Peer-Powered Collaboration Brings Life to Enterprise Analytics

Wednesday, April 27, 2016 - 12:00

What are the forces driving Enterprise Analytics to center-stage? Some of the strongest are the freedom of analytics from centralization strategies, expansion of intuitive data visualization technology, increasing computing power enabling statistical rigor, and an individual’s expectations of instant service. Underscoring these trends is our society’s adoption of social networks which change how we consume information and make decisions.

Peer-powered collaboration puts all players in the enterprise ecosystem in conversation. By learning from and contributing to a dialogue, business users, analysts, data scientists, and IT can present a compelling and empowering story about the data to decision makers.

Collaboration: Information Overload Averted

“A wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”

-Herbert Simon, Nobel Prize laureate, 1971

It goes without saying that there are limits to our human ability to process huge amounts of data, and that a wealth of information is not valuable until it can be accessed and understood. Despite these constraints, advancing collaboration technology allows users across the enterprise collaborate on interdisciplinary data problems. McKinsey claims that “if organizations and individuals deployed such techniques more widely, end-user demand for big data could strengthen significantly.”(1) Collaboration drives bigger business value.

Sophisticated visualization techniques and algorithms can make patterns in huge volumes of data apparent and enable analysts to make pertinent insights.(2) But, of course, not every business user will have the know-how to discover the secrets locked in petabytes of data.

Collaboration, especially via social networks, is the natural solution to this dilemma. Drawing on others ideas, pulling in users with relevant expertise, and searching for efficient techniques will boost innovation. Business users are already moving toward more integrated information sharing with their peers in their personal data usage. It will be a natural extension to introduce this sharing to the enterprise.

Curated Authorities Are Not First Choice for Younger Generations

Dependence on social networks for information distillation is particularly evident in younger generations. Tech-savvy individuals heavily rely on social networks to consume data and make decisions. When asked how much user-generated content plays in purchase decisions, 84% of Millennials said either “some” or “a lot” compared to 70% of Baby Boomers.(3) Younger generations also tend to get their info from peers, not centralized media. Centralized, curated authorities are not going to be their first choice of information if they are slow or incomplete.

Where do Millennials Get Their Information?

(4)

 

Reliance on social networks for information distillation is not unique to Millenials. Older populations are also adopting social networks in leaps and bounds. In 2011, McKinsey reported a 7% increase in social network users age 25-34, a 22% increase in those 35-54, and a 52% increase in those 55-64.(5) Millennials in an enterprise may be leading the trend, but all members of the enterprise are perpetuating it by their own familiarity with social media and networks.

As this continues, attitudes towards centralized and curated data sources are going to sour if they take too long to materialize. Centralization will still be key, but analytics needs to thrive in the interim. Communication between business users and IT will protect data integrity while improving self-service opportunities. Social integration fosters the enterprise ecosystem’s smooth evolution.

Storytelling and The Faces of Social Integration in the Enterprise

Social integration in the enterprise can take many different forms: storytelling, discussion threads, integration with social platforms, timelines, or real-time collaborations.(6) Being able to see comments and annotations that define a dialogue as a natural part of the workflow-driven process will enliven conversations and deepen insights. Discussion will be rooted in data, where multiple views and perspectives are presented by individuals with unique expertise and subject familiarity.

Perhaps the most valuable of these tools is storytelling. Engaging decision makers with a storyboard and the option to explore more granularity with a few clicks will shift the focus from the HIPPOs (highest paid person’s opinion) to the hard facts.

A good example of this in practice is Tableau’s Story Points feature. This allows an analyst to share a stream of thought with colleagues. Annotations prompt viewers to interact with the visualizations in each Story Point, exploring the data behind a proposed hypothesis.

From sharing with team members in scrum to persuading C-level executives or assuaging shareholders, storytelling through social networks brings the data to life. A compelling narrative will convince both colleagues and leaders to take action.

Social Solutions Bloom

Taking advantage of users’ personal social networking comfort level is going to revolutionize the way the enterprise views its data. Storytelling will take the place of canned reports, empowering executives and business users alike to explore details behind the scenes. Crowdsourcing to other departments and members in the enterprise will drive higher business value from data and BI investments.(7)

Encouraging analysts to communicate with their peers - both internal and external to the enterprise - about additional possible data stores, techniques, and solutions will inspire innovation. Insights provided with a clear narrative will have a more lasting impact. The value of analysts experience and creativity will increase as decisions become data-driven and the result of a cross-enterprise collaboration.

Pervasive insights and peer-powered collaboration are yielding an increasing irrelevance of centralization strategies - to the degree that they are encouraging conversations about data. The data-driven enterprise’s focus will shift from fearful grasping and constricting policies to a flexible governance made possible by the open communication around resources.

Enterprise Analytics - Join the Revolution

The age of search and intelligent web has conditioned the citizen data scientist to expect expediency and efficiency from data. The “connected everything” promises volumes to work with, and intuitive interfaces make exploration second-nature. Increasing computing power provides the means for testing hypotheses with robust statistical rigor, underpinning decisions with sound evidence. Social networks and storytelling create conversations around data, empowering impactful, data-driven decisions. This is the Movement. Join the Revolution. Welcome to Enterprise Analytics.

 

This is the final post in a series exploring the five trends that Inquidia sees in the business intelligence marketplace. Check out the previous posts linked below:


Endnotes

  1. "Big Data: The next Frontier for Innovation, Competition, and Productivity." McKinsey Global Institute, May 2011, 18.

  2. Ibid

  3. “Talking to Strangers: Millennials Trust People Over Brands.” BazaarVoice, January 2012. http://resources.bazaarvoice.com/rs/bazaarvoice/images/201202_millennials_whitepaper.pdf

  4. “How Millennials Get News: Inside the Habits of America’s First Digital Generation.” The Media Insight Project. http://www.americanpressinstitute.org/wp-content/uploads/2015/03/How-Millennials-Get-News-Media-Insight-Project-March-2015-FINAL.pdf

  5. "Big Data: The next Frontier for Innovation, Competition, and Productivity." McKinsey Global Institute, May 2011, 21.

  6. “Critical Capabilities for Business Intelligence and Analytics Platforms.” Gartner, May 2015, 24.

  7. “Critical Capabilities for Business Intelligence and Analytics Platforms.” Gartner, May 2015, 23.

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