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Perspectives


HOW THIRD-PARTY DATA CAN ENHANCE ANALYTICS


THE BENEFITS AND CHALLENGES OF EXTERNAL DATA SOURCES

Companies are increasingly seeking better insights by tapping into third-party
data. Outside sources can bring opportunity, but using them effectively can be
challenging.

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 * Save for later



EXPLORE CONTENT

 * Data volume and insights
 * Deriving value from external data
 * The challenges of external data
 * Tap into a data ecosystem
 * Connecting to the ecosystem

 * Get in touch
 * Related topics

Many executives already know the data generated from their operations can yield
valuable insights. Relying solely on internally generated information can leave
gaps, however, so many companies are looking to incorporate new, nontraditional,
and external sources of data into their analyses. This data can include almost
anything, from historical demographic and weather data to satellite imagery and
private company information.

Companies increasingly operate within networks of business partners such as
suppliers, resellers, channel partners, regulators, and other stakeholders.
These networks are often globally distributed and potentially affected by
economic, political, or environmental factors. Analyzing external data can help
companies see risks and opportunities they might otherwise miss from internal
operations, customers, and first-tier suppliers. Outside data can also
illuminate how factors such as shifting consumer behaviors, competitor
initiatives, or geopolitical events might affect a business.

As most business and technology professionals know, the volume of data being
created, shared, and stored is increasing at an exponential pace. According to
one study, the data stored in data centers will nearly quintuple to reach 1.3
zettabytes globally by 2021. (One zettabyte is equivalent to one trillion
gigabytes.) Along with the volume of information available, the potential value
of analyzing this data grows bigger by the day.

It’s not surprising, then, that companies on the leading edge of data and
analytics are more likely to make use of external sources. According to a recent
MIT Sloan Management Review report, the companies making the most innovative use
of data and analytics were more likely than others to leverage external data
sources, including social, mobile, and publicly available data. A separate study
found faster-growing companies were more likely to be considering the use of
external data than those with lower growth rates.

Back to top






DERIVING VALUE FROM EXTERNAL DATA



Third-party data sources can help businesses personalize marketing offers,
improve HR decisions, gain new revenue streams by launching new products or
services, enhance risk visibility and mitigation, and better anticipate shifts
in demand for products and services. In one case, a major semiconductor
manufacturer used third-party data to build predictive customer models. The
models identified potential targets that fit profiles similar to the company’s
most engaged customers. These lookalikes helped the organization optimize
marketing spend, reducing a major campaign’s cost per engagement by 75 percent.

There are numerous other examples of analytics programs generating value with
external data. Several startups monitor social networking data to predict
patterns of job-seeking behavior and retention risk, believing outside sources
are more predictive of an employee’s likelihood of leaving than any internal
data available. Others use geolocation and weather data to predict crop yields,
helping farmers optimize fertilizer use. Many retailers are using economic data
and forecasts, data from suppliers, and geolocation information to better
predict demand and reduce stock shortages.

Back to top






THE CHALLENGES OF EXTERNAL DATA



Access to external data is getting easier in some ways, but incorporating it can
still be daunting. Organizations report a wide variety of business and technical
challenges in deriving insights from external data. Among the business
challenges are the size and complexity of the data-provider market, which can
make it hard to identify the right data sources and partners. Negotiating data
acquisition can be arduous, depending on factors such as whether ongoing access
is needed for refreshing machine learning models, as well as determining usage
restrictions, vendor revenue-sharing needs, and liability if the data proves to
be inaccurate or tainted. Negotiation can also involve lengthy risk and legal
reviews of vendor contracts and licensing agreements. The ongoing management of
a growing roster of data-sharing relationships and partnerships can also be
taxing.

Technical challenges can include fundamentals such as data quality and accuracy:
A variety of studies have demonstrated that third-party data can be riddled with
inaccuracies. There can also be inconsistencies between external and internal
recording to resolve before performing analysis. Preprocessing—such as cleansing
and formatting—is time-consuming, accounting for as much as 80 percent of the
analysis effort by some estimates. Securely storing and cataloging data in an
easily accessible manner can require updating information management processes
and capabilities designed to handle only internal data. The longer it takes to
work through these challenges, the less time available to react to market trends
and external events with agility.

Back to top






TAP INTO A DATA ECOSYSTEM



Research suggests most companies haven’t yet developed the capabilities
necessary to use external data effectively. To close this gap, executives may
want to think of their companies as part of a data ecosystem—a network of
participants that directly or indirectly consume, produce, or provide data and
other related resources.

To be good at using external data can mean being competent in identifying,
evaluating, procuring, and preparing external data in a consistent and timely
manner. Companies will want to set up a continual process for identifying,
engaging with, and evaluating new external data sources and partners and, when
appropriate, integrating these data sources into analytics processes or product
offerings. Maximizing the value of external data often requires integrating it
with internal data for a more insightful analysis.

Companies also may want to form a cross-functional group that acts as the
organization’s interface to the broader data ecosystem. This group could draw on
competencies from multiple areas—including product management, business
analysis, data science, legal, and procurement—to address the previously
identified organizational and technical challenges. Some organizations have
created special roles charged with scanning the third-party data market and
matching business requests with relevant sources. These data curators can help
companies quickly identify and assess data sources matched to business needs
while reviewing external data sets for quality and accuracy using consistent
evaluation processes. Companies with effective tech-scouting capabilities may
look within this group for inspiration.

Back to top






CONNECTING TO THE ECOSYSTEM



Organizations looking to connect to a data ecosystem can turn to a wide and
growing variety of data and insights providers. Gartner Group categorizes data
services, for instance, by the level of insight they provide:

Simple data services. Data brokers collect information from multiple sources and
offer it in collected and conditioned form. The data is used as additional input
to a decision process by a person, an application system, or a device in an IoT
ecosystem.

Smart data services. Data is enhanced by applying analytical rules and
calculations. The results often take the form of scores or the tagging of
objects, as in services from marketing data providers and credit ratings
agencies.

Adaptive data services. Customers submit data pertaining to specific analytical
requests. Providers combine that data with data from other sources.

There are other ways to segment this dynamic marketplace. Some providers
specialize in serving industry sectors such as hedge funds or health care
organizations. Many consulting and systems integration services providers,
meanwhile, are leveraging publicly available data or information from
third-party partners and then integrating those sources with their clients’
internal data records to perform custom analysis.

Back to top





Companies are making growing use of data from third parties. To get more value
from their data analytics efforts, executives may want to consider enhancing
their ability to identify, evaluate, and contract for these new external sources
by creating a data ecosystem management program under a chief data office that
links to business, IT, and legal teams. The pressure on companies to innovate
and to improve the efficiency and effectiveness of their operations is
unrelenting; they cannot afford to ease off in their pursuit of insights. For
many companies, the effective use of external data is a critical new frontier.



Authors of Driving industry through advanced technology include: David Schatsky,
Craig Muraskin, and Jonathan Camhi.






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GET IN TOUCH

DAVID SCHATSKY

MANAGING DIRECTOR | DELOITTE LLP

dschatsky@deloitte.com

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David analyzes emerging technology and business trends for Deloitte’s leaders
and clients. His recent published works include Signals for Strategists: Sensing
Emerging Trends in Business and Technolog... More

CRAIG MURASKIN

DEPUTY CHIEF INNOVATION OFFICER | DELOITTE LLP

cmuraskin@deloitte.com

+1 212 492 3848



As deputy chief innovation officer for Deloitte LLP and senior managing director
of Deloitte’s US Innovation group, Craig oversees all ongoing innovation
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EXPLORE CONTENT

 * Data volume and insights
 * Deriving value from external data
 * The challenges of external data
 * Tap into a data ecosystem
 * Connecting to the ecosystem

 * Get in touch
 * Related topics

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