How high performing companies succeed with analytics

  • 60 percent of high performers invest more than 25 percent of their tech expenditure in analytics.

  • 81 percent of high performers use two or more advanced analytical techniques, such as optimization and crowd sourcing.

  • High performers are more successful at breaking down internal barriers.

Almost every large company realizes the importance of analytics in unlocking and leveraging insights from key data collected by the sensors and networked devices that form IoT platforms. Not all companies, however, engage in the operational and strategic best practices that yield successful outcomes of their analytics initiatives. But those that do, achieve far better results.

That’s the main takeaway from “Winning With Analytics,” a new report from Accenture Analytics and MIT. The results, culled from 864 respondents mainly in the banking, communications, consumer goods and services, energy, insurance, and retail industries found that high performing companies share a similar approach to choosing the investments, talent, and tools they use to get the most out of analytics. “The stronger a company’s commitment to analytics, the better it performs,” according to the report.

High performers embed analytics into decision-making processes linked to business outcomes, enabling them to make faster and more authoritative decisions. They also constantly monitor and course-correct those decisions. Twice as many high performers as low performers use analytics in key areas of their business.

Here are some highlights from the report, as well as strategies and best practices companies of almost any size can apply to their analytics initiatives:

  • High performers are almost four times as likely as low performers to generate significant ROI from analytics.
  • Almost 60 percent of high performers invest more than 25 percent of their technology expenditure in analytics, compared with 17 percent of low performers. 53 percent plan to greatly increase that investment during the next three years, compared with only 9 percent of low performers.
  • 82 percent of high performers make bigger investments in training and hiring staff and using consultants to drive analytics initiatives, compared with 40 percent of low performers.
  • Both high and low performers struggle to find the right talent to staff their analytics initiatives.
  • High performers, though, do a better job filling the talent gap. They partner with companies for needed skills (63 percent vs. 33 percent), partner with academic institutions (52 percent vs. 24 percent), and acquire companies to add needed skills (43 percent vs. 18 percent).
  • High performers are more successful breaking down internal barriers, such as resistance, silos, and politics when implementing analytics decisions. On the other hand, low performers cite “inability to change” and “politics” as main barriers.
  • High performers also use more data sources, advanced tools, and techniques.
  • Almost three times as many high performers (59 percent vs. 21 percent) leverage seven or more data sources.
  • More than twice as many (an average of 64 percent vs. 31 percent) use intermediate tools and advanced data tools, such as Hadoop and in-memory computing.
  • Nearly twice as many (81 percent vs. 45 percent) use two or more advanced analytical techniques, such as optimization, simulation, crowd-sourcing, and sentiment analysis.

It’s clear to see that high performing companies reap much better results using analytics, and it is one of the essential tools when it comes to shaping strategic direction, addressing growth opportunities, informing critical decisions, and managing risk.

Jeff O’Heir is an award-winning writer, editor, team manager, and highly adaptable journalist who transitions seamlessly between editorial and content marketing. All opinions are his own. AT&T has sponsored this blog post.

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