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4 How can big data augment or even
replace management?
Big data expands the operational space for
algorithms and machine-mediated analysis. At some
manufacturers, for example, algorithms analyze
sensor data from production lines, creating self-
regulating processes that cut waste, avoid costly
(and sometimes dangerous) human interventions,
and ultimately lift output. In advanced, digital oil
felds, instruments constantly read data on wellhead
conditions, pipelines, and mechanical systems. That
information is analyzed by clusters of computers,
which feed their results to real-time operations
centers that adjust oil fows to optimize production
and minimize downtimes. One major oil company has
cut operating and stafng costs by 10 to 25 percent
while increasing production by 5 percent.
Products ranging from copiers to jet engines can
now generate data streams that track their usage.
Manufacturers can analyze the incoming data and, in
some cases, automatically remedy software glitches
or dispatch service representatives for repairs. Some
enterprise computer hardware vendors are gathering
and analyzing such data to schedule pre-emptive
repairs before failures disrupt customers’ operations.
The data can also be used to implement product
changes that prevent future problems or to provide
customer use inputs that inform next generation
oferings.
Some retailers are also at the forefront of using
automated big data analysis: they use “sentiment
analysis” techniques to mine the huge streams of data
now generated by consumers using various types
of social media, gauge responses to new marketing
campaigns in real time, and adjust strategies
accordingly. Sometimes these methods cut weeks
from the normal feedback and modifcation cycle.
But retailers aren’t alone. One global beverage
company integrates daily weather forecast data from
an outside partner into its demand and inventory-
planning processes. By analyzing three data points—
temperatures, rainfall levels, and the number of
hours of sunshine on a given day—the company cut
its inventory levels while improving its forecasting
accuracy by about 5 percent in a key European
market.
The bottom line is improved performance, better
risk management, and the ability to unearth insights
that would otherwise remain hidden. As the price
of sensors, communications devices, and analytic
software continues to fall, more and more companies
will be joining this managerial revolution.
5 Could you create a new business model
based on data?
Big data is spawning new categories of companies
that embrace information-driven business models.
Many of these businesses play intermediary roles in
value chains where they fnd themselves generating
valuable “exhaust data” produced by business
transactions. One transport company, for example,
recognized that in the course of doing business, it
was collecting vast amounts of information on global
product shipments. Sensing opportunity, it created
a unit that sells the data to supplement business and
economic forecasts.
Another global company learned so much from
analyzing its own data as part of a manufacturing
turnaround that it decided to create a business to
do similar work for other frms. Now the company
aggregates shop foor and supply chain data for
a number of manufacturing customers and sells
software tools to improve their performance. This
service business now outperforms the company’s
manufacturing one.
Big data also is turbocharging the ranks of data
aggregators, which combine and analyze information
from multiple sources to generate insights for clients.
In health care, for example, a number of new entrants
are integrating clinical, payment, public-health, and
behavioural data to develop more robust illness
profles that help clients manage costs and improve
treatments.
And with pricing data proliferating on the Web
and elsewhere, entrepreneurs are ofering price
comparison services that automatically compile
information across millions of products. Such
comparisons can be a disruptive force from a retailer’s
perspective but have created substantial value for
consumers. Studies show that those who use the
services save an average of 10 percent—a sizable shift
in value.
From: http://www.mckinseyquarterly.com