Part 1 of a
2 Part Series
by Phil Phillips, PhD
Contributing Editor
phillips@chemarkconsulting.net
It wasn’t too long ago that data was gathered, analyzed, conclusions drawn from them and ashboards were instrument panels in autos
and trucks. Today, and in the future, analytics
is a must and dashboards are the narrow end
of the data funnel where well organized data is
management-ready in nano seconds
As a business strategy firm, CHEMARK
over the years has promoted data accuracy as
it’s hallmark. Believing the foundation of highly
valuable strategic decisions must be grounded
in accurate data first then to transmit this base
accuracy into an effective strategy, that accu-
rate data must be interpreted correctly. Pretty
simple . . . right?
We remain steadfastly loyal to that philosophy... Accurate Data provides the basis for
accurate information which leverages accurate
knowledge which provides an opportunity for
strategic wisdom.
The process of assembling crucial data
through primary research, and the gathering of
accurate data requires the astute use of established market rapport techniques by associates
that are expert in focused markets, combined
with secondary research efforts to assure we
know what is being broadcast through channels
most anyone can access via electronic means.
Considered by itself... what is
analytics?
Analytics is the discovery, interpretation, and
communication of meaningful patterns in data.
Especially valuable in areas rich with recorded
information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify
performance. Analytics often favors data visualization to communicate insight.
Organizations may apply analytics to business data to describe, predict, and improve
business performance. Specifically, areas within
analytics include predictive analytics, prescriptive analytics, enterprise decision management,
retail analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix modeling, web analytics,
sales force sizing and optimization, price and
promotion modeling, predictive science, credit
risk analysis, and fraud analytics. Since analytics
can require extensive computation (see big data),
the algorithms and software used for analytics
harness the most current methods in computer
science, statistics, and mathematics.
SOURCE: Wikipedia
Analytics Segment Examples:
• Marketing Optimization
• Portfolio Analysis – Banks
• Risk Analytics – Banks/Insurance
• Digital Analytics – Business/Technical
• Security Analytics – IT
• Software Analytics
Analytics, Dashboards and Data
