What Is Descriptive
Analytics?
Descriptive analytics is the translation of
historical data to higher understand modifications that
have occurred in commercial enterprise. Descriptive
analytics describes the use of more
than a few historic statistics to attract comparisons.
Most typically reported economic metrics are a made from descriptive
analytics—for example, 12 months-over-12 months pricing changes, month-over-month sales growth, the range of
users, or the full revenue per subscriber. These measures
all describe what has passed off in
a business during a set period.
Understanding Descriptive
Analytics
Descriptive analytics takes raw records and parses that information to attract conclusions that are beneficial and comprehensible by means of managers, investors,
and different stakeholders.
A file showing sales of $1 million may also sound impressive, but it lacks context. If
that discern represents
a 20% month-over-month decline, it's
miles a concern. If it's
miles a 40% year-over-year increase, then it suggests some thing is going right with the income strategy.
However, the larger context together with targeted increase is needed to achieve an knowledgeable view of the company's income overall
performance.
Descriptive analytics makes use of a
full range of data to give an correct photograph of what has took place in a enterprise and the way that differs
from different comparable periods. These overall performance metrics may be used to flag regions of strength and weakness to tell management strategies.
Descriptive analytics is one of the maximum basic portions of business intelligence a enterprise will use. Although
descriptive analytics can be industry-specific—such as the seasonal variant in shipment crowning glory times—analytics
use broadly everyday measures commonplace during the finance industry.
Return on invested capital (ROIC) is a descriptive-analytic created via taking three records points—net income,
dividends, and general capital—and
turning those data factors into an easy-to-apprehend percentage that may
be used to examine one employer’s overall performance to others.
Generally speaking, the larger and more complicated a corporation is,
the greater descriptive
analytics it'll use
to measure its performance.
KEY TAKEAWAYS
Descriptive analytics is the system of
parsing historical facts to higher recognize the changes that
have happened in commercial enterprise.
Using a variety of historic statistics and benchmarking,
decision-makers reap a
holistic view of overall
performance and tendencies on
which to base business strategy.
Descriptive analytics can help to discover the regions of strength and weak spot in an organization.
Special Considerations
Descriptive analytics offers important information in an easy-to-draw close format. There
will constantly be
a want for descriptive
analytics. However, more effort is going toward newer fields of analytics along with predictive and prescriptive analytics.
These forms of analytics
use descriptive analytics and integrate additional statistics from numerous sources to model probably results inside the close to term.
These forward-searching analytics
go beyond informing
decision-making. These kinds of analytics can also suggest publications of action that could maximize nice results and decrease negative ones.
That said, we aren't quite but at the factor in which benevolent and
prescient computers will
helm all essential corporations.
The majority of choices in offices and boardrooms global are made by using people the use of the same types of descriptive analytics
used 10, 20, and 30 years ago, including whether income were up or down compared to last month, is the product
getting to marketplace on
time, and does the organisation have sufficient supply primarily based on final month’s numbers.
Diagnostic Analytics
This is about looking into the past and determining why a
certain thing happened. This type of analytics usually revolves around working
on a dashboard. Diagnostic Analytics with Big Data helps in two ways:
(a) the additional data brought by the digital age
eliminates analytic blind spots, and
(b) the how and why questions deliver insights that pinpoint the actions need
to be taken.
What Are The
Benefits of Diagnostic Analytics?
Diagnostic analytics lets you understand your data faster to
answer critical workforce questions. Cornerstone View provides the fastest and
simplest way for organizations to gain more meaningful insight into their
employees and solve complex workforce issues. Interactive data visualization
tools allow managers to easily search, filter and compare people by
centralizing information from across the Cornerstone unified talent management
suite. For example, users can find the right candidate to fill a position,
select high potential employees for succession, and quickly compare succession
metrics and performance reviews across select employees to reveal meaningful
insights about talent pools. Filters also allow for a snapshot of employees
across multiple categories such as location, division, performance and tenure.