By Bill CabirĂ³
It should be no surprise that data-driven decision making works better than relying on managers’ intuition.
It should be no surprise that data-driven decision making works better than relying on managers’ intuition.
Research clearly
shows that analytics oriented organizations outperform their peers but making
sense of the data becomes an increasingly challenging task as corporate data
continues to grow at a 40% yearly rate as a result of the rapidly declining
cost of computer memory.
An IBM CFO study shows that analytics-driven organizations had
33% more revenue growth, 12 times the earnings (before interest, tax,
depreciation, and amortization) and 32 percent more return on capital invested.
This is where Business Analytics (BA) becomes crucial in
providing data management, integration, multi-dimensional analysis, visual
discovery, data mining and statistical methods to improve productivity in
nearly every business function.
Business Analytics is an all-encompassing name for a new
discipline resulting from the integration of Business Intelligence and
Predictive Analytics. BA not only
includes the classic Business Intelligence functions of reporting what
happened, drill-down to how it happened, find out the cause of why it happened
and alert management as soon key metrics move in the wrong direction.
In addition, BA includes a highly sophisticated subject
called Predictive Analytics that can be defined as Advanced Computational
Statistics. It uses large cleansed
historical data sets to look forward.
Specifically, Predictive Analytics finds patterns in the data to
forecast what has a high probability to happen in the future.
BA application includes operational intelligence, strategic
and competitive analytics, customer acquisition and retention, risk management,
fraud detection and demand driven forecasting among others.
According to Tom Davenport, “Companies that invest heavily
in advanced analytical capabilities outperform the S&P 500 on average by 64%”.
Having a clear view of the profitable customers, products,
regions and market segments is fundamental to understand the causes and expand
upon the successes. Equally important is
to find those customers, brands, markets, segments and competitors responsible
for draining cash and quickly stop the bleeding.
In their book, “Competing on Analytics – The Science of Winning”, Thomas Davenport and Jeanne Harris define decision support, business
intelligence, data mining and predictive analytics and put all these concepts
well in perspective.
The book shows the five stages of analytical competency and
gives plenty of examples of companies that are successful in both the internal
and external implementation.
Stage 1: Analytically Impaired – Lack of analytical skill or
executive interest.
Stage 2: Localized Analytics – Uncoordinated activities or silos.
Stage 3: Analytical Aspirations – Good intentions with slow
progress.
Stage 4: Analytical Companies – Widely use analytics
internally.
Stage 5: Analytical Competitors – Use analytics as a
competitive advantage.
Business Analytics is a fundamental discipline to find the
root cause of issues and probable outcomes.
Taking prompt corrective actions tends to satisfy customers’ needs
faster and better than the competition providing the company a competitive
advantage regardless of how small the business is.
Up until now, BA has been the exclusive domain of large
companies that were able to afford the investment. Companies like Bank of America, Progressive
Insurance, Amazon, Google, Walmart, Capital One and Google were pioneers in
this area.
This is no longer the case.
Today, there are many choices of analytic applications, either on
premise or in the cloud, that are powerful, user friendly and very
inexpensive. Mainly designed for
business users, they include interactive data discovery, self-serve visual analytics and open source statistical
tools that require minimal IT involvement, making them ideal to transform small
companies into analytic competitors.
Regardless of the company size, the strategic use of
Business Intelligence and Predictive Analytics can have major impact on the
growth and profitability of the company.
Unfortunately, today many small companies are still unclear
about the value analytics can bring to their business. Others, while aware of
the value may not be fully prepared to effectively utilize it. So what steps can a small business take to
begin effectively using analytics?
A starting point would be to determine where your business
stands regarding the capability to use data and analytics. This can be done in
less than10 minutes using our free assessment tool for small businesses.
Based on your responses to several questions this tool will
grade your company’s capability level in the analytical landscape. After you finish the grader, you may want to
download the Suggested Action Plan Report to help you take the next step in
your company’s Business Analytics journey.