44. See also next best offers
Teradata method (for ROI), 24-27
coordination of analytics, 205
global capability for analytics, 203-204
offer strategy design, 86
product data information, 88
360-degree view of customer data, 47-48
Ting, David Y., 227
traditional analytics, 171
traditional ROI calculations, 19-24
transactional history metrics, 49-50
U
unstructured data, analysis of, 17. See also big-data analytics
users, defined, 180
V
vendor integration, 133
visitor engagement. See engagement
Volinsky, Chris, 184
W
web analytics, 16. See also engagement
missing elements of, 50
as new information source, 51-52
360-degree view of customer data, 47-48
usage examples
advertising results assessment, 66-68
purchase paths and preferences, 56-57
Whittemore, Andy, 230
work location, analyst organization, 166