Glossary Flashcards
5S
workplace organization method promoting efficiency
and effectiveness; five terms based on Japanese
words for: sorting, set in order, systematic cleaning,
standardizing, and sustaining
5 Whys
iterative process of discovery through repetitively asking
‘why’; used to explore cause and effect relationships
underlying and/or leading to problem
80/20 Rule
AKA the Pareto principle: roughly 80% of results come
from 20% of effort
Accuracy
quality or state of being correct or precise, or the degree
to which the result of a measurement, calculation, or
specification conforms to the correct value or standard
Activity-based costing
method of assigning costs to products or services on
the resources that they consume
Agent-based modeling
a class of computation models for simulating actions and interactions of autonomous agents with a view to assessing their effects on the system as a whole
Algorithm
set of specific steps to solve a problem
Amortization
allocation of cost of an item or items over a time period
such that the actual cost is recovered; often used to
account for capital expenditures
Analytics
scientific process of transforming data into insight for
making better decisions
Analytics professional
person capable of making actionable decisions through
the analytic process; also a person holding the Certified
Analytics Professional (CAP®) credential
ANCOVA
Analysis of Covariance
ANOVA
Analysis of Variance
Artificial Intelligence
branch of computer science that studies and develops
intelligent machines and software
Artificial Neural
Networks
computer-based models inspired by animal central
nervous systems
Assemble-to-Order
manufacturing process where products are assembled as
they are ordered; characterized by rapid production and
customization
Assignment problem
one of the fundamental combinatorial optimization problems in the branch of optimization or operations research in mathematics;
Used to understand optimal way to assign n resources to n tasks in the most efficient way possible;
Consists of finding a maximum-
weight matching in a weighted bipartite graph
http://www.math.harvard.edu/archive/20_spring_05/handouts/assignment_overheads.pdf
Automation
use of mechanical means to perform work previously
done by human effort
Average
sum of a range of values divided by the number of
values to arrive at a value characteristic of the midpoint
of the range; see also, Mean
Batch production
method of production where components are produced
in groups rather than a continual stream of production;
see also, Continuous production
Benchmarking
act of comparison against a standard or the behavior of
another in attempt to determine degree of conformity to standard or behaviour
Benchmark problems
comparison of different algorithms using a large test set
Bias
a tendency for or against a thing, person, or group in
a way as to appear unfair; in statistics, data calculated
so that it is systematically different from the population
parameter of interest
Big data
data sets too voluminous or too unstructured to be analyzed by traditional means
Box-and-whisker plot
a simple way of representing statistical data on a plot
in which a rectangle is drawn to represent the second
and third quartiles, usually with a vertical line inside
to indicate the median value. The lower and upper
quartiles are shown as horizontal lines either side of the
rectangle
Branch-and-Bound
a general algorithm for finding optimal solutions of
various optimization problems; consists of a system
enumeration of all candidate solutions where large
subsets of fruitless candidates are discarded en masse
using upper and lower estimated bounds of the quantity
being optimized
Business analytics
refers to the skills, technologies, applications, and
practices for continuous iterative exploration and
investigation of past business performance to gain
insight and drive business planning; can be descriptive,
prescriptive, or predictive; focuses on developing new
insights and understanding of business performance
based on data and statistical methods
Business case
reasoning underlying and supporting the estimates of
business consequences of an action
Business intelligence
a set of methodologies, processes, architectures, and
technologies that transform raw data into meaningful
and useful information
Business Process
Modeling or Mapping
(BPM)
act of representing processes of an enterprise so that the
current process may be analyzed and improved; typically
action performed by business analysis and managers
seeking improved efficiency and quality
Chief Analytics Officer
CAO
possible title of one overseeing analytics for a company;
may include mobilizing data, people, and systems
for successful deployment, working with others to
inject analytics into company strategy and decisions,
supervising activities of analytical people, consulting
with internal business functions and units so they may
take advantage of analytics, contracting with external
providers of analytics
Chi-squared
Automated
Interaction
Detection (CHAID)
a technique for performing decision tree analysis
developed by Gordon V. Kass. CHAID is one of several
commonly used techniques for decision trees and
is based upon hypothesis testing using Bonferroni
correction
Classification
assortment of items or entities into predetermined
categories
Cleansing
AKA cleaning or scrubbing: the process of detecting and
correcting (or removing) corrupt or inaccurate records
from a record set, table, or database; may also involve
harmonization of data, and standardization of data
Clustering
grouping of a set of objects in such a way that objects
in the same group (cluster) are more similar to each
other than to those in other groups or clusters
Combinatorial
optimization
a topic that consists of finding an optimal object from a
finite series of objects; used in applied mathematics and
theoretical computer science
Confidence interval
a type of interval estimate of a population parameter
used to indicate the reliability of an estimate. It is
an observed interval (i.e., it is calculated from the
observations), in principle different from sample
to sample, that frequently includes the parameter
of interest if the experiment is repeated
Confidence level
if confidence intervals are constructed across many
separate data analyses of repeated (and possibly
different) experiments, the proportion of such intervals
that contain the true value of the parameter will match
the confidence level
Conjoint analysis
allows calculation of relative importance of varying
features and attributes to customers
Constraint
a condition that a solution to an optimization problem
is required by the problem itself to satisfy. There
are several types of constraints—primarily equality
constraints, inequality constraints, and integer
constraints
Constraint Programming
a programming paradigm wherein relations between
variables are stated in the form of constraints
Continuous Production
method of production where components are produced
in a continuous stream
Correlation
a broad class of statistical relationships involving dependence
Cost of capital
the cost of funds used for financing a business. Cost
of capital depends on the mode of financing used—it
refers to the cost of equity if the business is financed
solely through equity, or to the cost of debt if it is
financed solely through debt
Cumulative density
function
probability that a real-valued random variable X with a
given probability distribution will be found at a value
less than or equal to x; used to specify the distribution of
multivariate random variables
Cutting stock
problem
optimization or integer linear programming problem
arising from applications in industry where high
production problems exist
Data
(plural form of datum) values of qualitative or
quantitative variables, belonging to a set of items;
represented in a structure, often tabular (represented
by rows and columns), a tree (a set of nodes with
parent-children relationship), or a graph structure (a
set of interconnected nodes); typically the results of
measurements
Data mining
relatively young and interdisciplinary field of computer
science; the process of discovering new patterns from
large data sets involving methods at the intersection of
artificial intelligence, machine learning, statistics, and
database systems; see also, KDD
Data warehouse
a central repository of data that is created by integrating
data from one or more disparate sources; used for
reporting and data analysis
Database
an organized collection of data organized to model
relevant aspects of reality to support processes requiring
this information
Decision tree
graphic illustration of how data leads to decision when
branches of the tree are followed to their conclusion;
different branches may lead to different decisions
Decision variables
a decision variable represents a problem entity for
which a choice must be made. For instance, a decision
variable might represent the position of a queen on a
chessboard, for which there are 100 different possibilities
(choices) on a 10x10 chessboard or the start time of an
activity in a scheduling problem. Each possible choice
is represented by a value, hence the set of possible
choices constitutes the domain that is associated with a
variable
Descriptive analytics
prepares and analyzes historical data to identify
patterns for reporting trends
Design of
experiments
design of any information gathering exercise where
variation is present, whether under the control of the
experimenter or not; see also, Experimental design
Discrete event
simulation
models the operation of a system as a discrete sequence
of events in time; between events, no change in the
system is assumed thus a simulation can move in time
from one event to the next
Dynamic
programming
based on the Principle of Optimality, this was originally
concerned with optimal decisions over time. For
continuous time, it addresses problems in variational
calculus. For discrete time, each period is sometimes
called a stage, and the DP is called a multistage decision
process. Here is the Fundamental Recurrence Equation
for an additive process:
F(t, s) = Opt{r(t, s, x) + aF(t’, s’): x in X(t, s) and s’=T(t,
s, x)},
Effective domain
the domain of a function for which its value is finite
Efficiency
the comparison of what is actually produced or
performed with what can be achieved with the same
consumption of resources (money, time, labor, etc.). It
is an important factor in determination of productivity
Engagement
an estimate of the depth of visitor interaction against a
clearly defined set of goals; may be measured through
analytical models
Enterprise resource
planning (ERP)
a cross-functional enterprise system driven by an
integrated suite of software modules that supports the
basic internal business processes of a company
ETL (extract,
transform, load)
refers to three separate functions combined into a single
programming tool. First, the extract function reads data
from a specified source database and extracts a desired
subset of data. Next, the transform function works with
the acquired data—using rules or lookup tables, or
creating combinations with other data—to convert it to
the desired state. Finally, the load function is used to
write the resulting data (either all of the subset or just
the changes) to a target database, which may or may
not previously exist
Experimental design
in quality management, a written plan that describes the
specifics for conducting an experiment, such as which
conditions, factors, responses, tools, and treatments are
to be included or used; see also, Design of experiments
Expert systems
a computer program that simulates the judgment and
behavior of a human or an organization that has expert
knowledge and experience in a particular field. Typically,
such a system contains a knowledge base containing
accumulated experience and a set of rules for applying
the knowledge base to each particular situation that is
described to the program
Factor analysis
a statistical method used to describe variability among
observed, correlated variables in terms of a potentially
lower number of unobserved variables called factors.
Factor analysis searches for such joint variations in
response to unobserved latent variables
Failure Mode and
Effects Analysis
(FMEA)
a systematic, proactive method for evaluating a
process to identify where and how it might fail, and
to assess the relative impact of different failures to
identify the parts of the process that are most in need
of change
Fixed cost
a cost that is some value, say C, regardless of the level as
long as the level is positive; otherwise the fixed charge
is zero. This is represented by Cv, where v is a binary
variable. When v = 0, the fixed charge is 0; when v = 1,
the fixed charge is C. An example is whether to open
a plant (v = 1) or not (v = 0). To apply this fixed charge
to the non-negative variable x, the constraint x <= Mv
is added to the mathematical program, where M is a
very large value, known to exceed any feasible value
of x. Then, if v = 0 (e.g., not opening the plant that is
needed for x > 0), x = 0 is forced by the upper bound
constraint. If v = 1 (e.g., plant is open), x <= Mv is a
redundant upper bound. Fixed charge problems are
mathematical programs with fixed charges
