Companies Love Big Data but Lack the Strategy to Use
It Effectively
Big data is a critical competitive
advantage for companies that know how to use it. Harvard Business School
faculty share insights that they teach to executives.
Big data has shifted the ground under every business, enough so
that many managers are waking up to the fact that they are already behind in
developing a smart data strategy.
Data has always been important in business, of course. But with
the arrival of digital data—its volume, depth, and accessibility—it has become
clear it is key to helping companies develop sustainable competitive advantage.
“The new attention being given to data today is because
suddenly, everywhere, it’s become much cheaper to measure,” says John A.
Deighton, the Baker Foundation Professor of Business Administration at Harvard
Business School. “Used well, it changes the basis of competition in industry
after industry.”
The problem is that, in many cases, big data is not used well.
Companies are better at collecting data–about their customers, about their
products, about competitors– than analyzing that data and designing strategy around
it.
That’s
one reason eight HBS professors pooled resources in June to launch the Competing on Business Analytics and Big Data Executive Education
program. “It was unprecedented to engage eight faculty in a single program,”
says Deighton, “and it reflects the fact that data questions touch every part
of the enterprise.”
The
program drew C-suite executives and senior managers to look at how big data affects the supply chain, marketing, human resources,
and other key business functions. Attendees studied
how market-leading companies are harnessing data to reshape their companies,
and explored how they can put data to work for them in ways that create value
for their own businesses.
The data advantage in sports
Big data is already being used heavily in the sports world,
students heard from Karim Lakhani, co-chair of the program and part of the
Technology and Operations Management Unit. He discussed with students how
German soccer team TSG Hoffenheim deploys analytics in scouting and player
development. He also noted how New Zealand’s yacht designers and crew prepared
for the 1995 Americas Cup with a radical, data-intensive experimental design.
Deighton discussed how new sources of data starting to be generated
by the Internet of Things will impact the advertising-based hegemony of Google,
Amazon, and Facebook. “The best picture we have today of an industry running on
data is seen in advertising, where at least a third of all spending by brands
goes to digital media. What happens when products with sensors generate such
volumes of customer experience data that advertising may be a less significant
factor?”
Jeff Polzer, of the Organizational Behavior faculty, introduced
“people analytics,” the fast-growing field in which business managers, HR
specialists, and data scientists work together to use data to improve
employee-related decisions and practices. New analytic approaches and new
sources of digital data are starting to revolutionize this field, he said, such
as algorithmic approaches to hiring and promotion; real-time data streams that
track performance feedback and organizational culture; and analyses of digital
trace data to map and shape organizational networks.
“As managers and employees work through these challenges and
tradeoffs, the potential gains they can accrue from using data, including
benefits to employees who strive for feedback and self-improvement, mean that
day-to-day managerial life will increasingly be infused with employee-related
analytics,” says Polzer.
Turning to how data is analyzed, Dennis Campbell, of the
Accounting and Management Unit, discussed the data strategy of the MGM Grand
hotel in Las Vegas, and challenges to distinguishing between correlation and
causation in inferences drawn from large data sets.
Ariel Dora Stern, of the Technology and Operations Management
Unit, challenged the class to think about what couldn’t have been done without
recent advances in data. She took the class toward her personal passion,
precision medicine.
“Health care is rife with examples like these—and such
applications of big data will only expand over the coming years. I spend a lot
of time thinking about questions like, How will artificial intelligence change
the medical diagnostics industry? How will better data collection transform the
ways in which we do clinical trials for new cancer drugs? It is both staggering
and exciting to imagine how data and analytic capabilities will transform
entire industries and it was thrilling to engage in these conversations with
folks from such rich and diverse backgrounds.”
Kris Ferreira, also a Technology and Operations Management Unit
professor, sketched her approach to operationalizing a data strategy using
discussions around case studies.
“First, students learned a framework for combining intuition and
data/analytics (including regression and optimization) into a comprehensive
decision-making strategy. Second, students developed an implementation plan to
transform an intuition-based company into one that relied more heavily on data
and analytics; this included discovering important barriers to change that
require a broader understanding of the organizational culture and incentives.”
Ferreira also shared results of a survey of about 350 companies
in four industries about their analytics capabilities. “Results show strong
correlations between business performance metrics and analytics capabilities,
and highlight a variety of tasks in which top performing companies use
analytics…”
Feng Zhu, who teaches Digital Innovation
and Transformation, illustrated how big data is making new business models
possible. “Most organizations today use data analytics to optimize or improve
their existing businesses. But to take full advantage of data analytics, it
will be important for them to consider the following two strategic questions:
1) Can I use my data to offer new products or services to my existing
customers? 2) Can I leverage data to serve those customers who are currently
not served by me or my competitors?”
In class after class during the program, across the range of
disciplines that make up a business school, instructors emphasized the
importance of connecting analysis to an overarching data strategy. In Lakhani’s
final case discussion, which explored internal and customer transformation at
GE, it became clear that a data strategy wasn’t just about gathering and
analyzing information—it can be the unifying principle in corporate reinvention.
by Dina Gerdeman
http://hbswk.hbs.edu/item/companies-love-big-data-but-lack-strategy-to-use-it-effectively?cid=spmailing-16529700-WK%20Newsletter%2008-23-2017%20(MD%20Edit)%20(1)-August%2023,%202017
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